The Use of Pharmacotherapies in the Secondary Prevention

The Use of Pharmacotherapies in the

Secondary Prevention of Coronary Heart Disease

Margherita Veroni

BSc, MSc (Pharmacology), Grad Dip Computing

This thesis is presented for the degree of

Doctor of Philosophy of

The University of Western Australia

School of Population Health

2006

“Knowing is not enough; we must apply.

Willing is not enough; we must do.”

Johann Wolfgang von Goethe (1749-1832)

v

Abstract

Background

This thesis examines pharmacotherapy use in the secondary prevention of coronary heart

disease. It includes antiplatelet agents, beta-blockers, statins and ACE inhibitors, all shown in

landmark clinical trials and meta-analyses to reduce the risk of cardiac events in patients with

known coronary disease. Underuse of effective preventive therapies represents a lost

opportunity to reduce mortality and morbidity. Overseas studies have shown significant

underuse of effective therapies at the time of hospital discharge following an acute event and

later in ambulatory care. Australian data on prescribing practices following an acute coronary

event and, ongoing use in ambulatory care are sparse.

Aims

The aim of this thesis was to quantify the prescription of known effective therapies at the time

of hospital discharge following an acute coronary event and ongoing use in ambulatory care. A

secondary aim was to identify barriers to optimal secondary prevention thus providing an

evidential basis to recommend change.

Methods

This was an observational study of a cohort of post-MI patients admitted to a tertiary and

affiliate hospital in Perth, Western Australia. The continuum of care from the treatment plan at

discharge through to the treatment regimen and risk factor management 12 months post-MI was

examined. The intermediate step, communication about the treatment plan with the patient and

the primary health care provider was also examined. The study involved a review of hospital

medical records and follow-up questionnaires to patients and their general practitioners at 3 and

12 months post-MI. All post-myocardial patients were included in the analysis of prescriptions

at discharge. The follow-up study included patients 80 years and younger with no terminal

conditions. Patient interviews at 3 months and interviews and focus groups with key hospital

staff provided qualitative data to inform the quantitative data.

Results

The rate of prescription at hospital discharge was: antiplatelet agents 89%, beta-blockers 75%,

statins 70% and ACE inhibitors 60%. ACE inhibitor prescription increased over the study

period from 49% to 70%. In the subset of patients included in the follow-up study prescription

at discharge included antiplatelet agents 94%, beta-blockers 85%, statins 82% and ACE

inhibitors 62%.

vi

Information about medications given prior to discharge included; education 80%, a medication

list 80% and, other written materials 50%. Only 41% “definitely” had the purpose and side

effects of medications explained in a way that they could understand. Three months post

discharge, one third of patients had concerns about the purpose of their medications.

A discharge summary was received by 96% of general practitioners, while 50% received a

telephone call. One third of comments provided about the transition of care indicated problems

with the process. These comments usually related to the discharge summary, referring to

“legibility”, “timeliness” and “level of detail”.

Patient-directed strategies prior to discharge included education, provision of written materials

and patient review prior to discharge. Staff identified time constraints and unplanned discharges

as barriers to providing appropriate education and review. The quality of the discharge

medication list and discharge summary was also identified as barriers to effective

communication with patients and general practitioners respectively.

Drug use at 12 months included antiplatelet agents 89%, beta-blockers 72%, statins 85% and

ACE inhibitors 62%. Beta-blocker use decreased significantly over the follow-up period. The

proportion of patients prescribed doses equivalent to those used in clinical trials at 12 months

were beta-blockers 10%, statins 73% (from 60% at discharge, p<0.04) and ACE inhibitors 35%.

Based on patient interviews very few patients had poor adherence with the treatment regimen,

although some cases of intentional and unintentional non-adherence were noted. At 12 months,

50% had optimal LDL-cholesterol (<2.5 mmol/L) and one third had high blood pressure

(≥140/90).

Conclusions

The prevalence of drug use at the time of discharge and at follow-up was near optimal, except

beta-blockers with significant discontinuation during the follow-up period. However, the doses

prescribed may not be sufficient to achieve the risk-reduction benefit. In the case of statins this

was reflected in the failure to achieve optimal lipid levels. Barriers to effective communication

about the treatment plan with the patient and the general practitioner may explain at least part of

this treatment gap.

vii

Table of Contents

Statement of Candidate Contribution __________________________________________xiii

Acknowledgments __________________________________________________________ xv

Conference Presentations ___________________________________________________ xvii

Media Coverage ____________________________________________________________xix

List of Tables ______________________________________________________________xxi

List of Figures_____________________________________________________________xxix

Commonly Used Abbreviations ______________________________________________xxxi

CHAPTER 1 INTRODUCTION _____________________________________________ 1

1.1 OVERVIEW ____________________________________________________________ 1

1.2 BACKGROUND TO THE STUDY_____________________________________________ 2

1.2.1 Quality in healthcare __________________________________________________ 2

1.2.2 The Australian healthcare system ________________________________________ 5

1.2.3 International approaches to quality in health care ____________________________ 6

1.3 THE PROBLEM: UNDER USE OF PREVENTIVE THERAPIES_________________________ 9

1.4 HYPOTHESIS AND AIMS OF THE RESEARCH__________________________________ 12

1.5 PROJECT OUTLINE _____________________________________________________ 13

1.6 ORGANISATION OF THESIS_______________________________________________ 14

1.6.1 Background and Literature Review : Chapters 1-2 __________________________ 14

1.6.2 Methods: Chapter 3 __________________________________________________ 14

1.6.3 Results and discussion: Chapters 4-8_____________________________________ 14

1.6.4 Final discussion and recommendations: Chapter 9 __________________________ 15

CHAPTER 2 REVIEW OF THE LITERATURE ______________________________ 17

2.1 OVERVIEW ___________________________________________________________ 17

2.2 BACKGROUND ________________________________________________________ 18

2.2.1 Burden of coronary heart disease________________________________________ 18

2.2.2 Pharmacotherapies in the secondary prevention of CHD _____________________ 19

2.2.3 Sources of drug prescription and drug utilisation data________________________ 22

2.2.4 Summary __________________________________________________________ 33

2.3 EVOLUTION OF SECONDARY PREVENTION___________________________________ 34

2.3.1 Antiplatelet agents ___________________________________________________ 34

2.3.2 Beta-blockers _______________________________________________________ 40

2.3.3 Statins_____________________________________________________________ 48

2.3.4 ACE inhibitors ______________________________________________________ 60

2.3.5 Combined therapy ___________________________________________________ 68

viii

2.3.6 Summary___________________________________________________________69

2.4 EVIDENCE-BASED PRESCRIBING___________________________________________70

2.4.1 Antiplatelet agents ___________________________________________________71

2.4.2 Beta-blockers _______________________________________________________72

2.4.3 Statins _____________________________________________________________74

2.4.4 ACE inhibitors ______________________________________________________76

2.4.5 Summary___________________________________________________________79

2.5 DRUG UTILISATION IN AMBULATORY CARE __________________________________80

2.5.1 Prescribing in ambulatory care__________________________________________80

2.5.2 Patient adherence ____________________________________________________87

2.5.3 Summary__________________________________________________________104

CHAPTER 3 PROJECT DEVELOPMENT AND METHODS __________________ 105

3.1 OVERVIEW __________________________________________________________105

3.1.1 Study approach _____________________________________________________105

3.1.2 Chapter outline _____________________________________________________106

3.2 PROJECT DEVELOPMENT________________________________________________107

3.2.1 Development of data collection instruments ______________________________107

3.2.2 Feasibility and validity _______________________________________________109

3.3 METHODOLOGY ______________________________________________________113

3.3.1 The study sample ___________________________________________________113

3.3.2 Data collection _____________________________________________________114

3.4 DATA ANALYSIS ______________________________________________________117

3.4.1 Chapter 4:The study sample ___________________________________________117

3.4.2 Chapter 5: Secondary prevention therapies at discharge _____________________121

3.4.3 Chapter 6:Discharge planning and transition of care________________________125

3.4.4 Chapter 7:Long term secondary prevention therapy ________________________126

3.4.5 Chapter 8:Risk factor management _____________________________________131

3.4.6 Statistical methods __________________________________________________136

CHAPTER 4 THE STUDY SAMPLE _______________________________________ 139

4.1 INTRODUCTION_______________________________________________________139

4.1.1 Chapter outline _____________________________________________________140

4.2 BASELINE CHARACTERISTICS____________________________________________141

4.2.1 Demographics______________________________________________________141

4.2.2 Medical History ____________________________________________________142

4.2.3 Course of hospital episode ____________________________________________144

4.3 FOLLOW-UP COHORT __________________________________________________148

4.3.1 Patient selection ____________________________________________________148

ix

4.3.2 Response rate ______________________________________________________ 148

4.3.3 Time to follow-up __________________________________________________ 149

4.3.4 Post-discharge care _________________________________________________ 150

4.3.5 Current status ______________________________________________________ 153

4.3.6 General practitioner consultations ______________________________________ 158

4.4 SAMPLE VALIDITY ____________________________________________________ 159

4.4.1 Patient questionnaires _______________________________________________ 159

4.4.2 Patient interviews___________________________________________________ 160

4.4.3 GP questionnaires __________________________________________________ 165

4.5 DISCUSSION_________________________________________________________ 173

4.5.1 The follow-up cohort ________________________________________________ 173

4.6 CONCLUSIONS _______________________________________________________ 176

CHAPTER 5 SECONDARY PREVENTION THERAPIES AT DISCHARGE_____ 177

5.1 INTRODUCTION_______________________________________________________ 177

5.1.1 Evolving evidence __________________________________________________ 177

5.1.2 Evolving practice ___________________________________________________ 179

5.1.3 Objectives ________________________________________________________ 179

5.1.4 Chapter outline_____________________________________________________ 179

5.2 OVERVIEW OF DRUG PRESCRIPTIONS______________________________________ 180

5.2.1 Demographics _____________________________________________________ 180

5.2.2 Enrolment Period ___________________________________________________ 181

5.2.3 Comorbidity Index__________________________________________________ 182

5.2.4 Treatment Specialty _________________________________________________ 182

5.2.5 Cardiologists ______________________________________________________ 183

5.3 ANTIPLATELET AGENTS________________________________________________ 184

5.3.1 Type and dose _____________________________________________________ 184

5.3.2 Associations with antiplatelet agent prescription___________________________ 184

5.3.3 Independent predictors of antiplatelet agent prescription ____________________ 187

5.3.4 Summary _________________________________________________________ 188

5.4 BETA-BLOCKERS _____________________________________________________ 189

5.4.1 Type and dose _____________________________________________________ 189

5.4.2 Associations with beta-blocker prescription ______________________________ 189

5.4.3 Independent predictors of beta-blocker prescription________________________ 192

5.4.4 Summary _________________________________________________________ 194

5.5 STATINS ____________________________________________________________ 195

5.5.1 Type and dose _____________________________________________________ 195

5.5.2 Associations with statin prescription ____________________________________ 196

x

5.5.3 Independent predictors of new statin prescription __________________________199

5.5.4 Summary__________________________________________________________199

5.6 ACE INHIBITORS______________________________________________________200

5.6.1 Changes in prescribing over time _______________________________________200

5.6.2 Type and dose______________________________________________________202

5.6.3 Associations with ACE inhibitor prescription _____________________________203

5.6.4 Independent predictors of ACE inhibitors ________________________________207

5.6.5 Summary__________________________________________________________210

5.7 CALCIUM ANTAGONISTS________________________________________________211

5.7.1 Type and dose______________________________________________________211

5.7.2 Associations with calcium antagonist prescription__________________________211

5.7.3 Summary__________________________________________________________215

5.8 DISCUSSION _________________________________________________________216

5.8.1 Overview _________________________________________________________216

5.8.2 Antiplatelet agents __________________________________________________217

5.8.3 Beta-blockers ______________________________________________________219

5.8.4 Statins ____________________________________________________________224

5.8.5 ACE inhibitors _____________________________________________________226

5.8.6 Calcium antagonists _________________________________________________229

5.8.7 Limitations ________________________________________________________230

5.9 SUMMARY ___________________________________________________________231

5.10 CONCLUSIONS________________________________________________________232

CHAPTER 6 DISCHARGE PLANNING AND TRANSITION OF CARE_________ 233

6.1 INTRODUCTION_______________________________________________________233

6.1.1 Objectives_________________________________________________________233

6.1.2 Chapter outline _____________________________________________________233

6.2 PATIENT PERSPECTIVE_________________________________________________234

6.2.1 Prescriptions at discharge _____________________________________________234

6.2.2 Information about medications_________________________________________235

6.2.3 Risk factor modification ______________________________________________236

6.2.4 Written Information _________________________________________________236

6.2.5 Outpatient cardiac rehabilitation _______________________________________237

6.2.6 Knowledge about medications _________________________________________238

6.2.7 Patient satisfaction __________________________________________________238

6.3 GENERAL PRACTITIONER PERSPECTIVE____________________________________240

6.3.1 Type of communication ______________________________________________240

6.3.2 Transition of care ___________________________________________________240

xi

6.4 CARDIOLOGY STAFF PERSPECTIVE________________________________________ 242

6.4.1 Communication with patients _________________________________________ 242

6.4.2 Communication with general practitioner ________________________________ 246

6.5 DISCUSSION_________________________________________________________ 247

6.5.1 The patient perceptive _______________________________________________ 247

6.5.2 General practitioner perspective _______________________________________ 249

6.5.3 The system ________________________________________________________ 250

6.6 SUMMARY __________________________________________________________ 252

6.7 CONCLUSIONS _______________________________________________________ 252

CHAPTER 7 LONG TERM SECONDARY PREVENTION THERAPY__________ 253

7.1 INTRODUCTION_______________________________________________________ 253

7.1.1 Objectives ________________________________________________________ 253

7.1.2 Chapter outline_____________________________________________________ 253

7.2 PREVALENCE OF DRUG USE_____________________________________________ 254

7.2.1 Use of medications prior to hospital admission ____________________________ 254

7.2.2 During follow-up ___________________________________________________ 258

7.3 TREATMENT REGIMENS IN FOLLOW-UP CARE _______________________________ 263

7.3.1 Antiplatelet agents __________________________________________________ 263

7.3.2 Beta-blockers ______________________________________________________ 264

7.3.3 Statins____________________________________________________________ 266

7.3.4 ACE inhibitors _____________________________________________________ 268

7.3.5 Calcium antagonists_________________________________________________ 270

7.3.6 Prescription of effective doses _________________________________________ 271

7.4 ADHERENCE WITH TREATMENT REGIMEN__________________________________ 272

7.4.1 Survey-drug inventory concordance ____________________________________ 272

7.4.2 Patient-doctor concordance ___________________________________________ 272

7.4.3 Patient interview ___________________________________________________ 274

7.5 PREDICTORS FOR USE OF SECONDARY PREVENTION THERAPY__________________ 282

7.5.1 Use prior to admission _______________________________________________ 282

7.5.2 Drug discontinuation ________________________________________________ 293

7.6 DISCUSSION_________________________________________________________ 304

7.6.1 The treatment gap __________________________________________________ 304

7.6.2 Predictors of long-term drug use _______________________________________ 314

7.7 SUMMARY __________________________________________________________ 318

7.8 CONCLUSIONS _______________________________________________________ 318

CHAPTER 8 RISK FACTOR MANAGEMENT______________________________ 319

8.1 INTRODUCTION_______________________________________________________ 319

xii

8.1.1 Objectives_________________________________________________________319

8.1.2 Chapter outline _____________________________________________________319

8.2 LIPID MANAGEMENT___________________________________________________320

8.2.1 Management of lipids prior to admission _________________________________320

8.2.2 Inpatient monitoring and management of lipids____________________________321

8.2.3 Monitoring and management of lipids in follow-up care _____________________325

8.3 MANAGEMENT OF OTHER RISK FACTORS___________________________________332

8.3.1 Blood pressure _____________________________________________________332

8.3.2 Management of blood glucose _________________________________________334

8.3.3 Smoking __________________________________________________________336

8.3.4 Weight management and physical activity________________________________338

8.4 DISCUSSION _________________________________________________________339

8.4.1 Lipids ____________________________________________________________339

8.4.2 Other risk factors ___________________________________________________343

8.4.3 Limitations ________________________________________________________345

8.5 SUMMARY ___________________________________________________________346

8.6 CONCLUSIONS________________________________________________________346

CHAPTER 9 FINAL DISCUSSION ________________________________________ 347

9.1 OVERVIEW OF STUDY__________________________________________________347

9.1.1 Antiplatelet agents __________________________________________________348

9.1.2 Beta-blockers ______________________________________________________349

9.1.3 Statins ____________________________________________________________350

9.1.4 ACE inhibitors _____________________________________________________351

9.1.5 Calcium Antagonists ________________________________________________352

9.1.6 Summary__________________________________________________________352

9.2 LIMITATIONS OF THE STUDY_____________________________________________354

9.3 FUTURE WORK _______________________________________________________355

9.3.1 Effectiveness of current prescribing practices _____________________________355

9.3.2 Strategies to improve long-term treatment of patients following AMI __________357

9.4 IMPORTANCE OF THE STUDY_____________________________________________362

9.5 CONCLUDING COMMENTS_______________________________________________364

References ________________________________________________________________ 365

Appendices _______________________________________________________________ 401

Appendix A Medical record review data set

Appendix B Documentation for 3 month (early) follow-up

Appendix C Documentation for 12 month (late) follow-up

Appendix D Patient interview

Appendix E Cardiology staff interviews

xiii

Statement of Candidate Contribution

This project was initiated and developed by the candidate under the guidance of Professors

Holman and Thompson. The candidate was responsible for:

• The study design.

• The design of all data collection instruments including the medical record review, the

questionnaires, patient interviews, staff interviews and focus groups.

• Arranging and conducting medical record reviews.

• The administrative procedures necessary to distribute and follow-up the questionnaires and

patient interviews.

• Arranging and conducting Patient interviews.

• Designing the qualitative research.

• Arranging and conducting staff interviews and focus groups.

• All data entry, including the design of the Access databases.

• All analysis.

• Preparation of the thesis.

xv

Acknowledgments

The Commonwealth Department of Health and Aged Care funded this work through a Quality

Use of Medicine (QUM) Scholarship as part of the Quality Use of Medicine Evaluation

Program (QUMEP). I am grateful to the Pharmaceutical Health And Rational use of Medicines

(PHARM) committee for this funding and their forbearance.

I would like to thank my supervisors Professor D’Arcy Holman and Clinical Professor Peter

Thompson for lending me their knowledge and experience - and for signing those letters!

I am also grateful to

• The participants in this project; patients, general practitioners and cardiology staff

• The Medical Records Department at both hospitals who provided weekly lists of new

hospital episodes with a diagnosis of myocardial infarction and accommodated me while I

reviewed medical records.

• The Western Australian Data Linkage Unit for providing the comorbidity codes for all the

index admissions.

• Annette Mercer for providing guidance on the qualitative research.

• Alison Talbot who assisted me by taking notes during the focus groups.

My thanks too to my friends for the support and encouragement provided without which this

may never have seen the light of day. Finally to my mother who taught me to strive for better

and, David who allows me the space to be the person I know I can be, thank you with all my

heart.

xvii

Conference Presentations

M Veroni, CDJ Holman and PL Thompson.

Use of pharmacotherapies in the secondary prevention of coronary heart disease.

Third National Medicines Symposium. Brisbane 2004.


Post-MI Medication: Dosages don’t reflect the evidence.

51st Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand. Adelaide

2003


Post-MI lipid lowering therapy, what happened to the lipids? Only half achieve target LDL-

cholesterol and fewer achieve target total cholesterol.

51st Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand. Adelaide

2003


Quality prescribing of effective pharmacotherapies post myocardial infarction.

Second National Medicines Symposium. Canberra 2002.

M Veroni, CDJ Holman, PL Thompson.

Do we need national guidelines for optimal post infarction management?

Fourth International Conference on the Scientific Basis of Health Services Research. Sydney

2001.

xix

Media Coverage

The West Australian, Health + Medicine (Supplement), 24 October 2001 Pages 4-5.

“When less is not best”. Cathy O’Leary

Australian Doctor, 22 August 2003.

“Cardiac drugs let down in the real world”. Michael Woodhead

Australian Doctor, 4 August 2004.

“Knowledge affects patient compliance” Bianca Nogrady

xxi

List of Tables

Table 1.1: Four levels for improving quality ________________________________________ 4

Table 1.2: Barriers to implementation of preventive services. _________________________ 10

Table 2.1: Secondary prevention of CHD studies using administrative databases __________ 22

Table 2.2: Secondary prevention studies using data from randomised control trials_________ 24

Table 2.3: Secondary prevention studies using data from registers______________________ 26

Table 2.4: Secondary prevention studies using data from multicentre surveys_____________ 28

Table 2.5: Secondary prevention studies using data from single institutions. ______________ 29

Table 2.6: Secondary prevention studies using Quality improvement initiatives ___________ 32

Table 2.7: Initial evidence from the Antiplatelet Trialists’ Collaborations ________________ 34

Table 2.8 Longitudinal studies of aspirin prescription following an ACS_________________ 39

Table 2.9: Long term secondary prevention trials for beta-blockers _____________________ 40

Table 2.10: Late benefits of beta-blockers post-MI__________________________________ 40

Table 2.11: Pooled odds of death in long term beta-blocker trials ______________________ 41

Table 2.12 Longitudinal studies of beta-blocker prescription following an ACS ___________ 47

Table 2.13: Characteristics of statin secondary prevention trials _______________________ 48

Table 2.14: Outcomes from the statin secondary prevention trials ______________________ 49

Table 2.15: Lipid management guidelines for CHD _________________________________ 50

Table 2.16: Proportion of patients achieving treatment goals __________________________ 56

Table 2.17: Dispensed price ($A) of statins in Australia per patient per year ______________ 57

Table 2.18 Pharmacokinetic characteristics of commonly used statins___________________ 57

Table 2.19 Longitudinal studies of lipid lowering prescription following an ACS__________ 59

Table 2.20: Long term ACE inhibitors with LVD post-MI ____________________________ 60

Table 2.21: Long-term ACE inhibitors in LVD post-MI______________________________ 60

Table 2.22: Benefits of ACE inhibitor therapy in post-MI patients______________________ 61

Table 2.23: Early ACE inhibitor trials____________________________________________ 62

Table 2.24: Primary, secondary and other outcomes in HOPE study ____________________ 63

Table 2.25 Longitudinal studies of ACE inhibitors prescription following an ACS _________ 67

Table 2.26: Predictors of antiplatelet agent prescription ______________________________ 72

Table 2.27: Predictors of ACE inhibitor prescription ________________________________ 77

Table 2.28: Predictors of ACE inhibitor prescription stratified by left ventricular function ___ 78

Table 2.29: In-hospital lipid measurement ________________________________________ 83

Table 2.30: Proportion of patients achieving therapeutic goals in ambulatory care _________ 85

Table 2.31: Achieving therapeutic goals for statins in ambulatory care __________________ 85

Table 2.32: Discontinuation in RCT of statins ____________________________________ 100

Table 2.33: Effect of initial drug choice on persistence with antihypertensive therapy _____ 102

xxii

Table 3.1: Response to pilot project _____________________________________________109

Table 3.2: Characteristics of respondents to pilot questionnaire _______________________110

Table 3.3: Sensitivity and specificity of questionnaire compared with interview __________112

Table 3.4: Drug contraindications ______________________________________________122

Table 3.5: Drug indications ___________________________________________________123

Table 3.6: Potential cumulative impact of secondary prevention therapy ________________126

Table 3.7: Clinical trial dosage regimen__________________________________________128

Table 4.1: Demographics of the study cohort______________________________________141

Table 4.2: Prior history of heart related disease. ___________________________________142

Table 4.3: History of cardiac procedures at hospital admission________________________143

Table 4.4: Drug use prior to hospital admission____________________________________143

Table 4.5: Details of hospital stay ______________________________________________144

Table 4.6: Characteristics of myocardial infarction. ________________________________145

Table 4.7: Cardiac complications during hospital course_____________________________145

Table 4.8: Investigations and procedures during hospital admission____________________146

Table 4.9: Risk factors documented during admission_______________________________146

Table 4.10: Mean and distribution of comorbidity index_____________________________147

Table 4.11: Reasons for exclusion from follow-up _________________________________148

Table 4.12: Reasons for non-response to follow-up_________________________________148

Table 4.13: Reason for no patient interview_______________________________________149

Table 4.14: Time from discharge to completion of patient questionnaire ________________149

Table 4.15: Time from discharge to completion of GP questionnaire ___________________149

Table 4.16: Time lag from patient to doctor questionnaire ___________________________150

Table 4.17: Inhospital or post-discharge cardiac rehabilitation ________________________150

Table 4.18: Early follow-up consultations ________________________________________151

Table 4.19: Healthcare since index admission _____________________________________151

Table 4.20: Patient satisfaction with patient-provider interaction ______________________152

Table 4.21: Providers of information about medications _____________________________153

Table 4.22: Medications reported at follow-up ____________________________________153

Table 4.23: Smoking status at follow-up _________________________________________154

Table 4.24: Changes in health transition _________________________________________154

Table 4.25: SF-36 Item mean scores ____________________________________________155

Table 4.26: Differences in SF-36 scores between surveys____________________________155

Table 4.27: Shortness of breath related to the heart _________________________________156

Table 4.28: Differences in shortness of breath between surveys _______________________156

Table 4.29: Angina medication use and chest pain. _________________________________156

Table 4.30: Mean scores for each component of SAQ_______________________________157

xxiii

Table 4.31: Differences in SAQ scores between surveys ____________________________ 157

Table 4.32: Sociodemographic factors at follow-up ________________________________ 157

Table 4.33: Number of visits to general practitioner ________________________________ 158

Table 4.34: Days between visits _______________________________________________ 158

Table 4.35: Comparison of responders and non-responders to the patient surveys_________ 160

Table 4.36: Comparison of interviewed and non-interviewed patients __________________ 161

Table 4.37: Comparison of post-discharge care by patient interview ___________________ 162

Table 4.38: Comparison of patient-provider interaction by patient interview_____________ 163

Table 4.39: Comparison of drug use by patient interview. ___________________________ 163

Table 4.40: Comparison of SF36 scores by patient interview _________________________ 164

Table 4.41: Comparison of antianginal medications by patient interview________________ 164

Table 4.42: Comparison of social factors by patient interview ________________________ 165

Table 4.43: Patient characteristics by availability of GP questionnaire__________________ 166

Table 4.44: Care in early follow-up period by availability of GP questionnaire___________ 167

Table 4.45: Tests and procedures by availability of GP questionnaire __________________ 168

Table 4.46: Patient-provider interaction by availability of GP questionnaire _____________ 169

Table 4.47: Medication use by availability of GP questionnaire_______________________ 169

Table 4.48: SF-36 score by the availability of GP questionnaire ______________________ 171

Table 4.49: Antianginal medications and chest pain by availability of GP questionnaire____ 172

Table 4.50: Social factors by availability of GP questionnaire ________________________ 172

Table 5.1: Drug prescription by Comorbidity index ________________________________ 182

Table 5.2: Variation in new prescription rates among cardiologists ____________________ 183

Table 5.3: Influence of relative contraindications on antiplatelet prescription.____________ 185

Table 5.4: Influence of relative contraindications by treatment speciality. _______________ 185

Table 5.5: Antiplatelet prescription by demographic and clinical variables ______________ 186

Table 5.6: Independent predictors for prescription of antiplatelets _____________________ 187

Table 5.7: Influence of relative contraindications for beta-blocker prescription___________ 190

Table 5.8: Influence of relative contraindications by treatment specialty. _______________ 190

Table 5.9: Beta-blocker prescription by demographic and clinical variables _____________ 191

Table 5.10: Independent predictors of beta-blocker prescription ______________________ 193

Table 5.11: Independent predictors for beta-blocker prescription by treatment specialty____ 194

Table 5.12: Statin doses (mg) prescribed at discharge_______________________________ 195

Table 5.13: Unadjusted odds ratio (OR) for statin prescription by lipid levels ____________ 197

Table 5.14: New statin prescription by demographic and clinical variables ______________ 198

Table 5.15: Logistic regression model for new statin prescription _____________________ 199

Table 5.16: Cardiologist by prescribing rate ______________________________________ 201

Table 5.17: ACE inhibitor doses (mg) prescribed at discharge ________________________ 202

xxiv

Table 5.18: Influence of relative contraindications to ACE prescription_________________203

Table 5.19: Influence of indications on ACE inhibitor prescription ____________________203

Table 5.20: ACE inhibitor prescription by indication and treatment speciality ____________204

Table 5.21: ACE inhibitor prescription by indication _______________________________204

Table 5.22: Influence of heart failure and LVD on ACE inhibitor prescription ___________204

Table 5.23: Changes in ACE inhibitor prescription over the study by indication __________205

Table 5.24: New ACE inhibitor prescriptions over the study _________________________205

Table 5.25: ACE inhibitor prescription by demographic and clinical variables. ___________206

Table 5.26: Logistic regression model for ACE inhibitor prescription at discharge ________207

Table 5.27: Logistic regression models for new ACE inhibitor prescription______________209

Table 5.28: Logistic regression model for ACE inhibitor prescription __________________210

Table 5.29: Influence of indications on calcium antagonist prescriptions ________________211

Table 5.30: Influence of angina on calcium antagonist prescription ____________________211

Table 5.31: Calcium antagonist prescription by demographic and clinical variables _______213

Table 5.32: Independent predictors for no calcium antagonist prescription_______________214

Table 5.33: Independent predictors for new calcium antagonist prescription _____________214

Table 5.34: Independent predictors for calcium antagonist prescription by treatment ______215

Table 5.35: Comparison of factors associated with aspirin prescription _________________219

Table 5.36: Comparison of predictors of beta-blocker prescription_____________________223

Table 6.1: Medications at discharge reported in the early patient survey ________________234

Table 6.2: Information provided about medications in hospital________________________235

Table 6.3: Proportion of patients reporting interventions about risk factors ______________236

Table 6.4: Written information provided at discharge _______________________________237

Table 6.5: Reported referrals at discharge ________________________________________237

Table 6.6: Concern about purpose of medication___________________________________238

Table 6.7: Reported satisfaction with care received in hospital ________________________239

Table 6.8: General practitioner comments about transition of care _____________________241

Table 6.9: Patient-directed strategies ____________________________________________243

Table 6.10: Barriers to education strategies _______________________________________243

Table 6.11: Barriers to providing appropriate written materials _______________________244

Table 6.12: Barriers to an effective review prior to discharge _________________________246

Table 6.13: Correspondence with the patient’s nominated general practitioner. ___________246

Table 7-1: Medication use prior to admission _____________________________________254

Table 7-2: Missed opportunity for secondary prevention of CHD______________________255

Table 7-3: ACE inhibitor use by previous history __________________________________256

Table 7-4: Population estimates of drug use in patients with a history of CHD ___________257

Table 7-5: Comparison of estimates with prescriptions at discharge post-MI. ____________257

xxv

Table 7-6: Comparison of drug use at follow-up with prescriptions at discharge __________ 258

Table 7-7: Influence of period of enrolment on drug use at follow-up __________________ 259

Table 7-8: Trends in drug use from hospital discharge to late follow-up ________________ 259

Table 7-9: Initiation of therapy in 223 respondents to both surveys ____________________ 260

Table 7-10: Odds of initiating therapy compared to odds of initiating statins_____________ 260

Table 7-11: Discontinuation of therapies in 223 respondents to both surveys ____________ 261

Table 7-12: Odds of discontinuation compared` to the odds of discontinuing statins_______ 261

Table 7-13: Reasons reported for drug discontinuations _____________________________ 262

Table 7-14: Prescription of antiplatelet agents in primary care ________________________ 263

Table 7-15: Daily dosages of aspirin prescribed ___________________________________ 263

Table 7-16: Prescription of beta-blockers in primary care____________________________ 264

Table 7-17: Daily dosages of beta-blockers prescribed ______________________________ 265

Table 7-18: Prescription of lipid lowering therapy in primary care_____________________ 266

Table 7-19: Daily doses of statins prescribed _____________________________________ 267

Table 7-20: ACE inhibitor prescription in primary care _____________________________ 268

Table 7-21: Daily dosages of ACE inhibitors prescribed in primary care________________ 269

Table 7-22: Prescription of calcium antagonists ___________________________________ 270

Table 7-23: Initiation of calcium antagonist during follow-up ________________________ 270

Table 7-24: Proportion of patients prescribed an effective dose _______________________ 271

Table 7-25: Drug inventory at interview compared with questionnaire _________________ 272

Table 7-26: Discordant pairs by drug class _______________________________________ 273

Table 7-27: General practitioner discordant pairs __________________________________ 273

Table 7-28: Concordance by drug group at late follow-up ___________________________ 274

Table 7-29: Drug use prior to admission by gender_________________________________ 282

Table 7-30: Drug use prior to admission by period of study __________________________ 284

Table 7-31: Smoking and medication use with CHD _______________________________ 285

Table 7-32: Drug use prior to admission by previous medical history __________________ 286

Table 7-33: CHD subgroup1 drug use prior to admission by previous medical history _____ 287

Table 7-34: Drug use with number of concomitant secondary prevention therapies________ 288

Table 7-35: Trend analysis for number of drugs used in the CHD cohort________________ 288

Table 7-36: Independent predictors of antiplatelet use ______________________________ 290

Table 7-37: Independent predictors of beta-blocker use _____________________________ 290

Table 7-38: Independent predictors of lipid lowering therapy use _____________________ 291

Table 7-39: Independent predictors of ACE inhibitor use____________________________ 291

Table 7-40: Independent predictors of calcium antagonist use ________________________ 292

Table 7-41: Predictors of underuse of cardioprotective therapies ______________________ 292

Table 7-42: Number of drug discontinued________________________________________ 293

xxvi

Table 7-43: Drug discontinuation by characteristics at hospital discharge _______________294

Table 7-44: Drug discontinuation by medical history on admission ____________________294

Table 7-45: Drug discontinuation by inpatient experience____________________________296

Table 7-46: Drug discontinuation by post-discharge treatment ________________________297

Table 7-47: Drug discontinuation by patient-general practitioner relationship ____________298

Table 7-48: Drug discontinuation by risk factor monitoring __________________________298

Table 7-49: Drug discontinuation by concomitant therapies __________________________299

Table 7-50: Drug discontinuation by current status _________________________________299

Table 7-51: Drug discontinuation by heart related health ____________________________300

Table 7-52: Drug discontinuation by Seattle Angina Questionnaire scores1 ______________300

Table 7-53: Drug discontinuation by general health status ___________________________301

Table 7-54: Multivariate logistic regression model for drug discontinuation _____________303

Table 8.1: Lipid levels (mmol/L) at the time of admission ___________________________320

Table 8.2: Missed opportunity for treatment with statins with prior CHD________________321

Table 8.3: Bivariate analysis of patient characteristics and complete lipid profile _________322

Table 8.4: Multivariate analysis for predictors of lipid profile recorded _________________322

Table 8.5: Inpatient management of lipids ________________________________________323

Table 8.6: Lipid concentrations (mmol/L) by newly prescribed statin __________________324

Table 8.7: Lipid levels as predictors of statin prescription____________________________324

Table 8.8: Last lipid measurement at late follow-up________________________________325

Table 8.9:Mean lipid levels (mmol/L) at follow-up by statin use ______________________326

Table 8.10: Direct comparison of lipid levels following statin prescription ______________326

Table 8.11:Changes in lipids from MI to late follow-up in all patients __________________327

Table 8.12: Factors associated with achieving therapeutic goals_______________________329

Table 8.13: Bivariate analysis for factors associated with having high lipid levels_________330

Table 8.14: Logistic regression model for achieving therapeutic goals __________________331

Table 8.15: Logistic regression model for high lipids _______________________________331

Table 8.16: Inpatient management of blood pressure________________________________332

Table 8.17: Last blood pressure measurement at late follow-up _______________________333

Table 8.18: Distribution of blood pressure at follow-up _____________________________333

Table 8.19: Prescription of BP lowering medications by blood pressure_________________334

Table 8.20: Blood glucose during hospital admission_______________________________334

Table 8.21:In hospital blood glucose intervention __________________________________335

Table 8.22: Blood glucose monitoring in follow-up care_____________________________335

Table 8.23: Blood glucose and HbGA1 levels _____________________________________336

Table 8.24: Smoking intervention ______________________________________________337

Table 8.25: Smoking status at follow-up _________________________________________337

xxvii

Table 8.26: Weight management interventions ____________________________________ 338

Table 8.27: Physical activity interventions _______________________________________ 338

xxix

List of Figures

Figure 1.1: Continuum of patient care following an acute event for a chronic condition ______ 9

Figure 1.2: Project outline _____________________________________________________ 13

Figure 4.1: Patient participation in study_________________________________________ 139

Figure 4.2: Sample population by age and gender__________________________________ 141

Figure 4.3: Patient perception of health compared to 12 months ago ___________________ 154

Figure 5.1: Drug prescriptions by gender ________________________________________ 180

Figure 5.2: Percentage prescribed drugs by age____________________________________ 181

Figure 5.3: Trends in drug prescription (percentage) with annual quarters_______________ 182

Figure 5.4: Drug prescription by treatment specialty________________________________ 183

Figure 5.5: Changes in ACE inhibitor prescription over the study _____________________ 200

Figure 5.6: Changes in cardiology prescribing of ACE inhibitors______________________ 201

Figure 7.1: Use of cardioprotective therapies _____________________________________ 255

Figure 7.2: Drug use prior to admission by age____________________________________ 283

xxxi

Commonly Used Abbreviations

ACE inhibitors Angiotensin converting enzyme inhibitors

ACC American College of Cardiology

ACCEPT American College of Cardiology Evaluation of Preventive Therapeutics

ACS Acute Coronary Syndrome

AF Atrial Fibrillation

AHA American Heart Association

AIRE Acute Infarction Ramipril Efficacy Study

AMI Acute Myocardial Infarction

APAC Australian Pharmaceutical Advisory Council

ARB Angiotensin Receptor Blockers

ASPIRE Action on Secondary Prevention through Intervention to Reduce Events

CABG Coronary Artery Bypass Graft

CAPRIE Clopidogrel versus Aspirin in Patients at Risk of Ischaemic Events

CARE Cholesterol and Recurrent Events

CARP Coronary Artery Revascularisation Procedure (CABG or PCI)

CCP Cooperative Cardiovascular Project

CHAMP Cardiac Hospitalisation Atherosclerosis Management Program

CHD Coronary Heart Disease

CHF Congestive Heart Failure

CK Creatine Kinase

COPD Chronic Obstructive Pulmonary Disease

CURE Clopidogrel in Unstable angina to prevent Recurrent Events

CVD Cerebrovascular Disease

ENACT European Network for Acute Coronary Treatment

EUROASPIRE European Action on Secondary Prevention through Intervention to

Reduce Events

EUROPA EURopean trial On reduction of cardiac events with Perindopril in stable

coronary Artery disease

GAP Guidelines Applied in Practice

GTN Glyceryl Trinitrate

GP General Practitioner

HDL-C High Density Lipoprotein Cholesterol

HOPE Heart Outcomes Prevention Evaluation study.

HR Hazard Ratio

xxxii

HMG CoA Hydroxymethyl glutaryl coenzyme A reductase inhibitor (statins)

IFG Impaired Fasting Glucose

IHD Ischaemic Heart Disease

LDL-C Low Density Lipoprotein Cholesterol

LIPID Long-term Intervention with Pravastatin in Ischaemic Disease

LOS Length of stay

LVD Left Ventricular Dysfunction

LVEF Left Ventricular Ejection Fraction

MI Myocardial Infarction

MONICA MONItoring of trends and determinants in CArdiovascular disease

NCEP National Cholesterol Education Program

NRMI The National Registry of Myocardial Infarction

OR Odds Ratio

PBS Pharmaceutical Benefits Scheme

PCI Percutaneous Coronary Intervention

RAAS Renin Angiotensin Aldosterone System

RCT Randomised Control Trial

RMO Resident Medical Officer

RR Relative Risk

SAQ Seattle Angina Questionnaire

SAVE Survival and Ventricular Enlargement

SOLVD Studies of Left Ventricular Dysfunction

STEMI ST Elevation Myocardial Infarction

TC Total Cholesterol

TRACE Trandolapril Cardiac Evaluation

4S Scandinavian Simvastatin Survival Study

VF Ventricular fibrillation

VT Ventricular Tachycardia

1 Chapter 1: Introduction

CHAPTER 1

INTRODUCTION

1.1 Overview

This thesis examines pharmacotherapy use for long-term risk reduction in patients with

coronary disease. In particular, it is concerned with the underuse of these therapies. This is

because the underuse of effective preventive therapies represents a loss of opportunity to reduce

mortality, morbidity and relative costs. This study provides an example of the broader issue of

the prevention and management of chronic disease in the study setting and informs on current

practice, including barriers and enablers within the current system to optimal use of preventive

therapies.

This observational study examined the use of these therapies in post-myocardial infarction (MI)

patients admitted to a tertiary hospital and an affiliate hospital in Perth, Western Australia.

Information about prescriptions at discharge was obtained from medical record review. A

subset of these patients and their general practitioners were contacted over the following year to

measure ongoing use of therapies.

This chapter provides background to the study and places it within the context of quality in

health care, particularly the rational use of medicines. It provides a brief overview of the

Australian healthcare system and quality improvement initiatives in Australia, the United

Kingdom and the United States. This is followed by an overview of the concept of the

continuum of patient care following an acute episode of a chronic condition. It introduces the

concept that barriers are present at every level from the patient through to the health care setting

and society. The hypothesis and aims of the research are then enunciated followed by a brief

description of the organisation of the thesis.


1.2 Background to the study

1.2.1 Quality in healthcare

The quality of health care has become a priority in the delivery of health care over the last

decade. Chassin and Galvin defined quality of health care as, “The degree to which health

services for individuals and populations increase the likelihood of desired health outcomes and

are consistent with current professional knowledge” (Chassin et al. 1998). Until about 20 years

ago it was assumed that, following publication in the medical literature, advances in medical

knowledge were appropriately translated into practice. In recent years, however, gaps between

evidence and practice have been documented in all health care settings and in all types of

treatment whether preventive, chronic or acute (Schuster et al. 1998). Several factors have

contributed to this.

The explosion of new knowledge generated about the efficacy, or lack of it, of many therapies

in recent years has enabled reliable and valid quality indicators to be developed. These in turn

have led to the documentation of widespread failures in the application of existing knowledge to

routine care. Paradoxically, while it is the new evidence about the effectiveness of therapies

that has provided part of the impetus for the Quality Movement, it has also been part of the

problem. Methods of training clinicians and the systems for supporting them in the delivery of

health care have not kept pace with the overwhelming increase in knowledge about efficacy

(Chassin et al. 1998).

The move to improve the quality of health care also coincides with an imperative to contain

spending within the health care sector (Bodenheimer 1999; Woolf et al. 1999). In the 35 years

from 1960 to 1994 the mean proportion of GDP devoted to health in OECD countries increased

from 5% to 10% (Mooney et al. 1999) and this is likely to increase with a rapidly aging

population. In Australia, health expenditure as a proportion of GDP more than doubled over the

last four decades, from 4.2% in 1960–61 to 9.5% in 2002–03 (Australian Institute of Health and

Welfare 2004a).

The goals of the application of evidence-based medical knowledge and cost containment may be

at odds. Reducing problems of overuse and misuse of treatments is ultimately about increasing

patient safety by reducing possible harm. On the other hand, underuse of effective therapies

leads to major foregone opportunities to improve health and function. Therefore, while

reducing overuse/misuse increases quality of health care and reduces the cost, fixing problems

of underuse increases both the quality and cost of health care. The exception to this is

preventive treatments, where the disease or complication prevented would otherwise cost more

than the preventive treatment.


It is the underuse of effective preventive therapies that is the subject of this thesis. While

preventive therapies in the context of quality health care include screening tests, monitoring of

risks and lifestyle factors, it is the underuse of pharmacotherapies that is the focus of this work.

The rational or quality use of medicines is based on the criteria that prescribing should be

appropriate, effective, safe and economic. Differences in the quality of prescribing have been

observed at every level from individual clinicians, hospitals and group practices to geographical

variations at regional and national levels. In a study of international variation in prescribing

patterns Veninga et al found that little of the difference in prescribing could be attributed to

deviations from guidelines in terms of knowledge and attitudes. Rather it was the regulation,

marketing and distribution of drugs that seemed to be of much more importance. Other factors

that contributed to differences in prescribing were education, sources of information and

organisation of practices as well as the regulation, reimbursement and organisation of health

care (Veninga et al. 2000).

Pharmaceuticals account for a significant and increasing proportion of health care spending. In

Australia, for the financial year 2000-01, pharmaceuticals accounted for 16% of the total

government spending on health, a 50% increase from the previous five years (Mooney et al.

1999; Australian Institute of Health and Welfare 2003). Concern about the rising cost of

prescribed drugs led to various initiatives to curb prescribing or at least to alter the pattern of

drug utilisation (Bradley 1991). Much of the early effort towards the rational use of medicine

related to concern about the risk of excessive prescribing of inappropriate or unnecessary drug

therapy. Irrational use of drugs is still most commonly associated with over prescribing, multi-

drug prescribing, misuse and use of unnecessary expensive drugs (Le Grand et al. 1999). The

growing armamentarium of pharmacotherapies known to be effective has seen a shift towards

concerns about the consequences of under prescribing of potentially beneficial therapies (Smith

1996; Rochon et al. 1999b). Following from this is the realisation that strategies that seek to

limit the number of drugs prescribed in the name of improving quality of care may be seriously

misdirected (Rochon et al. 1999b). The increasing emphasis on the management of chronic

disease and preventive medicine, rather than acute care of acute conditions, has also contributed

to the growing concern with underuse, which is most common in these settings. The prevention

of fatal and non-fatal cardiac events in patients known to have coronary heart disease, referred

to as secondary prevention, provides a good example of possible underuse of effective

preventive therapies.


Multiple levels at which change can occur to improve the quality of health care have been

suggested (Table 1.1). Successful quality improvement also requires: leadership at all levels; a

pervasive culture that supports learning throughout the care process; an emphasis on the

development of effective teams; and greater use of information technologies for both continuous

improvement work and external accountability (Ferlie et al. 2001).

Table 1.1: Four levels for improving quality

Level Intervention

Individual Education

Academic detailing

Data feedback

Benchmarking

Guideline, protocol, pathway implementation

Leadership development

Group/team Team development

Task redesign

Clinical audit

Breakthrough collaborative

Guideline, protocol, pathway implementation

Organisation Quality assurance

Continuos quality improvement/total quality management

Organisation development

Organisation culture

Organisation learning

Knowledge management/transfer

Health care system National bodies

Evidence-based practice centres

Accrediting/licensing agencies

Public disclosure

Payment policies

Legal systems

(Ferlie et al. 2001)

The degree to which each level can influence the quality use of medicines depends on the

environment in which the health care system operates. The United Kingdom with its centralised

National Health Service (NHS) and the United States with its pluralistic and decentralised

system are often thought to represent the two extremes. Australia with its blend of universal

health cover and privately funded health care sits in between.


1.2.2 The Australian healthcare system

1.2.2.1 The Hospital Sector

The hospital sector comprises a mix of public and private hospitals. Public hospitals are funded

through the State governments under a funding arrangement with the Commonwealth. All

Australians are entitled to free access to treatment and accommodation as public patients in

public hospitals. Patients may have private insurance to cover treatment and accommodation as

a private patient in either a public or private hospital. Privately insured patients may opt to be

treated as a public patient when presenting to an emergency department of a public hospital

since treatment as a private patient in a public hospital may result in out of pocket expenses.

The medical team usually comprises a resident medical officer, a registrar and a consultant.

Clinical pharmacists are assigned to one or more wards in tertiary hospitals.

Hospital discharge in the study setting

As part of standard care, the resident medical officer completes a handwritten proforma at the

time of discharge. The patient is given a copy and another copy is sent to the patient nominated

general practitioner. In some hospitals, and in some departments, the resident medical officer

may also dictate a more detailed discharge summary that is subsequently forwarded to the

general practitioner. In the case of private patients, the treating specialist may send a detailed

typed discharge summary to the general practitioner.

1.2.2.2 Medical services

All Australians are automatically insured for medical services provided outside hospitals by

private practitioners on a fee-for-service basis at 85% of the fee set under the Medicare Benefits

Schedule (MBS). Beneficiaries must be referred for specialist consultations by their general

practitioner (GP) to be covered by the MBS for these consultations.

The remaining out of pocket expense for medical services is subject to a maximum gap per

service ($335.50 at January 2005) after which 100% of the scheduled fee is reimbursed.

Doctors, however, are free to set their fees above the MBS fee in which case the patient must

meet the difference. An annual safety net is also in place for concession and general

beneficiaries. At January 2005, the thresholds were $306.90 and $716.10 for concession and

general beneficiaries respectively. Once this threshold is reached, 80% of out-of-pocket costs

are reimbursed.

Doctors may also bill the MBS directly (bulk-billing) and receive just the 85% of the scheduled

fee. The latest statistics suggest that two thirds of all general practitioner consultations are

billed in this manner, although only one quarter of specialist consultations are bulk-billed

(Department of Health and Aging 2003).


1.2.2.3 Pharmaceuticals

The Pharmaceutical Benefits Scheme (PBS) is a Commonwealth funded scheme, which

subsidises the cost of government listed prescription medicines, dispensed by private

pharmacies. Over 90% of all drugs available are listed on the PBS. Patients are classified into

two groups: concession and general beneficiaries. Concession beneficiaries, pensioners and

other low-income groups, are charged a relatively small fee per prescription (currently $4.60) up

to a maximum of 52 items a year, after which all prescriptions are free. General beneficiaries

receive a subsidy only on items costing more than the threshold (currently $28.60), in which

case they pay the threshold with the remainder subsided. A safety net for general beneficiaries

is available after out-of-pocket expenses within one calendar year exceed a specified amount

(currently $874.90). This allows general beneficiaries to pay only the concession rate for the

reminder of the year.

Brand choice (Reference based pricing)

The PBS will pay only for the cost of the cheapest brand of any drug. When a more expensive

drug is prescribed the beneficiary must pay the difference between the cost of that brand and the

lowest priced drug. This extra cost does not count towards the PBS safety net. Pharmacists are

able to substitute a cheaper generic for the more expensive drug, with the approval of the client.

1.2.3 International approaches to quality in health care

In the United States, the Institute of Medicine convened the National Round Table on Health

Care Quality in 1995 to help increase awareness of quality in health care. The National

Committee for Quality Assurance has a primary focus on the underuse of health care within

Health Management Organisations. This voluntary system provides accreditation for Health

Management Organisations and publishes measures of performance in the Health Plan

Employer Data and Information Set. The Health Care Financing Administration is responsible

for ensuring that institutions providing services to Medicare and Medicaid beneficiaries meet

certain standards of quality and compliance is compulsory.

In the United Kingdom, the National Institute of Clinical Excellence was set up as a Special

Health Authority for England and Wales in 1999. Part of the NHS, its role is to provide

patients, health professionals and the public with authoritative, robust and reliable guidance on

current “best practice”. This covers both individual health technologies (including medicines,

medical devices, diagnostic techniques, and procedures) and the clinical management of specific

conditions. The NHS Frameworks in key clinical areas provide a set of explicit minimum

standards to which the localities are expected to adhere. At a more local level clinical

governance and quality-improvement collaboratives are designed to involve and empower local

providers and managers.


In Australia, the National Health and Medical Research Council has published Guidelines for

the Development and Implementation Of Clinical Practice Guidelines (National Health and

Medical Research Council (NHMRC) 1999), as well as publishing a number of specific

guidelines. Efforts to improve the use of medicines through a national medicines policy have

been underway for more than a decade. The Pharmaceutical Health and Rational Use of

Medicines (PHARM) committee and the Australian Pharmaceutical Advisory Council (APAC)

were established to advance the National Medicines Policy which was released in 2000 with the

core objectives of: providing timely access to medicines; medicines meeting appropriate

standards of quality, safety and efficacy; quality use of medicines; maintaining a responsible

and viable medicines industry. (Commonwealth Department of Health and Aged Care 1999).

APAC and PHARM have sought to achieve their gaols through policy development and funding

of strategic research (Pharmaceutical Health and Rational Use of Medicines Committee

(PHARM) et al. 2001). The six strategic areas for quality use of medicine include: policy

development and implementation; facilitation and coordination of Quality Use of Medicine

(QUM) activities at a national level; provision of objective information and assurance of ethical

promotion of medicine; training of health professionals in QUM; provision of services and

appropriate interventions; and routine data collection (Commonwealth Department of Health

Housing and Community Services 1995). The Australian Government also funds the National

Prescribing Service a non-profit organisation independent of government and the

pharmaceutical industry with a mission to “create an awareness, culture and environment that

will support Quality Use of Medicines among all stakeholders” (National Prescribing Service).

Good progress has been made in all these strategies (Roughead et al. 1999). There are, however,

to date no national or state-wide explicit minimum standards nor systems for monitoring and

feedback of performance on a wide scale (Scott 2002). Facilitating the improvement in quality

of care must also ensure that there is adequate infrastructure for monitoring changes in practice

and for producing, gathering, summarising and disseminating evidence (Sheldon et al. 1998).

Recent initiatives should address this problem.

Early in 2000 the Australian Council on Safety and Quality was established, to ensure that

systematic improvement occurs within the health care system through an increase in the safety

and quality of health care provision while the National Institute of Clinical Studies (NICS),

“Australia’s agency for closing the gaps between evidence and health care” was only

established at the end of 2000 (National Institute of Clinical Studies (NICS); National Health

Priorities and Quality 2002a). Finally, the Clinical Support Systems Program (CSSP), a joint

initiative of the Commonwealth Government and the Royal Australasian College of Physicians

was established with funding provided by the Commonwealth Government is with additional

funding and strong support provided by the New South Wales and Victorian governments


(National Health Priorities and Quality 2002b). The purpose of the CSSP is to evaluate the

effects of combining evidence based medicine with tools for clinical practice improvement with

the main aim to set up a cycle of continuous improvement and to work towards creating systems

that will: CSSP. The CSSP will provide input to both the Safety and Quality Council and NICS.

National guidelines to achieve the continuum of quality use of medicines between hospital and

community were published in 1998 (Australian Pharmaceutical Advisory Council 1998) and are

currently under review. This encompassed seven principles that relate to:

• development of a medication discharge plan,

• accurate medication history at the time of admission,

• evaluation of current medications at the time of admission, in consultation with the patient's

general practitioner, including appropriateness and effectiveness, allergies and any previous

adverse drug reactions and compliance with medication regime,

• communication with patient and other interested parties about the treatment plan, including

the provision of interpreters where applicable and appropriate written information. Issues

about compliance should also be addressed,

• pre-discharge medication review and dispensing of adequate medication should take place

in a planned and timely fashion,

• provision of verbal and written information including: with a discharge folio containing

relevant information such as Consumer Medicine Information; a medication record;

patient/carer plan; and information on the availability and future supply of medication,

• communication with patient’s nominated health care provider prior at the time of discharge

with details of the admission, medication changes (including additions/deletions) and

arrangements for follow-up have been communicated to the healthcare provider(s)

nominated by the patients as being responsible for his or her ongoing care.


1.3 The problem: Under use of preventive therapies

Increasingly, the resources for health care have shifted away from the care of acute disease to

the management of chronic disease in ambulatory care, albeit interspersed with acute episodes

requiring hospitalisation. The management of chronic disease is a multidisciplinary process as

depicted in Figure 1.1. Multiple opportunities for failure exits within this process with the result

that the preferred outcome of reduced risk of further events or complications of the disease is

not achieved. At the hospital level these include implementation of the appropriate treatment

plan and effective transition of care through effective communication with both the primary care

provider and the patient. In ambulatory care, the primary care provider has a role in maintaining

an optimal treatment plan with appropriate adjustments while the patient is the final arbiter of

whether or not to adhere with the treatment plan. Both the initial interaction with the hospital

and the ongoing interaction with the primary care provider are important factors in achieving

optimal treatment results and enhanced patient outcomes.

Figure 1.1: Continuum of patient care following an acute event for a chronic condition

Risk Reduction

Primary care provider Patient

Acute Event

Maintain /Enhance the care plan

Adher

e to

the

care

plan

Acute Event

Inpatient Care

Ambulatory Care

Implement the care plan

Patient/Provider interaction

Patient EducationTransition of c

are


Possible barriers to optimal care within the health care system adapted from Pearson (Pearson et

al. 1996) are summarised in Table 1.2. Treatment of patients with coronary heart disease

provides a good example. In addition to the influence of individual hospitals and primary care

providers, the health care system can provide barriers to the implementation of optimal care

through a lack of policy and standards and lack of reimbursement.

Table 1.2: Barriers to implementation of preventive services.

Level Barrier

Hospital

Acute care priority

Lack of resources and facilities

Lack of system for preventive services

Time and economic constraints

Poor communication between hospital and primary

care providers

Lack of policies and standards

Ambulatory care

Primary care Physician Problem-based focus

Feedback on prevention is negative or neutral

Time constraints

Lack of incentive, including reimbursement

Lack of training

Poor knowledge of benefits

Perceived ineffectiveness

Lack of skills

Lack of hospital-generalist communication

Lack of perceived legitimacy

Patient Lack of knowledge and motivation

Lack of access to care

Cultural factors

Social factors

(Pearson et al. 1996)

Adherence to recommended medications (and lifestyle changes) for the prevention of

cardiovascular disease is a crucial element in the path to the reduction of risk factors and

subsequent disease-related events. Lack of adherence to therapeutic regimens has been

recognised as a problem for many years (Sackett et al. 1979). Data suggest that by 12 months,

adherence to cardioprotective therapy, including Hydroxymethyl glutaryl coenzyme A (HMG-

CoA) reductase inhibitors and Angiotensin Converting Enzyme (ACE) inhibitors, had dropped


to 50% (Ockene et al. 2002). There is a clear need for more effective approaches to adherence

with emphasis on patients, providers, systems of health care delivery and relevant social factors.

A multidisciplinary task force of the American Heart Association addressed the problem of

adherence in a special report “The Multilevel Compliance Challenge”, which detailed the

importance of a multilevel approach including the patient, the provider and the health care

system. Patients need the knowledge, attitude, and skills to follow an appropriately prescribed

regimen. Providers need the knowledge, attitude and skills not only to follow established

guidelines in prescribing that regimen, but also to; (i) ensure that patients understand the reason

for prescribed dugs, the possible side effects, the interactions with other agents and the manner

in which the drug is to be taken; and (ii) recommend a regimen that is not unnecessarily

complex and therefore difficult to follow. The system or organisation within which the provider

works needs to provide resources and policies that support optimal practices, particularly

prevention oriented activities. A number of web-based resources have been developed to assist

patients to adhere to recommended therapies. These include the AHA Compliance Action

Program, which contains information tools for both patients and professionals (Compliance

Action Program), as well as the hospital based Get with the Guidelines (Get with the

guidelines).

The secondary prevention of coronary heart disease (CHD) provides one example of underuse

of effective treatment modalities. Survivors of myocardial infarction have a 10% risk of death

in the first year with a subsequent risk of 5% per year - six times that in people of the same age

who do not have CHD (Mehta et al. 1998). There is strong (Level 1) evidence that

pharmacotherapies are effective in reducing this risk, and guidelines have been developed to

assist in applying this evidence to clinical practice. Nonetheless, a number of shortcomings in

treatment have been documented in both North America and Europe (Ellerbeck et al. 1995;

Euroaspire I and II Group 2001). No such systematic evaluations have been conducted in

Australia, where only relatively small ad hoc projects have been conducted.


1.4 Hypothesis and aims of the research

This research evaluated the working hypothesis that there is underuse of cardioprotective

medications in patients with CHD due to underprescribing at hospital discharge and in primary

care, and, patients’ partial or complete non-adherence with the prescribed regimen. These

medications include antiplatelet agents, beta-blockers, hydroxymethyl glutaryl coenzyme A

(HMG CoA) reductase inhibitors (statins) and angiotensin converting enzyme (ACE) inhibitors.

This working hypothesis, if substantiated, lays the groundwork for appropriate systematic

changes in discharge planning and transition of care to increase the appropriate use of

medications. The objectives of the research were to

• Quantify the gap between evidenced-based recommendations for cardioprotective

medications and actual practice in the care plans implemented at hospital discharge and in

ongoing ambulatory care.

• Identify barriers to the use of effective therapies, at various points in the continuum of

patient care.

• Provide an evidential basis to recommend changes at all levels of health care to reduce these

barriers.


1.5 Project outline

The outline for the project is shown in Figure 1.2. The project involved patients with a hospital

discharge diagnosis of myocardial infarction and included a review of the hospital medical

record and early (3 months post-discharge) and late (12 months post-discharge) follow-up

surveys. These questionnaires collected data from patients and their primary care doctor.

Patient interviews at the time of the early follow-up provided some qualitative data on patterns

of medication use.

Figure 1.2: Project outline

Medical record review

Early patient survey

Eligible for late follow-up

Patient interview

Early GP survey

Late patient survey

Late GP survey

Consent to contact GP

Consent to contact GP

Eligible for follow-up


1.6 Organisation of thesis

1.6.1 Background and Literature Review : Chapters 1-2

Chapter one introduces this thesis within the context of improving quality in health care and, in

particular, the rational use of medicines. It provides a brief overview of the literature on quality

in health care and describes the tension between cost containment and quality when problems of

underuse are addressed. It outlines the continuum of patient care for chronic disease and

introduces the example of the prevention of cardiac events in patients known to have CHD. The

emphasis is placed on the health care system, hospitals and clinician behaviour in the care they

provide which includes enabling patients to adhere with the treatment regimen.

Chapter two provides a review of the literature on secondary prevention of CHD. The first

section provides a brief overview of the burden of CHD, the role of pharmacotherapies in the

secondary prevention of CHD, and sources of drug prescription and drug utilisation data. The

second section examines each drug class in turn with an overview of the available evidence for

the benefits in secondary prevention, and trends in the use of the various therapies. The third

section examines factors associated with the prescription of each secondary prevention therapy.

The final section specifically examines the use of drugs in ambulatory care including the

influences on prescribing in ambulatory care, and aspects of patient adherence.

1.6.2 Methods: Chapter 3

Chapter three describes the approach taken in designing this study. It describes the

development of the project, including the development of the research instruments, early

investigations on the feasibility of the project and the validation of the research instruments. It

describes how the project was conducted and how the data were analysed.

1.6.3 Results and discussion: Chapters 4-8

Each of these chapters examines a different aspect of the continuum of care and includes both

the results and discussion of the implications of the results.

Chapter four describes the study sample and the follow-up cohort and examines the validity of

the sample by comparing characteristics between participants and non-participants for each

phase of the study.

Chapter five describes the pattern of prescription at hospital discharge and examines the extent

to which these are explained by current recommendations.

Chapter six examines the process of communicating the care plan implemented at hospital

discharge. This is examined first from the patients’ perspective, then from the perspective of


the general practitioner and, finally, from the perspective of hospital staff involved in patient

education and discharge.

Chapter seven examines the use of medications in ambulatory care. The first part examines the

prevalence of these therapies prior to admission and during follow-up. The second part details

the treatment regimen prescribed. The third part examines aspects of patient adherence. The

final part examines predictors of drug discontinuation during the follow-up.

Chapter eight examines the management of coronary risk factors. Management of lipids is

examined in some detail including the management of lipids prior to the index admission,

during the inpatient period and then in follow-up. Other risk factors examined include high

blood pressure, smoking, hyperglycaemia, weight management and physical activity.

1.6.4 Final discussion and recommendations: Chapter 9

This final chapter brings together all the results and discusses their implications for the quality

of care for chronic disease in the Australian health care setting. It makes recommendations on

strategies that could be implemented to increase adherence with best practice and through them

to ensure patient adherence with the treatment regimen.

17 Chapter 2: Review of the literature

CHAPTER 2

REVIEW OF THE LITERATURE

2.1 Overview

Reducing the risk of fatal and non-fatal cardiac events in patients with known CHD provides

one example of the management of chronic disease within the existing Australian health system.

In epidemiological terms this represents tertiary prevention. However, in the cardiovascular

literature it is idiosyncratically referred to as secondary prevention (Ebrahim et al. 2005). This

thesis follows that convention.

The extent of CHD within the community and the strong evidence for benefits of a number of

strategies in reducing the risk of initial and subsequent cardiac events provide an opportunity to

prevent significant numbers of events by appropriate management. Based on Perth MONICA

(MONItoring of trends and determinants in CArdiovascular disease) data (1985-93), almost

60% of all CHD deaths and 35% of non-fatal myocardial infarctions occur in people with a

previous hospital admission for CHD, although they represented only 5% of the population

(McElduff et al. 2001).

This chapter provides a review of the literature on the secondary prevention of CHD. The

chapter is divided into Background, Evolution of Secondary Prevention, Evidence-Based

Prescribing and Drug utilisation in Ambulatory Care.


2.2 Background

This section provides a summary of trends in the burden of CHD over time. This is followed by

an outline of pharmacotherapies used in the secondary prevention of CHD with a brief summary

of the mechanisms of risk reduction. Finally, the various sources of drug prescription and drug

utilisation data available are reviewed.

2.2.1 Burden of coronary heart disease

Despite an average annual decrease in CHD mortality of 4.8% in the 10 years from 1988 to

1998, and a more than a two-fold decrease in CHD mortality between the late 1960s and 1999

(de Looper et al. 2001), CHD remained the greatest single cause of death in Australia in 1999

accounting for 22% of deaths. Worldwide, there was an annual decrease of 4.5% with two

thirds of this attributed to a lower coronary event rate and one third to a decrease in 28 day case

fatality (Tunstall-Pedoe et al. 1999).

The decline in CHD related mortality is attributed to both reductions in various primary and

secondary coronary risk factors and improvements in treatment and care. Jamrozik et al found

that changes in risk factor prevalence between 1980 and 1983 accounted for about one half of

the decline in mortality attributed to CHD (Jamrozik et al. 1989). Hunick et al estimated that

about 25% of the decline in CHD related mortality between 1980 and 1990 was explained by

primary prevention, a further 29% resulted from reduction of risk factors in patients with CHD

and 43% by other improvements in the treatment of patients with CHD (Hunink et al. 1997).

In Australia, the age standardised incidence of CHD also decreased by one quarter between

1993/94 and 2001/02 (Australian Institute of Health and Welfare 2004b). The prevalence of

CHD in the 2001 National Health Survey was 1.9%, with about one third of these reporting a

heart attack. There was, however, a 12% increase in the age-standardised rate of

hospitalisations for CHD from 1993/94 to 2001/02, while hospitalisation for acute myocardial

infarction (AMI) over the same time increased by 23% (Australian Institute of Health and

Welfare 2004b). In 2001/02, CHD was the principal diagnosis for 2.5% of all hospital

admissions with one quarter for AMI (Australian Institute of Health and Welfare 2004b). While

the increased hospitalisation for CHD in general, and AMI in particular, is due at least in part to

improved survival, changes in diagnostic technology and case definitions (Antman et al. 2000)

will have also contributed to the observed trends.

2.2.1.1 Opportunities for a reduction in the burden of disease

Despite the observed reduction in incidence of CHD events and mortality, there are significant

further opportunities for reductions. In an assessment of care for post-MI patients in general

practice, Bradley et al estimated that there was the potential to prevent between 4 and 9 deaths


within the group of 266 patients over the next 2 years (Bradley et al. 1997). Using data from a

large international study it was calculated that greater use of aspirin, beta-blockers and ACE

inhibitors in “ideal” patients would respectively save 9, 11 and 23 lives per 1000 patients treated

per year (Alexander et al. 1998). McElduff et al estimated that a 40% reduction in coronary

events was possible if all Australian targets for risk reduction were achieved, of which more

than one third involved secondary prevention risk reduction (McElduff et al. 2001).

2.2.2 Pharmacotherapies in the secondary prevention of CHD

The treatment and care of patients with known CHD, particularly following an acute event,

boasts some of the best evidence for increased survival and decreased morbidity in any aspect of

medical practice (Thompson 2001b). Over the last 20 years a number of strategies have been

identified that reduce the risk of future cardiac events in patients with known CHD. These

include:

• Invasive revascularisation therapies including Coronary Artery Bypass Graft (CABG) and

Percutaneous Coronary Intervention (PCI),

• Lifestyle factors particularly smoking cessation, dietary changes and increases in physical

activity,

• Medical management of the risk factors hypertension, hyperlipidemia and diabetes.

• Pharmacotherapies that reduce the risk of cardiac related mortality and morbidity

independent of other established risk factors. These include:

• Antiplatelet agents

• Beta-blockers

• HMG CoA reductase inhibitors, or statins

• ACE inhibitors

In the light of the strong evidence for the beneficial effects of these strategies, there is a gap,

albeit decreasing, between recommendations and actual practice. In the case of lifestyle, risk

factors and pharmacotherapies, this shortfall can be attributed to both failure of healthcare

providers to prescribe and monitor these strategies and a failure by patients to adhere to

recommended strategies. This thesis is restricted largely to the use and underuse in clinical

practice of four relevant pharmacotherapies: antiplatelet agents; beta-blockers; statins and ACE

inhibitors.

2.2.2.1 Antiplatelet agents

Platelets and thrombosis play important roles in the pathogenesis of acute coronary syndromes.

The role of antiplatelet agents in preventing myocardial infarction has been reviewed

extensively (Fuster et al. 1993; Hennekens et al. 1997), and has led to almost universal

acceptance of its’ use in patients with CHD (Antman et al. 2004).


Antiplatelet agents inhibit the platelet aggregation process at various points in the platelet

aggregation cascade. Aspirin, the oldest and most commonly used agent, inhibits platelet

aggregation through inhibition of thromboxane A2 formation in platelets and the synthesis of

prostacyclin in endothelial cells. Thienopyridines are another class of antiplatelet agents which

act via a different mechanism by blocking ADP dependent activation of platelets. Clopidogrel

is the most commonly used of these agents and together with aspirin are currently recommended

as first line agents while the benefits of combining these two agents remains unclear (Tran et al.

2004b).

More recent understanding of the involvement of inflammation in the occurrence of Acute

Coronary Syndrome (ACS) suggests another role of aspirin, which is also a potent anti-

inflammatory agent (Topol 2001).

2.2.2.2 Beta-blockers

It is generally agreed that beta-blockers exert their protective influence by inhibiting the

adrenergic system and thereby attenuating a number of negative effects of the adrenergic system

in the immediate post infarction period, including persistent myocardial ischaemia and cardiac

arrhythmias (Frishman et al. 1999; Wiklund et al. 2002). Inhibition of the adrenergic system

results in attenuation of the arrhythmogenic potential of the acutely damaged myocardium,

reducing myocardial oxygen requirements and, therefore, myocardial ischaemia. Beta-blockers

also inhibit hemodynamic changes that are associated with atherosclerotic plaque rupture.

Although the evidence for beta-blockade in patients with AMI is based on older clinical trials,

there is support for their use in current practice (Kloner et al. 2004). Furthermore, the role of

beta-blockers has been extended to include the treatment of heart failure, initially considered a

contraindication to beta-blocker use (Giesler et al. 2004).

More recent evidence suggests an antiatherosclerotic effect of beta-blockers. Hedblad et al

found a reduced rate of progression of carotid intima-media thickness with beta-blockers in

asymptomatic patients with carotid plaque (Hedblad et al. 2001). Wiklund et al observed an

additive effect of beta-blockers to the statin mediated reduction in IMT progression leading to

the conclusion that statins and beta-blockers affect different mechanisms in the atherosclerotic

process (Wiklund et al. 2002).

2.2.2.3 HMG-CoA reductase inhibitors

HMG-CoA reductase inhibitors (statins) competitively inhibit the rate-limiting step in the

cholesterol synthesis pathway. The resulting reduction in intracellular cholesterol concentration

in the liver then activates low density lipoprotein cholesterol (LDL-C) receptors leading to

greater clearance of LDL-C (Gotto 1997). In addition to lowering LDL-C, statins cause


relatively small reductions in triglyceride levels (5 to 10%) in conjunction with minor increases

in high density lipoprotein cholesterol (HDL-C) (5 to 10%) (Vaughan et al. 2000).

The clinical benefit of cholesterol management, “a continuous, graded, strong relationship

between serum cholesterol and age-adjusted CHD death rate” is supported by more than 20

years of clinical and laboratory research (Stamler et al. 1986; Gotto 1997). This is supported by

more recent studies showing that statins slow the progression of atherosclerotic disease and

induce regression in some lesions (Nissen et al. 2004b)

The effects of statins have been so convincing in clinical trials of over 84,000 patients that

current recommendations advise the use of statins in all patients who have had a coronary event,

irrespective of cholesterol or LDL-C levels (Grundy et al. 2004). The notion of nonlipid effects

of statins is supported by the observation that the benefits of statins extend to patients with

“normal” LDL-C (Sacks et al. 1996; Long-term Intervention with Pravastatin in Ischaemic

Disease (LIPID) Study Group 1998; Heart Protection Study Collaborative Group 2002). These

so called pleiotropic effects of statins have been covered in a number of reviews (Gotto 1997;

Vaughan et al. 2000; Clark 2003).

The beneficial action of statins occurs rapidly and may yield clinically important anti-ischaemic

effects as early as one month after treatment commences (Cannon et al. 2004)

2.2.2.4 Angiotensin Converting Enzyme inhibitors

Several extensive reviews on the role of ACE inhibitors in CHD have been written including

those by Lonn et al and Gomma et al (Lonn et al. 1994; Gomma et al. 2002).

The Renin Angiotensin Aldosterone System (RAAS) is complex and acts as a circulating

hormonal system, endogenous tissue hormonal system with autocrine and paracrine effects and

a neurotransmitter and neuromodulator. ACE inhibitors inhibit the RAAS by inhibiting the

conversion of angiotensin I to angiotensin II (A2). The influence of ACE inhibitors in reducing

the risk of cardiovascular events appears to be mediated through its influence on the endogenous

RAAS by containing the negative effects of A2, including platelet aggregation, the activity of

white cells, and smooth muscle hypertrophy.

Normally A2 (whose effects in excess are harmful) is kept in check by the activity of

vasodilator agents (primarily nitrous oxide (NO) and prostaglandins) produced by the

endothelium. However, damage to the endothelium through smoking, hypercholesteremia,

diabetes, hypertension or superoxides inhibit NO release, allowing A2 to exert harmful effects.

Use of ACE inhibitors is associated with increased availability of NO and results in

improvement and restoration of endothelial function, thus counteracting the initiation and

progression of atherosclerosis.


The evidence for ACE inhibitors after acute myocardial infarction is convincing and has led to

recommendations to commence all patients with an acute myocardial infarction on an ACE

inhibitor (Antman et al. 2004)

2.2.3 Sources of drug prescription and drug utilisation data

2.2.3.1 Administrative databases

Administrative databases provided some of the earliest evidence of a gap between the evidence

and clinical practice in the secondary prevention of CHD (Table 2.1). Most studies used

hospital discharge abstracts to identify patients with acute coronary syndromes and linked these

to prescription claims (Soumerai et al. 1997; Rochon et al. 1999a; Smith et al. 1999b; Heller et

al. 2000; Jackevicius et al. 2001). Other studies used insurance claims from a health

management organisation (Brand et al. 1995; Barron et al. 1998b) or networks of GENERAL

PRACTITIONER records (Hippisley-Cox et al. 2001; DeWilde et al. 2003).

The main advantages of administrative databases are ease of access, large patient samples, and

rigorous protocols for data collection. Limitations include; lack of detailed clinical information

and the restricted populations for whom data is available, usually the elderly and other

disadvantaged groups with state funded medication insurance or subsets of healthcare providers.

Furthermore, prescription claims may not reflect prescribing patterns since they are distorted by

patient adherence. Nonetheless administrative databases can provide useful data, particularly

about trends.

Table 2.1: Secondary prevention of CHD studies using administrative databases

Study Year Sample Variables of interest

(Soumerai et al. 1997) 1987-90 5332 Beta-blockers, determinants, outcomes

(Barron et al. 1998b) 1990-92 6851 Beta-blockers, dosages

(Brand et al. 1995) 1992 307 Beta-blockers

(Pilote et al. 2000) 1988-95 76,012 Trends in use

(Smith et al. 1999b) 1990-95 1462 Trends in use

(Rochon et al. 1999a) 1993-95 15,542 Beta-blockers, determinants, dosages

(Jackevicius et al. 2001) 1992-97 42,628 Statins, trends in use

(Heller et al. 2000) 1994-97 9534 Beta-blockers, trends in use

(Hippisley-Cox et al. 2001) n/a 5891 Gender

(Simpson et al. 2003) 1996-98 14,057 Trends in use, dosages

(DeWilde et al. 2003) 1994-01 ~30,000pa Trends in use, determinants

(Bennett et al. 2002) 1999-00 n/a Region, determinants


The Australian experience

Drug utilisation data from administrative databases are currently available in only a limited way

in Australia. All prescriptions submitted for payment of a subsidy under either the

Pharmaceutical Benefits Scheme (PBS) for the general community, or Repatriation

Pharmaceutical Benefits Scheme (RPBS), are processed by the Health Insurance Commission

(HIC) that maintains a computerised database of information relating to prescriptions. This

database is limited to prescriptions that attract a subsidy thus excluding:

• medications for general beneficiaries where the PBS dispensed price is lower than the

general copayment, estimated to account for about 10% of all cardiovascular drug

prescriptions in 1994 (Waters et al. 1998). In the current context this would be particularly

relevant to the older beta-blockers; and

• over the counter drugs, as the major proportion of aspirin use.

The Pharmacy Guild Survey collects all dispensing information from a random sample of about

300 pharmacies every month. The Department of Health and Family services uses data

collected from the Pharmacy Guild Survey to estimate the prescription volume for drugs in the

non-subsidised categories, although these data are only aggregated at the national level.

The Drug Utilisation Sub-Committee (DUSC) database combines the data from the HIC and the

estimates for unsubsidised categories. While this database is useful to monitor a number of

trends in drug utilisation, it is not useful for monitoring drug use for patients with specific

conditions, nor for monitoring drug use in individual patients because the DUSC database

contains no patient identifying data or sociodemographic data, nor does it contain any

information on the condition for which the drug was prescribed. Demographic information

about concessional beneficiaries (pensioners and other concession card holders) can be obtained

through linkage with the Department of Social Security data. Reports are available showing

drug utilisation trends with no reference to condition being treated (Waters et al. 1998;

Australian Institute of Health and Welfare 2004b).

In 2002 the HIC database started collecting Medicare numbers with all prescriptions dispensed.

This change, together with a Memorandum of Understanding recently signed by the

Commonwealth Department of Health and Aging and the Health Department of Western

Australia will soon make possible the analysis of the drug prescription data by individual

patients and specific health conditions (personal communication, J. Bass).

2.2.3.2 Randomised Controlled Trials

Another source of data about prescribing patterns has been randomised controlled trials (RCTs)

(Table 2.2). As with the administrative databases, the data have been collected to rigorous

specifications and are usually derived from a large patient sample. The advantage of RCTs over


administrative databases is the richness of clinical information available in RCT databases.

Multicentre clinical trials also provide comparison of prescribing patterns across geographical

locations (Rouleau et al. 1993; Faergeman et al. 1998). Extended patient follow-up allows for

measures of drug changes over time in individual patients (Kizer et al. 1999) and long term

(Aronow et al. 2001a). The main disadvantage of RCTs is their narrow eligibility criteria,

which means that prescribing patterns are available in only a select subgroup of patients.

Furthermore, as pointed out by Kizer et al prescribing patterns of clinicians who participate in

RCTs differ from routine clinical practice (Kizer et al. 1999) and, participation in a RCT could

influence follow-up use of drugs because of the more intense follow-up. As with the

administrative data, information from RCTs is particularly useful to show changes in

prescribing patterns over time.

Table 2.2: Secondary prevention studies using data from randomised control trials

Study Trial Year Sample Variables of interest

(Kizer et al. 1999) MILIS,

TIMI 1,2,4-6, 9B

1978-95 8,386 Trends in use, setting

(Lamas et al. 1992) SAVE 1987-89 2231 Trends in use

(Rouleau et al. 1993) SAVE 1987-89 2231 Region

(Zuanetti et al. 1996) GISSI 1-3 1984-93 36817 Trends in use, determinants

(Faergeman et al. 1998) 4S 1988-89 4444 Region

(Alexander et al. 1998) GUSTO-IIB 1994-95 7,743 Determinants

(Ganz et al. 1999) PASE 1993-94 407 Age

(Miller et al. 2000) PREVENT 1994-97 825 Lipid management, gender

(Aronow et al. 2001a) GUSTO-IIB

PURSUIT

1994-97 20,809 Outcomes

2.2.3.3 Myocardial infarction registers

Myocardial infarction registers provide another useful source of data about prescribing practices

at hospital discharge following an ACS (Table 2.3). Advantages of these datasets include the

specificity of the data collected and the broader selection of patients and clinicians.

Comparisons between the community setting and RCTs showed differences in prescribing

practices between these settings and suggested that prescribing in RCTs is more likely to be

evidence based (Col et al. 1996; Kizer et al. 1999).

The Worcester Heart Attack Study

This longitudinal community-wide study of patients hospitalised with a primary or secondary

diagnosis of myocardial infarction in the 16 acute hospitals in Worcester, Massachusetts

commencing in 1975, provides information about trends in medication use over more than two

decades (Spencer et al. 2003).


MONICA (MONItoring of trends and determinants in CA rdiovascular disease)

A World Health Organisation initiative, conducted over 10 years with the objective of

measuring trends in, and determinants of, cardiovascular disease in different populations around

the world. While focus was on trends in event rates and cardiovascular risk factors in men and

women aged 25-64, prescription data have been analysed at several sites, including a

comparison of the two Australian sites (Nicholls et al. 2001).

The National Registry of Myocardial Infarction

The National Registry of Myocardial Infarction (NRMI) is a pharmaceutical industry sponsored

observational study of AMI in US hospitals. Since 1990, NRMI has collected data on more

than 2 million AMI patients, with more than 1,600 participating hospitals (The National

Registry of Myocardial Infarction 2004).


Table 2.3: Secondary prevention studies using data from registers

Study Year Sample Variables of interest

Worcester Heart Attack Study

(Gurwitz et al. 1992) 1975-88 4,762 Beta-blockers, age, trends in use

(Goldberg et al. 1997) 1986-93 3,824 Lipid management

(McCormick et al. 1999b) 1986-93 933 Insurance type

(McCormick et al. 1999a) 1986-95 1710 Trends in use, determinants

(Spencer et al. 2001) 1986-97 5739 Trends in use, determinants

(Yarzebski et al. 2001) 1986-97 5204 Trends in use, lipid management

MONICA (MONItoring of trends and determinants in CArdiovascular disease)

(Thompson et al. 1992) 1984-90 5294 Trends in use

(Heller et al. 1992) 1984-85/ 88-90 1303 Trends in use

(Lim et al. 1998) 1988-94 1982 Diabetes, trends in use

(Lim et al. 1999) 1990-94 1406 Hospital type

(Bourquin et al. 1998) 1986-93 632 Trends in use

(Nicholls et al. 2001) 1985-93 6269 Trends in use, comorbidities, region

National Registry of Myocardial Infarction

(Chandra et al. 1998) 1990-94 354,435 Gender

(Barron et al. 1998a) 1994-96 192,609 ACE inhibitors, determinants

(Rogers et al. 2000) 1990-99 1.5 million Trends in use

(Fonarow et al. 2001a) 1998-99 138,001 Lipid levels, clinical determinants

2.2.3.4 Multicentre surveys

These large multicentre surveys were all specifically designed to collect data about the quality

of care in patients with known CHD including the use of secondary prevention

pharmacotherapies (Table 2.4). Specific predetermined quality indicators derived from

guidelines prevalent at the time informed the type of data collected.

Four surveys all used similar methods: the Action on Secondary Prevention through

Intervention to Reduce Events (ASPIRE) survey, the European Action on Secondary Prevention

through Intervention to Reduce Events (EUROASPIRE I) and its successor EUROASPIRE II;

and the American College of Cardiology Evaluation of Preventive Therapeutics (ACCEPT)

study. Based on the original ASPIRE, they were cross sectional studies of patients hospitalised

for one of four diagnostic categories: coronary bypass artery grafting, percutaneous transluminal

coronary angioplasty, AMI, and acute myocardial ischaemia without evidence of infarction and

involved data from both the medical record and patient interview. These surveys were

conducted under the auspices of the professional bodies, including the British Cardiac Society

(Epidemiology and Prevention Committee); European Society of Cardiology (Working Group

on Epidemiology and Prevention); and the American College of Cardiology. While ASPIRE


and EUROASPIRE I only collected data about medications by patient report at 6 months,

ACCEPT and EUROASPIRE II also collected medications prescribed at the time of hospital

discharge. Together EUROASPIRE I and II allowed a comparison of practices in nine

European countries at two time points.

PREVENIR and ENACT (European Network for Acute Coronary Treatment) examined the

influence of percutaneous coronary interventions on prescribing practices while the Quebec

survey compared practices in tertiary and community hospitals. The collaboration between the

Italian Society of hospital pharmacy (SIFO) and the European Society of Clinical Pharmacy

(ESCP) compared nine European countries and one Canadian province and examined a number

of determinants of drug prescription.

The National Ambulatory Medical Care Surveys

The National Ambulatory Medical Care Surveys are conducted by the National Centre for

Health Statistics, to assess office practices of US physicians. These surveys have been used to

describe national prescribing patterns in the ambulatory setting. However these surveys were

not specific to patients who had experienced an ACS. Nonetheless, these surveys provide

information about the patterns of use of beta-blockers (Wang et al. 1998) and aspirin (Stafford

2000) in patients with CHD and patterns of statin use (Wang et al. 2001).


Table 2.4: Secondary prevention studies using data from multicentre surveys

Study Year Sample Variable

(Czarn et al. 1992) 1984-88 2016 Since discharge

(Viskin et al. 1995) 1993 606 Determinants

Dosages

(Simpson et al. 1997) 1993-94 882 Quality indicators

Action on Secondary Prevention through Intervention to Reduce Events (ASPIRE)

(ASPIRE Steering Group 1996) 1994-95 2583 Quality indicators

EUROSPIRE I

(EUROASPIRE Study Group 1997) 1995-96 4863 Quality indicators

EUROSPIRE II

(Euroaspire II Study Group 2001) 1999-2000 8181 Quality indicators

(Euroaspire I and II Group 2001) 1995-96/99-00 6948 Time trends

American College of Cardiology Evaluation of Preventive Therapeutics (ACCEPT)

(Pearson et al. 1997b) 1996 1797 Quality indicators

SIFO/ESCP collaboration

(Venturini et al. 1999) 1996 1976 Determinants

PREVESE 94/98

(de Oya et al. 2000) 1994/98 3296 Time trends

PREVENIR

(Danchin et al. 2002) 1998 1394 Determinants

Quebec hospitals

(Beck et al. 2001) 1996-98 1090 Hospital type

European network for acute coronary treatment (ENACT)

(Steg et al. 2002b) 1999 3092 Determinants

PIN Study (Post Infarct Care)

(Willich et al. 2001) n/a 2441 Quality indicators

Brisbane study

(Scott et al. 2002) 2000-01 397 Quality indicators

2.2.3.5 Single centre surveys

Quality audits in single institutions also provide insight into prescribing practices in patients

following ACS (Table 2.5). The main disadvantage of these studies is the relatively small

sample sizes, which are balanced against an extended period of data collection. Protocols for

data collection may not be as rigorous as in large studies with data collection at multiple sites by

multiple staff. However, these studies have been specifically designed to examine prescription

of secondary prevention therapies and therefore appropriate variables including indications and

contraindication for treatment are included.


Table 2.5: Secondary prevention studies using data from single institutions.


(Agusti et al. 1994) 1982-88 737 Time trends, determinants

(Rumboldt et al. 1995) 1983/1993 366 Time trends

(Herholz et al. 1996) 1988-90 1357 Gender, race

(Eccles et al. 1991) 1989-90 267 Determinants

(Whitford et al. 1994) 1991-92 272 Quality indicators

(Giugliano et al. 1998) 1991-92 280 Determinants

(Aronow 1996) n/a 500 Quality indicators

(Aronow 1998) n/a 500 Lipid management

(Martinez et al. 1998) 1989-94 324 Time trends

(Silagy 1996) 1993-95 793 Since discharge

(Brotons et al. 1998) 1995 380 Quality indicators

(Luzier et al. 1999) 1996-97 541 Determinants

(Mendelson et al. 1997) 1996-97 162 Quality indicators

(Mendelson et al. 1998) 1996-97 161 Quality indicators

(Strandberg et al. 1999) 1997-98 127 Time of episode

(Mudge et al. 2001) 1998-99 352 Lipid management

(Whincup et al. 2002) 1998-00 3689 20 year follow-up

(Dalal et al. 2003) 2000-01 179 Quality indicators

2.2.3.6 Physician Surveys

Several studies asked physicians about their knowledge, beliefs and prescribing practices in

patients after hospital discharge following AMI. However, voluntary participation is a

limitation, because respondents and non-respondents may differ in their practice. Furthermore

studies have found that self-reported practice patterns may not accurately reflect actual practice.

Lim et al found that the stated practice of physicians participating in the Acute Cardiac Care

Project was greater than actual use observed during the project (Lim et al. 2000). Similarly,

McBride et al found that physicians overestimated the lipid lowering treatment provided to

patients with cardiovascular disease (McBride et al. 1998).

One advantage of these surveys is the ability to ask doctors about reasons for prescribing (or not

prescribing) treatments in particular situations. This differs from all other data sources where

reasons for non-prescription can only be inferred, without being privy to the decision making

process. Baber et al found that although 72% of cardiologists reported prophylactic use of beta-

blockers following myocardial infarction the circumstances under which they prescribed beta-

blockers varied considerably (Baber et al. 1984).


Other physician surveys include:

• A series of doctor’s surveys documented marked changes in clinical management of

uncomplicated myocardial infarction from 1970 to 1987. Some of the largest shifts in

practice reported were for the use of medications after hospital discharge (Hlatky et al.

1988).

• A survey of 160 Scottish consultant physicians noted marked differences in the reported use

of beta-blockers in the management of survivors of myocardial infarction between

cardiologists (58%) and other physicians (31%) (Hutchison et al. 1987).

• A survey of cardiologists, internists and family practitioners about their knowledge and

practices in prescribing post-MI drug therapy found differences by specialty that were

maintained even after adjusting for the doctor’s age, board certification, number of

myocardial infarction patients treated within 3 months, size and teaching status of the

principal hospital (Ayanian et al. 1994). Ayanian et al found an adjusted odds ratio (95%

CI) for cardiologists believing that long-term aspirin use definitely improved survival was

2.04 (1.42-2.86) compared with internists and 2.63 (1.82-3.85) compared with family

doctors. Similarly for long-term beta-blocker therapy the adjusted odds ratio (95% CI) for

cardiologists compared with internists and family doctors was 2.63 (1.82-3.70) and 3.12

(2.13-4.76) respectively. Ayanian et al also noted differences (p<0.001) in reported

prescribing practices for beta-blockers between New York and Texas. Within each field of

practice higher rates of prescription were reported in New York.

2.2.3.7 Quality improvement initiatives

Initiatives put in place to improve the long-term management of CHD including the use of the

pharmacotherapies provide information about drug prescribing practices. These range from

large-scale government sponsored initiatives to small one-site initiatives. While most initiatives

revolved around the commencement of appropriate therapy at the time of hospital discharge,

some initiatives were aimed at ambulatory care through the introduction of nurse run clinics in

general practice (Campbell et al. 1998a).

The Cooperative Cardiovascular Project (CCP) was the first program implemented under the US

Health Care Financing Administration’s Health Care Quality Improvement Initiative to improve

the quality of care for Medicare patients hospitalised with AMI. Quality indicators were

developed based on the AHA(American Heart Association)/ACC(American Cardiac Society)/

clinical practice guidelines. The Medicare National Claims History File was used to identify

patients with a principal diagnosis of AMI. Hospital medical records were then reviewed to

obtain data for each quality indicator. Potential candidates were divided into two groups – ideal

candidates for whom the treatment would always be indicated and less-than-ideal candidates for

whom the therapy was contraindicated, controversial or for whom data for determining the


appropriateness of the intervention were missing (patients with an exclusion). The pilot project

involved all acute care hospitals in four states and included all hospitalisations for Medicare

patients discharged with a principal diagnosis of AMI between June 1992 and February 1993.

This was followed by a second data collection period during 1994 and 1995 throughout the

United States. The disadvantage of this project was the inclusion of only Medicare patients,

with most studies further restricted to patients 65 years and older.

The Minnesota Clinical Comparison and Assessment Program included data from 37

community based hospitals including two teaching hospitals and representing 80% of all

community hospital beds and one half of all myocardial infarction in the state. In addition to

comparison of management before and after the intervention, one study examined the treatment

of hyperlipidemia (prior to hospital admission) in patients previously diagnosed with CHD

(Majumdar et al. 1999).

The West Morton Coronary Outcomes Program was a quality improvement initiative introduced

into all acute hospitals within a health district in Queensland. This was followed by the

Collaborative for Healthcare Improvement Cardiac Collaborative including nine public

hospitals in Queensland in a federally funded Clinical Support Systems Program.

The Guidelines Applied in Practice (GAP) Initiative was sponsored by the American College of

Cardiology and initiated in Michigan. The first phase included 10 acute-care hospitals in

southeast Michigan. Phases two and three introduced a further 23 hospitals to the program. The

total of 33 hospitals varied in size and type and included patients with various forms of health

insurance (Eagle 2003).


Table 2.6: Secondary prevention studies using Quality improvement initiatives


Cooperative Cardiovascular Project (CPP)

(Krumholz et al. 1996) 1992-93 5490 Aspirin

(Jollis et al. 1996) 1992-93 8,241 Doctor speciality

(Krumholz et al. 1997) 1992-93 5453 ACE inhibitor

(Marciniak et al. 1998) 1992-93 /94-95 23,535 Quality intervention

(Krumholz et al. 1998) 1994-95 45,308 Beta-blockers

(Chen et al. 1999b) 1994-95 149, 177 Hospital ranking

(O'Connor et al. 1999) 1994-95 186,800 Region

(Allison et al. 2000) 1994-95 114,411 Hospital type

(Mehta et al. 2000b) 1994-95 8,455 Diabetes

(Frances et al. 1999; Frances et al. 2000) 1994-95 161,558 Doctor speciality

(Seddon et al. 2001) 1996-97 3721 Insurance Type

(Rathore et al. 2003) 1994-96 146,718 Age

(Ayanian et al. 2002) 1999-2000 815 5 year follow-up, Lipids

Grampians general practitioner study

(Campbell et al. 1998b) n/a 1921 Quality indicators

(Campbell et al. 1998a) n/a 1173 Quality indicators

Minnesota Clinical Comparison and Assessment Program

(Majumdar et al. 2001) 1992-93/95-96 5347 Physician speciality

West Morton Coronary Outcomes Program

(Scott et al. 2000b) 1995-98 649 Quality indicators

Collaborative for Healthcare Improvement Cardiac Collaborative

(Scott et al. 2004) 2001-02/02-03 1524 Quality indicators

Guidelines Applied in Practice (GAP)

(Mehta et al. 2002) 1998-99/2000 1649/914 Quality indicators

(Eagle 2003) n/a 1892/2065 Quality indicators

Single site initiatives

(Fonarow et al. 2001b) 1992-93/94-95 558 Quality indicators

(Sarasin et al. 1999) 1994-95/95-96 355 Beta-blockers

(Lacy et al. 2002) 1996-97 813 Lipid management


2.2.4 Summary

While risk factor management and advances in the treatment of CHD have paralleled declines in

the mortality and incidence of CHD, the prevalence of CHD remains high and imposes a

significant burden. This burden could be reduced considerably by the enhanced and more

systematic application of secondary prevention strategies. Strategies to reduce the risk of

coronary events include the use of antiplatelet agents, beta-blockers, statins and ACE inhibitors.

These all exert a beneficial effect independent of traditional risk and prognostic factors. Data

about prescribing practices and drug utilisation in the secondary prevention of CHD are

available from various sources each with its limitations and advantages.


2.3 Evolution of secondary prevention

In the era of evidence-based medicine, the translation of scientific evidence into clinical practice

is often preceded by clinical practice guidelines. The AHA/ACC has led the way in publication

of guidelines that have been followed by European medical groups. Australian professional

bodies lagged behind in the publication of guidelines. Possible reasons for updating or

introducing clinical practice guidelines include; evidence of existing benefits and harms,

outcomes considered important, available interventions, evidence that current practice is not

optimal, values placed on outcomes, and resources available for healthcare (Shekelle et al.

2001).

For each drug class, the evidence of benefits current at the time of commencing this study are

summarised, followed by recent developments in the available evidence and guidelines.

Finally, trends in the prescribing of each drug class are examined.

2.3.1 Antiplatelet agents

2.3.1.1 Evidence and guidelines

Initial evidence for the use of antiplatelet agents in the secondary prevention of cardiovascular

events came from two large meta-analyses from the Antiplatelet Trialists’ Collaboration

published in 1988 (25 trials enrolling 29,000 patients) and 1994 (133 trials enrolling 53,000

patients). The relative reduction of endpoints are summarised in Table 2.7. The second

collaboration evaluated subgroups of patients including women, the elderly, and patients with

comorbidities such as hypertension and diabetes. In addition to showing the benefits of

antiplatelet therapy, both collaborations showed that no other antiplatelet agent was better than

aspirin and that medium doses (75-325 mg daily) of aspirin were as effective as higher doses.

Table 2.7: Initial evidence from the Antiplatelet Trialists’ Collaborations

Percent reduction (mean±SD) in selected endpoints with antiplatelet therapy

19881 19942

End points All Prior MI All Prior MI

Non-fatal MI 32±5 31±5 35±4 31±6

Non-fatal strokes 27±6 42±11 31±5 39±11

Cardiovascular death 15±4 13±5 18±3 15±5

All vascular events 25±3 25±4 27±2 25±4 1(Antiplatelet Trialists' Collaboration 1988), 2(Antiplatelet Trialists' Collaboration 1994)

The CAPRIE (Clopidogrel versus Aspirin in Patients at Risk of Ischaemic Events) Trial

(CAPRIE Steering Committee 1996) compared the benefit of clopidogrel to that of aspirin in

high risk patients (previous stroke, previous myocardial infarction or peripheral arterial disease).


Overall there was a small and marginally significant benefit with clopidogrel compared with

aspirin (Relative reduction; 95% CI; 8.7%; 0.3 to16.5), however, this benefit did not extend to

the subgroup of patients with a previous myocardial infarction, but was restricted to the

subgroup of patients with peripheral arterial disease. The CAPRIE study found that the safety

profile was similar for clopidogrel and relatively high doses (325 mg) of aspirin.

2.3.1.2 Recent developments

Despite longstanding evidence for the benefit of antiplatelet agents the development of new

antiplatelet agents with different modes of action have led to some debate about the selection of

antiplatelet agent and the role of anticoagulants in the inhibition of thrombosis.

Clopidogrel

The CURE (Clopidogrel in Unstable angina to prevent Recurrent Events) Trial examined the

benefits of adding clopidogrel to usual care (aspirin 75-325 mg) in patients with ACS without

ST segment elevation (The Clopidogrel in Unstable Angina to Prevent Recurrent Events

(CURE) Trial Investigators 2001). In this group of high-risk patients, an added risk reduction

benefit for death from cardiovascular causes, nonfatal myocardial infarction, or stroke was

observed (RR:0.80, 95% CI:0.72-0.90) for clopidogrel. However, this was achieved at the cost

of an increased risk of major bleeding (RR:1.38, 95% CI:1.13-1.67).

In an analysis of the early and late effects of clopidogrel in the CURE study, Yusuf et al found a

significant reduction in cardiovascular death, myocardial infarction, stroke and severe ischaemia

within 24 hours of the first clopidogrel dose, which was sustained throughout the 12 months of

the study (Yusuf et al. 2003). On the other hand, the investigators found no excess risk of

bleeding within the first 24 hours but a small excess in major bleeding after this time with the

use of clopidogrel.

A short course, two to four weeks, of a thienopyridines (clopidogrel) added to aspirin provided

greater protection from thrombolytic complications following PCI than aspirin alone (Steinhubl

et al. 2002).

Oral glycoprotein IIb/IIIa receptor antagonists

Glycoprotein IIb/IIIa receptor antagonists are the most potent currently available antiplatelet

agents and these block the final common pathway for platelet aggregation. Despite compelling

data showing the efficacy of intravenous glycoprotein IIb/IIIa inhibitors in reducing coronary

events in the setting of PCI, three large long term studies of oral glycoprotein IIb/IIIa inhibitors

failed to show a clinical benefit (Heeschen et al. 2000). A subsequent meta-analysis found that

oral glycoprotein IIb/IIIa inhibitors were associated with increased all cause mortality (OR=1.3,


95% CI 1.15-1.67) and increased incidence of ischaemic events (Newby et al. 2002). Results

were similar regardless of whether the agent was added to or substituted for aspirin therapy.

Anticoagulant agents

Results of two trials comparing oral anticoagulants and aspirin were published in 2002 (Hurlen

et al. 2002; van Es et al. 2002). One study of more than 3000 post-MI patients found that

moderate intensity warfarin, either in combination with aspirin or alone, was more effective

than aspirin alone in reducing cardiac events. However, the benefit was restricted to a reduction

in nonfatal events with no effect on mortality. Furthermore the risk of bleeding was also higher

in the warfarin groups (Hurlen et al. 2002). Similarly the ASPECT-2 study compared high

intensity anticoagulant with moderate intensity anticoagulant plus low dose aspirin with aspirin

alone and found that the anticoagulant regimens were more effective (van Es et al. 2002). With

a smaller number of patients, ASPECT-2 was less conclusive about the effects on bleeding

complications. However, the investigators noted that the number of patients to permanently

discontinue therapy was twice as great with the anticoagulant regimens and suggested that

differences in adherence related to the frequent monitoring required with the anticoagulants.

Recently the ESTEEM investigators reported on the findings of a new class of oral

anticoagulant, a direct thrombin inhibitor, ximelagatran, for secondary prophylaxis after

myocardial infarction (Wallentin et al. 2003). They found that ximelagatran added to aspirin

significantly reduced the risk for the primary endpoint (death, MI or severe recurrent ischaemia)

compared with placebo (HR 0.76, 95% CI 0.59-0.98), while not increasing the incidence of

bleeding or other drug related adverse events.

Antithrombotic Trialists' Collaboration

The introduction of new agents and uncertainty about whether very low dose aspirin (<75 mg)

was as effective as low dose (75-150 mg) aspirin led to the Antithrombotic Trialists’

Collaboration (Antithrombotic Trialists' Collaboration 2002), which included studies published

up to September 1997. This study concluded that uncertainty remained about the efficacy of

very low dose aspirin and therefore continued to recommend use of 75-150 mg of aspirin daily.

The study also concluded that compared with aspirin, the thienopyridines (clopidogrel) were

more effective in reducing serious vascular events. However, they noted that since the 95%

confidence interval ranged from 0.3% to 16.5% the true size of the benefit could not be reliably

estimated and very large trials would be needed to measure this small difference. Although not

included in the meta-analysis the Trialists acknowledged the CURE study and the benefit of

adding clopidogrel to aspirin. They noted that more evidence was needed particularly about the

addition of clopidogrel to patients who were taking aspirin when a cardiac event occurred.


2.3.1.3 Selection of antithrombotic agent

While efficacy and safety are important considerations in deciding between alternative

therapies, cost is also a consideration. Aspirin has been available since the 1950s, while the

Food and Drug Administration only approved clopidogrel in the late 1990s resulting in a

considerable price differential. Gorelick et al estimated that based on cost alone, aspirin

provides a 45 fold advantage, while the cost of preventing an event ranged from about $9000 for

aspirin to about $45,000 for clopidogrel, giving a 5-7 fold cost advantage for aspirin over

clopidogrel (Gorelick et al. 1999). The conclusions of Gorelick et al, that clopidogrel is a

viable alternative to aspirin only for patients who do not benefit from aspirin has been echoed

more recently by others (Antithrombotic Trialists' Collaboration 2002; Hung et al. 2003; Dalal

et al. 2004). In contrast Yusuf advocated the addition of clopidogrel to aspirin (Yusuf et al.

2003).

Another important consideration in deciding on the use of different therapies is patient

convenience. Given the need for continual monitoring with warfarin treatment, the current

recommendation remains that warfarin use be reserved for survivors of myocardial infarction at

high risk of systemic thromboembolism because of atrial fibrillation, mural thrombus,

congestive heart failure and previous embolisation (Hung et al. 2003; National Heart

Foundation of Australia et al. 2003)

In the Clopidogrel for the Reduction of Events During Observation (CREDO), Steinhubl et al

found that the benefits of clopidogrel added to aspirin extended to at least one year post-PCI

(Steinhubl et al. 2002).

2.3.1.4 Time trends

While the absolute proportion of patients prescribed an antiplatelet agent differed across studies

there was a consistent trend of increased prescription through the 1980s with a plateau by the

early 1990s (Table 2.8).

Changes in clinical practice commenced following early trials showing a benefit of aspirin, but

preceding the publication in 1988 of ISIS-2 (Second International Study of Infarct Survival

Collaborative Group 1988) and the first Antiplatelet Trialists' Collaboration (Antiplatelet

Trialists' Collaboration 1988). Hlatky et al noted that the finding that 80% of respondents

reported routine use of aspirin in uncomplicated MI was surprising because the 1987 survey

preceded the first major meta-analysis by the Antiplatelet Trialists’ Collaboration (Hlatky et al.

1988). Similarly, Kizer et al noted that the initial sharp increase in aspirin prescriptions in

patients participating in RCTs resulted from protocol directives, which were driven by the

findings of several early trials showing the benefit of antiplatelet agents (Kizer et al. 1999). The

early rise in aspirin use probably reflected approval by the Food and Drug Administration’s


approval of the use of aspirin for secondary prophylaxis in post-MI patients. Prescribing

practices for aspirin in the secondary prevention of CHD have been relatively stable in recent

years. Jencks et al found that in 1998-99 and 2000-2001 85% and 86% of post-MI Medicare

beneficiaries respectively were prescribed aspirin at the time of hospital discharge (Jencks et al.

2003). Unfortunately the study did not include prescription of other antiplatelet agents,

particularly clopidogrel.


Table 2.8 Longitudinal studies of aspirin prescription following an ACS

Year

Study 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00

Percent

Registers

(Heller et al. 1992) 12 68

(Thompson et al. 1992) 15.7 33.3 41.3 57.1 71.2 82.9 82.6

(Bourquin et al. 1998) 42 84 85

(Spencer et al. 2001) 13 43 62 65 70 82 80

Administrative

(Smith et al. 1999b) 1 73.0 79.7 80.2 74.7 76.9 74.1

(Pilote et al. 2000) 65 66 66 66 66

(Heller et al. 2000) n/a

RCT

(Lamas et al. 1992) 38.8 54.4 71.9

(Kizer et al. 1999) 10 74 89 84 88

Surveys

(Agusti et al. 1994) 0 2 0 3 15 38 32

(Martinez et al. 1998) 28 75 71

(Rumboldt et al. 1995) 57 90.8 1 Following hospital episode of unstable angina (all other studies follow myocardial infarction)


2.3.2 Beta-blockers

2.3.2.1 Evidence and Guidelines

The benefits of long-term beta-blocker use in post-MI patients for both mortality and non-fatal

reinfarction has been known since the early 1980s (Table 2.9).

Table 2.9: Long term secondary prevention trials for beta-blockers

Norwegian Multicentre

Study1

Beta-Blocker Heart Attack

Trial2

Year published 1981 1982

Subjects (n) 1884 3887

Treatment duration 1-3 y Median 2 y

Time of starting treatment (days post-

MI)

7-28 5-21

Placebo Timolol

20 mg

Placebo Propranolol

180-240 mg

Total mortality

Incidence (%) 17.5 10.6 9.8 7.2

RRR (95% CI) 0.60 (0.45-0.79) 0.72 (0.56-0.91)

Non-fatal reinfarction

Incidence (%) 14.0 9.5 5.3 4.4

RRR (95% CI) 0.65 (0.36-0.93) 0.84 (0.57-1.12) 1(The Norwegian Multicentre Study Group 1981), 2(Beta-Blocker Heart Attack Trial Research Group 1982);(Beta-Blocker Heart Attack Trial Research Group 1983)

Yusuf et al used a meta-analysis of 24 randomised trials of beta-blockers, commenced either

early (8 trials) or late (16 trials) after the myocardial infarction, to calculate the benefit of beta-

blockers from 8 days onwards (Yusuf et al. 1985). The results of this analysis of more than

20,000 patients are summarised in Table 2.10.

Table 2.10: Late benefits of beta-blockers post-MI

Beta-blocker1 Placebo

Percent OR (95%CI)

Total mortality 7.9 10.0 0.77 (0.70-0.85)

Nonfatal reinfarction 5.7 7.5 0.74 (0.66-0.83)

Sudden death 3.6 5.2 0.68 (0.63-0.73) 1(Yusuf et al. 1985)

The original trials showing the benefits of beta-blockers in the post-MI setting were conducted

prior to the introduction of thrombolysis, antiplatelet agents and other secondary prevention

therapies. This raised some concern about whether the introduction of these therapies reduced


the benefits of beta-blockers in post-MI patients. However, a meta regression analysis by

Freemantle et al (Freemantle et al. 1999) showed no influence of time (and therefore adjunctive

therapy) on the odds of death (OR;95% CI) (1.04; 0.82-1.28). Cardioselectivity (1.10; 0.89-

1.39) and intrinsic sympathomimetic activity (ISA) (1.19; 0.96-1.47) showed a non-significant

trend towards reduced benefit, although the evidence was stronger for ISA

Pooled results for each beta-blocker are shown in Table 2.11, including the presence of

cardioselectivity and intrinsic sympathomimetic activity. Fremantle et al found evidence of

reduced odds of mortality for four drugs: propranolol, timolol, metoprolol and acetbutolol.

They noted that while atenolol is commonly prescribed in secondary prevention of CHD, it had

not been adequately assessed in this setting.

Table 2.11: Pooled odds of death in long term beta-blocker trials

Trials1

N (Weight %)

OR (95% CI) Cardioselective ISA

Acetbutolol 1(2.9) 0.49 (0.25-0.93)2 -ve -ve

Alprenolol 4 (6.6) 0.83 (0.59-1.17) +ve +ve

Atenolol 2 (1.6) 1.02 (0.52-1.99) +ve -ve

Carvedilol 1 (0.3) 0.62 (0.05-5.61) -ve -ve

Metoprolol 7 (23.1) 0.80 (0.66-0.96) 2 +ve -ve

Oxprenolol 4 (11.8) 0.91 (0.71-1.17) -ve +ve

Pindolol 1 (3.6) 0.96 (0.60-1.55) -ve +ve

Practolol 2 (13.9) 0.80 (0.63-1.02) +ve +ve

Propranolol 7 (26.6) 0.71 (0.59-0.85) 2 -ve -ve

Sotalol 1 (5.3) 0.81 (0.54-1.21) -ve -ve

Timolol 2 (13.6) 0.59 (0.46-0.77) 2 -ve -ve

Xamoterol 1 (0.1) 3.45 (0.25-188.83) +ve +ve 1 (Freemantle et al. 1999), 2statistically significant reduction, ISA intrinsic sympathomimetic activity

Generally all guidelines recommended long-term use of beta-blockers in all post-MI patients

without a clear contraindication. However areas of uncertainly remained.

Patient selection

Since the absolute benefit of treatment is proportional to the absolute risk, the benefit of treating

low risk patients has been questioned. At the other extreme, patients considered sickest

according to their Acute Physiology and Chronic Health Evaluation score and Killip heart class

are also less likely to be prescribed beta-blockers (Gottlieb et al. 1998). However, all subgroups

of patients prescribed a beta-blocker were shown to have a 40% reduction in mortality (Gottlieb

et al. 1998). This finding that beta-blockers substantially improved survival even when the

absolute benefit was not as great was reflected in the AHA/ACC guidelines (Gottlieb et al.

1998; AHA/ACC 1999). Reluctance to treat low risk patients revolved around the possible


adverse effects of beta-blockers, including fatigue, depression, sexual dysfunction, nightmares

and difficulty with recognition of hypoglycaemia in diabetic patients. However, the AHA/ACC

guidelines concluded that the frequency and severity of adverse events are sufficiently low to

warrant the their use even in low risk patients (AHA/ACC 1999).

Patients with relative contraindications

Asthma and chronic obstructive pulmonary disease, insulin dependent diabetes mellitus, severe

peripheral vascular disease, PR interval >0.24 sec and moderate LV failure have all traditionally

been considered contraindications for the use of beta-blockers. However, current thinking

suggests that that the benefits of beta-blockers in reducing reinfarctions and mortality may

actually outweigh its risks even in patients with these comorbidities, although monitoring of

these patients is essential.

Duration of treatment

While earlier guidelines recommended treatment with beta-blockers for 12 months post-MI,

current recommendations suggest ongoing use.


Despite more than 20 years of evidence and experience in the use of beta-blockers in post-MI

patients, evidence and practice continues to evolve (Gheorghiade et al. 2002; Borrello et al.

2003; Dalal et al. 2004).

Benefits of beta-blockers in current clinical practice

The CAPRICORN trial provided direct evidence of the benefit of beta-blockers in the new

treatment era (The CAPRICORN Investigators 2001). In this trial of carvedilol in post-MI

patients with left ventricular dysfunction (LVD), almost one half of the patients received

thrombolysis or primary angioplasty, 86% were prescribed aspirin and 98% were also

prescribed an ACE inhibitor. However the reduction in all cause mortality of 23% was similar

to that observed in the early trials (Yusuf et al. 1985).


Relative contraindications

A study examining the health and economic benefits of beta-blockers following myocardial

infarction found that patients with relative contraindications including diabetes mellitus,

peripheral vascular disease, chronic obstructive pulmonary disease and congestive heart failure

derived substantial benefits from beta-blockers at reasonable costs. (Phillips et al. 2000).

Several studies have also examined specific contraindications.

Heart failure

The use of beta-blockers in post-MI patients with LVD with or without the symptoms of heart

failure represents the biggest change in beta-blocker use. The situation changed from one where

heart failure was considered a contraindication for beta-blockers to one where in conjunction

with more traditional therapies including ACE inhibitors, beta-blockers are viewed as an

important therapy, in the treatment of heart failure (Abraham 2000; Chavey II 2000; Hermann

2002). This change arises from a better understanding of the mechanisms of heart failure and

evidence of the benefit of treating heart failure with beta-blockers (Packer et al. 2001; Poole-

Wilson et al. 2003). Beta-blockers are beneficial patients with mild, moderate and severer heart

failure (Packer et al. 2001; Yancy 2001; Farrell et al. 2002; Foody et al. 2002; Goldstein 2002).

A number of studies have provided either direct or indirect evidence that showed post-MI

patients with signs or symptoms of heart failure benefited from the use of a beta-blocker.

In their meta-regression analysis Houghton et al showed that inclusion of patients with a history

of myocardial infarction and, heart failure or evidence of major cardiac dysfunction, did not

influence the benefit of beta-blockers (Houghton et al. 2000). Indeed, because patients with

heart failure were at greater risk, the relative benefit of beta-blockers was also greater.

Houghton et al suggested that because it was unlikely that patients with severe or worsening

heart failure were included in the trials, there was no evidence of a benefit in patients with

severe or progressively worsening heart failure and, therefore, these patients should not receive

a beta-blocker immediately after myocardial infarction.

More direct evidence of the benefit of beta-blockers in patients with LVD came from the a trial,

of patients with a proven myocardial infarction and LVD (Left Ventricular Ejection Fraction

(LVEF) ≤40%) (The CAPRICORN Investigators 2001). The all cause mortality was reduced in

the carvedilol group (HR=0.77, 95% CI 0.60-0.98, p=0.03).

Chronic obstructive pulmonary disease /asthma

Given the potential for bronchoconstriction with beta-blockers, these agents have traditionally

been contraindicated in patients with pulmonary conditions such as asthma and chronic


obstructive pulmonary disease (COPD). However, it has been suggested more recently that the

survival benefit from beta-blockers outweighs the risk of adverse effects in these patients with

the guidelines modified to reflect this view (Ryan et al. 1999).

Data from a large multicentre study was used to determine the effect of beta-blocker

prescription in patients stratified by severity of asthma or COPD, a group of patients excluded

from the landmark trials. (Chen et al. 2001). Chen et al found that in patients with moderate

asthma or COPD and not requiring beta-agonist therapy, beta-blockers were associated with

lower one-year mortality similar to that for patients with no asthma or COPD. However, no

survival benefit was observed in the group requiring a beta-agonist or steroids for the treatment

of severe asthma or COPD. This confirmed the view that beta-blockers should be considered as

prophylactic post-MI therapy in patients with moderate asthma or COPD, but for not those with

severe disease, particularly those requiring inhaled Beta-adrenergic agonist therapy (Farrell et

al. 2002). Meta-analyses have also shown the benefits of beta-blockers in both COPD and

reversible airway disease in patients with indications for beta-blockers including hypertension,

heart failure and CHD (Salpeter et al. 2004).

Diabetes Mellitus

Diabetes is a risk factor for early and late mortality after myocardial infarction (Zuanetti et al.

1993) However, concern about the modulating effect on hypoglycaemic symptoms and the

potential interference with insulin release has resulted in the underuse of these agents in this

group of patients (Chowdhury et al. 1999; Mehta et al. 2000b). Nonetheless diabetic patients

prescribed beta-blockers post-MI have improved survival compared with those not prescribed a

beta-blocker (Gottlieb et al. 1998; Chen et al. 1999a). Given the higher mortality rate of

diabetic patients after myocardial infarction the absolute benefit of beta-blocker use is greater

than in lower risk patients (Gottlieb et al. 1998).

Peripheral vascular disease

Peripheral vascular disease has been considered a relative contraindication to beta-blocker

therapy because of concern about aggravation of intermittent claudication. The current

consensus is that patients with mild or moderate disease can be safely treated with beta-

blockers, while caution must be exercised for patients with severe disease. (Gheorghiade et al.

2002; Borrello et al. 2003; Dalal et al. 2004). In a study to determine the effects of beta-blocker

on peripheral skin microcirculation in severe peripheral vascular disease Ubbink et al found no

negative effect and concluded that beta-blockers are not contraindicated in patients with

peripheral vascular disease (Ubbink et al. 2003). Similarly a study in patients with lower

extremity peripheral vascular disease found no association with beta-blockers and any of the

functional measures examined (McDermott et al. 2003).


Elderly age

Since randomised clinical trials traditionally excluded elderly patients, the benefits in this

subgroup were unclear. However, subsequent studies have confirmed that beta-blockers are

beneficial in all post-MI patients regardless of age (Soumerai et al. 1997; Krumholz et al. 1999).

Indeed, because the absolute risk is greater in elderly patients so is the absolute benefit (Gottlieb

et al. 1998).

Adverse effects

Concern about adverse effects is often blamed for the low utilisation of beta-blockers in “ideal”

patients. In fact, adverse effects have been responsible for relatively few withdrawals of

medication in the beta-blocker trials, including 0.7% for bradycardia, 1.2% for hypotension,

1.5% for fatigue, 0.4% for depression and 0.2% for sexual dysfunction (Beta-Blocker Heart

Attack Trial Research Group 1982). Ko et al conducted a review of the adverse effects

associated with beta-blocker therapy (Ko et al. 2002). They found that while there was

evidence of an increased incidence of fatigue and sexual dysfunction in the beta-blocker group

compared with the placebo group, there was no evidence of increased incidence of depression

with beta-blockers. Even for fatigue and sexual dysfunction the moderately large increased

risks associated with beta-blockers did not translate into large absolute increases. For example

there was an increased withdrawal of medication due to fatigue of 4 patients for every 1000

patients treated. The increase was even lower for sexual dysfunction with an increase of 2

patients for 1000 patients treated. The review by Ko et al confirms the views expressed in the

AHA/ACC guidelines that the potential benefits should outweigh any concern about adverse

effects.

The COMET trial of carvedilol and metoprolol in heart failure found that the drugs were

permanently stopped in about one third of surviving patients with a similar pattern of adverse

events between groups. (Poole-Wilson et al. 2003). The investigators noted that where adverse

events were reported, only a fraction were serious including about one in three cases of

bradycardia and one in five cases of hypotension.

In their meta-analysis of beta-blocker use following AMI, Freemantle et al noted that reports of

dizziness, depression, cold extremities and fatigue were only marginally more common in the

treatment than control groups (Freemantle et al. 1999). Overall, 23% withdrew from treatment

with withdrawal slightly more common in the beta-blocker group.


2.3.2.3 Selection of beta-blockers

There is thought to be a class effect of beta-blockers although this is not so clear for patients

with LVD and heart failure (Sackner-Bernstein 2003). Classification of beta-blockers into those

without or without cardioselectivity or intrinsic sympathomimetic activity provided ambiguous

results (Freemantle et al. 1999). Cardioselectivity showed a non-significant trend towards a

reduced benefit, while the trend was stronger in the same direction for beta-blockers with

intrinsic sympathomimetic activity. Freemantle et al concluded that agents with intrinsic

sympathomimetic activity should be avoided. They note that evidence to support long-term use

was available for metoprolol, propranolol and timolol, although atenolol is most commonly

prescribed in secondary prevention despite a lack of evidence in this setting.

A comparison of carvedilol and metoprolol for patients with chronic heart failure found that

carvedilol improved survival compared with metoprolol, while the incidence of adverse effects

and withdrawals was similar between the two drugs (Poole-Wilson et al. 2003).

2.3.2.4 Time trends

Trends with regards to the prescription of beta-blockers have shown some variability (Table

2.12). Notably, two Australian centres for the MONICA study found markedly different

prescribing patterns with the Perth centre noting a steady increase in beta-blocker prescription

(Thompson et al. 1992), while the Newcastle centre found no increase over time during the

period under observation (Heller et al. 1992). The increase in prescription of beta-blockers was

more gradual than the increase in antiplatelet agents. While the increasing use of aspirin

preceded the large RCT, meta-analysis and guidelines, the increased use of beta-blockers lagged

behind the RCTs and meta-analysis available in the early 1980s and subsequent guidelines. The

study by Spencer et al indicated that prescribing of beta-blockers in patients hospitalised with

AMI in Worchester Massachusetts continued to increase throughout the 1990s (Spencer et al.

2001). Similarly a comparison of 22 quality indicators between 1998-1999 and 2000-2001 by

Jencks et al found that the greatest improvement was for the prescription of beta-blockers at

discharge in post-AMI patients from 72% to 79% (Jencks et al. 2003).


Table 2.12 Longitudinal studies of beta-blocker prescription following an ACS

Year

Study 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00

Percent

Registers

(Heller et al. 1992) 41 39

(Thompson et al. 1992) 46.1 48.5 56.8 57.6 60.7 67.3 64.6

(Bourquin et al. 1998) 37 40 63

(Spencer et al. 2001) 36 37 47 57 62 70 75

Administrative

(Smith et al. 1999b)1 33.3 26.8 35.1 31.5 29.9 36.4

(Pilote et al. 2000) 33 38 43 47 50

(Heller et al. 2000) 39.6 47.2 52.5 58.6

RCT

(Lamas et al. 1992) n/a

(Kizer et al. 1999) 30 57 63 65

Surveys

(Agusti et al. 1994) 20 18 21 23 33 37 34

(Martinez et al. 1998) 34 62 63

(Rumboldt et al. 1995) 39 70 1 Following hospital episode of unstable angina (all other studies follow myocardial infarction)


2.3.3 Statins


Table 2.13 summarises the major secondary prevention trials of statins in CHD up to early

2000. A major difference between the earlier Scandinavian Simvastatin Survival Study (4S)

and the subsequent Cholesterol and Recurrent Events (CARE) and Long-term Intervention with

Pravastatin in Ischaemic Disease (LIPID) trials was the lipid criteria for entry into the trial.

While 4S included only participants with elevated lipid levels, CARE and LIPID included

normolipidemic participants. Furthermore, in the 4S study, dosages of simvastatin were titrated

to achieve a total cholesterol (TC) level of 3.0 to 5.2 mmol/L while the other trials used fixed

dosages.

Table 2.13: Characteristics of statin secondary prevention trials

4S1 CARE2 LIPID3

Year published 1994 1996 1998

Participants 4444 4159 9014

% female 19 14 17

%>65 years 23 31 39

Trial duration (years) 5.4 5.0 6.1

Statin Simvastatin Pravastatin Pravastatin

Dosage (mg/daily) 10-40 40 40

Inclusion criteria

History Angina/MI MI Unstable Angina/MI

Lipid levels (mmol/L) 5.5-8.0 <6.2 4.0-7.0

Baseline lipids (mmol/L)

TC 6.75 5.40 5.64

LDL-C 4.87 3.59 3.88

HDL-C 1.19 1.01 0.93

Triglycerides 1.50 1.76 1.58

Net change lipids (%)

TC -26 -20 -18

LDL-C -35 -28 -25

HDL-C +8 +5 +5

Triglycerides -10 -14 -11 1(Scandinavian Simvastatin Survival Study Group 1994), 2(Sacks et al. 1996) 3(Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Group 1998)


Major outcomes of these trials are summarised in Table 2.14. LaRosa et al in their meta-

analysis reported a pooled risk reduction of 30% (95% CI 24-35%) for major coronary events

(LaRosa et al. 1999). Similarly, treatment with statins was associated with lower risk of

mortality, both coronary (OR 0.71, 95% CI 0.63-0.80) and from all causes (OR, 0.77; 95% CI

0.70-0.85).

Table 2.14: Outcomes from the statin secondary prevention trials

Events (%)

N All deaths Coronary Death Major coronary events4

4S1

Placebo 2223 11.5 8.5 28.0

Simvastatin 2221 8.2 5.0 19.4

χ2p <0.001 <0.001 <0.001

RRR (95% CI) % 30 (15-42) 42 (27-54) 34 (25-41)

CARE2

Placebo 2078 9.4 5.7 13.2

Pravastatin 2081 8.7 4.6 10.2

χ2p 0.38 0.13 0.002

RRR (95% CI) % 9.0 (-12-26) 20 (-5-39) 24 (9-36)

LIPID 3

Placebo 4502 14.1 8.3 15.9

Pravastatin 4512 11.0 6.4 12.3

χ2p <0.001 <0.001 <0.001

RRR (95% CI) % 22 (13-31) 24 (12-35) 24 (15-32) 1(Scandinavian Simvastatin Survival Study Group 1994), 2(Sacks et al. 1996) 3(Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Group 1998) 4 4S:coronary death, nonfatal MI, silent MI or resuscitated cardiac arrest, CARE, LIPID; coronary death and non-fatal infarction

A subgroup analysis of 4S examined the benefits of statin therapy in women (Miettinen et al.

1997). Miettinen et al noted that less than 1 in 5 participants were female and about 1 in 4

participants were ≥65 - 70 years or age (at the time of recruitment). They noted that while

simvastatin produced similar reductions in relative risk for major coronary events for women

and elderly patients, there was no significant relative risk reduction for mortality in females over

a median follow-up period of 5.4 years. This was attributed to the small number of female

deaths making it difficult to assess the effects of statins on mortality. On the other hand there

was a significant reduction in mortality in elderly patients. While the relative risk in elderly

patients was similar to the overall relative risk, the increased absolute risk of death in elderly

patients was about double that in younger patients (Miettinen et al. 1997). Safety and

tolerability in women and elderly patients was similar to that of the overall cohort.


While the management of lipids is universally recommended in secondary prevention

guidelines, there are some differences in the goals of treatment and when treatment should be

commenced. Table 2.15 summarises guidelines for the use of statins in secondary prevention of

CHD in early 2000. While the National Cholesterol Education Program (NCEPII)

recommended initiation of pharmacotherapy if LDL-C exceeded 130 mg/dL (3.4 mmol/L) after

maximal dietary therapy, the American Heart Association Task Force on Risk Reduction in

1997 recommended initiation of pharmacotherapy at the time of hospital discharge in patients

with CHD (Grundy et al. 1997).

Table 2.15: Lipid management guidelines for CHD

Lipid levels (mmol/L)

Goal Initiate therapy Lifestyle modification first

TC LDL TC LDL

Australia1 <4.5 <2.5 >5 >3 No

US2 <5.2

(200 mg/dL)

<2.5

(100mg/dL)

≥3.4

(130mg/dl

)

Yes

Europe3 <5 <3 ≥5 ≥3 Yes

1(National Heart Foundation of Australia 1999), 2(Adult Treatment Panel II 1993), 3(Second Joint Task Force of European and other Societies on coronary prevention 1998; British Cardiac Society et al. 2000)


Patient selection

The traditional process of patient selection in RCTs meant a paucity of data on the benefits of

statins in a number of subgroups of patients including those with diabetes mellitus and elderly

patients, although both groups have higher absolute risks. This lack of evidence for specific

subgroups has been addressed in a number of recent studies.

Diabetes

Initial subgroup analysis of the main RCTs suggested that statin use with diabetes achieved at

least as much benefit in reducing major coronary events as in the nondiabetic cohort (Goldberg

1999). The problem of small sample sizes was addressed in the pravastatin pooling project,

which pooled the results of CARE and LIPID with those of the primary prevention trial

WOSCOPS (Sacks et al. 2000). However, even with pooled results the relatively small number

of patients with diabetes did not provide sufficient statistical power for the primary end point of

myocardial infarction or unstable angina. When the end point was expanded to include

revascularisation procedures, event reduction was significantly reduced (RRR 26, 95% CI:38-

11)).


Changes to the definition of diabetes (blood glucose≥7.0 mmol/L) and the introduction of the

category of impaired fasting glucose (IFG) (6.1- 6.9 mmol/L) allowed the initial RCT data to be

reanalysed using these new definitions. Haffner et al reanalysed data from 4S using these new

definitions expanding the number of diabetics from 202 to 483 with an additional 678 with IFG

(Haffner et al. 1999). Haffner et al noted a progressive rise in major cardiovascular events with

increased glucose status. They were also able to demonstrate reduction of major coronary

events with simvastatin in all groups based on glucose status, although the benefits on coronary

and overall mortality in the diabetic group were not statistically significant. Haffner et al

attributed the lack of significance to small sample sizes.

LIPID study data was also reanalysed using the new definitions of diabetes (Keech et al. 2003).

Keech et al confirmed an increased rate of major cardiovascular events with diabetes (61%

increase) and IFG (23% increase) compared with normal fasting glucose in the placebo group.

In LIPID, pravastatin reduced the risk of major events by 23% (p<0.001) in the non-diabetic

group, 36% (p=0.009) in the IFG group and 19% (p=0.11) in the diabetic group although the

treatment effects were not significantly different (p=0.53) between groups. Pravastatin reduced

the risk of any cardiovascular event by 21% (p<0.008) in the diabetic group and 37.1%

(p=0.003) in the IFG group. Keech et al included a meta-analysis of the three secondary

prevention trials and confirmed the benefits of statin therapy independent of glucose status with

a 28% reduction in coronary events in the diabetic group (p=0.001), 39% in the IGF group

(p<0.001) and 29% in the normal glucose group (p<0.001) (Keech et al. 2003).

Elderly patients

A number of recent studies have confirmed the benefits of statin therapy in elderly CHD

patients. Two studies specifically looked at elderly patients

• In an elderly cohort (70-82 years) Shepherd et al found that statin therapy reduced LDL-C

by 34% with a reduced risk (95% CI) of fatal and non-fatal coronary events of 0.81 (0.69-

0.94). (Shepherd et al. 2002).

• A study of new coronary events in elderly patients with a prior myocardial infarction and

elevated LDL-C found that use of a statin was an independent predictor of reduced coronary

events, even after adjusting for lipid levels. The benefit was noted in each age group up to

and including 100 years of age. The adjusted risk ratio for statins was 0.50 (95% CI 0.43-

0.57) (Aronow et al. 2002).


Other studies that included older patients with CHD and showed benefits at all ages include.

• Subgroup analysis of the LIPID study, which showed similar relative risk of major events in

older (65 to 75 years of age) and younger patients (RR (95% CI); 0.78 (0.66-0.91) and 0.75

(0.64-0.88) respectively. They noted, however, that the absolute risk and, therefore, the

absolute benefit was greater in the older patients. (Hunt et al. 2001)

• The Heart Protection Study, which included high risk patients up to 80 years (CHD or

occlusive arterial disease or diabetes), found the benefits of statins to apply irrespective of

gender, age or initial cholesterol concentration. In non-diabetic subjects less than 65 years,

simvastatin reduced the event rate from 23.1% to 17.6%, while in similar patients 65 years

and older the event rate was reduced from 26.9% to 21.3%. (Heart Protection Study

Collaborative Group 2002)

• In patients with angiographically defined CHD, statin therapy was associated with reduced

mortality in all age groups, including those 80 years and older with the absolute risk

reduction greater in the older patients (Allen Maycock et al. 2002).

Initiation of therapy

Traditionally, lifestyle changes were recommended first with pharmacotherapy added only

when lipid levels failed to reach optimal levels. There is now a shift towards initiating therapy

prior to hospital discharge. This results from several factors including the increased likelihood

of long-term use, a better understanding of the effects of statins and new evidence of an early

benefit of statins.

Increased likelihood of long-term use

Several studies observed that where lipid-lowering therapy was initiated prior to discharge, it

was more likely to be maintained in follow-up care. In a cohort of patients with a baseline

LDL-C ≥100/mg/dL (2.5 mmol/L) undergoing PCI Muhlestein et al found prescription of a

statin at discharge increased the likelihood of using statins at long term follow-up (77%

compared with 40%, p<0.001) (Muhlestein et al. 2001). Muhlestein suggested this indicated

better adherence with treatment when treatment was prescribed at discharge. Furthermore,

patients prescribed statins at discharge had reduced mortality at long-term follow-up (5.7%

compared with 11.7%, p<0.001). Even more convincing was the Cardiac Hospitalisation

Atherosclerosis Management Program (CHAMP) where the increased statin prescriptions at

discharge following the program implementation (6% pre-CHAMP to 86% post-CHAMP) was

maintained at 12 months (10% pre-CHAMP to 91% post-CHAMP) (Fonarow et al. 2001b).

Fonarow argued that in-hospital initiation of lipid lowering therapy enhanced long-term

treatment and patient compliance through:

• Treatment started when the focus is on cardiovascular risk assessment and reduction.


• Expertise of inpatient nurse and pharmacists facilitates patient education on lipid lowering

therapy.

• Hospital-based initiation can allay patient concerns about treatment.

• Linking the initiation of (all) secondary prevention therapy and the patients cardiac

hospitalisation strengthens the perception that the therapy is an essential part of long-term

treatment.

• Hospital initiation may facilitate the coordination of lipid care between the cardiologists and

primary care doctors by inclusion in the discharge summary with a follow-up plan.

As a result of these considerations, the latest US Guidelines recommend commencing the statin

prior to hospital discharge (Grundy et al. 2004).

Better understanding of the effects of statins

A better understanding of the effects of statins, including antithrombotic and anti-inflammatory

effects as well improvement of endothelial function, suggest a more immediate beneficial effect

(Thompson 2001a).

Evidence of the early benefits of statins

There is now a strong body of evidence on the benefits of early statin use in ACS (Pepine 2003).

The evidence comes from both observational studies and RCTs.

Using data from two RCTs Aronow et al estimated the effect of statin therapy on short term

mortality immediately after an ACS (Aronow et al. 2001a). Aronow et al found reduced 30-day

mortality in patients prescribed therapy at hospital discharge (HR 0.44; 95% CI 0.27-0.73).

After adjusting for the propensity to be prescribed lipid lowering therapy and other potential

confounders, prescription at discharge was still associated with a reduced risk of death at 6

months (0.67, 0.48-0.95) (Aronow et al. 2001a). Stenestrand et al used data from the Swedish

Register of Cardiac Intensive Care to investigate the relationship between statins commenced at

or before hospital discharge in post-MI patients and 1-year mortality (Stenestrand et al. 2001).

Adjusting for confounding factors and propensity score for statin use, Stenestrand et al found

reduced 1-year mortality in association with use of statins (RR=0.75, 95% CI 0.63-0.89).

Direct evidence of the benefits of early statin therapy came from the Myocardial Ischemia

Reduction with Aggressive Cholesterol Lowering (MIRACL) Study. MIRACL enrolled

patients with unstable angina or non-Q-wave myocardial infarction to compare atorvastatin 80

mg or matching placebo, commenced between 24 and 96 hours after hospital admission. At 16

weeks follow-up, the primary end point was reduced from 17.4% in the placebo group to 14.8%

in the treatment group (RR=0.84; 95% CI, 0.70-1.00). However, the benefit was restricted to a

lower risk of symptomatic ischaemia with objective evidence and requiring emergency


rehospitalisation (6.2% versus 8.4%; RR 0.74; 95% CI 0.57-0.95) with no effect on risk of

death, nonfatal myocardial infarction, or cardiac arrest. (Schwartz et al. 2001).

Results of the Pravastatin Acute Coronary Treatment (PACT) study, which compared

pravastatin and placebo for one month with 12 month follow-up found that statin therapy could

be safely commenced within 24 hours of the onset of a coronary event (Thompson et al. 2004).

Intensity of therapy

In contrast to the findings that reduction of LDL-C to levels below 3.2 mmol/L (125mg/dL)

gave no further benefit (Sacks et al. 1998), recent studies suggest increased risk reduction

associated with statin treatment at lower LDL-C levels.

The Heart Protection Study in the United Kingdom showed a 25% overall reduction in the

incidence of coronary events associated with a reduction of 1 mmol/L in LDL-C. This benefit

was observed in patients with LDL-C considered to be normal by current guidelines (<3

mmol/L) (Heart Protection Study Collaborative Group 2002).

Other evidence that intensive statin lipid lowering is more effective than moderate lipid

lowering came from studies of the progression of disease as measured by intravascular

ultrasound (Nissen et al. 2004b) and clinical outcomes (Cannon et al. 2004)). Nissen et al

showed that intensive lipid lowering with atorvastatin 80mg compared to moderate lipid

lowering with pravastatin 40mg reduced progression of coronary atherosclerosis in CHD

patients. Cannon et al showed that lipid lowering with atorvastatin 80 mg was more effective

than moderate lipid lowering with pravastatin 40 mg in reducing coronary events in the

subsequent 2 years when the statin was commenced early (Cannon et al. 2004)

Lipid management

All patients hospitalised for ACS should have their LDL-C levels measured, preferably within

the first 24 hours (Adult Treatment Panel III 2002). While several studies have shown the

levels of TC, LDL-C and HDL-C are significantly decreased between day 1 and day 4 post-MI,

neither the LDL-C/HDL-C nor the TC/HDL-C ratios change significantly and can still be used

to provide insights into a patient’s risk status (Pepine 2003).

Following from the studies suggesting early benefits of statins in ACS and additional benefits of

intense versus moderate intensity statin therapy, current recommendations suggest early

initiation of statin therapy in ACS in most patients although some variation remains.

• In Australia treatment is recommended “for all patients with CHD (apart from exceptional

circumstances)” (National Heart Foundation of Australia et al. 2003).


• The NCEPIII guidelines state that patients with LDL-C ≥130 mg/dL (3.3 mmol/L) should

be commenced on statin therapy prior to discharge, while for those with LDL-C of 100-129

mg/dL, a number of options are provided including initiation of statin therapy (Adult

Treatment Panel III 2002). The AHA/ACC guidelines for the management of unstable

angina and non-ST elevation have been updated to recommend commencement of statins in

all patients with LDL-C ≥100.g/dL (2.5 mmol/L) (Braunwald et al. 2002). Similarly, in his

review of lipid management in patients with ACS, Pepine concluded that early, intensive

statin therapy should be commenced in all ACS patients without contraindications (Pepine

2003).

• The European guidelines maintain more conservative thresholds for initiation of therapy,

TC ≥5mmol/L (190 mg/dL) or LDL-C ≥3mmol/L (115 mg/dL) (Van de Werf et al. 2003).

In Britain the National Institute for Clinical Excellence do not recommend initiation of

therapy prior to discharge (North of England Evidence-based Guidelines Development

Project 2001).

2.3.3.3 Selection of statin treatment

New statins

All the large long term RCTs examining the benefits of statins in either primary or secondary

prevention used either simvastatin (Scandinavian Simvastatin Survival Study Group 1994) or

pravastatin (Sacks et al. 1996; Long-term Intervention with Pravastatin in Ischaemic Disease

(LIPID) Study Group 1998). The Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering

Arm (ASCOT-LLA), was the first multicentre randomised controlled trial showing the

effectiveness of atorvastatin in the long term prevention of major cardiovascular event (Sever et

al. 2003). ASCOT-LLA showed that atorvastatin 10 mg in hypertensive patients with at least

three other risk factors and average or lower than average cholesterol levels (≤6.5 mmol/L)

reduced the risk of cardiovascular events (HR 0.64; 95% CI 0.50-0.83). This benefit was

apparent in the first year of follow-up.

The Greek Atorvastatin And Coronary-Heart-Disease Evaluation (GREACE) study compared

atorvastatin, titrated up to 80 mg to achieve the NCEP goal of LDL-C < 100 mg/dl (2.6 mmol/l)

with “usual care”. The mean dosage of atorvastatin required to achieve treatment goals in

GREACE was 24 mg, with a reduced risk of death or a recurrent event with atorvastatin

compared with “usual care” (RR 0.49, 95% CI 0.27-0.73) (Athyros et al. 2002).


Efficacy

Even without evidence of the long-term benefits of atorvastatin a number of studies have

compared the efficacy of statins to reduce LDL-C. Generally these studies all showed that,

compared with patients using other statins, patients using atorvastatin were -

• More likely to achieve target lipid levels; (Brown et al. 1998; Hunninghake et al. 1998;

Andrews et al. 2001; Shepherd et al. 2003).

• More likely to be using low mean doses (Brown et al. 1998; Hunninghake et al. 1998).

• Greater percentage reduction in lipid levels (Jones et al. 1998).

A comparison of the starting doses of statins, including rosuvastatin, the latest statin on the

market (although not yet in Australia), showed rosuvastatin to be the most efficacious in terms

of the proportion of patients achieving treatment goals irrespective of treatment goal assessed

(Shepherd et al. 2003). (Table 2.16).

Table 2.16: Proportion of patients achieving treatment goals

LDL-C goals

Atorvastatin

10mg

Rosuvastatin

10 mg

Simvastatin

20 mg

Pravastatin

20 mg

Rosuvastatin

10mg

All goals (NCEP III) 53% 76% 64% 49% 86%

≤100 mg/dL 19% 60% 22% 5% 63%

<3 mmol/L (116mg/dL) 51% 82% 48% 16% 80% 1Elevated TG 32% 66% 54% 20% 80%

Adapted from (Shepherd et al. 2003) 1Patients with triglycerides (TG )>200 mg/dL achieving NCEP III gaols

While lipid management has primarily focused on LDL-C, the importance of HDL-C and non-

HDL-C is now better understood (Adult Treatment Panel III 2002). A comparison of the effects

of statins on the lipid, lipoprotein, and apolipoprotein (apo) A-I-containing HDL subpopulation

profiles found a beneficial effect of atorvastatin compared with simvastatin and pravastatin

(Asztalos et al. 2002).

Safety

Studies have shown comparable rates of adverse effects for all currently used statins

(Hunninghake et al. 1998; Jones et al. 1998). One statin, cerivastatin, however was withdrawn

from the market in August 2001 because of a severe muscle adverse reaction (U.S.Food and

Drug Administration 2001).

Cost

As noted by Topol, cost is an important reason for undertreatment, consideration of which

applies both to the choice of agent and the dose (Topol 2004). Table 2.17 shows the current


dispensing price ($A) per patient per year for the most commonly used statins in Australia.

These costs are borne by the government through the Pharmaceutical Benefits Scheme, while

the patient copayment is constant irrespective of the drug and dose (Pharmaceutical Benefits

Scheme 2004). In the Australian setting neither the specific agent nor the dose should impact

on undertreatment, although the cost to the health system is particularly dependent on dose.

Table 2.17: Dispensed price ($A) of statins in Australia per patient per year

Dosage

10 mg 20 mg 40 mg 80 mg

Statin

Atorvastatin 518 715 1001 1408

Pravastatin 402 603 908 -

Simvastatin 492 679 948 1332

Schedule of pharmaceutical benefits, effective May 2004

Timing of dose

Convenience is another important factor in treatment adherence of which timing of the dosing is

an important component. Table 2.18 lists the pharmacokinetic characteristics of commonly

used statins (Knopp 1999). Pravastatin is hydrophilic and should therefore taken on an empty

stomach while simvastatin and atorvastatin are lipophilic and should be taken with meals.

Atorvastatin with a much longer half life has been shown to be as effective when taken in the

morning as in the evening (Cilla et al. 1996), while use of simvastatin in the morning has been

shown to reduce the efficacy (Wallace et al. 2003).

Table 2.18 Pharmacokinetic characteristics of commonly used statins

Pravastatin Simvastatin Atorvastatin

Maximal dose (mg) 40 80 80

Maximal LDL-C reduction 34 47 60

Plasma half life 1-2 1-2 14

Solubility Hydrophilic Lipophilic Lipophilic

Effect on food absorption Decreased None None

Optimal time of administration Bedtime Evening Evening

Penetration of nervous system No Yes No

Renal excretion of absorbed dose (%) 20 13 2

Mechanism of hepatic metabolism Sulphation Cytochrome

450 3A4

Cytochrome

450 3A4

Adapted from Knopp 1999 (Knopp 1999)


2.3.3.4 Time trends

Data on trends in prescription of statins at the time of hospital discharge following an ACS are

scant (Table 2.19). Until recently, CHD per se was not considered an indication for statin

therapy. Instead, recommendations for lipid lowering therapy related to lipid levels and in many

cases only after failure of lifestyle changes to suitably reduce lipid levels. Thus, a measure of

statin prescription at hospital discharge was not in itself a quality care indicator. Nonetheless, it

is clear from the data available that while the prescription of lipid lowering therapy increased

slowly over the 1980s the rate of change increased sharply after 1994 and publication of the

results of the 4S trial.

Other studies not specifically addressing discharge prescriptions post-ACS also showed marked

increases in the use of statins following the landmark clinical trials. De Wilde et al using data

from general practices across England and Wales found that prescription of statins increased

from 1994 to 2001 in patients with ischaemic heart disease, while patients with a previous

infarction or revascularisation procedure were 2-4 times more likely to be prescribed a statin

than patients with angina or other unspecified ischaemic heart disease. In a 20 year follow-up

of the British Heart Study, Whincup et al found a clear trend in the use of lipid lowering therapy

with the year of diagnosis (Whincup et al. 2002).

Other non-CHD specific studies using administrative data have all shown changes in line with

the evolving evidence. Using data from the Prescription Pricing Authority changes in

prescribing of lipid lowering therapy from 1990 to 1996 was described by an initial linear phase

followed by an exponential phase, with the change point closely related to the publication of the

4S results (Baxter et al. 1998). A study of prescriptions from 1996 to 1998 showed that

prescriptions for statins increased fourfold during this period (Packham et al. 2000). In

Australia the use of statins has increased considerably since 1994 and the publication of 4S,

with the number of prescriptions almost doubling between 1998 and 2000. (Australian Institute

of Health and Welfare 2004b). Although not exclusive to patients with existing CHD, these

studies provide evidence of the changing prescribing patterns in response to new evidence.


Table 2.19 Longitudinal studies of lipid lowering prescription following an ACS

Year

Study 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00

Percent

Registers

(Heller et al. 1992) 1 4

(Thompson et al. 1992) 1.0 0.5 1.8 2.5 3.8 3.2 3.1

(Bourquin et al. 1998) n/a

(Spencer et al. 2001) 1 5 5 4 9 10 23

(Yarzebski et al. 2001) 0.4 10.7

Administrative

(Pilote et al. 2000) 5 7 7 9 13

(Heller et al. 2000)2 8.4 11.9 15.2 22.3

(Jackevicius et al. 2001) 5.5 6.9 9.6 17.8 24.9 2 Prescription dispensed within 3 months of discharge


2.3.4 ACE inhibitors


The role of ACE inhibitors in the secondary prevention of CHD has evolved since they were

introduced into clinical practice in the mid 1980s (Lonn et al. 1994; Latini et al. 1995).

Although initially marketed as antihypertensive agents, evidence of a direct benefit of ACE

inhibitors in heart disease soon followed. First came trials showing the benefit of ACE

inhibitors in the treatment of CHF. These were followed by trials showing the long-term benefit

of ACE inhibitors in post-MI patients with moderate left ventricular function in preventing the

sequale of heart failure, and ACS. Benefits of early treatment with ACE inhibitors in all post-

MI patients followed. Finally ACE inhibitors were shown to reduce the risk of mortality and

ACS in high-risk patients. Table 2.20 summarises the initial large long-term trials that

commenced ACE inhibitor therapy soon after MI in patients with CHF or LVD. Long-term all

cause mortality was significantly reduced in all three studies, while there was a trend for

reduced rate of long-term reinfarction (Table 2.21).

Table 2.20: Long term ACE inhibitors with LVD post-MI

SAVE1 AIRE2 TRACE3

Year published 1992 1993 1995


Trial duration (months) 42 15 36

Days post-MI 3-16 3-10 3-7

Inclusion criteria LVEF<40% Clinical heart failure LVEF<35%

ACE inhibitor Captopril Ramipril Trandolapril

Dosage (mg daily) 75-100 5-10 1-4 1(Pfeffer et al. 1992), 2(Acute Infarction Ramipril Efficacy (AIRE) Study Investigators 1993) 3(Kober et al. 1995)

Table 2.21: Long-term ACE inhibitors in LVD post-MI

SAVE1 AIRE2 TRACE3

All cause mortality Placebo 24.6 23 42.3

ACE inhibitor 20.4 17 34.7

χ2 p 0.019 0.002 0.001

RRR 19 (3-32) 27 (11-40) 22 (9-33)

Reinfarction Placebo 15.2 8.9 12.9

ACE inhibitor 11.9 8.0 11.3

χ2 p 0.015 0.48 0.29

RRR 25 (5-40) 11 (-22-35) 14(-13-34) 1(Pfeffer et al. 1992), 2(Acute Infarction Ramipril Efficacy (AIRE) Study Investigators 1993), 3(Kober et al. 1995),


A meta-analysis of early studies of long-term ACE inhibitor therapy in patients with heart

failure or LVD, with a history of myocardial infarction, are summarised in Table 2.22. Flather

et al found that the benefits were observed early after therapy was initiated and persisted

throughout. They noted that the benefits were independent of age, sex, and baseline use of

aspirin, beta-blockers and diuretics (Flather et al. 2000).

Table 2.22: Benefits of ACE inhibitor therapy in post-MI patients

SAVE/AIRE/TRACE SOLVD All


OR (95% CI)

Mortality 0.74 (0.66-0.83) 0.87 (0.78-0.98) 0.80 (0.74-0.87)

Reinfarction 0.80 (0.69-0.94) 0.78 (0.65-0.92) 0.79 (0.70-0.89)

Readmission Congestive Heart Failure 0.73 (0.63-0.85) 0.63 (0.56-0.72) 0.67 (0.61-0.74)

All events 0.75 (0.67-0.83) 0.70 (0.64-0.78) 0.72 (0.67-0.78) 1(Flather et al. 2000)

Evidence of the benefits of ACE inhibitors in the immediate post-MI period independent of

heart function came from a number of trials (Latini et al. 1995). The ACE inhibitor Myocardial

Infarction Collaborative Group conducted an overview of four of these trials for which data

were available at the patient level. (ACE Inhibitor Myocardial Infarction Collaborative Group

1998). The characteristics of these trials are summarised in Table 2.23. Using data from 98,496

patients the Collaborative Group concluded that:

• There was a small but significant reduction in 30-day mortality that translated into 5 deaths

avoided per 1000 patients.

• Most of this benefit was apparent within the first week with 4 lives saved per 1000 patients.

• The relative benefit was consistent across various patient groups, but patients at higher risk

experienced a greater absolute risk reduction.

• There was no subgroup of patients in which treatment was shown to be harmful, although

adverse effects of hypotension and renal dysfunction were more prevalent in older patients

(≥75 years) and there was no evidence of a survival advantage in this group.


Table 2.23: Early ACE inhibitor trials

CONSENSUS-II GISSI-3 ISIS-4 CCS-1

Participants 6090 19394 58050 14962

Hours post-myocardial infarction <24 <24 <24 <36

ACE inhibitor Enalapril Lisinopril Captopril Captopril

Initial Dose 1mg IV infusion 5 mg 6.25 mg 6.25 mg

Ongoing dose (mg daily) 5-20 10 100 37.5

Treatment duration (days) 180 42 28 28

≥75 years 23 18 15 9

% Female 27 22 26 26 1(ACE Inhibitor Myocardial Infarction Collaborative Group 1998)

The ACE Inhibitor Myocardial Infarction Collaborative Group suggested two possible strategies

for the use of ACE inhibitors post-MI (ACE Inhibitor Myocardial Infarction Collaborative

Group 1998).

• Starting ACE inhibitor therapy in AMI for all patients without a clear contraindication.

Treatment should be evaluated at discharge or after a few weeks and should be continued

long term only in patients at highest risk.

• Initiate and continue therapy in patients with anterior infarct, and other high-risk patients,

including those with heart failure, high heart rate, and diabetes.

The uncertainly about patient selection is echoed in the AHA/ACC guidelines that recommend

the early use of ACE inhibitors in patients with an anterior infarction in the absence of

hypotension (<100 mm Hg) or known contraindication as a Class I recommendation, while the

early use of ACE inhibitors in all other patients is a Class IIa recommendation (AHA/ACC

1999). Others advocate a more aggressive approach “ACE inhibitors should be considered in

every patient with acute myocardial infarction soon after the decision on the use of aspirin,

reperfusion and beta-blockers has been made. Patients at increased risk for early death, such as

those with a past history of hypertension, diabetes or prior infarcts, or who present with higher

heart rates, anterior ECG involvement, manifest pulmonary congestion, or LVD on an

assessment of ventricular performance have the most to gain from the early initiation of an ACE

inhibitor” (Pfeffer 1998).

Unequivocal evidence of the benefit of ACE inhibitors in high-risk patients with no known

LVD came with the publication of the Heart Outcomes Prevention Evaluation (HOPE) study.

The study recruited 9297 high risk patients with either vascular disease or diabetes plus at least

one other cardiovascular risk factor and not known to have a low LVEF (Yusuf et al. 2000).

Treatment with ramipril commenced at 2.5 mg daily, titrated over one month to 10 mg daily.

Outcomes of the HOPE study are shown in Table 2.24.


Table 2.24: Primary, secondary and other outcomes in HOPE study

Ramipril

N=4645

Placebo

N=4652

RR

(95% CI)

Percent

Primary end points

Combined 14.0 17.8 0.78 (0.70-0.86)

Cardiovascular death 6.1 8.1 0.74 (0.64-0.87)

Myocardial infarction 9.9 12.3 0.80 (0.70-0.90)

Stroke 3.4 4.9 0.68 (0.56-0.84)

Secondary end points

Death (any cause) 10.4 12.2 0.84 (0.75-0.95)

Revascularisation 16.0 18.3 0.85 (0.77-0.94)

Diabetic complications 6.4 7.6 0.84 (0.72-0.98)

Hospitalisation, unstable angina 11.9 12.1 0.98 (0.87-1.10)

Hospitalisation, heart failure 3.0 3.4 0.88 (0.70-1.10)

Other end points

Cardiac arrest 0.8 1.3 0.62 (0.41-0.94)

New diagnosis of diabetes 3.6 5.4 0.66 (0.51-0.85)

Heart failure, any 9.0 11.5 0.77 (0.67-0.87)

Worsening angina 23.8 26.2 0.89 (0.82-0.96)

UA with ECG changes 3.8 3.9 0.97 (0.79-1.19)

(Yusuf et al. 2000)

The benefits of ramipril were independent of age, gender, and medical history including

cardiovascular disease, diabetes, hypertension, CHD, myocardial infarction, cerebrovascular

disease, peripheral vascular disease or microalbuminuria. Reduction in the primary endpoint

(composite of myocardial infarction, stroke, or death from cardiovascular causes was evident at

one year (RR 0.85; 95% CI 0.70-1.05) and statistically significant by the second year (RR 0.82;

95% CI 0.70-0.94).

Consistent with other studies (Lewis et al. 1993; GISEN Group (Gruppo Italiano di Studi

Epidemiologici in Nefrologia) 1996; Hansson et al. 1999), the HOPE study found a decrease in

diabetic complications and points to an important role of ACE inhibitors in all diabetic patients

(Heart Outcomes Prevention Evaluation Study Investigators 2000).



Patient selection

Following the publication of the HOPE study, recommendations for the use of ACE inhibitors

in the secondary prevention of CHD were modified to recommend that ACE inhibitors should

be considered in all patients after myocardial infarction, irrespective of the presence of LVD.

With the exception of Scottish guidelines that were updated early in 2000 (Scottish

Intercollegiate Guidelines Network 2000), there was a significant time lag before other

guidelines were updated (Smith et al. 2001a; National Heart Foundation of Australia et al. 2003;

Van de Werf et al. 2003)

Publication of the EURopean trial On reduction of cardiac events with Perindopril in stable

coronary Artery disease (EUROPA) trial in 2003 confirmed the benefits of ACE inhibitors in

patients with CHD with no evidence of heart failure (The EURopean trial On reduction of

cardiac events with Perindopril in stable coronary Artery disease Investigators 2003). EUROPA

enrolled 12218 patients with no evidence of heart failure but with CHD documented by

• a myocardial infarction more than three months prior;

• a revascularisation procedure more than six months prior; or

• angiographic evidence of at leat 70% stenosis in one or more major coronary arteries.

Patients were randomly assigned to 8mg of perindopril or placebo. Perindopril was reduced to

4mg in 7% of patients who did not tolerate the higher dose. The study found a 20% Relative

Risk Reduction (9 to 29%, p<0.001) in the primary end point (composite of cardiovascular

mortality, non-fatal myocardial infarction and successful resuscitation of cardiac arrest). The

outcome was improved in all age groups and among patients with and without hypertension,

diabetes mellitus, previous myocardial infarction and concomitant lipid lowering therapy or

beta-blockers.

ACE inhibitor doses

Several recent studies addressed the issue of the effect of specific doses of the most common

ACE inhibitors and suggested dose related benefits on cardiovascular related outcomes.

Study to evaluate carotid ultrasound changes in patients treated with ramipril and

vitamin E (SECURE) (Lonn et al. 2001)

This sub-study of the HOPE study assessed the effects of 2.5 mg/day or 10 mg/day ramipril on

atherosclerosis. The investigators found that 10 mg/day of ramipril slowed atherosclerotic

progression compared with both placebo and 2.5 mg/day ramipril. Although 2.5 mg/day did not

significantly reduce progression compared with placebo, there was a trend suggesting a dose


dependent effect. Importantly the influence on blood pressure between the two doses of

ramipril was similar.

DIABHYCAR (non-insulin-dependent diabetes, hypertension, microalbuminuria or

proteinuria, cardiovascular events and ramipril) study (Marre et al. 2004)

This study examined the effects of low dose (1.25 mg/day) ramipril on cardiovascular and renal

outcomes in patients with type 2 diabetes and raised urinary albumin excretion. The study with

a median follow-up time of 4 years found no difference in either cardiovascular or renal events.

These findings contrast with both the HOPE and MICRO-HOPE studies that showed that

10mg/day of ramipril was both cardioprotective and renoprotective. This suggested that a

marked inhibition of the RAAS is required to reduce cardiovascular risk associated with type 2

diabetes and raised urinary albumin excretion.

Angiotensin receptor blockers

Angiotensin receptor blockers (ARB) block the RAAS by inhibiting A2 receptors and

theoretically provide a more complete block and should therefore be more effective than ACE

inhibitors in reducing the post-MI risk. Several studies compared ARBs and ACE inhibitors

post-MI.

Optimal Trial in Myocardial Infarction with Angiotensin II Antagonist Losartan

(OPTIMAAL) (Dickstein et al. 2002)

The hypothesis for this study was that treatment with losartan (ARB) would be at least as

effective as captopril (ACE inhibitor) at decreasing the risk of all cause mortality in high risk

post-MI patients with signs or symptoms of heart failure. However, this study of more than

5000 patients found a non-significant difference in all cause mortality in favour of captopril

(RR 1.13, 95% CI 0.99-1.28) and a significant difference in favour of captopril for

cardiovascular death (RR 1.07, 95% CI 1.01-1.34). This led Dickstein et al to conclude that

ACE inhibitors should remain the first line of treatment in patients after a complicated

myocardial infarction; however, losartan should be considered for patients who cannot tolerate

ACE inhibitors.

Valsartan In Acute Myocardial Infarction Trial (VALIANT) (Pfeffer et al. 2003)

This study compared the effects of captopril (ACE inhibitor), valsartan (ARB) or a combination

of both in high-risk post-MI patients with clinical or radiological evidence of heart failure or

LVD. VALIANT found no difference in mortality between the three treatment groups. Nor

were there any differences in cardiovascular morbidity and mortality between the three

treatment groups. Adverse effects, however, were more common with combined therapy.


2.3.4.3 Selection of ACE inhibitor

While the benefits of ACE inhibitors are assumed to be a class effect, it is true that as in an

editorial accompanying the publication of EUROPA, “findings with high dose perindopril and

ramipril (both long acting ACE inhibitors with high penetration into tissue) may not be

applicable across the range of ACE inhibitors with varying properties and administered in

different doses” (White 2003).

Trials of ARBs failed to prove these agents more effective than ACE inhibitors indeed they may

even be less effective and raise questions about the comparability of various ARBs. Given the

cost differential between generic ACE inhibitors and ARBs, ACE inhibitors remain the first line

treatment for high-risk post-MI patients. However, there is now an alternative for patients who

cannot tolerate ACE inhibitors (Mann et al. 2003).

2.3.4.4 Time trends

Moderate increases in the prescription of ACE inhibitors following myocardial infarction were

noted through the 1990s, reflecting the evolving evidence for ACE inhibitors use post-MI

(Table 2.25). Two recent studies utilising administrative prescription databases showed a

marked increase in ACE inhibitor prescriptions since the beginning of 2000 and the publication

of the HOPE study. A linear increase in ACE inhibitor prescriptions from 1985 to 2001 was

observed, although trends varied for individual ACE inhibitors (Hemels et al. 2003). Hemels et

al noted a marked increase in ramipril prescriptions from 9.2% to 32.8% of all ACE inhibitor

prescriptions, which was attributed to the HOPE study. A study of elderly patients in Ontario,

found relatively constant new ACE inhibitor prescriptions from 1993 to late 1999 when there

was a significant increase in new prescriptions, attributed to the HOPE study (Tu et al. 2003).


Table 2.25 Longitudinal studies of ACE inhibitors prescription following an ACS

Year

Study 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00

Percent

Registers

(Heller et al. 1992) 2 17

(Thompson et al. 1992) n/a

(Bourquin et al. 1998) n/a 19 30

(Spencer et al. 2001) n/a n/a 17 19 22 27 43

(Barron et al. 1998a) 25.0 30.7

Administrative

(Pilote et al. 2000) 33 36 34 37 41

RCT

(Kizer et al. 1999) n/a n/a n/a n/a 7.0 33.1

Surveys

(Martinez et al. 1998) n/a n/a 14 23


2.3.5 Combined therapy

The increasing number of therapies shown to be effective in the secondary prevention of CHD

raises questions about the efficacy of each therapy in combination with other therapies. For

example, the common pathway of aspirin and ACE inhibitors through prostaglandins led to

some speculation that the beneficial effects of ACE inhibitors may be attenuated in patients

receiving aspirin.

This concern was fuelled by observations from studies that suggested a trend towards a reduced

benefit of ACE inhibitors in patients receiving antiplatelet agents (Nguyen et al. 1997) This

theory was tested in a meta-analysis of more than 22,000 patients from six large long term trials

of ACE inhibitor therapy (Teo et al. 2002). When the SOLVD trials were excluded from the

analysis Teo et al found no significant interaction between aspirin and ACE inhibitors for the

composite of major vascular events (p=0.15). They also found no significant interaction for

individual end points including death, stroke, admission for CHF and revascularisation,

although there was a significant interaction between aspirin and ACE inhibitors for myocardial

infarction (p=0.01). Even when the SOLVD trials were included in the analysis there was a

marked benefit of ACE inhibitors both with (0.71,0.620.81) and without (0.80,0.73-0.88) aspirin

use at baseline, with no significant interaction (p=0.07). The authors note that the analysis was

complicated by differences in patient characteristics for those using aspirin at baseline compared

with those who were not, with patients using aspirin having a better prognosis. Teo et al

concluded that in a setting where a RCT to test the interaction between aspirin and ACE

inhibitors is inappropriate, there were clinically important benefits with ACE inhibitor therapy

irrespective of aspirin therapy and both therapies should be considered concomitantly (Teo et al.

2002).

Evidence of the additive effects of these two agents was also provided by data from the CCP

that showed the reduction in 1-year mortality with both ACE inhibitors and aspirin was greater

than for either drug alone in elderly post-MI patients (Krumholz et al. 2001). However, this was

neither significant nor substantial.

Comparisons of the benefits of ACE inhibitors and beta-blockers alone and together in post-MI

patients with reduced left ventricular function have shown an additive benefit. Aronow et al

showed that the reduction in new coronary events was 25% for beta-blockers alone, 17% for

ACE inhibitors and 37% for combined therapy (Aronow et al. 2001b). Similarly, Shiplack et al

found that compared to patients prescribed neither drug, 1-year mortality was reduced for ACE

inhibitors, beta-blockers or both drugs. Furthermore, use of both drugs reduced 1-year mortality

compared with ACE inhibitor alone (HR 0.84, 95% CI 0.73 to 0.98) and beta-blockers alone

(HR 0.86, 95% CI 0.71 to 1.06) (Shlipak et al. 2001). The efficacy of beta-blockers has also


been shown to be independent of time, and therefore concomitant therapies (Freemantle et al.

1999).

Mukherjee et al assigned appropriateness scores to all patients with ACS based on the number

of indicated secondary prevention therapies used. They found an incremental benefit with

increasing appropriateness score (Mukherjee et al. 2004).

In an editorial accompanying the paper by Mukherjee et al it was noted that the benefit of

statins in the presence of other secondary prevention therapies was shown in both LIPID and

CARE where more than 80% of patients were using aspirin and in ASCOT where statins were

added to antihypertensive therapy including beta-blockers and ACE inhibitors (White et al.

2004). Similarly, in EUROPA, background therapy included antiplatelet agent 92%, beta-

blockers 62%, and lipid lowering therapy 58%.

Yusuf estimated that use of all four pharmacotherapies would reduce the risk of an event within

two years from 8% to 2.3% in a person with CHD (Yusuf 2002). This assumes an independent

effect of each therapy, however, as suggested by Mukherjee the risk may be reduced by as much

90% with the use of all four therapies (Mukherjee et al. 2004).

2.3.6 Summary

Use of antiplatelet agents, particularly aspirin, beta-blockers, statins and ACE inhibitors

increased in association with the evidence of the benefit of each of these agents in the secondary

prevention of CHD. Relative to the other therapies use of beta-blockers has lagged behind the

available evidence. New developments in terms of new drugs, eligible populations and

evidence of benefits all point towards the increasing use of these therapies in the secondary

prevention of CHD. The benefit of each drug appears to be via independent pathways thus

providing an additive risk reduction.


2.4 Evidence-based prescribing

As early as 20 years ago the gap between the evidence from RCTs and clinical practice was

noted. In 1983, an analysis of the impact of the Coronary Drug Project on clinical practice

found a considerable time lag between the publication of the findings and assimilation of this

information into practice (Friedman et al. 1983). The authors noted “that investigators and

clinical trial sponsors must devote considerable time and effort to disseminate results if they are

to be incorporated into clinical practice. Findings must be reported at scientific meetings, in

peer-reviewed journals, in journals for medical practitioners and to the general media. Public

health leaders and policy makers including medical professional organisations must share

responsibility for educating medical practitioners in the clinical implications of findings from

clinical trials”. Since that time a number of studies focusing on physicians’ prescribing patterns

in post infarction patients have been published.

The time of hospital discharge provides one opportunity to examine prescribing practices

following an ACS. However, while this provides a clear indication of the treatment plan

devised at hospital discharge, it may not reflect long term treatment, which will be influenced

by both the primary healthcare provider and the patient. Measures of drug use in ambulatory

care, on the other hand, provide a better measure of missed opportunities for secondary

prevention but reflect a combination of doctors’ practices and patient factors. Drug

prescriptions at hospital discharge are usually derived from the patient hospital medical record,

while measures of drug use in ambulatory care may be derived from medical records, patient

report or through prescription claims. Drug use at the time of admission in patients with a

previous history of disease has also been used as a measure of drug use in ambulatory care.

Drug use at the time of admission with a prior diagnosis of ACS can be useful in describing

changing trends and indicate the type of patients least likely to be using appropriate therapies

(Phillips et al. 1996; Majumdar et al. 1999; McCormick et al. 1999a; Putnam et al. 2004).

However, given the benefits of drug therapy, estimates of drug use based on admissions with a

cardiac event would represent an underestimation of the use in ambulatory care.

While a simple measure of the proportion of patients prescribed a therapy provides some

information about the level of evidenced-based prescribing, there are a number of clinical

factors that may legitimately influence prescribing while other clinical or demographic factors

may influence prescribing inappropriately. This section reviews the literature on the factors that

influence prescription of secondary prevention therapies. Most of these studies examine

prescribing at the time of hospital discharge, with fewer studies in the ambulatory care setting.



Recent estimates of prescription of antiplatelet agents at the time of hospital discharge were

relatively high with more that 80% of patients prescribed an antiplatelet agent at discharge

(Rogers et al. 2000; Danchin et al. 2002; Steg et al. 2002a; Eagle et al. 2004). Nonetheless,

recent interventions to improve the quality of secondary prevention for CHD suggest that

improvement is still possible (Fonarow et al. 2001b; Mehta et al. 2002), although at least one

study found no significant improvement in antiplatelet agent prescriptions following a quality

improvement intervention (Scott et al. 2004).

Results from studies that examined independent predictors of antiplatelet agent prescription are

summarised in Table 2.26. Lamas et al examined the influence of the publication of ISIS-2 in

1988 on clinical practice using SAVE study data. This included post-MI patients less than 80

years of age with a LVEF less than 40% (Lamas et al. 1992). Krumholz et al included only a

subset of “ideal” elderly Medicare patients from the CCP pilot study in their analysis. Patients

were included if they were at least 65 years of age, had no terminal illness (including a life

expectancy of less than 6 months, documented palliative care only or “not for resuscitation”)

and no relative contraindication to aspirin; including the use of warfarin, history of

haemorrhagic stroke, active bleeding in hospital, history of gastrointestinal bleeding, high

creatine level or low platelet count or low hematocrit (Krumholz et al. 1996). PREVENIR

compared the medication management of myocardial infarction and unstable angina between

conservative treatment and PCI. The ENACT study compared medication management with the

availability and use of coronary interventions.

A number of aspects of care were consistently associated with increased odds of aspirin

prescription including a revascularisation procedure and preadmission use of aspirin. Other

aspects of patient care associated with increased prescription were thrombolytic therapy, aspirin

in hospital, beta-blocker prescription and admission to a university hospital.

Although the study by Krumholz et al included only “ideal” patients, and excluded patients with

terminal illness, there was a negative association between aspirin prescription and a number of

measures of comorbidity and complications including extended hospital stay, reduced albumin,

reduced left ventricular function and diabetes. The negative association with diabetes was also

observed by Lamas et al although diabetes was not associated with aspirin prescription in the

two more recent studies. The negative association with left ventricular function was also

observed by Spencer et al (Spencer et al. 2001), while LVD was not associated with aspirin

prescription in PREVENIR and heart failure was positively associated with aspirin prescription

in ENACT. These findings correspond with the wider use of aspirin in the later studies, and

accord with the evidence that suggests the greatest benefit is derived for those at greatest risk.


While none of the studies listed found any association with age, the study by Spencer et al

found that the odds of aspirin prescription were uniformly reduced for all patients 55 years and

older compared with younger patients. The finding of an association between male gender and

aspirin prescription in ENACT is somewhat surprising since gender was not associated with

aspirin prescription in the earlier studies.

Table 2.26: Predictors of antiplatelet agent prescription

SAVE1

1987-90

CCP2

1992-93

PREVENIR3

1998

ENACT4

1999

Aspirin prescription 58.7% 76% 90% ~80%

Odds Ratio (95% CI)

Post ISIS-2 2.28 (1.89-2.76)

Preadmission aspirin 2.99 (2.29-3.92) 1.65 (1.39-1.94) 4.24 (2.61-6.31)

PCI 2.21 (1.64-2.97) 1.63 (1.24-2.14) 2.97 (1.82-4.52) 1.89 (1.37-2.61)

CABG 2.07 (1.43-3.01) 2.02 (1.59-2.57) Exclusion NS

Thrombolytic therapy 1.52 (1.22-1.90) NS NS

Cardiac angiogram 1.37 (1.10-1.69) NS 1.29 (.99-1.66)

LVEF determined Inclusion criteria 1.38 (1.17-1.64)

aspirin in hospital NI1 14.10 (11.5-17.1)

Beta-blocker discharge NI 1.68 (1.42-2.00)

University hospital NI NI 2.02 (1.32-3.09) 1.35 (1.11-1.65)

Discharged home NI 1.97 (1.67-2.31) NI

Ventricular Tachycardia NI 1.44 (1.03-2.02) NI

LOS>12 days NI 0.58 (0.48-0.71) NI

Albumin <265.2µmol/L NI 0.74 (0.63-0.86) NI

LVEF<40% Inclusion criteria 0.68 (0.56-0.84) NS

Heart failure 1.96 (1.57-2.44)

Diabetes 0.78 (0.62-0.98) 0.81 (0.70-0.94) NS NS

Current smoking 1.54 (1.00-2.39) NS

Admission for MI Inclusion criteria Inclusion criteria 2.21 (1.47-3.33)

Final diagnosis cardiac 3.04 (2.20-4.20)

Anterior site

Q-wave

Warfarin after MI 0.25 (0.21-0.31) Exclusion

Male NS NS NS 1.32 (1.08-1.61)

Age (years) NS NS NS NS

1(Lamas et al. 1992), 2(Krumholz et al. 1996), 3(Danchin et al. 2002), 4(Steg et al. 2002b) NI –not included in model

2.4.2 Beta-blockers

Recent estimates of beta-blocker prescription suggest that prescribing of these agents may also

be nearing optimal levels. Two recent intervention studies showed no significant increases in

the proportion of patients prescribed beta-blockers at discharge (Mehta et al. 2002; Scott et al.


2004). These findings contrasted with another study where beta-blocker prescription post-MI

was the quality indicator showing the greatest improvement (Jencks et al. 2003)

A lack of consensus in the literature about what constitutes contraindications to beta-blockers

complicates any measure of the appropriate use of beta-blockers. As previously discussed this

is one area that continues to evolve. Estimates of patients with clear contraindications to beta-

blockers vary from 18% (Viskin et al. 1995) to 60% (Krumholz et al. 1998). However, in their

analysis on the use of beta-blockers in the CCP pilot study Krumholz et al examined various

definitions of “ideal” patients and found that varying the criteria for ideal patients did not alter

the rate of beta-blocker use (Krumholz et al. 1998). While a number of studies included only

ideal patients (Viskin et al. 1995; Soumerai et al. 1997; Krumholz et al. 1998) other studies

have included these as covariates in a multivariate analysis. Inclusion of contraindications was

incomplete in studies using administrative data (Soumerai et al. 1997; Beck et al. 2001).

As expected, studies found that historical contraindications, including heart failure, were

negatively associated with beta-blocker prescription (Agusti et al. 1994; Heller et al. 2000;

Beck et al. 2001; Spencer et al. 2001; Danchin et al. 2002). There was a positive association

with other indications for beta-blockers including hypertension (Agusti et al. 1994; Spencer et

al. 2001) and angina (Spencer et al. 2001), while alternative therapies for beta-blocker

indications were inversely associated with beta-blocker prescription including calcium

antagonist (Agusti et al. 1994; Soumerai et al. 1997; Krumholz et al. 1998; Heller et al. 2000),

ACE inhibitors, (Soumerai et al. 1997; Krumholz et al. 1998; Heller et al. 2000), diuretic drugs

(Viskin et al. 1995; Krumholz et al. 1998; Heller et al. 2000)) and digoxin (Soumerai et al.

1997; Heller et al. 2000). Severity of infarction was directly associated with beta-blocker

prescription (Krumholz et al. 1998; Heller et al. 2000; Beck et al. 2001; Spencer et al. 2001)),

while signs of LVD were inversely related to beta-blocker prescription (Viskin et al. 1995;

Danchin et al. 2002).

Other associations noted included an inverse relationship with increasing age (Agusti et al.

1994; Viskin et al. 1995; Soumerai et al. 1997; Krumholz et al. 1998; Beck et al. 2001; Spencer

et al. 2001; Danchin et al. 2002) and variable associations with gender (Heller et al. 2000; Beck

et al. 2001). Associations included previous history (Krumholz et al. 1998) and patterns of care

(Krumholz et al. 1998; Danchin et al. 2002). Negative associations were noted for various

measures of overall well being including; length of hospital stay (Krumholz et al. 1998; Heller

et al. 2000), severity score at admission (Heller et al. 2000), number of previous hospital

admissions, number of secondary diagnosis (comorbidities) and high risk secondary diagnosis

including cancer, renal failure, pneumonia or cerebrovascular disease (CVD) (Soumerai et al.


1997). Physician specialities (Krumholz et al. 1998; Heller et al. 2000) and regional differences

(Krumholz et al. 1998; Heller et al. 2000) were also associated with beta-blocker prescription.

2.4.3 Statins

Until recently, relatively low levels of statin prescription at discharge had been recorded,

reflecting the evolving guidelines which recommended non-pharmacological efforts to reduce

lipid levels prior to initiation of statins. In CHAMP, an intervention with a goal to increase

prescription of statins at discharge, the proportion of patients receiving statins increased from

6% to 86% (Fonarow et al. 2001b).

In this setting it might be expected that a number of factors would be associated with the

prescription of lipid lowering therapy. Using logistic regression analysis, demographic, clinical,

treatment and process-of-care factors have been shown to be associated with the prescription of

statins in the post ACS setting.

An inverse relationship between prescription of statins and increasing age has been shown

consistently across all studies (Beck et al. 2001; Fonarow et al. 2001a; Spencer et al. 2001;

Danchin et al. 2002; Steg et al. 2002b). Gender was not associated with statin prescriptions in

the Worcester Heart Attack Study or the French PREVENIR study, while males were

marginally more likely to be prescribed statins in the NRMI and, males were even more likely

to be prescribed statins in the ENACT study.

When included in the model, hyperlipidemia was associated with increased odds of statin

prescription (Beck et al. 2001; Fonarow et al. 2001a; Danchin et al. 2002; Steg et al. 2002b).

Associations with other medical history were more variable. For example, angina was

positively associated (Spencer et al. 2001) or not associated (Beck et al. 2001; Danchin et al.

2002). Hypertension was positively associated with lipid lowering therapy (Beck et al. 2001;

Spencer et al. 2001; Steg et al. 2002b). The observed associations between statin prescription

and diabetes include reduced odds (Beck et al. 2001; Danchin et al. 2002), increased odds

(Fonarow et al. 2001a) and no association (Spencer et al. 2001). Similarly, smoking was found

to be positively associated with statin therapy in one study (Danchin et al. 2002) while the

reverse was observed in the NRMI (Fonarow et al. 2001a). Spencer et al found an inverse

relationship between prescription of lipid lowering therapy and a complication of heart failure,

anterior site of infarction and first infarction (Spencer et al. 2001).

The intensity of the treatment provided in hospital was shown in a number of studies to be

directly associated with prescription of lipid lowering therapy. These associations included

undergoing PCI (Fonarow et al. 2001a; Danchin et al. 2002; Steg et al. 2002b), treatment in a

tertiary hospital (Danchin et al. 2002) and treatment in hospitals with facilities for cardiac


catheterisation (Steg et al. 2002b). Prescription of other evidence based therapies including

aspirin, beta-blockers or ACE inhibitors were also positively associate with prescription of lipid

lowering therapy. Smoking cessation counselling in smokers was also associated prescription of

lipid lowering therapy (Fonarow et al. 2001a).

The influence of new evidence on prescribing patterns has been documented many times. For

example, using prescribing analysis and cost data from the Prescription Pricing Authority to

perform a time trend analysis Baxter et al found that while the prescribing of statins by

individual practices within and between health authorities was highly variable, the changes in

prescribing of statins in all four health authorities were described by a single model with an

initial linear phase followed by an exponential phase. The change point from linear to

exponential was closely related to the publication date of the 4S study (Baxter et al. 1998).

Similarly Jackevicius et al found a 3.6-fold significant increase in the monthly rate of statin use

in post-AMI patients after the publication of 4S (Jackevicius et al. 2001). Jackevicius et al

noted differential application of the new evidence with younger patients and males more likely

to use statins. Furthermore, it was only after the publication of 4S that patients admitted to

hospital under he care of a specialist were more often dispensed statins than those admitted

under the care of a nonspecialist. (0.6% increase per month compared with 0.29%, p<0.001)

indicating an independent effect of physician speciality

The observations with patient age accord with the self reported practices in the study by

Yarzebski et al. In a community wide questionnaire survey of cardiologists, general internists

and family physicians practicing in Worcester Massachusetts, Yarzebski et al found that in

patients with a recent myocardial infarction, lipid lowering therapy in younger patients was

initiated at lower total and LDL-C levels (Yarzebski et al. 2002). A number of physician-

related factors were also found to impact on prescribing practices. These included higher

threshold levels for treatments in physicians 55 years and older, while internists and

cardiologists initiated lipid lowering therapy at lower LDL-C levels than those in general or

family practice (Yarzebski et al. 2002).

Similar to the results of studies carried out at the time of hospital discharge, an ambulatory

study, in patients with ischaemic heart disease from general practices in England found that men

were more likely than women to be prescribed lipid lowering therapy (Hippisley-Cox et al.

2001). Prescription of lipid lowering therapy increased with age up to 55-64 years after which

prescription decreased. Diabetes and hypertension were also associated with increased

prescription of lipid lowering therapy in the study by Hippisley-Cox et al.

A similar biphasic association with age was observed by Sueta et al in an analysis of data from

the Quality Assurance Program (QAP) in ambulatory care (Sueta et al. 1999) although in the


QAP the greatest prescription of lipid lowering therapy was in patients 45-54 years. Sueta et al

found no association with gender. A history of hypertension and treatment in cardiology were

directly associated with lipid lowering therapy. Sueta et al included a variable showing whether

LDL-C was documented. This was a strong predictor for prescription of lipid lowering therapy.


The evolving role of ACE inhibitors in the treatment and prevention of CHD has seen an

increased use of ACE inhibitors in post-MI patients. In this setting it might be expected that the

independent predictors of ACE inhibitor prescription might also evolve.

Predictors of ACE inhibitor prescription determined in studies examining all therapies are

shown in Table 2.27. Gender was not associated with ACE prescription in three of the four

studies, while the findings for age were more variable. Indications for ACE inhibitors including

heart failure, hypertension and diabetes were always positive predictors, when included, as were

anterior site of infarction, reduced left ventricular function, in-hospital heart failure or

cardiogenic shock. When included, prior use of an ACE inhibitor was a strong predictor of

ACE inhibitor prescription at discharge. The finding by Beck et al that care in a tertiary

hospital reduced the odds of ACE inhibitor prescription was unexpected (Beck et al. 2001). To

further examine this unexpected finding Beck et al performed a stratified analysis by hospital

type. They found that while prescription of ACE inhibitors at both community and tertiary

hospitals were in agreement with guideline recommendations, the independent predictors varied

between hospital types with independent predictors in the community hospitals including

hypertension and anterior site while at the tertiary hospitals the independent predictors included

anterior site and higher Creatine Kinase (CK) levels.


Table 2.27: Predictors of ACE inhibitor prescription

Study Study

period

Data source Positive Negative No association

Martinez1 1986-94 Survey Female

In-hospital heart

failure,

hypertension,

previous MI

Calcium

antagonist,

beta-blocker

Age

Spencer2 1986-97 Register Age,

Diabetes,

Hypertension,

Heart failure,

Anterior site,

In-hospital HF,

Cardiogenic

shock

Initial MI Gender, Angina

history, Stroke,

Q-wave

Dwamena3 1994-95 Survey Age,

Heart failure

Anterior site

Prior use

No LVEF

measured

LVEF>40%

Acute renal

failure

Gender

Hypotension

Aortic stenois

Chronic renal

failure

Beck4 1996-98 Administrative Diabetes,

Anterior site,

Peak CK,

Killip Class >1,

Inhospital HF,

Prior use

Tertiary care Age, Gender,

Angina history,

Hypotension, AF

Danchin5 1998 Survey Hypertension,

Prior use

Age, LVEF Gender, Stroke,

PVD, Hospital

type, PCI 1(Martinez et al. 1998) 2(Spencer et al. 2001) 3(Dwamena et al. 2000) 4(Beck et al. 2001) 5(Danchin et al. 2002)

Several studies specifically examined ACE inhibitor prescriptions and stratified the analysis

according to the extent of left ventricular dysfunction have also been published. These studies

are summarised in Table 2.28. LVEF less than 40% was always associated with increased

prescription of ACE inhibitors


Table 2.28: Predictors of ACE inhibitor prescription stratified by left ventricular function

LVEF<40 LVEF1>=40

Positive Negative Positive Negative

Krumholz1 1992-93 Time, female, diabetes, CHF, VT,

loop diuretics

PCI, Beta-blocker

Barron2 1994-96 Anterior site, Killip>1,

CHF/pulmonary oedema, in-

hospital coronary angiography or

echocardiography,

number of discharge drugs,

Intraaortic balloon pump,

Hypotension,

calcium antagonist,

inhospital PCI or CABG,

(anterior site)

Time,

History of Diabetes, hypertension,

CHF,

heart rate,

echocardiography,

Intraaortic balloon pump,

(no CHF and non-anterior site)

Time,

History of diabetes, hypertension, CHF,

MI, CABG, stroke

Blood pressure, heart rate

echocardiography,

Intraaortic balloon pump

(anterior site)

Non-Q wave,

Calcium antagonist, in-hospital CABG

(no CHF and non-anterior site)

Calcium antagonist, in-hospital CABG,

number of discharge drugs, tobacco

use

Luzier3 1996-97 Hypertension, digoxin, age >=67, Female, hypertension, diabetes, aspirin 1(Krumholz et al. 1997) 2(Barron et al. 1998a) 3(Luzier et al. 1999)

79

Since Krumholz et al considered determination of left ventricular function a prerequisite for

prescription of ACE inhibitors they also determined the factors associated with left ventricular

function determination. Positive predictors of measure of left ventricular function included

hospital use of aspirin and thrombolytic therapy as well as a number of factors associated with

the patients condition including a higher CK peak, congestive heart failure, hypertension,

recurrent chest pain, atrial fibrillation, low hematocrit and long hospital stay. Very old patients

(75 years and older), patients with poor mobility and patients with only Medicaid insurance

were all less likely to be prescribed ACE inhibitors. (Krumholz et al. 1997).

A multicentre, retrospective, medical record review was undertaken to document prescribing of

ACE inhibitors in survivors of myocardial infarction at 12 academic health centres in the United

States during 1993 (Yim et al. 1995). The study found that while 62 of 101 patients with

known LVD were prescribed an ACE inhibitor only 24 of 63 with a diagnosis of CHF but no

known LVD were prescribed an ACE inhibitor. Yim et al noted that in addition to the 39%

with LVD not prescribed an ACE inhibitor, less than half of the patients with a diagnosis of

CHF and no LVEF measurement were prescribed an ACE inhibitor although the benefits of

ACE inhibitors in symptomatic heart failure are well documented. Yim et al also noted that

patients treated at centres that participated in the SAVE trial were more likely to be prescribed

an ACE inhibitor. Overall, Yim et al found that a significant portion of patients (39%) did not

have an objective measure of LVEF during hospitalisation even though systolic performance is

a good a prognostic indictor. As noted by Yim et al this does not include assessments made

after discharge.

In a hospital based primary care geriatric practice, the proportion of patients with a history of Q-

wave myocardial infarction using ACE inhibitors varied from 35% for all patients with a history

of Q-wave infarction to about 65% in patients with a history of Q-wave infarction with either

LVD or CHF to 83% in patients with a history of Q-wave infarction with both LVD and CHF

(Mendelson et al. 1998).

2.4.5 Summary

While many of the independent predictors for prescription of the various secondary prevention

drugs were in accordance with indications and contraindications for these drugs, a number of

factors, particularly those associated with aspects of patient care, including revascularisation

procedures and other non clinical factors such as age, suggested that current practice falls short

of the evidence base with a resultant underuse of the these protective therapies.

80

2.5 Drug utilisation in ambulatory care

The previous section was concerned with practice patterns around the prescription of

medications. This section examines patterns around the use, and underuse, of effective cardiac

medications after hospital discharge and incorporates aspects of both:

• prescribing in ambulatory care, including influences on prescribing as well as the

monitoring of therapy in ambulatory care, with regard to dosages and, where applicable,

attainment of therapeutic goals; and

• patient adherence, including an overview of aspects of patient adherence followed by a

review of patient adherence in CHD.

2.5.1 Prescribing in ambulatory care

Prescription at the time of hospital discharge represents only a first step in the process of

secondary prevention of CHD, which requires ongoing prescription by primary care providers.

This section examines some of the factors that influence the prescribing patterns of primary care

providers.

2.5.1.1 Influences on prescribing practices

Assessing and evaluating the evidence

Studies with general practitioners found that a lack of understanding of the terminology was a

major barrier to the use of evidence-based medicine (McColl et al. 1998; Young et al. 2002).

Similarly, in a qualitative study, using semi structured interviews, general practitioners admitted

to lacking both the time and skills necessary to appraise the content of scientific papers, and

therefore, “rarely said that they appraised the methods and content of trials, rather they judged

the trustworthiness of the source of trial evidence” (Fairhurst et al. 1998). Fairhurst et al found

that clinical trial data only became relevant when it was confirmed and underpinned by a clear

consensus. Similarly, clinical guidelines were not instrumental to changing practice, but rather

were only seen as useful when they embodied and reinforced consensus. More importantly, in

discussing sources of information, general practitioners placed more value on personal contact

than on written sources. Doctors reported getting most of their information from postgraduate

meetings, in particular those addressed by specialist colleagues, from person contact with

hospital consultants, from written hospital correspondence and from colleagues in general

practice. Hospital consultants were said by general practitioners to be among the most credible

sources of evidence. In keeping with this sentiment, doctors said that local guidelines produced

by people known to the doctors were more widely used than national guidelines. The study by

Fairhurst et al contrasts with the conclusions of McColl et al who suggest that efforts to

encourage general practitioners to implement evidence-based general practice should focus on

81

promoting and improving access to summaries of evidence, although both underline the

importance of developing local evidence based guidelines and advice.

Hospitals and specialists

A number of other studies provide direct and indirect evidence of the important role of hospitals

and specialists in influencing the prescribing practices of primary care providers.

In a qualitative study to describe the range of factors that influence general practitioners’ and

consultants’ clinical practice, contact with professionals was the third most common influence

(13%) after organisational factors (18%) and education (17%) (Allery et al. 1997). An earlier

study found that the most important factor in the prescribing of a particular preparation of

glyceryl trinitrate in general practice was the hospital catchment area of the practice (Pryce et al.

1996).

A qualitative study of general practitioners’ reasons for recent changes in their prescribing

behaviour described three models of change driving prescribing practices (Armstrong et al.

1996). While change was sometimes precipitated suddenly, for example by a catastrophic or

near catastrophic event, most change came at the end of a gradual accumulation of cues. This

depended both on the weight of the evidence, including journal articles, talks or consultants

letters, and the relative authority of the sources. Consultants were often mentioned as

influencing behaviour usually describing the consultant as "trusted" or "respected" or having a

"good reputation."

Another study to explore reasons why general practitioners don’t always implement best

practice identified six main themes, including a perceived tension between primary and

secondary care. General practitioners thought that specialists approached evidence-based

practice differently (Freeman et al. 2001).

Tomlin et al found that the main source of information used by general practitioners was

practice partners and hospital doctors(Tomlin et al. 1999). This included personal contact with

hospital doctors as well as observation of their practice through seeing patients after they were

treated in hospital.

Evidence from several studies suggests that prescribing at hospital the time of hospital discharge

is an important predictor of ongoing management (Fonarow et al. 2001b; Muhlestein et al.

2001; Danchin et al. 2002). Studies suggest a very low rate of treatment initiation by primary

care doctors in patients following hospital discharge as evidenced by the PREVENIR. One

study that documented the influence of hospital prescribers on prescribing in general practice

found that 60% of all cardiovascular drugs were initially commenced in hospital (Feely et al.

1999).

82

2.5.1.2 Monitoring therapies

There is increasing evidence that even when effective cardiac drugs are prescribed they are

often prescribed at lower doses than those shown to be effective in the landmark clinical trials

and that treatment goals for lipids and other risk factors are often not achieved.

Antiplatelet agent

In the study by Luzier et al, where an appropriate dose of aspirin was defined as at least 160 mg

daily, 87% were prescribed aspirin but only 79% of patients were treated with an adequate dose

(Luzier et al. 1999). Simpson et al found that 99% of post-MI discharge prescriptions were for

an adequate dose (Simpson et al. 2003).

Beta-blockers

Use of low doses of beta-blockers have been noted in several post-MI studies (Viskin et al.

1995; Barron et al. 1998b; Luzier et al. 1999), where a low dose was defined as less than 50%

of the dosages used in the RCT (Barron et al. 1998b; Rochon et al. 1999a).

Data from 1990 to 1992 showed that of patients prescribed beta-blocker therapy, 48.1% were

treated with dosages less than 50% of the dosage found to be effective in preventing cardiac

death in large randomised clinical trials, with 8.5% receiving less than 25%, and 40% receiving

25% to 49%. Doses equivalent to those used in trials were prescribed to only 6% of MI

survivors in 1993, and only 11% received dosages equivalent to more than 50% of the effective

dosages (Viskin et al. 1995). Since only 49% of patients were prescribed a beta-blocker, about

20% of prescriptions were for dosages greater than 50% of those used in the RCT. A study of

prescribing patterns from 1993 to 1995 found that of MI survivors prescribed beta-blockers,

37.0% were dispensed low-dose therapy (Rochon et al. 1999a). Luzier et al found that while

57% of post-MI patients in 1996 to 1997 were prescribed beta-blockers, only 8% were

prescribed doses equivalent to those used in the RCTs (Luzier et al. 1999). Data from 1996 to

1998 showed that only 20% of patients with beta-blocker prescriptions were prescribed clinical

trial doses at hospital discharge and similarly at follow-up one year later (Simpson et al. 2003).

Statins

In a study that used potencies per milligram to calculate all statin doses as simvastatin

equivalents DeWild et al found that the proportion of patients using the equivalent of at least 20

mg of Simvastatin increased from about 22% in 1994 to 67% in 2001 (DeWilde et al. 2003).

As with beta-blockers, studies have shown use of statin doses less than those used in the

secondary prevention trials. A 20 year follow-up of British men with established CHD in 1998-

00 found that of those using simvastatin only 41% were using 20-40 mg daily, a dose similar to

that used in the 4S study (Whincup et al. 2002). Whincup et al found no trend in the proportion

of patients prescribed appropriate dosages with increasing time.

83

If the benefit of statins were limited to the lipid lowering effect, then achieving appropriate lipid

levels, rather the actual dosages used would be of importance. However, the studies showing

use of low dose statins are part of a broader suite of studies that show less than optimal

monitoring of lipid levels in high risk patients and when levels are monitored a significant

proportion of patients fail to achieve the therapeutic targets.

Monitoring of lipid levels

• Hospital episode

In the Worcester Heart Attack Study, Yarzebski et al found that over the period 1986 to 1997,

in-hospital measurement of serum lipids in patients with AMI increased markedly from 1986 to

1991, but then decreased again. Only one quarter of patients had cholesterol levels measured in

hospital in 1997. Factors independently associated with cholesterol measurement during

hospitalisation in the Worcester Heart Attack Study included an inverse association with

advanced age, a history of diabetes and hypertension, while patients with a Q-wave infarction

were more likely to have cholesterol measured.

Other studies examining lipid measurement in hospital at the time of an acute event are shown

in Table 2.29. These show considerable room for improvement in what is considered to be a

quality indicator for patients with AMI.

Table 2.29: In-hospital lipid measurement

Study Time Diagnosis In-hospital measurement Performed

ASPIRE1 n/a AMI Total cholesterol M 53%, F 39%

CHAMP2 1992-3/1994/5 AMI LDL-C(within 12 hours) 5%/ 68%

Mudge et al3 1998-99 ACS Total Cholesterol 82%

GAP4 1998-99/2000 AMI LDL-C 64%/ 70%

EUROASPIRE II5 1999-00 AMI Total cholesterol 53% 1(ASPIRE Steering Group 1996), 2(Fonarow et al. 2001b), 3(Mudge et al. 2001), 4(Mehta et al. 2002), 5(Euroaspire II Study Group 2001)

An English study that examined lipid monitoring in patients admitted with a myocardial

infarction or an elective revascularisation procedure in 1997 found that 99% of patients had a

TC measurement (Holt et al. 2000). This was a higher rate of monitoring than observed in

ASPIRE and EUROASPIRE II.

• Ambulatory care

Measures of monitoring of lipid levels in follow-up care come from a number of studies in

primary care. While the proportion of patients with documented lipid levels varied between

studies, the consistent conclusion was that of less than optimal monitoring of an important risk

factor in a high risk group of patients.

84

McBride et al found that 33% of patients with cardiovascular disease in primary care practices

had no lipid assessment recorded, and noted that, more recently graduated physicians ordered

more lipid panels (McBride et al. 1998). Examining the primary care records of patients with

CHD, serum cholesterol was documented in 18% of men and 27% of women (Flanagan et al.

1999). Using ambulatory care from the QAP Sueta et al found that 66% of patients with CHD

had a TC level documented, but only 44% had LDL-C level documented within one year of the

last visit (Sueta et al. 1999). A study of English general practices by Hippisley-Cox et al found

that only 35% of female patients and 50% of male patients with a diagnosis of ischaemic heart

disease had a recording of fasting cholesterol (Hippisley-Cox et al. 2001). In a large study that

identified the recording of risk factors for patients with a diagnosis of CHD Brady et al found

that 65% of men and 48% of women had at least one cholesterol measurement recorded in

primary care (Brady et al. 2001).

Hippisley-Cox et al found that male gender, diabetes, hypertension and obesity were all positive

predictors of lipid level documentation in patients with ischaemic heart disease. Current

smoking was a negative predictor, while there was a biphasic relationship with the youngest and

eldest patients, the least likely to have lipids documented.

Achieving therapeutic targets

Studies that examined lipid levels in either low or high-risk primary prevention of CHD or in

secondary prevention of CHD found that a significant proportion failed to achieve the

therapeutic targets for lipids. This was true in patients known to be using lipid lowering therapy

as well studies that considered all patients irrespective of the use of lipid lowering therapy.

85

Table 2.30: Proportion of patients achieving therapeutic goals in ambulatory care

Setting Goal Percent

(ASPIRE Steering Group 1996) ASPIRE AMI follow-up <5 mmol/L 23 M, 13 F

(Schrott et al. 1997) HERS (secondary prevention) <130 mg/dl

<100 mg/dl

36.6

9.6

(Harris et al. 1998) Lipid clinic hyperlipidemia

Primary care

<200 mg/dl 52

34

(McBride et al. 1998) Primary care <2.58 mmol/L 14

(Vale et al. 2002b) Secondary prevention

Intervention

Usual care

<4.5 mmol/L

31%

10%

(Vale et al. 2002a) Secondary prevention

1996-98

1999-00

<5/ <4 mmol/L

30/ 4

64/ 26

(Brady et al. 2001) General practice <5 mmol/L 53 M, 60 F

(Holt et al. 2000) General practice 5.2 mmol/L 31

(Euroaspire II Study Group 2001) EUROASPIRE II TC<5 44

Table 2.31: Achieving therapeutic goals for statins in ambulatory care

Sample Study Goal Percent

Hyperlipidemia (Hippisley-Cox et al. 2003) TC<5 mmol/L 54.8

Secondary prevention (Whincup et al. 2002) TC<5 mmol/L 46

Secondary prevention (Sueta et al. 1999) LDL-C<100 mg/dl 25

Post-AMI (Majumdar et al. 1999) TC<160 mg/dl 15

Secondary prevention (Marcelino et al. 1996) LDL-C ≤100 mg/dl 24

Secondary prevention (Pearson et al. 2000) LDL-C ≤100 mg/dl 18

Secondary prevention (Pearson et al. 1997c) LDL-C <100 mg/dl 24

Secondary prevention (Dalal et al. 2003) TC<5 mmol/L 75

Secondary prevention (Vale et al. 2002a) TC<5/<4 mmol/L

LDL-C<2.5 mmol/L

69/ 29

50

Secondary prevention (EUROASPIRE Study Group 1997) TC<5.5 56

These studies do not suggest a lack of efficacy of statins, but rather suggest a failure to

effectively treat patients. Harris et al showed that lipid clinics, with a more aggressive approach

to lipid lowering, had greater achievement of the treatment goal (Harris et al. 1998). Marcelino

et al found that only 2 of 60 patients not achieving the treatment goal were using maximal

dosage regimens and, only 13 of these 60 had a regimen change since the last measurement,

including nine where the dose increased (Marcelino et al. 1996). In the study by Whincup et al

they found that only 46% of patients using a statin achieved the treatment goal, however 59%

were using dosages lower than those used in the RCTs (Whincup et al. 2002).

86

In L-TAP a number of factors were identified as independent predictors of achieving treatment

goals, including risk group, sex and menopausal status, race, treatment with statins, compliance

with dietary therapy, instructions to lower cholesterol and diabetes. (Pearson et al. 2000).

ACE inhibitors

Studies that examined the dosages of ACE inhibitors prescribed either for heart failure or post-

MI have also found the use of dosages significantly less than those used in RCTs (Hillis et al.

1996; Luzier et al. 1999; Roe et al. 1999; Sueta et al. 1999).

In 1992, 76% of heart failure patients were on lower doses of ACE inhibitors than those used in

the major survival studies; with 69% receiving similar doses two years later (Hillis et al. 1996).

Mean daily dosages of 8.9 mg for ramipril, 58 mg for captopril and, 12 mg for enalapril were

found by Sueta et al from 1994-1996 (Sueta et al. 1999). Roe et al found that in 1995-96 the

mean dose of ACE inhibitor prescribed was only 79% of an adequate dose, with only 34%

dispensed an adequate dose (Roe et al. 1999). A survey of physician’s knowledge and use of

ACE inhibitors in CHF found that 45% of cardiologists said they titrated ACE inhibitor dosages

to a specific dose compared with 27% of generalists and 26% of family practitioners (Chin et al.

1997). Chin et al also found that 43% cardiologists were more likely to tolerate systolic blood

pressures of 90 mm Hg or less compared with 15% of generalists.

In a study of ACE inhibitor use post-MI, Luzier et al found that during 1996 and 1997, 34% of

patients were treated with an ACE inhibitor, but only 11% received recommended doses.

Luzier et al noted that while patients with a low LVEF were more likely to be prescribed an

ACE inhibitor, they were also more likely to be prescribed a lower than recommended dose than

those with preserved LVEF (Luzier et al. 1999). As noted by Luzier the dosages may not have

been titrated to the target dose.

In contrast to the previous studies Simpson et al found that during the period from 1996 to

1998, 88% of post-MI patients prescribed an ACE inhibitor were prescribed an adequate dose

(Simpson et al. 2003). However adequate doses in the study by Simpson et al were

significantly lower than those defined in other studies. These included captopril 12.5mg,

enalapril 5 mg, lisinopril 5 mg, perindopril 2 mg, ramipril 5 mg compared with captopril 100-

150 mg, enalapril 20 mg, lisinopril 10-20 mg and ramipril 10 mg.

Two studies using lower dosages of ramipril showed that lower dosages do not confer the same

benefit as 10 mg. In a comparison of 2.5 and 10 mg dosages of ramipril in inhibiting

atherosclerosis the SECURE substudy of the HOPE study found that while the effects on blood

pressure were similar for both doses, there was a dose response effect on atherosclerotic

progression. In this substudy the difference in progression of disease between 2.5 mg of

87

ramipril and placebo was not significant. (Lonn et al. 2001). The DIABHCAR study of

cardiovascular and renal outcomes of ACE inhibitors in diabetic patients found that compared to

placebo, 1.25 mg of ramipril did not reduce the incidence of cardiovascular death, non-fatal

myocardial infarction, stroke, heart failure leading to hospital admission, and end stage renal

failure, all benefits previously noted with 10 mg (Marre et al. 2004).

2.5.2 Patient adherence

The prescribing of appropriate medication is necessary but not sufficient to ensure the effective

use of the treatment. Patients must fill the initial prescription, take the appropriate dose in the

appropriate manner, fill subsequent prescriptions and continue to take the medication as

prescribed. This complex behavioural process is influenced by the patient, the treatment, cost,

healthcare providers and how the healthcare system delivers care (Miller et al. 1997).

The ever expanding armamentarium of therapies proven to be effective and the increasing role

of disease prevention and disease management in health care underscores the importance of the

understanding and improving patient adherence with recommended behaviour changes,

including the use of pharmacotherapies. Programs aimed at optimising the organisation and

financing of medical care, focusing on quality of care and clinical outcomes, have also led to an

examination of compliance management in an attempt to gain more effective and economical

medical care (Skaer et al. 1996; Insull 1997).

2.5.2.1 Overview

The issue of patient adherence is a complex one dealing with patient factors, the characteristics

of the disease and the treatment, the healthcare setting, the provider and the patient-provider

relationship (Pearson et al. 1997a). Several conceptual theories and models of health behaviour

change and intervention underlie approaches to adherence research in behavioural medicine.

This, however, is beyond the scope of this thesis and those interested are referred elsewhere

(Sherbourne et al. 1992; Dunbar-Jacob et al. 1998; Kehoe et al. 1998; Ockene et al. 2002). In

more recent years there has been a shift away from the focus of the patient as the source of

“nonadherence” and an increasing emphasis on the role of practitioners, the health system and

the patient-provider interaction (Lutfey et al. 1999; Dunbar-Jacob et al. 2000). This overview

briefly examines the extent of the problem, how it can be measured and the role of the

healthcare provider and healthcare system in enabling patient adherence.

Defining the problem

Terminology

Historically “the extent to which a person’s behaviour (in terms of taking medications,

following diets, or executing lifestyle changes) coincides with medical or health advice” has

88

been described as “compliance” (Haynes et al. 1979). A number of authors have taken issue

with the term “compliance”, preferring the term “adherence” which in their view implies a more

patient centred perspective (Brawley et al. 2000). Others have rejected both terms suggesting

both are too simplistic to describe complex behaviours (Marinker 1997; Steiner et al. 2000).

More recently the term “persistence” has entered the lexicon. Persistence is a measure of the

time over which a patient had medication available (Benner et al. 2002).

Regardless of the terminology, there is agreement that the old model of the practice of medicine

“driven by benign paternalism and based on patients trusting their doctors must make way for a

new relationship between doctors and patients that is based more on openness and respect in

accordance with the modern concern for transparency of information and participative decision

making” (Marinker 1997).

Intelligent nonadherence

Related to the concept of the patient, as a partner in the treatment plan is the notion that from the

patient’s point of view, nonadherence may be a reasoned decision rather than poor behaviour.

Patients make their own decisions about how they will manage their medications, based on their

beliefs and information (Donovan et al. 1992; Miller 1997). A concept of “intelligent

nonadherence” has been proposed to describe the situation where a prescribed medication is

purposely not taken as prescribed with apparently valid reason for nonadherence (Becker 1985;

Donovan et al. 1992; Steiner et al. 2000). Reasons for intelligent nonadherence include:

• patients experiencing substantial adverse reactions or side effects (Becker 1985); and

• patients unilaterally concluding that they can attain their treatment goal while reducing their

medication dose (Steiner et al. 2000)

Nonadherence or medication error

There is also a need to distinguish intentional differences between the patient’s medication-

taking behaviour and the recommended regimen and medication errors. In the case of

medication errors, the patient’s intent is to adhere, but circumstances result in the patient being

unable to follow the instructions (Gordis 1979). While the outcome may be loss of therapeutic

benefit in both cases the strategies required to change behaviour will be very different.

Patterns of nonadherence

Nonadherence may represent overuse or underuse of medications. While overuse of

medications can represent a risk to a patient’s health, it is the underuse of mediations that

represents a missed opportunity. The remainder of the review is therefore restricted to forms of

underuse of medications. Underuse of medications can take a number of different forms

including:

89

• never filling a prescription; with estimates in some settings that 20-30% of prescriptions

never filled (Miller 1997; Dunbar-Jacob et al. 2000);

• completely stopping a medication; with generally accepted rates of cumulative

discontinuation of 50% at one year and 85% at two years (Insull 1997);

• miss an occasional tablet, take drug holidays or take medication sporadically;

• take a consistent but reduced dose of medication;

• take medication at the wrong time occasionally; and

• consistently take medication at the wrong time.

In the first cases the patient does not use a medication and therefore gains no therapeutic benefit

from the medication. However with the remaining four behaviours the level of benefit derived

from the treatment will be variable depending on the degree to which the patient adheres with

the treatment regimen as well as the properties of the therapy (Gordis 1979). Studies suggest

that between one half and three quarters of patients across a broad range of disease adhere

sufficiently to obtain therapeutic benefit (Dunbar-Jacob et al. 1995).

The extent to which a patient takes a medication as prescribed is therefore a continuous variable.

However, adherence is often referred to as a dichotomous variable with a particular level of

adherence used as a cut off to define “adherers” and “nonadherers”. Ideally this would be based

on the level of adherence required to achieve a therapeutic effect. This level is often unknown

and arbitrary values, usually somewhere between 75-85%, are used.

Partial adherence

Partial adherence is used to describe the broad range of patient behaviour where the medication

is not taken as prescribed 100% of the time. While earlier reports described one third of patients

as adequate adherers, one third as partial adherers and one third non-adherent (Wright 1993),

more sophisticated methods of measuring patient adherence have revealed a somewhat different

pattern. One study found that 52% of patients were near optimal compliers taking ≥80% of

prescribed doses, 40% of the group took between 40-79% of prescribed doses while 8% of the

group took <40% of prescribed doses (Rudd et al. 1993). Svarstad et al found that only one

quarter of patients fully adhered with the treatment regimen while, one half took at least 80% of

prescribed doses, defined as sporadic adherence, and one quarter of patients took less than 80%

of prescribed doses, defined as repeat nonadherence (Svarstad et al. 1999). Rudd et al found

that 50 to 60% of patients show near optimal compliance, while at the other extreme a small

group of patients (5% -10%) were classed as nonadherers. The remaining group (30% - 40%)

are partial adherers exhibiting highly variable adherence (Rudd 1995). Estimates of missed

doses vary from 13% to 25% (Svarstad et al. 1999; Cramer 2002).

90

Adherence over time

Nonadherence varies over the course of treatment for chronic disease. Even when a treatment is

initially adopted, discontinuation during the first few months is high and the cumulative rate of

discontinuation continues to increase, albeit to a lesser extent with time (Insull 1997; Dunbar-

Jacob et al. 2000). The Lipid Research Clinic -Coronary Prevention Trial showed a 43%

dropout rate at six months, and an additional 44% dropout rate at 12 months, giving a

cumulative drop out of 68%. (Burke et al. 1997)

Adherence has also been shown to decrease between visits to the doctor. In a study of

antiepileptic medication, adherence rates during the 5 days before and after a clinic visit were

88% and 86% respectively, however this decreased to 73% (p=0.01) at 1 month post visit

(Cramer et al. 1990; Rudd et al. 1990).

Measuring adherence

A number of methods have been used to measure adherence with medication in the research

setting. Direct measures such as measuring drug or metabolite levels are not widely available

so a number of indirect methods, including self report, pill counts, prescription refills and

electronic monitoring, must be applied. The strengths and weaknesses of these indirect

measures are discussed below (Dunbar-Jacob et al. 1995; Burke et al. 1997; Cramer 2002).

Self report

This includes interviews, structured questionnaires and daily diaries, all of which have a

tendency to overestimate adherence since:

• Patients tend to tell doctors what they want to hear

• Patient who forget to take medication may not realise the frequency of missed doses

Pill counts

These are commonly used in clinical trials with patients asked to return unused medications at

each visit. The logistics of using this measure in other settings is problematic “since care must

taken to determine the amount of medication that has been dispensed, the date of the most

recent prescription refill was commenced, how much was left over from the previous

prescription when the current prescription was begun, whether there have been any changes in

the prescription not noted on the pill container, and whether the patient has caches of pills in

other locations” (Stephenson et al. 1993). One study using pill counts as a measure of

adherence during a home visit one week after hospital discharge reported that valid pill counts

could only be carried out for 54% of patients because the hospital-derived medications had been

mixed with pre-existing medications or with those prescribed by the general practitioner since

discharge (Stewart et al. 1999)

91

Pill counts can provide an estimate of the number of prescribed doses consumed so the measure

of compliance would be in terms of the proportion of prescribed doses consumed.

Prescription refill records

Historically this was only applicable where patients used one consistent pharmacy. However,

with the increasing sophistication of tracking systems for health care utilisation it has become

increasingly feasible to monitor patient adherence by examining pharmacy databases. These

databases can provide exact information on the regime prescribed, the amount of medication

dispensed and the timing of refills. This methodology is particularly useful for large-scale

population studies of patient adherence.

These measures of compliance often include not only the proportion of prescribed doses

consumed, but assuming that the medication regimen is followed, the number of days on which

medication was available.

Electronic monitoring

The increased availability of computer-based technology has introduced a new strategy for

adherence monitoring. Electronic monitoring devices record the date and time of each opening

of a pill bottle or releasing a blister pack. The expense involved in these devices has limited the

size of studies. The ability to monitor the precise timing of each dose taken has provided

information about timing related issues in compliance. An overview of 76 studies using

electronic monitoring found that while about 71% of doses were taken, only 59% of doses were

taken with an appropriate time interval. (Claxton et al. 2001).

Electronic monitoring can provide information on the overall number of doses consumed as

well the number of doses taken at the appropriate time. The number of days on which the drug

was taken appropriately can also be determined.

Measuring adherence in clinical practice

While adherence is routinely measured in the clinical trial setting where inadequate adherence

can reduce the apparent efficacy of a treatment, it is rarely measured in the clinical setting

where inadequate adherence can reduce the effectiveness of therapy. Clinical judgement has

been shown to be a poor measure of adherence with a no better than even chance at telling

which patients are following the treatment regimen as prescribed (Eraker et al. 1984; Steele et

al. 1990; Rudd et al. 1993; Stephenson et al. 1993).

There are, nonetheless, a number of steps that clinicians can take to identify patients who may

have less than optimal adherence. These include being aware of patient behaviour in terms of

attendance at the clinic and noting a lack of responsiveness to treatment, but ultimately

questioning the patient. While patient self report is known to overestimate adherence, studies

92

comparing self report with other methods of assessment have found substantial intercorrelations

(Becker 1985) and a combined analysis of four studies showed that self report has a sensitivity

of 55%, a specificity of 87% and a likelihood ratio of 4.4 (Stephenson et al. 1993). In addition,

self-report is particularly useful for detecting a patient’s misunderstanding of treatment

regimens or where the patient has changed the treatment regimen for what the patient believes is

a legitimate reason (Donovan et al. 1992).

The manner in which a patient is asked about adherence to treatment is important. The

approach should be non-judgemental and nonthreatening. Both structured questionnaires and

unstructured conversations have been used successfully (Morisky et al. 1986; Steele et al. 1990;

Kravitz et al. 1993; Australian Pharmaceutical Advisory Council 1998). A broad conversation

about the identity and dosage of each drug and the consequences of medication-taking will

identify a greater proportion who deviate from the prescribed regimen than directly worded

inquiries (Steele et al. 1990; Stephenson et al. 1993)

A study comparing a questionnaire with electronic monitoring found that sensitivity levels

varied for different types of adherence issues and screening tools (Svarstad et al. 1999).

Svarstad et al used three screening tools:

• Regimen Screen, asking patients to describe how they take each medication;

• Belief Screen, asking about concerns with efficacy and side effects, and

• Recall Screen, asking about problems with remembering to take medications.

The Regimen and Beliefs Screens had good sensitivity for “repeat” nonadherence and poor

sensitivity for “sporadic” nonadherence. The Recall Screen had good sensitivity for “sporadic”

nonadherence but poor sensitivity for “repeat” nonadherence. These observed differences

suggest that sporadic nonadherence is unintentional, while repeat nonadherence probably

reflects a more deliberate deviation from the medication regimen. The Regimen Screen had

sensitivity, a positive predictive value and specificity level of 100% and an overall accuracy of

95%.

An inventory of the patient’s medication can provide information on patient adherence and

compared favourably with several other measures of adherence, including pharmacy records and

serum levels (Sjahid et al. 1998; Smith et al. 1999a). Going through all a patient’s medicines

asking about how each medication is used can provide useful information about patient

adherence and also provides an opportunity to correct any misunderstandings about the purpose

and correct usage of medications (Nathan et al. 1999).

93

2.5.2.2 Adherence in CHD

The evidence of the benefits of the various components of secondary prevention of CHD,

including pharmacotherapies is so compelling to suggest that nonadherence with these regimens

is yet another risk factor for CHD (LaRosa 2000). This echoes the sentiment originally

expressed by the AHA of the importance of patient adherence “attention to enhancing patient

compliance is an integral part of any risk reduction strategy” (AHA Consensus Panel Statement

1995). The AHA later convened two task forces to examine the issue of adherence (Miller et al.

1997; Ockene et al. 2002). In both cases the emphasis was on a multilevel approach

incorporating the patient, the provider and the healthcare system. The boxes highlight the

actions and strategies for patients, providers and the healthcare system that enhance compliance

with prevention and treatment recommendations to reduce risk and improve patient outcomes

(Miller et al. 1997).

Actions and Strategies for Patients

Actions Specific Strategies

Engage in essential prevention and treatment behaviour.

Decide to control risk factors Understand rationale, importance of commitment

Negotiate goals with providers Develop communication skills

Develop skills for adopting and maintaining

recommended behaviours

Use reminder systems

Monitor progress towards goals Use self monitoring skills

Resolve problems that block the achievement of

goals

Develop problem solving skills, use social support

networks

Communicate with providers about prevention and treatment services

Define own needs on basis of experience

Validate rationale for continuing to follow

recommendation

(Miller et al. 1997)

94

Actions and Strategies for Providers

Foster effective communication with patients.

Provide clear, direct messages about the

importance of a behaviour or therapy.

Provide verbal and written instruction, including

rationale for treatments.

Develop skills in communication/counselling.

Include patients in decisions about

prevention and treatment goals and related

strategies.

Use tailoring and contracting strategies.

Negotiate goals and a plan.

Anticipate barriers to compliance and discuss solutions

Incorporate behavioural strategies into

counselling.

Use active listening

Develop multicomponent strategies (cognitive and

behavioural)

Document and respond to patients’ progress towards goals

Create an evidence-based practice Determine methods of evaluating outcomes

Assess patient’s compliance at each visit Use self-report or electronic data

Develop reminder systems to ensure

identification and follow-up of patient status

Use telephone follow-up

Actions and Strategies for the Healthcare Organisations

Actions Specific Strategies

Develop an environment that

supports prevention and treatment

interventions

Develop training in behavioural science, office set-up for all

personnel

Use pre-appointment reminders

Use telephone follow-up

Schedule evening/weekend office hours

Provide group/individual counselling for patients and families

Provide tracking and reporting

systems

Develop computer-based systems (electronic medical records)

Provide education and training for

providers

Require continuing education courses in communication,

behavioural counselling

Provide adequate reimbursement

for allocation of time for all

healthcare professionals

Develop incentives tied to desired patient and provider

outcomes

Healthcare organisations must

adopt systems to rapidly and

efficiently incorporate innovations

into medical practice.

Incorporate nursing case management

Implement pharmacy patient profile and recall review systems

Use electronic storage of patient’s self-monitored data

Obtain patient data on lifestyle behaviour before visit

Provide continuous quality improvement training

(Miller et al. 1997)

95

Factors affecting adherence

Aspects of the disease and treatment regimen are commonly associated with adherence. These

include; high cost, side effects and a lack of understanding of the perceived benefits provided by

the therapy, all relevant to preventive interventions with lifelong therapy for asymptomatic

conditions. Secondary prevention of coronary artery disease is one such example.

Duration of treatment

Nonadherence is estimated at 20% in the case of short term treatment for an acute symptomatic

condition, but this increases to 50% for longer term chronic conditions (Sherbourne et al. 1992).

In chronic conditions adherence decreases with time. Estimates of discontinuation rates among

long term regimens for all types of drugs are generally accepted to increase from about 50% at

one year and 85% at two years (Insull 1997).

Complexity of regimen

Studies have shown that adherence decreases with increasing complexity of the regimen in

terms of the frequency of the dosing. A study of anticonvulsant medications, found that

adherence rates varied between: 87% for once daily, 81% for twice daily, 77% for three times a

day, and 39% for four times a day regimen (Cramer et al. 1989). When comparing the

proportion of prescribed doses of antihypertensive medication taken adherence was lower for

the three times a day regimen (84%) compared with once (96%) and twice (93%) a day (Eisen

et al. 1990). Claxton et al calculated a mean dose-taking compliance of 79% for once daily

regimes, decreasing to 69%, 65% and 51% for two, three and four times a day dosing

respectively (Claxton et al. 2001). In all these studies there was a trend of decreased adherence

with increased frequency of dosing, however the difference between once and twice a day

dosing were not significantly different, but with more than twice a day dosing adherence was

significantly decreased.

One study that compared mono and poly therapy for the treatment of Type 2 diabetes mellitus

found that patients on monotherapy had higher rates of compliance than patients using

polytherapy (Dailey et al. 2001).

The influence of the overall number of drugs used by a patient on adherence is less clear. Some

studies found no association while others found a negative association and yet others a positive

association (Monane et al. 1997; Balkrishnan 1998; Stewart et al. 1999). Cramer reports that

the number of drugs taken by a patient does not correlate with compliance because patients

prescribed several medications tend to either take them all at once or forget them all (Cramer

2002). In addition to its effect on the complexity of the regimen there are a number of

competing effects of the number of medications including severity of disease or perception of

vulnerability and cost.

96

Lack of immediate or perceived benefits

Several aspects of the disease treated have been shown to be associated with treatment

adherence including:

• Lack of symptoms

Nonadherence for asymptomatic conditions with longer term benefits is estimated at 71%

compared with 50% for symptomatic conditions (Sherbourne et al. 1992).

• Severity of disease

Studies suggest an association between perceptions about the severity of the disease and

adherence. Observed positive associations include; a history of CHD was associated with better

compliance in patients with peripheral vascular disease (Pettinger et al. 1999), higher levels of

persistence with lipid lowering therapy associated with the presence of risk factors for future

cardiac events including hypertension, diabetes and CHD (Avorn et al. 1998), and increased

comorbidity and health services utilisation associated with adherence in a study of newly

initiated antihypertensive therapy (Monane et al. 1997). Better adherence with lipid lowering

therapy has been noted in secondary prevention compared with in primary prevention(Insull

1997; Ockene et al. 2002)

Cost

Cost is a complex notion encompassing out of pocket expenses, side effects and cost in terms of

inconvenience and disruption to the daily routine. In the context is this thesis, it is aspects of

cost that are modifiable by the healthcare system and healthcare providers that are the primary

focus particularly out of pocket expenses. However, the healthcare system and healthcare

providers can also impact the cost in terms of adverse events through the choice of agent.

The impact of side effects and adverse reactions is perhaps nowhere better illustrated than in the

comparison of adherence with the older classes of lipid lowering therapy and the newer statins.

A study in two Health Management Organisations found adverse effects accounted for more

than 60% of all discontinuations for lipid lowering therapy and that discontinuation was

significantly lower for statins (15% for lovastatin) compared with other lipid lowering therapy

(41% for bile acid sequestrants, 46% for niacin, 37% for Gemfibrozil)(Andrade et al. 1995)..

Another study with adverse events the main reason for discontinuation found higher rates of

discontinuation in the groups taking cholestyramine alone or in combination with pravastatin

56% and 47% compared with groups treated with pravastatin alone, 24% for 20mg and 22% for

40mg (Eriksson et al. 1998).

Out of pocket expenses can be influenced by the type of funding for prescriptions provided by

the healthcare system, the availability of insurance and the cost of the medication. A number of

quasi-experimental studies suggest that policies for containing drug costs by limiting the level

97

of reimbursement can also result in the underuse of effective medications. These studies are all

from the United States and Canada.

• Insurance

A study in elderly Medicare patients with CHD found that use of the relatively expensive statins

was more sensitive to the type of insurance available than the relative inexpensive beta-blockers

and nitrates (Federman et al. 2001). In their study Federman et al found that while the

proportion of income spent on drugs was highest in patients without drug coverage (7.9% versus

1.7% with employer sponsored drug coverage) use of statins was lowest in the group with no

drug coverage (4% compared with 27%).

• Prescription limits

In a series of studies examining the effects of a three prescription monthly limit (cap) on the use

of drugs, Soumerai and colleagues showed reduced use of medications both in elderly patients

with at least one chronic disease (35% reduction) and in patients with schizophrenia (15 to 49%

for various psychotropic drugs) (Soumerai et al. 1991; Soumerai et al. 1994). Another study on

the use of essential medications in a cohort of patients found a mean decrease in drug use of

34% following the introduction of the cap (Fortess et al. 2001). The observed change was

proportional to the number of drugs used with a 33% decrease in patients using four drugs up to

a 50% decrease in patients using six medications a month.

• Cost sharing

The introduction of prescription cost sharing on patient adherence with medications was

investigated using Quebec administrative data (Tamblyn et al. 2001). Increased cost sharing for

prescription drugs had the desired effect of reducing the use of less essential drugs, but had the

unintended effect of also reducing the use of drugs essential for disease management and

prevention. This reduction in drug use was accompanied by an increase in the rates of adverse

events and Emergency Department visits with a dose-response relationship between the

magnitude of the reduction in the use of essential drugs and the risk of adverse events and

Emergency Department visits. Time series analysis found that a 25% cost sharing policy led to

a 9.1% reduction in the use of essential drugs and a 14% increase in the number of Emergency

Department visits by the elderly.

Another study assessing the impact of increased prescription cost-sharing in Quebec found no

evidence of decreased use or persistence with beta-blockers, lipid lowering therapy and ACE

inhibitors in post-MI patients (Pilote et al. 2002). In their study Tamblyn et al included a wide

range of chronic conditions and essential drugs while Pilote et al study’s was confined to

cardiovascular drugs following a myocardial infarction. A monthly prescription limit was found

to impact on drug use in only some chronic conditions, not including heart disease (Fortess et

al. 2001).

98

Data from the 1992 Medicare Current Beneficiary Survey was use to examine the impact of

Medicaid prescription drug copayment policies in 38 states and found significantly lower drug

use, in states with copayment provisions compared with states without copayments (Stuart et al.

1999). After adjusting for other factors the primary effect of copayments was to reduce the

likelihood that Medicaid recipients fill any prescriptions during the year rather than the number

of prescriptions filled. The study also found a relationship between self reported health status

and copayment related differences in drug use patterns. Drug use increased markedly as health

status deteriorated, but the rate of the increase was much lower in copay states. This difference

was entirely attributable to differences in the proportion of patients reporting any drug use rather

than differences in the quantity of drugs used by medication users. For those in poor health who

filled a script, drug use rates were identical in both groups.

Using data from two large Health Management Organisations to examine the impact of

increased prescription cost sharing on drug utilisation, Johnson et al found that moderate

increases in copayment resulted in lower per capita prescription use (Johnson et al. 1997a). In a

companion study examining specific drug classes no consistent effects were observed (Johnson

et al. 1997b). However the study did find that increased copayments reduced the total number

of days of use for two essential drug classes: cardiac agents and diuretics. They also found that

in the time period when the increase in cost was greatest, drug use, in terms of number exposed

and total days of use decreased for some essential medications and that this was accompanied

by a decrease in health status. The authors concluded that larger increases in copayment may

reduce the use of drugs essential to maintaining health.

• Reference based pricing

The introduction of reference based pricing for ACE inhibitors resulted in an immediate and

sustained decrease (29%) in the use of cost sharing ACE inhibitors accompanied by a delayed

18% increase in the use of no cost ACE inhibitors leaving an 11% decrease in ACE inhibitor

use although use of antihypertensives overall was unchanged (Schneeweiss et al. 2002a). The

investigators conclude that the long-term reduction in use of ACE inhibitors was caused by a

combination of dose reductions and the discontinuation of therapy by 3% of patients. Although

the authors state that the rate of discontinuation after the policy change reflects the rate of

discontinuation before the policy change, they make no further comment on the dose reductions.

The majority of patients (75%) continued with the cost sharing ACE inhibitor and it is possible

that some patients may have reduced the number of doses used each month in an attempt to

offset the shared cost of the medication. However, a companion paper found no difference in

health care utilisation between patients who switched to no cost ACE inhibitors compared with

those using a cost sharing ACE inhibitor (Schneeweiss et al. 2002b), suggesting no negative

impact.

99

• Patient income

Low income was found to be an independent predictor of low drug use in multivariate analysis

that included type of insurance (Avorn et al. 1998; Federman et al. 2001). This suggested that

poverty has a complex impact on the use of medications and may indicate less access to health

care or basic health knowledge.

Magnitude of the problem

This section provides an overview of what is already known about adherence rates for the drugs

of interest, though not necessarily for use in the secondary prevention of coronary artery

disease. For example, primary prevention of coronary artery disease may involve long-term

treatment for hypertension and hyperlipidemia as well as the use of low dose aspirin. CHF on

the other hand is a symptomatic condition that is often preceded by an infarction.

Adherence rates in randomised control trials

Adherence rates in RCTs may not be applicable to the clinical setting because of patient

selection bias. In addition, the resources available during a clinical trial to encourage patient

adherence means a greater likelihood of adherence. Nonetheless, information from clinical

trials can provide a best estimate of patient adherence with medications.

• Aspirin

A primary prevention study of cardiovascular disease in the elderly reported a compliance rate

determined by pill counts of 87% for low dose aspirin (Silagy et al. 1994). The discontinuation

rate was 14%.

• Beta-blockers

The Beta-blocker Heart Attack Trial found that only 7% of the total cohort had poor adherence,

defined as taking ≤75% of prescribed doses (Horwitz et al. 1990).

• Statins

Discontinuation rates in the large RCTs for statins as summarised by Insull (Insull 1997) are

shown in Table 2.32. Discontinuation rates were highest in the primary prevention trials. In

WOSCPS, 26% of patients were taking less than 75% of medication after 5 years which

translated into a reduced risk reduction (West of Scotland Coronary Prevention Study Group

1997).

100

Table 2.32: Discontinuation in RCT of statins

Trial Drug Study Sample Follow-up period

Years

Discontinuation

Percent

Primary prevention

EXCEL Lovastatin 6582 1.0 16.5

WOSCOPS Pravastatin 3302 4.9 29.6

Secondary prevention

4S Simvastatin 2221 5.4 10.4

LIPID Pravastatin 4007 4.0 12.0

CARE Pravastatin 2081 5.0 6.0

Adapted from (Insull 1997)

Using a definition of adherence of ≥80% of the scheduled tablets since the previous follow-up,

levels of compliance with simvastatin in the Heart Protection Study were 89%, 85%, 84%, 83%

and 82% each year respectively (includes use of other statins). In this setting only 2% of

patients took less than 80% ie partial compliers, with complete discontinuation in the remainder

(Heart Protection Study Collaborative Group 2002).

• Hyperlipidemia

In the Coronary Drug Project, one third of patients were poor adherers taking <80% of

prescribed doses (Coronary Drug Project Research Group 1980). Good adherence to clofibrate

was associated with lower mortality (15.0 versus 24.6%), although similar findings were noted

in the placebo group, suggesting a general benefit in good adherers.

In WOSCOPS 15% of patients had withdrawn from treatment at the end of 12 months,

increasing to 30% by the end of five years (The West of Scotland Coronary Prevention Study

1997). Compliance was defined as the relative frequency of visits at which medication was

issued and patients with 75% or greater compliance were classified as good compliers.

Compliance based on pill count was 85% at the first visit increasing to 93% by the end of the

study. In terms of therapeutic benefits, the study found no benefit for patients with <75%

compliance and similar benefits for near optimal (75-99%) and optimal compliers (100%).

• ACE inhibitors

In the HOPE study 1035 patients of 10,576 eligible patients (9.8%) were not randomised due to

noncompliance (<80% of pills taken), side effects, abnormal serum creatinine or potassium

levels or withdrawal of consent. In patients randomised to receive 10mg of ramipril persistence

rates were 87.4%, 85.0%, 82.2%, 75.1%, and 78.8% at one, two, three, four and five years

respectively with a cumulative discontinuation rate of 29%. The proportion of patients

receiving the full dose of ramipril was 82.9%, 74.6%, 70.9%, 62.4% and 65.0% at one, two,

three, four and five years respectively (Yusuf et al. 2000).

101

Adherence rates in observational studies

A number of observational studies provide information about medication taking habits. These

studies usually focus on a particular condition although several studies have been clinic based.

One clinic-based study found discrepancies between patient report and medical records for 76%

of patients. Prescription medications accounted for 61% of all discrepancies including about

25% involving cardiac medications. Discrepancies for cardiac medications were fairly evenly

distributed between medications not recorded in the medical record (8%), patient not taking

(7%) and dose discrepancy (9.2%). Discrepancies were most frequent for nitrates and diuretics

accounting for 36% of the cardiac discrepancies. ACE inhibitors, beta-blockers and lipid

lowering therapy accounted for 14%, 13% and 12% of discrepancies respectively. Dose

discrepancies accounted for about one half of all discrepancies for ACE inhibitors and beta-

blockers, while discrepancies were evenly distributed between all categories for lipid lowering

therapy (Bedell et al. 2000).

Butler et al found a significant shortfall in outpatient adherence to beta-blocker therapy post-MI.

They found that about 80% of patients prescribed beta-blockers at discharge used beta-blockers

during the first 30 days. The proportion of patients filling prescriptions continued to fall during

the fist 90 days and then plateaued, so that from day 90 to day 365, about 60% to 65% of

patients prescribed beta-blockers at discharge continued to fill prescriptions (Butler et al. 2002).

Using the international Global Registry of Acute Coronary Events (GRACE) registry, Eagle et

al found that six months after hospitalisation for an ACS, use of secondary prevention therapies

was reduced. This varied between 20% for ACE inhibitors to 8% for aspirin. Beta-blockers

and statins had been stopped in 12% and 13% of patients prescribed therapy at discharge (Eagle

et al. 2004).

• Angina

The use of electronic monitoring in patients prescribed isosorbide dinitrate three times a day

showed that 74% of patients took correct doses on <70% of days with only 16% taking correct

doses on at least 85% of days. The mean percent of days when the drug was taken three times a

day was 66% (±29%) and the mean number of days in which it was taken three times a day with

appropriate timing was 53% (±31%) (Straka et al. 1996). Patient diaries, while overestimating

compliance, still only showed a compliance rate of 71% (±30%) (Straka et al. 1997).

• Hypertension

Antihypertensive treatment has been an area of intense interest in the field of adherence

research. Treatment of hypertension provides a good analogy for the secondary prevention of

CHD since it is an asymptomatic condition requiring long-term treatment. Furthermore, three

of the drug classes used for the secondary prevention of CHD are also used for the treatment of

hypertension.

102

An early study of hypertensive therapy using pill counts to measure adherence found that only

56% of patients took at least 80% of the prescribed dose and only 48% achieved the target blood

pressure. Achieving the target blood pressure was associated with taking at least 80% of tablets

with more than one half of patients taking less than 80% of tablets failing to achieve the target

blood pressure (Rudd 1995). Using administrative data in a cohort of elderly patients, one study

estimated that antihypertensive medications were only available on an average of 179 of 365

days (49%) and that only 23% of patients had a level of adherence ≥80% (Monane et al. 1996).

Studies using electronic monitoring to measure adherence have consistently shown that

estimates based on the overall proportion of doses consumed are higher than when the timing of

the dose is taken into account. For example, one study of antihypertensive adherence revealed

that while 92% of doses were taken only 63% were taken with 2 hours of the recommended

time (Choo et al. 1999). Another study found that using electronic monitoring the number of

days on which the prescribed doses were taken were 84%, 75% and 59% for once, twice and

three times a day medication respectively however they found that 96%, 93% and 85% of all

doses were consumed (Eisen et al. 1990).

Two studies determined the effect of initial drug choice on persistence with antihypertensive

therapy using large administrative databases. Although using very different populations and

different mixes of drugs the two studies both found higher persistence in patients treated with

ACE inhibitor (Table 2.33).

Table 2.33: Effect of initial drug choice on persistence with antihypertensive therapy

(Monane et al. 1997) (Caro et al. 1999b)

% persistent OR (95%CI) % persistent OR (95%CI)

Diuretics 50 Referent 42 Referent

Beta-blockers 12 1.4 (1.2-1.7) 12 1.25 (1.12-1.39)

Calcium antagonist 12 1.7 (15.-2.1) 14 1.51 (1.36-1.69)

ACE inhibitors 5 1.9 (1.6-2.1) 32 1.92 (1.76-2.09)

The study by Caro et al also found that changes in therapeutic regimen were associated with a

lower level of persistence so that for patients with 2 changes in the therapeutic regimen in the

first six months the risk of not persisting increased with risk ratio (95% CI) of 1.25 (1.12-1.37)

(Caro et al. 1999b). In a companion study Caro et al found that use of antihypertensive therapy

prior to the time period examined were more likely to persist with therapy than newly diagnosed

patients (Caro et al. 1999a). While persistence in patients with established hypertension was

97% at 1 year and 82% at 4.5 years, it was significantly lower in newly diagnosed disease: 78%

at 1 year and 46% at 4.5 years (p<0.001). Logistic regression analysis of persistence through

the first year showed that established hypertension was highly predictive of persistence with an

103

adjusted OR (95% CI) of 10.7 (10.0-11.5). This suggests that once therapy is established it is

more likely to be continued.

• Hyperlipidemia

Lack of adherence with statins is well documented (Simons et al. 1996; Simons et al. 2000;

Benner et al. 2002; Jackevicius et al. 2002). However patients with CHD consistently had

higher rates of adherence. The finding by Larsen et al that adherence varies between two areas

in Europe suggests systematic differences rather than patient differences (Larsen et al. 2000).

• Heart Failure

Medication compliance measured at a home visit one week post discharge in a group of patients

with congestive heart failure, showed that 46% (95% CI 39-54%) of those with a reliable pill

count were poor compliers (Stewart et al. 1999). Good compliance was defined as taking 85 to

115% of prescribed doses. Of the patients with no reliable pill count, 22% (95%CI 16-30%)

reported that they had completely omitted taking one or more medications, although the authors

did not identify drug types. In this study older age, less formal education and, an index hospital

admission caused by an acute exacerbation of a pre-existing chronic disease, were

independently correlated with a lower composite score of medication-related knowledge.

However, the only independent correlate of poor compliance was a greater number of prescribed

medications with the adjusted odds ratio of 2.6 (95%CI 1.4-5.2) for patients with more that 5

prescribed medications (Stewart et al. 1999).

Using integrated medical and pharmacy claims Roe et al found that in patients with a diagnosis

of heart failure and a prescription for an ACE inhibitor, an ACE inhibitor available on only 71%

of days. Only 50% of patients had an ACE inhibitor available on at least 80% of days, thus

indicating “good compliance”. At 180 days following the “index” prescription 86% of patients

continued to take an ACE inhibitor decreasing to 78% at 300 days. Both the percent of days in

which drugs were available and continuation rates were independently related to ongoing use of

ACE inhibitors (compared with new users), male gender, having a greater number of outpatient

visits and absence of renal insufficiency. Renal insufficiency and new users probably represent

legitimate reasons for discontinuation since the former is considered a relative contraindication

and patients with ongoing use of ACE inhibitors are known to tolerate ACE inhibitors while

some new users may be intolerant to ACE inhibitors (Roe et al. 1999)

104

2.5.3 Summary

Local consensus rather than guidelines are most useful to primary care providers. Local

specialists and hospitals also have an important role in influencing prescribing practices of

primary care providers. The dosages of beta-blockers, statins and ACE inhibitors used in

secondary prevention of CHD have been consistently shown to be less than the dosages shown

to be efficacious in RCTs. Furthermore treatment guidelines for statins are not achieved in a

significant proportion of patients receiving therapy, although very few people are on maximal

recommended dosages.

There are many examples of less than optimal adherence and persistence in various secondary

prevention therapies under a number of conditions. The healthcare provider and the healthcare

system in which they operate, are important partners with patients to achieve optimal adherence

with their treatment regimen.

105 Chapter 3: Project development and methods

CHAPTER 3

PROJECT DEVELOPMENT AND METHODS

3.1 Overview

This chapter describes the project development and methodology used to meet the study

objectives of:

• quantifying the gap between evidenced-based recommendations for cardioprotective

medications with known CHD and actual practice at the time of hospital discharge and in

ongoing ambulatory care;

• identifying barriers to the use of effective therapies at the various points in the continuum of

patient care; and

• providing an evidential basis to recommend changes at all levels of health care to reduce

these barriers.

3.1.1 Study approach

To achieve the study objectives, information about drug prescriptions at the time of hospital

discharge following AMI and drug use in ambulatory care needed to be collected . In addition,

other demographic and clinical data were required to adjust for indications (and

contraindications) as well as other factors that might impact on the doctor’s decision to

prescribe or a patient’s decision to follow the treatment regimen.

A review of medical record provided information about drugs prescribed at hospital discharge

as well as other data that might explain prescribing decisions. Drug use in ambulatory care was

reported by the patients and their nominated general practitioners in the early post-discharge

period (3 months) and then, at least 12 months post-discharge (late follow-up) using written

questionnaires.

The early follow-up written questionnaires also collected details of communication about the

treatment plan between the hospital and the patient and the hospital and the general practitioner.

The late follow-up questionnaires collected details about the monitoring and management of

risk factors from the perspective of the patient and the general practitioner.

Interviews conducted in patients’ homes at the time of the early follow-up provided information

about patients’ medication taking patterns. An inventory of medications and a check of the

patient’s understanding about the treatment regimen were also conducted.


On completion of the early follow-up data collection, focus groups and in depth interviews were

conducted with cardiology staff in order to explore several issues about discharge planning and

the actual discharge process that emerged during the patient interviews.

3.1.2 Chapter outline

This chapter comprises three sections. Project development, Methodology, and Data analysis.

The first section describes the development of the data collection instruments and, a study to

determine the feasibility and validity of the study. The second section describes patient

selection and data collection for each phase of the study. The third section describes the data

analysis.


3.2 Project development

3.2.1 Development of data collection instruments

The two principal considerations in developing the data collection tools were to ensure that the

appropriate data were collected and to optimise the response rates for patient and general

practitioner follow-up. This involved ensuring the face and content validity of the research

instruments, as well as minimising the burden to respondents. The first step in developing the

data collection tools involved extensive literature reviews, review of locally available data

collection tools, and consultation with local experts in the field.

3.2.1.1 Medical record data collection form

Determining the minimum data set required an extensive review of the literature relating to

indications and contraindications for each drug class. These included published guidelines for

the use of drugs, and studies that considered indications and contraindications. The literature

was also reviewed for studies that examined factors associated with the prescription of each of

the drugs of interest as well as studies of quality of care in CHD. Cardiovascular medicine

related data collection instruments used previously within the department or hospitals were also

reviewed. Finally, variables to be collected were also discussed with local experts in

cardiovascular medicine.

3.2.1.2 Patient questionnaires

A review of the literature identified other studies that measured drug use in ambulatory care.

Locally available questionnaires sent to CHD patients were also reviewed. Discussions were

undertaken with other researchers about their own experience with patient questionnaires.

Use of existing tools

A number of existing tools for use within the questionnaire were reviewed. Following this

review the following tools were selected for inclusion in the questionnaires:

• Current health status -

• The SF-36V2 was used to measure general health (Quality Metric Incorporated and

Medical Outcomes Trust 1998).

• The Seattle Angina Questionnaire (SAQ) was used as a functional status measure for

CHD (Spertus et al. 1995).

• Patient-provider interactions -

• The Picker Inpatient questionnaire of patient satisfaction for medical patients included

24 items in seven dimensions of patient centred care, including patient preferences,

coordination of care, information and education, physical comfort, emotional support,


involvement of family and friends and continuity and transition (Cleary et al. 1991).

The questionnaire was used in the Massachusetts Health Quality Partnerships Statewide

Patient Survey (Massachusetts Health Quality Partnerships 1998). Questions were

selected from the information and education, involvement of family and friends, and

continuity and transition dimensions.

• The American Board of Internal Medicine Patient Satisfaction Questionnaire (PSQ)

(American Board of Internal Medicine 1999).

The draft questionnaires were circulated for comments to senior staff within the department as

well as a consumer representative. Based on feedback provided, changes were made to increase

the face and content validity of the questionnaires.

3.2.1.3 Patient interview

A review of the literature on measuring patient adherence, particularly relating to direct patient

interviews was conducted prior to designing the interview. Discussions were also held with

colleagues who had conducted home visits following hospital discharge.

3.2.1.4 General practitioner questionnaires

A review of the literature was undertaken for ways of increasing health professionals’ response

to questionnaires. This suggested that questionnaires should be kept as short as possible and

that the status of the signatory may impact the response. Several general practitioner

questionnaires were reviewed with informal discussions with colleagues regarding the

questionnaires. Informal discussions were also conducted with a small convenience sample of

general practitioners regarding questionnaires to gain insight into what general practitioners

might find acceptable. Finally feedback about the draft questionnaire was sought from senior

colleagues.

3.2.1.5 Cardiology staff interviews

Following the early follow-up of the study patients it was decided to clarify aspects of discharge

planning and the discharge process within participating study hospitals. While it was initially

intended to include both the tertiary and affiliate hospitals, time constraints eventually precluded

interviews at the affiliate hospital. This research was preceded by discussion with an

experienced qualitative researcher (A. Mercer) and recommended readings.

The individual interviews and focus groups were developed around three main topics: what was

expected to occur in terms of discharge planning and the discharge process; circumstances

under which this did not occur; and changes that might improve the process. A number of

probes were listed under each topic to ensure that all points were covered.


Individual interviews

The cardiac rehabilitation nurse identified a number of other key personnel involved in the

discharge process. The interviews were slanted towards the interviewees role as well their

understanding of the role of others.

Focus groups

Focus groups were conducted with cardiology ward nurses. A focus group was seen as

advantageous because of the time constraints on both the nurses and the investigator and also

because the group dynamic would facilitate discussion of issues in an area not familiar to the

investigator. Issues addressed in planning the focus groups included the level of structure in the

discussion and, the level of involvement of the moderator (the investigator). To avoid the

investigator tainting the discussions with opinions already formed during the earlier research it

was appropriate to have low moderator involvement, although the discussion would be

moderately structured to ensure that all topics were covered. Topics were as for the individual

interviews, with probes for each topic, where necessary.

3.2.2 Feasibility and validity

3.2.2.1 Follow-up study pilot

A small pilot project was carried out to determine the feasibility of the main project. Of interest

were the number of respondents to the patient survey, how many would be prepared to have an

interview in their home, how many would consent to contacting their general practitioner, and

how many general practitioners would respond to the questionnaire.

Patients for the pilot study (n=19) were discharged from the tertiary care hospital with a clinical

diagnosis of MI in November and December, 1999. The pilot study included 19 otherwise-well

patients. Table 3.1 shows the result of this pilot investigation. Questionnaires were posted in

January and February 2000 with a follow-up telephone call one week later to make an

appointment for a home visit and to encourage completion of the questionnaire.

The response to the questionnaire was 73.7% with 78.6% of these respondents agreeing to an

interview and another 78.6% of respondents providing consent to contact their general

practitioner. The response rate for the general practitioner questionnaire was 63.6% after six

weeks.

Table 3.1: Response to pilot project

Patient questionnaire Patient Patient GP questionnaire

Sent Telephone contact Returned Interview Consent to contact GP Returned

19 16 14 11 11 7


Three patients could not be contacted by telephone:

• one who returned the questionnaire with the consent; and

• two of non-English speaking background; an elderly (90 year old) lady and a young

(57 year old) man.

Of the 16 patients contacted by phone, those who did not agree to an interview included:

• one that had moved out of the metropolitan area;

• one that did not recall the letter, but later returned the questionnaire (without consent to

contact the doctor);

• another, elderly (90 year old) male of NESB would only give his daughter’s phone number,

who then gave her brother’s phone number. A message was left but no contact made; and

• the remaining two had been unwell.

Of the three patients who did not provide consent to contact their general practitioner, one

returned the questionnaire by mail and did not include consent while two others provided details

of their cardiologist rather than their general practitioner. Only one patient required more than

one visit to the home and the second visit was successful.

Four of six women (67%) and 10 of 13 (77%) men returned the questionnaire. Questionnaires

were usually completed fully and missed questions were randomly distributed.

Table 3.2: Characteristics of respondents to pilot questionnaire

Number sent: Percent returned:

Age 51-60 5 60

61-70 4 100

71-80 7 86

81+ 3 33

Treatment speciality Cardiology 14 86

Other 5 40

The pilot indicated that the project was feasible in terms of the number of responses that could

be expected. However, patients older than 80 years and patients where language barriers were

noted in the medical records would be excluded from the main study.


3.2.2.2 Criterion Validity

To validate not previously used questions, responses provided in the questionnaire were

compared with responses to the same questions in a face to face interview carried out at the time

of the patient interview in 21 patients.

Comparison of the responses provided in the questionnaire and in a face to face interview

included the number of concordant pairs, the number of positive responses in the questionnaire

with corresponding positive responses at interview (sensitivity) and the number of negative

responses in the questionnaire with corresponding negative responses at interview (specificity).

Table 3.3 shows there was almost complete concordance between the questionnaire and

interview for previous history and treatment in hospital, however a number of the other

questions, achieved less than 75% sensitivity or specificity. Of particular interest were:

• medication side effects and discharge medications lists which had almost complete

concordance, compared with other information about medications where reproducibility

was lower;

• inhospital risk factor interventions for smoking and diabetes which were near optimal, while

risk factors interventions for cholesterol, blood pressure, weight management and physical

activity were less reproducible; and

• ambulatory monitoring for smoking and diabetes also showed near optimal concordance,

while monitoring of cholesterol, blood pressure and weight management were also high

although monitoring of physical activity had very low concordance.

The validation study suggested that while patients were able to clearly report on medical history

and interventions in hospital, there was less certainty with some aspects of inhospital education

and risk factor interventions as well as ambulatory monitoring of risk factors, particularly:

• purpose and timing of medications, reminder strategies and other written information about

medications;

• inhospital interventions for cholesterol, blood pressure and physical activity; and

• ambulatory care monitoring of physical activity.


Table 3.3: Sensitivity and specificity of questionnaire compared with interview

Concordant pairs Sensitivity Specificity

N=21 Percent

Previous history

Heart disease 21 100 100

Cardiac catheter 18 100 83

PCI 21 100 100

CABG 20 100 95

Hospital episode

MI 21 100 100

Cardiac catheter 18 83 100

PCI 21 100 100

CABG 21 100 100

Medication education

Purpose 17 94 40

Timing 15 93 28

Reminder strategies 16 40 88

Side effects 19 80 94

Medication list 21 100 100

Other written information 15 90 54

Risk factor interventions

Smoking 21 100 100

Cholesterol 14 62 80

Blood pressure 16 100 64

Diabetes 19 100 88

Weight management 18 67 93

Physical activity 15 86 43

Ambulatory monitoring

Smoking 21 100 100

Cholesterol 18 90 82

Blood pressure 18 100 40

Diabetes 20 100 94

Weight management 19 75 94

Physical activity 13 40 69


3.3 Methodology

3.3.1 The study sample

The setting for this study was a tertiary hospital and one of its affiliate hospitals in Perth,

Western Australia. The tertiary hospital was a public hospital while the affiliate hospital was a

private hospital contracted to provide care for public patients. At the time of the study the same

cardiologists consulted at both hospitals. The affiliate hospital did not have facilities for cardiac

angiogram or CARP so patients requiring invasive procedures were transferred either to the

tertiary hospital or another private hospital.

Institutional ethics committee approval was obtained from both hospitals to access patient

medical records and to contact patients.

3.3.1.1 Patient selection

The study population consisted of all hospital discharges where the patient was discharged

home with a primary or secondary diagnosis of myocardial infarction from January 2000 to

September 2001. A clinical diagnosis of myocardial infarction, rather than standardised

diagnostic criteria, was used because it was reasoned that all cases with a clinical diagnosis

should be managed appropriately both with regard to the use of secondary prevention therapies

and risk factor interventions. Hospital episodes were not included where:

• there was no documentation of a myocardial infarction in the medical record;

• it was not the first hospital episode following the myocardial infarction;

• the record was not available within six months of discharge; or

• the patient was already included in the study.

Patient selection for follow-up study

Not all post-MI patients with a medical record review available were followed up. Exclusion

criteria included; deceased prior to follow-up, greater than 80 years of age, documented

language difficulties and, any significant comorbidity or other significant or multiple diseases

where secondary prevention of CHD might not be indicated.

Patient interview

All patients completing the early follow-up questionnaire were asked to participate in an

interview in their homes as part of the study.

General practitioner survey

Consent to contact the patient’s general practitioner was sought from all study patients.


3.3.2 Data collection

Data collection took place over the period from January 2000 to October 2002 with data from

all sources collected contemporaneously.

3.3.2.1 Medical record review

Participating hospitals provided a weekly list of hospital episodes with a primary or secondary

diagnosis of AMI (ICD-10 12.1). Medical records were reviewed in the Medical Records

department of the participating hospitals on a weekly basis. Data were entered directly into an

Access database. A list of the variables collected is included in Appendix A.

Drugs prescribed at discharge, including dose and frequency, were recorded from the copy of

the discharge summary filed in the medical record. Drugs used prior to admission, including

dose, were recorded from the list of drugs on admission recorded by the admitting doctor in the

medical record.

3.3.2.2 Comorbidity

The primary diagnosis and up to 21 secondary diagnoses (ICD-10) for each index hospital

admission were obtained from The Western Australian Hospital Morbidity System Data System

retrospectively. Approval from the Confidentiality of Health Information Committee was

obtained to access this information. Details of the hospital episodes including patients’ name,

date of birth, dates of admission and discharge and treating hospital were provided to the Data

Linkage Unit at the Department of Health, Western Australia which then provided the compete

list of primary and secondary diagnoses recorded for each of the hospital episodes.

3.3.2.3 Patients questionnaires

Questionnaires were mailed out in batches every two weeks. Data were entered into an Access

database on a weekly basis. All questions were coded as laid in the questionnaires.

Early follow-up

The early follow-up questionnaire was mailed to patients as soon as practicable following the

medical record review. Copies of the letter, information sheet and questionnaire are included in

Appendix B. One week after questionnaires were sent, at least three attempts were made to

contact patients including at least one attempt after 7pm and one attempt on the weekend. The

purpose of the telephone call was to encourage patients to participate in the survey, and to

recruit patients for the home visit component of the study. Patients who agreed to a home visit

had the option of returning the questionnaire at the time of the home visit. A reply paid

envelope was included with the questionnaire for patients not wishing to have an interview.


Late follow-up

Questionnaires were mailed out in batches every two weeks at least 12 months after the index

hospital admission. Copies of the letter, information sheet and questionnaire are included in

Appendix C. Two weeks after questionnaires were mail out at least two attempts were made to

contact patients who had not returned the questionnaire. This included one attempt after 7pm or

during the weekend. This purpose of the telephone call was to encourage patients to complete

and return the questionnaire.

Respondents who did not report use of a secondary prevention therapy they were previously

using, were contacted by telephone to ascertain reasons for discontinuation. At least two

attempts were made to contact each of these patients with at least one attempt after 7pm.


The information sheet accompanying the early follow-up questionnaire asked patients to

consider a brief interview by the investigator in their home. Patients who did not wish to be

interviewed were advised to return the questionnaire using the reply paid envelope. One week

after the questionnaire mail out, patients who had not returned the questionnaire by mail were

contacted to ask if they were happy to have a home visit and an appointment was arranged

usually within the following week. A copy of the interview guide and data collection sheet is

included in Appendix D.

The home visit consisted of two parts:

A semi-structured interview where patients were asked about their medication taking routine.

Factors of interest were:

• Missed/forgotten medications-

• habits around medication use;

• reasons for stopping medications.

• Patients were then asked to show all their current medications. For each medication they

were asked about -

• the dose and timing of each medication;

• their understanding of the purpose for taking the medication.

Responses were transcribed in the form of notes.

3.3.2.5 General practitioner survey

At both the early and late follow-up, patients were asked to complete a consent form to allow

their general practitioner to be contacted for further details. Copies of the letters to general

practitioners and the questionnaires are included in Appendix B and C. Letters to general

practitioners were sent on a fortnightly basis, so that letters to general practitioner went out not


more than two weeks after the receipt of the patient questionnaire. Both doctoral supervisors

signed all letters. One reminder was sent after three weeks.

Early follow-up questionnaire

Patient specific letters and questionnaires were computer generated and included a list of

medications at discharge, including dosages and timing, as recorded on the discharge summary.

Late follow-up questionnaire

Patient specific letters and questionnaires were computer generated and contained a list of

medications. The list of medications were taken from:

• the early follow-up general practitioner questionnaire; or

• the early follow-up patient questionnaire; or

• hospital discharge summary.

3.3.2.6 Cardiology staff interviews

This qualitative research was carried out in the cardiology ward of the department of

Cardiovascular Medicine at the tertiary hospital. Patients were usually admitted to the Coronary

Care Unit and transferred to the step down ward prior to discharge. All individual interviews

and focus groups were preceded by a brief history of the project and a statement that the

investigator was outside the hospital system and wanted to listen and learn from their

experiences and insight. A list of topics to be covered in the interviews and focus groups is

included in Appendix E.

Individual interviews

Key personnel were approached individually and an interview arranged at a time and place

convenient to the interviewee. The interviews were tracked to ensure that all the topics were

covered, however the order in which the topics were covered were flexible within the

interviews. Interviews were taped for later transcription by the investigator.

Focus groups

Nurses from the cardiology ward were included in the focus groups. These were voluntary and

conducted at a time usually reserved for educational meetings, thus not impacting on nurses’

time. Two focus groups were conducted one week apart. While both focus groups commenced

with the same topic the order of the topics covered was flexible, based on the group discussion.

Everyone was encouraged to participate on most topics. Focus groups were taped and a scribe

recorded notes. The investigator later transcribed the tapes and amalgamated these with the

scribe’s notes.


3.4 Data analysis

This section describes the analysis performed in each of Chapters 4 to 8. This is followed by a

description of the statistical methods used.

3.4.1 Chapter 4:The study sample

3.4.1.1 Baseline characteristics

Variables from the medical record review were recorded and used as dichotomous variables

unless specified.

• Age was calculated from the date of birth and date of discharge and was used as a

continuous variable, a categorical variable in multivariate analysis (<60 years, 60-69 years,

70-79 years and ≥80 years) and also as a dichotomous variable (<60 years, ≥60 years).

• Patient insurance type was used as a dichotomous variables with patients classed as either

Public patients or Private and Veterans affairs.

• Enrolment period was derived from the date of discharge and measured time lapsed. This

was used as a continuous variable indicating the number of months since January 2000 and

as a categorical variable with either:

• seven categories representing annual quarters from January 2000 through to September

2001; or

• three categories Early (January to July 2000), Middle: (August 2000 to January 2001)

and Late (February to September 2001) for subgroup analysis.

• Revascularisation procedures PCI and CABG were considered individually and together as

any CARP.

• Treatment speciality was based on the discharge ward and treated as a dichotomous variable

to indicate either a cardiology unit or any another unit.

• Primary diagnosis was a dichotomous variable indicating that MI was listed as the primary

diagnosis on the handwritten discharge summary prepared by the responsible medical

officer.

• Length of stay (LOS) was calculated from the date of admission and the date of discharge.

This was used a dichotomous variable to indicate a LOS>10 days (Long-stay).

Approximately 20% of hospital episodes had a LOS>10 days.

• The MI was described in terms of three dichotomous variables indicating:

• sustained ST-elevation recorded in the medical record;

• anterior site of infraction;

• a large infarction based on a peak CK >720 U/L that represented four times the normal

level (High-CK).


• Reperfusion procedure included either the use of a thrombolytic agent or a primary PCI.

• A Comorbidity Index at the time of discharge was calculated using the primary diagnosis

and up to 21 secondary diagnoses (ICD-10) for each hospital admission as recorded in the

Western Australian Hospital Morbidity System Data System. The list of conditions and

weighting for these conditions were based on the Charlson Comorbidity Index (Charlson et

al. 1987). Conditions were mapped to ICD-10 using a method previously developed locally

(K Brameld, personal communication). Since all patients had a diagnosis of myocardial

infarction, and heart failure was considered independently, these two diagnoses were

omitted from the Comorbidity Index. Where MI was not the primary diagnosis, the primary

diagnosis was also included in the list. The Comorbidity Index was used as a continuous

variable and as a categorical variable with four categories (0,1,2 and 3 or more).

Descriptive analysis

Variables used to describe the study sample included:

• demographic variables;

• medical history prior to admission;

• details of the hospital admission including hospital, specialty and LOS;

• details of the MI;

• cardiac complications during the hospital episode;

• investigations and procedures performed during the hospital episode;

• documented risk factors; and

• comorbidity index.

Bivariate analysis

The sample was analysed by gender and treatment specialty to provide a better understanding of

the sample.

3.4.1.2 The follow-up cohort


Analysis of the follow-up cohort included:

• reasons for exclusion from the follow-up study;

• the response rates; and

• time to follow-up, days from the date of discharge to completion of the questionnaire.

Other analysis included details of post-discharge care and current status:

• post-discharge care during the early follow-up period reported by patients included:

• attendance at cardiac rehabilitation sessions (either inpatient or outpatient);


• consultation with health professionals, including tests, procedures and readmissions;

and

• patient-provider interaction as categorical variables and a dichotomous variable

indicating less than optimal satisfaction defined as a score of “good”, “fair” or “poor”.

• Post-discharge care during the late follow-up period reported by patients included:

• time since last consultation with a cardiologist as a categorical variable including <3

months, ≤6 months, >6 months and not seen;

• tests, procedures and readmissions; and

• source of information about medications.

• Current status at both early and late follow-up included:

• current medications;

• smoking status as a categorical variable;

• items in the SF-36 and SAQ calculated according to the manuals (Spertus 1993; Quality

Metric Incorporated and Medical Outcomes Trust 1998)

• shortness of breath as a categorical variable; and

• social factors including living with family and working arrangements.

• Post-discharge care reported by the general practitioner at the early and late follow-up

included:

• the number of consultations during each follow-up period; and

• the mean number of days between consultations calculated the number of days since

discharge and the number of consultations reported.

Bivariate analysis

Analysis of the current status included a comparison between the early and late follow-up

questionnaires of smoking status, mean scores on items in the SF-36 and SAQ and the

proportion of patients with lower or higher scores for items in the SF-36, SAQ and shortness of

breath.


3.4.1.3 Sample validity

Early and late follow-up cohort

This bivariate analysis included all patients eligible for follow-up and compared responders and

non-responders in terms of demographic characteristics, medical history and course of hospital

episode.

Interview group

This bivariate analysis included all responders to the early follow-up patient questionnaire and

compared patients with and without an interview in terms of demographic characteristics,

medical history and course of hospital episode as well as post-discharge care and current status.

GP questionnaire group

This bivariate analysis included all responders to the patient follow-up questionnaires and

compared the group with and without complete GP questionnaires in terms of demographic

characteristics, medical history and course of hospital episode as well as post-discharge care and

current status.


3.4.2 Chapter 5: Secondary prevention therapies at discharge

Descriptive and bivariate analyses were used to describe the proportion of patients prescribed

each of the secondary prevention therapies, antiplatelet agents, beta-blockers, statins and ACE

inhibitors at discharge, as determined from the medical record review. Prescribing patterns for

the secondary prevention therapies were juxtaposed against the prescribing patterns for calcium

antagonist, a drug commonly prescribed in patients with CHD but not recommended as routine

treatment in the secondary prevention of CHD. Multivariate analysis was used to determine the

independent predictors for drug prescription for each secondary prevention therapy and non-

prescription of calcium antagonist.

3.4.2.1 Overview

A bivariate analysis of prescribing practices of all secondary prevention therapies included

prescriptions by gender, age (4 categories), comorbidity index (4 categories), treatment specialty

and enrolment period (7 annual quarters). The variation in prescribing by individual

cardiologists for patients not using the drug class prior to admission was examined and the

variation in prescribing of ACE inhibitors compared with that of the other secondary prevention

therapies.

3.4.2.2 Individual drug classes


Analysis included the proportion of patients prescribed each drug, reasons provided for drugs

not prescribed and the types of drugs and doses prescribed. Analysis of antiplatelet agent

prescription was stratified by PCI prior to discharge, since treatment recommendations differ in

this group. Analysis of statin and ACE inhibitor prescription included the frequency of changes

in the type of drug prescribed in the group already using the drug class prior to admission.

Analysis of statin prescription also included the timing of the dose prescribed.

Bivariate analysis

Analysis of the doses prescribed for statins and ACE inhibitors included a comparison of mean

doses between the group newly prescribed the drug class and the group using the drug class

prior to admission.

The increase in ACE inhibitor prescriptions with enrolment period (3 categories) was analysed

by treatment speciality. The cardiology cohort was further analysed for changes in prescribing

practices in patients not using an ACE inhibitor prior to admission. Based on individual ACE

inhibitor prescribing rates, cardiologists were divided into three groups; low (<mean-1SD),

intermediate and high (>mean+1SD) prescribers of ACE inhibitors. Changes in the type of


ACE inhibitor (Ramipril or other) prescribed over the time of study (7 annual quarters) were

examined.

Bivariate analysis for all drug classes included a comparison of the prevalence of relative

contraindications (Table 3.4) between the groups prescribed and not prescribed individual

drugs. The presence of relative contraindications in the group prescribed the drug was

compared by treatment specialty.

Table 3.4: Drug contraindications

Drug Contraindication Definition

Antiplatelet agent Anticoagulant

Bleeding

Peptic Ulcer Disease (PUD)

Adverse drug reaction

Prescription of an anticoagulant

Bleeding complication documented

Diagnosis with prescription of an H2

antagonist or proton pump inhibitor

Recorded

Beta-blocker Chronic airways limitation (CAL)

Heart block

Bradycardia

Cardiogenic shock

Hypotension


Diagnosis of COPD or asthma

2nd degree or complete heart block

Sinus bradycardia or HR<60bpm

Diagnosis

Diagnosis or discharge SBP<95 mmHg

Recorded

Statin Liver dysfunction


Diagnosis

Recorded

ACE inhibitor Aortic stenosis

Renal failure

Hypotension


Diagnosis

Diagnosis or serum creatinine >300 µmol/L

Diagnosis or discharge SBP<95 mmHg

Recorded

The influence of relative indications (Table 3.5) on drug prescription was also examined. This

included the influence of lipid levels (as categorical variables) on prescription of statins and the

prevalence of each post-MI indication for an ACE inhibitor between the group prescribed and

not prescribed ACE inhibitors was compared. The prescription of ACE inhibitors by indication

was compared by treatment specialty.

The five post-MI indications for ACE inhibitors were then defined as absolute(symptomatic

heart failure or LVD) or relative (Anterior site/high-CK/Diabetes) indications to compare the

level of indication (absolute, relative or none) on the odds of ACE inhibitor prescription. The

interaction between heart failure and known LVD was examined using a stratified analysis.


The increase in ACE inhibitor prescriptions with increasing time since January 2000

(3 categories) was examined by post-MI indications (absolute, relative or none), including a sub

analysis of the cardiology cohort and in the group not using ACE inhibitors prior to admission.

Table 3.5: Drug indications

Drug Indication

Antiplatelet agent All patients

Beta-blocker All patients

Statin Lipid profile recorded in notes (mmol/L) including total Cholesterol,

LDL-C, HDL-C and Triglycerides concentrations

Categorical variables:

• TC;<4 , ≥4and <5 , ≥5 and <6, ≥6,

• LDL-C; <2.5. ≥2.5 and <3.5, ≥3.5 and <4.5, ≥4.5.

• Triglycerides; <2, ≥2 and <4, ≥4.

• HDL-C <1, ≥1.

ACE inhibitor

Absolute indication

Relative indication

Known LVD (LVEF ≤40% or a qualitative assessment of at least a

moderate dysfunction on echocardiography or radionuclide study).

Diagnosis of heart failure

Large infarction (peak CK>720 U/L)

Anterior Infarction

Diabetes

Bivariate analysis of the influence of other clinical variables on drug prescription included all

the variables collected in the medical record review as previously described as well other

secondary prevention therapies prescribed at discharge and the number of drugs prescribed at

discharge.

Multivariate analysis

All variables with at least 20 cases and with a p-value <0.10 in bivariate analysis were included

in multivariate logistic regression analysis to determine independent predictors for each drug

class. Some aspects of the analysis varied by drug class.

Analysis of independent predicators of antiplatelet agent prescription was restricted to patients

with no revascularisation procedure prior to discharge. Logistic regression models included the

complete cohort, new prescriptions only, that is patients not using the drug prior to admission,

and a model stratified by treatment speciality.


The analysis of independent predictors of beta-blocker prescription included an analysis for the

subset of patients not using a beta-blocker prior to admission and an analysis stratified by

treatment specialty.

Multivariate analysis of statin prescription included only patients not using statins prior to

admission and included an analysis stratified by treatment specialty. Within each analysis two

different models were analysed. One model included all patients and did not include lipid

levels, but included a variable to indicate whether a complete lipid profile was recorded. The

second model included only patients with a cholesterol level recorded.

Multivariate analysis of ACE inhibitors included the date of hospital discharge expressed as the

number of months since January 2000. Models examined included the complete cohort and new

prescriptions only. Analysis was stratified by the presence or absence of either symptomatic

heart failure or LVD. The interaction between the month of hospital discharge and the level of

indication (absolute, relative or none) was further analysed in a separate multivariate analysis.


3.4.3 Chapter 6:Discharge planning and transition of care

This analysis examined variables that may influence the long-term use of secondary prevention

therapies from the patient point of view. It also described the transition of care from the general

practitioner perspective and, explored strategies and barriers to optimal discharge planning and

transition of care from the perspective of cardiology staff.

3.4.3.1 Patient perspective


The early follow-up patient questionnaire provided data on:

• the treatment regimen at the time of discharge including;

• the proportion of discharge prescriptions recorded in the medical record with

corresponding prescription reported by the patient in the questionnaire (sensitivity) and,

• the proportion of medical records with no prescription at discharge with a

corresponding response reported by patient in the questionnaire (specificity).

• the information provided about medications including the health professional involved;

• risk factor interventions discussed and provided;

• the type of written information provided;

• aspects of cardiac rehabilitation in either hospital or follow-up care;

• confidence in their knowledge about medications; and

• patient satisfaction with the information received during the hospital episode.

Bivariate analysis

Responses were compared by hospital.

3.4.3.2 General practitioner perspective

This descriptive analysis included receipt of a discharge summary and telephone call from the

hospital. Based on comments provided the transition of care classified into one of three

categories (good, no problems and could be done better).

3.4.3.3 Hospital staff perspective

Comments provided during the interviews and focus groups were organised under headings:

• roles in providing information to the patients about the discharge;

• responsibility of making sure patients have a clear understanding about the medications they

have to take at home;

• written information provided to the patient given;


• responsibility for making sure the patient has been given all the written information prior to

discharge; and

• barriers to the provision of this information occurring.

3.4.4 Chapter 7:Long term secondary prevention therapy

Outcome variables of interest in this analysis were:

• the prevalence of drug use in ambulatory care;

• the proportion of the follow-up cohort that discontinued use of each of the secondary

prevention therapies during the follow-up period;

• the proportion of patients using doses at least equivalent to the doses used in the RCTs that

provided the evidence for the use of these drugs in the secondary prevention of CHD; and

• the proportion of patients adherent with the prescribed treatment regime.

3.4.4.1 Prevalence of drug use

Prior to admission

This descriptive analysis included the proportion of the study sample and the subgroup with

established CHD (previous MI or CARP) using each of the secondary prevention therapies and

the number of therapies used.

The proportion of patients with established CHD eligible for each secondary prevention therapy

prior to admission was estimated from the number of patients using therapy prior to admission

and the number of new prescriptions at discharge. Underuse of a therapy was estimated as the

proportion of eligible patients not using therapy prior to admission

The cumulative risk reduction impact, as determined by Yusuf (Yusuf 2002) and shown in

Table 3.6, was applied to the study cohort to estimate the proportion of patients with a history of

CHD using secondary prevention therapies in the community of patients eligible for admission

to a participating hospital.

Table 3.6: Potential cumulative impact of secondary prevention therapy

Relative Risk Reduction 2-year event rate

None .. 8%

Antiplatelet agent 25% 6%

Beta-blocker 25% 4.5%

Lipid lowering (by 1.5 mmol/L) 30% 3.0%

ACE inhibitor 25% 2.3%

The Relative Risk Reduction was used to estimate the 2-year event rate for each combination of

secondary prevention therapy. The inverse of the estimated event rate was then applied to the


number of patients in the study using that combination of drugs to estimate the number in the

community with known CHD and eligible for admission to a participating hospital using that

combination of drugs. The proportion of patients in the wider community using each drug

combination and each drug was then estimated.

During follow-up


The descriptive analysis of current medications reported in patient questionnaires was restricted

to the subgroup with both early and late patient questionnaires completed and included:

• changes in the prevalence of drug use from discharge to late follow-up;

• the proportion of patient with no prescription at discharge that commenced drug use in

ambulatory care determined by direct comparison of prescriptions at discharge with current

drug use at early and late follow-up for individual patients.

• the proportion of patients that discontinued drug use during ambulatory care determined by

direct comparison of prescriptions at discharge with current use at early and late follow-up

for individual patients;

• reasons for discontinuing drugs provided by patients.

Bivariate analysis

In this bivariate analysis of current medications reported in all patient questionnaires, the early

and late follow-up cohort were analysed separately to determine:

• differences in drug use from hospital discharge to follow-up;

• drug use at early and late follow-up by enrolment period (3 categories).

The odds of initiating and discontinuing therapy for each of the drug classes was compared with

the odds of initiating and discontinuing statin therapy in the subgroup with both early and late

patient questionnaires completed.

3.4.4.2 Treatment regimen


Reasons provided by the general practitioner for stopping and initiating drugs were examined,

including changes within the drug class and reasons provided for the changes.

Bivariate analysis

Data from the GP questionnaires and the medical record review were used to examine changes

in the treatment regimen from hospital discharge to late follow-up. This included:

• changes in the proportion prescribed specific drugs;


• changes in the proportions prescribed various dosages; and

• changes in the mean dose prescribed for specific drugs.

• changes in the proportion of patients prescribed doses equivalent to those used in the

clinical trials (Table 3.7)

Table 3.7: Clinical trial dosage regimen

Clinical trial/meta analysis target dosage (mg/day)

Antiplatelet agents

Aspirin ≤150 mg (Antithrombotic Trialists' Collaboration 2002)

Clopidogrel 75 mg (CAPRIE Steering Committee 1996; The Clopidogrel in Unstable

Angina to Prevent Recurrent Events (CURE) Trial Investigators 2001)

Beta-blockers

Metoprolol 200 mg (Hjalmarson et al. 1981)

Atenolol 100 mg (Wilcox et al. 1980)

Statins

Simvastatin 20 mg (Scandinavian Simvastatin Survival Study Group 1994)

Pravastatin 40 mg (Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID)

Study Group 1998)

ACE inhibitors

Ramipril 10 mg (Heart Outcomes Prevention Evaluation Study Investigators 2000)

Perindopril 4 mg1 (Lau et al. 2002)

Trandolapril 1 mg2 (Kober et al. 1995) 1 EUROPA target dose was perindopril 8mg/day (The EURopean trial On reduction of cardiac events with Perindopril in stable coronary Artery disease Investigators 2003) 2 PEACE target dose was 4 mg trandolapril (Braunwald et al. 2004)

3.4.4.3 Adherence with treatment regimen

Use of a patient questionnaire to obtain information about current drug use was evaluated by

direct comparison of drug use reported by patients in the early follow-up questionnaire and the

drug inventory at the time of interview. Analysis included the number of matched (concordant

pairs) and unmatched pairs (discordant pairs).

Comparison of patient reported drug use and drug use reported by the doctor provided a

measure of adherence with the prescribed treatment regimen. Analysis included:

• the number of discordant pairs at early and late follow-up based on drug class;

• at late follow-up, the analysis included the number of discordant pairs based on specific

drugs and doses reported.

Information collected at the patient interview was analysed using a mixture of ethnographic and

content summary. Topics included sporadic and systematic deviations from the treatment

regimen, and factors associated with partial adherence with the treatment regimen.


3.4.4.4 Predictors for use of secondary prevention

Factors associated with drug use prior to admission

Bivariate analysis

The complete study sample and the subgroup with prior CHD were each analysed for factors

associated with drug use prior to admission. Non-clinical factors considered included age

(categorical variable), gender, enrolment period (3 categories) and smoking. Clinical factors

included contraindications, medical history and the number of other secondary prevention

therapies used prior to admission


The multivariate analysis of the complete study sample to determine independent predictors of

drug use included all variables with a χ2 p-value <0.10 in bivariate analysis.

A multivariate analysis of the subgroup with prior CHD examined independent predictors of

underuse of secondary prevention therapies. Underuse was defined as the use of no therapies

and then as the use of less than two therapies.

Factors associated with drug discontinuation

Bivariate analysis

This analysis examined factors associated with the discontinuation of any drug during the

follow-up period for the early and late follow-up cohorts. Variables from the medial record

review and patients questionnaires were considered.

Variables from the medical record review included:

• the demographics variables with age treated as a dichotomous variable; and

• aspects of the hospital episode including, hospital and patient type, treatment speciality, risk

factors, the presence of at least one comorbidity and treatment prior to discharge.

Variables from the early follow-up patient questionnaire included aspects of past history and the

inhospital experience. Variables from the early and late follow-up patient questionnaires

included aspects of post-discharge treatment, post-discharge risk monitoring. Categorical

variables were converted into dichotomous variables to indicate:

• No counselling about a risk factor. These variables were then combined to indicate no

counselling about 3 or more risk factors.


• The patient was definitely not satisfied with the aspect of communication prior to discharge.

These variables were combined to indicate that the patient was definitely not satisfied with

one or more aspect of communication prior to discharge.

• A variable was then defined to indicate less verbal communication if a patient had no

counselling about 3 or more risk factors and was definitely not satisfied with one or more

aspect of communication prior to discharge.

• Less discharge planning was defined as any two of; no counselling about 3 or more risk

factors; definitely not satisfied with one or more aspect of communication prior to discharge

and no discharge medication list.

• Dissatisfaction with aspects of the relationship with the general practitioner, defined as a

score less than “Excellent” or “Very Good”. These variables were then combined to

indicate dissatisfaction with at least four aspects of the relationship.

• No monitoring of a risk factor at early follow-up.

• No cholesterol or blood pressure had been measured in the previous 12 months. and

• High cholesterol or blood pressure at late follow-up.

• A poor score for each domain of SAQ was defined as a score of less than 60, and a good

score was for each domain of SAQ was defined as a score than 80.

• A poor score for each domain of the SF-36 was defined as a score < (mean – 1SD) and good

score was defined as a score >(mean + 1SD).


All variables with χ2<0.10 were included in a multivariate analysis of the independent

predictors of drug discontinuation in the early and late follow-up cohorts. An additional

analysis was undertaken including only patients participating in both the early and late follow-

up surveys and including all the independent predictors from the early and late follow-up

cohort.


3.4.5 Chapter 8:Risk factor management

This analysis examined risk factor management at each point in the continuum of care. Of

particular interest in this analysis were the proportion of patients achieving treatment goals for

lipids, blood pressure and blood glucose.

3.4.5.1 Lipids

Prior to index admission

This analysis included all patients with lipid levels recorded during the hospital admission.


Lipid levels at the time of infarction (categorical variables) were described in terms of the

proportion of patients with each lipid level and included the subgroup with a history of

hyperlipidemia and the subgroup with a history of CHD. Within each group lipid levels were

examined by statin use.

The proportion of patients with established CHD (previous MI or CARP) eligible for statin

therapy prior to admission was estimated from the number of patients using therapy prior to

admission and the number of new prescriptions at discharge. Underuse was estimated as the

proportion of eligible patients not using therapy prior to admission.

Bivariate analysis

For the subgroup with established CHD, use of statins prior to admission, the proportion of

patients estimated to be eligible for statin therapy prior to admission and, underuse prior to

admission, were compared by prior history of hyperlipidemia.

Inpatient monitoring and management


This analysis included:

• measurement of cholesterol levels and the availability of complete lipid profiles;

• inhospital management was described in terms of interventions discussed and provided

during the hospital episode including the health professional involved;

• the proportion of patients with higher than recommended lipid levels prescribed a statin at

discharge; and

• the proportion of patients not prescribed statins who had higher than recommended lipid

levels was determined.


Bivariate analysis


• the association between the availability of a complete lipid profile and a number of factor

including age and commodity index as continuous variables and other dichotomous

variables available at the time of admission including the hospital and treatment speciality,

details of the myocardial infarction and medical history; and

• differences in mean lipid levels by statin prescription at discharge



• logistic regression analysis to determine independent predictors of a complete lipid profile

recorded in hospital; and

• logistic regression analysis to determine the influence of TC, LDL-C and HDL-C, as

continuous variables on statin prescription.

Monitoring and management in follow-up care


Analysis of information from the patient questionnaires included:

• the proportion of respondents to the early follow-up questionnaire reporting no monitoring

of lipid levels, including the proportion with a new statin prescription

• at late follow-up,

• months since the last measurement, a categorical variable including ≤ 3 months, ≤ 6

months, ≤ 12 months and ≥ 12 months and no measurement reported; and

• patient reported TC level as a categorical variable <4.5, 4.5 –< 5.5, ≥5.5 mmol/L.

Analysis of the general practitioner reported monitoring of lipid levels included:

• the proportion of cases with cholesterol levels and complete lipid profiles reported including

a sub analysis by statin use;

• time since last measurement, reported as the mean and quartiles and calculated using the

date of the measurement and the date of the general practitioner report where the date of the

measurement was after the date of hospital discharge; and

• the range and mean of lipid levels;

• direct comparison of lipid levels at hospital episode and late follow-up in the cohort not

using statins prior to admission and with measurements at both time points -

• absolute differences; mean and quartiles,

• relative difference; mean and quartiles;

• the proportion of patients achieving therapeutic goals.


Bivariate analysis

Information from the patient questionnaires was examined for an association between time since

last lipid measurement, as a categorical variable, and TC level, as dichotomous variable (<5.5

mmol/L).

Analysis of the general practitioner reported monitoring of lipid levels included:

• Using TC, LDL-C and HDL-C as continuos variables to compare mean lipid levels

• by statin use in the follow-up cohort; and

• from the time of myocardial infarction to late follow-up

− in the follow-up cohort;

− the subgroup with a new statin prescriptions at discharge.

• Using TC, LDL-C and HDL-C as categorical variables to examine changes in lipid levels

from hospital episode to late follow-up for the overall cohort and the subgroup not using

statins prior to prescription were examined by:

• comparing the proportion of patients within each lipid level;

• changes in the distribution of lipid levels

• Using lipid levels as a dichotomous variables to indicate achievement of therapeutic goals

(TC<4 mmol/L, LDL-C <2.5 mmol/L) and high lipid levels (TC>5 mmol/L, LDL-C>3

mmol/L), factors associated with lipid levels were examined including:

• age as a continuos variable;

• use of statins at follow-up and, prior to the index MI;

• lipids measured within 90 days of the general practitioner report;

• the type of statin prescribed;

• low dose of statin prescribed to indicate a dose of statin less than those used in the

RCTs;

• use of a dose of statin greater than those used in the RCTs.

Doses for pravastatin and simvastatin used in the clinical trials are listed in Table 3.7. In the

absence of any RCTs for the long-term effectiveness of atorvastatin, atorvastatin 20 mg was as

the cut point.


All variables with a p-value <0.10 in bivariate analysis were included in a logistic regression

analysis to examine independent predictors of achieving therapeutic goals; and high lipid levels.


3.4.5.2 Other risk factors

Blood pressure monitoring and management


Inhospital management was described in terms of interventions provided and discussed during

the hospital episode including the health professional involved.

Analysis of management and monitoring during follow-up care included:

• the proportion of patients with at least one blood pressure measurement since discharge at

the time of early follow-up;

• at late follow-up

• months since the last measurement, as a categorical variable including <1 month,

<3 months, <6 months, <12 months, >12 months and missing

• patient reported blood pressure as a categorical variable: good, a bit high, high, low,

unsure and missing.

Analysis of the general practitioner reported monitoring of blood pressure included a descriptive

analysis of:

• the proportion of cases with blood pressure measures reported;

• time since last measurement, reported as the mean and quartiles;

• blood pressures reported used as categorical variables optimal (<120/80), normal (<130/85),

high normal (<140/90) and high.

Bivariate analysis

Analysis of the association between the use of blood pressure lowering medication and high

blood pressure included:

• a comparison of the proportion of patients with high blood pressure by use of any blood

pressure lowering medication;

• a comparison of the proportion of patients using each of the blood pressure lowering

medications by the presence of high blood pressure;

• the relationship between the number of blood pressure lowering medications used and the

presence of high blood pressure.

Monitoring and management of blood glucose

This descriptive analysis included of the monitoring of blood glucose during the hospital

episode involved the compete study sample and included:

• the proportion of the study sample with a blood glucose measurement recorded;


• the proportion of patients with known diabetes or IFG with a blood glucose and glycated

haemoglobin recorded;

• blood glucose levels reported as a categorical variable <6 mmol/L, 6-7 mmol/L and >7

mmol/L;

• glycated haemoglobin reported as a dichotomous variable <7%.

Patient reported monitoring and management included:

• at early follow-up;

• interventions provided and discussed during the hospital episode including the type of

health professional involved;

• monitoring of blood glucose, including the proportion with diabetes and IFG;

• at late follow-up;

• the proportion of patients with diabetes or IFG reporting monitoring since discharge

was determined including;

• months since the last measurement, a categorical variable including < 3 months,<6

months, <12 months and no measurement reported; and

• patient reported blood glucose levels as a categorical variable including good, a bit

high, high, not sure and missing.

Analysis of the general practitioner reported monitoring of blood glucose levels included:

• the proportion of patients reported by the doctor to be diabetic or glucose intolerant who

were monitored during the follow-up period including measurement of blood glucose and

glycated haemoglobin;

• the time since last measurement reported as the mean number of days and quartiles;

• blood glucose and glycated haemoglobin levels reported as means and quartiles; and

• the proportion of patients known to be well controlled based on the dichotomous variable

for glycated haemoglobin <7%.

Smoking

A descriptive analysis of smoking interventions included:

• interventions provided and discussed during the hospital episode including the type of

health professional involved, as reported in the early patient questionnaire; and

• the proportion of patients with any counselling for smoking during the early follow-up

period.

Smoking status at early and late follow-up was described as a categorical variable including

never smoked, stopped before MI, stopped since MI, trying to stop, current smoker and missing.

Smoking cessation during the follow-up period was determined by a direct comparison of


patient reported smoking prior to the hospital admission with reported smoking status at early

and late follow-up.

Discrepancies between patient and doctor reported smoking were determined by a direct

comparison of smoking status between patient and doctor questionnaire at late follow-up.

Weight and physical activity

Self reported prevalence of these risk factors at the time of admission was examined together

with any inhospital intervention and the type of intervention provided.

3.4.6 Statistical methods

All quantitative data was entered into a Microsoft Access 2000 database and later exported to

PC-SAS Version 8e (SAS Institute Inc, Cary, NC) for statistical analysis

3.4.6.1 Descriptive analysis

Dichotomous and continuous variables were described using frequency distributions while

continuous variables were described in terms of means, standard deviation (SD), minimum,

maximum and quartiles.

3.4.6.2 Bivariate analysis

Frequency distributions for dichotomous variables were compared using the χ2 statistic or the

Fisher exact test, when n<5 in any cell. Odds ratio with 95% Confidence Intervals(OR,

95% CI) also provided a comparison between frequencies for dichotomous variables.

Ordinal categorical variables were examined for trends using a two-sided Cochrane-Armitage

test.

Unpaired Student t-test was used to compare means for continuous variables except in

comparison of time points in the subgroup of patients with complete follow-up data when the

paired t-test was used. Variance between two samples was compared using the F-test.

3.4.6.3 Multivariate analysis

Stratified analysis of dichotomous variables used the Breslow-Day χ2 test used to test for

homogeneity of the Odds Ratios.

Age was included (forced) in all logistic regression models as a categorical variable. Enrolment

period (months since January 2000) and comorbidity index were treated as continuous variables.

All other variables were treated as dichotomous variables.


All variables with p<0.10 in bivariate analysis were included in the logistic regression models.

A backward stepwise selection procedure was used to remove non-significant variables while

adjusting for age. Several factors were considered in selecting variables for removal. All

variables with Wald-test p<0.05, when adjusting for all possible confounders, were retained in

the model. No variable was removed if removing the variable significantly (p<0.05) decreased

the fit of the model as measured by the difference in the deviance (-2 log likelihood). The

c-statistic, the area under the receiver operating characteristic (ROC) curve, was used to

measure the discriminating ability of the model.

139 Chapter 4: The study sample

CHAPTER 4

THE STUDY SAMPLE

4.1 Introduction

The objective of this chapter is to describe the patient sample included in the medical record

review and the subset of patients at each phase of the study including early and late patient

follow-up, patient interview and early and late general practitioner follow-up (Figure 4.1). The

aims are two-fold. First, to describe the cohort of patients and the care received in the study

setting and then to determine the validity of the sample at each phase of data collection.

Figure 4.1: Patient participation in study

Medical record reviewn=621

Early patient surveyn=292

Eligible for late follow-upn=327

Patient interviewn=213

Early GP surveyn=238

Late patient surveyn=240

Late GP surveyn=172

Consent to contact GPn=265

Consent to contact GPn=207

Eligible for follow-upn=364



Section 4.2 describes the sample of patients included in the hospital medical record review. It

describes the cohort in terms of demographics, medical history, course of hospital episode and

drugs prescribed at discharge. These variables are examined by gender and treatment specialty.

Section 4.3 describes the follow-up cohort including patient selection, response rate, time to

follow-up, post-discharge care and current status reported by respondents to the early and late

follow-up patient questionnaire and the number of consultations during the follow-up period

reported by the general practitioners. Section 4.4 examines the internal validity of the follow-up

sample by comparing respondents and non-respondents in terms of demographics, medical

history and course of hospital episode and drugs prescribed at discharge. Post-discharge care

and current status are also compared between respondents with and without a patient interview

and without a without completed general practitioner questionnaires. The results are briefly

discussed in Section 4.5 and implications for the remainder of the analysis discussed in Section

4.6.


4.2 Baseline characteristics

Data from the medical record review were used to describe the study sample in terms of

demographics, medical history and the course of the hospital episode.

4.2.1 Demographics

The study sample consisted of 621 patients aged between 25 and 96 years. Females comprised

35% of the sample, with a significant difference in age distribution observed between males and

females (Figure 4.2). There were significant differences in basic patient demographics based on

gender and treatment specialty (Table 4.1). In addition to the age difference, females were more

likely to be a public patient. Patients treated in a cardiology unit were younger. Only 9.7% of

patients younger than 70 years were treated in a non-cardiology unit, while patients 80 years of

age and older represented only 10.9% of patients treated in a cardiology unit. Patients treated in

a cardiology unit were more likely to be males, however there was no difference in the

proportion of public patients with speciality.

Figure 4.2: Sample population by age and gender

0

10

20

30

40

50

Per

cen

t

<60 60- <70 70- <80 >=80Age

Male Female

Table 4.1: Demographics of the study cohort

All Gender Treatment Specialty

N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154

mean (SD) t-test p mean (SD) t-test p

Age 68 (14) 65 (14) 74 (13) <0.001 64 (13) 81 (8) <0.001

Percent χχχχ2 p Percent χχχχ2 p

Public Patient 79.1 75.9 85.1 0.007 78.8 79.9 0.777

Male 72.4 44.2 <0.001


4.2.2 Medical History

4.2.2.1 History of cardiovascular disease

The prevalence of cardiovascular and related diseases in the patient cohort is shown in Table

4.2. Compared with females, males had a greater prevalence of CHD defined, as either a

previous MI or CARP, but a lower prevalence of CHF or CVD. There was no difference in the

prevalence of CHD in patients treated in a cardiology unit compared to those treated in another

unit, however the prevalence of CHF, atrial fibrillation (AF) and CVD were all higher for

patients not treated in a cardiology unit. Patients treated in a cardiology unit were more likely to

have a history of hyperlipidemia compared to non-cardiology patients. No previous history of

heart disease was recorded for 49.8% of patients while 20.5% of patients had neither a history of

cardiovascular disease nor any previously diagnosed risk factor for cardiovascular disease.

Table 4.2: Prior history of heart related disease.

All Gender Treatment specialty

N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154

Heart Disease Percent χχχχ2 p Percent χχχχ2 p

IHD 38.3 38.7 37. 7 0.81 36.6 43.5 0.13

CHD 25.0 28.1 19.1 0.014 25.5 23.4 0.60

MI 20.3 21.4 18.1 0.33 20.3 20.1 0.96

CHF 11.0 7.6 17.2 <0.001 7.5 21.4 <0.001

AF 9.0 8.1 10.7 0.29 6.4 16.9 <0.001

CVD 13.0 10.8 17.2 0.025 8.6 26.6 <0.001

Risk Factors

Hypertension 47.8 45.6 52.1 0.12 47.5 48.7 0.802

Hyperlipidemia 37.5 39.9 33.0 0.09 43.5 21.4 <0.001

Diabetes 22.4 21.9 23.3 0.70 21.4 25.3 0.31

, CHD Coronary Heart Disease, MI Myocardial Infarction, CHF Congestive Heart Failure, AF Atrial Fibrillation, CVD Cerebrovascular Disease

4.2.2.2 History of cardiac procedures

Cardiac procedures prior to hospital admission are shown in Table 4.3. Revascularisation

procedures, particularly coronary artery bypass grafts, were more common in males than

females. Revascularisation procedures, in particular percutaneous coronary intervention and

cardiac angiogram were more common in patients treated in a cardiology unit.


Table 4.3: History of cardiac procedures at hospital admission


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154

χ2 p


Angiogram 11.0 12.1 8.8 0.220 13.3 3.9 0.001

CARP 11.9 15.0 6.0 0.001 13.5 7.1 0.035

CABG 8.4 10.3 4.6 0.015 9.0 6.5 0.33

PCI 4.5 5.7 2.3 0.056 5.6 1.3 0.027

4.2.2.3 Drugs on admission

The prevalence of drug use at the time of admission is shown in Table 4.4. Gender differences

were observed for calcium antagonist and diuretics, both being more prevalent among females.

A greater proportion of non-cardiology patients were using antiplatelets, ACE inhibitors, angina

medication, diuretics and antiarrhythmics, while a greater proportion of cardiology patients

were using lipid lowering therapy prior to admission.

Table 4.4: Drug use prior to hospital admission


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154


Aspirin 36.4 35.0 39.1 0.32 35.1 40.3 0.25

All antiplatelet agents 39.1 37.4 42.3 0.24 36.8 46.1 0.041

Anticoagulant 5.2 4.9 5.6 0.72 4.3 7.8 0.089

Beta-blocker 23.0 21.9 25.1 0.37 21.8 26.6 0.22

ACE inhibitor 25.0 23.4 27.9 0.22 22.5 32.5 0.013

ARB 6.0 5.4 7.0 0.44 6.0 5.8 0.94

Statin 27.9 27.3 28.8 0.69 30.4 20.1 0.014

All Lipid Lowering 28.5 28.1 29.3 0.75 31.3 20.1 0.008

Calcium Antagonists 19.7 16.8 25.1 0.012 18.6 22.7 0.27

Anti-anginal 15.3 14.8 16.3 0.62 13.1 22.1 0.007

Diuretic 18.4 15.0 24.6 0.003 14.6 29.9 <0.001

Antiarrhythmic 8.4 7.9 9.3 0.54 6.4 14.3 0.002

Hypoglycaemic 15.3 14.3 17.2 0.34 14.6 17.5 0.37

Insulin 2.7 3.0 2.8 0.91 3.6 0.6 0.055


4.2.3 Course of hospital episode

4.2.3.1 Hospital Admission

Details of the hospital stay are shown in Table 4.5. About three quarters of all patients were

discharged from the tertiary hospital. This included patients who were transferred from the

affiliate hospital to the tertiary hospital for procedures. Patients treated in the tertiary hospital

were more likely to be treated in a non-cardiology unit compared to patients in the affiliate

hospital.

Chest pain on admission was more common in males than females and more common in

patients treated in a cardiology unit. More males than females had a primary diagnosis of

myocardial infarction, as did more patients treated in a cardiology unit.

Significant differences in the length of stay were observed between cardiology and non-

cardiology patients but not between males and females. A greater proportion of non-cardiology

patients had a long hospital stay (greater than 10 days) with a median length of stay (LOS) of 5

days for cardiology patients and 9 days for non-cardiology patients.

Table 4.5: Details of hospital stay


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154


Tertiary hospital 75.5 74.6 77.2 0.48 73.2 82.5 0.021

Cardiology 75.2 83.2 60.0 <0.001 -

Chest pain at admission 65.2 71.7 53.0 <0.001 76.2 31.8 <0.001

Primary diagnosis 88.7 91.9 82.8 <0.001 96.2 66.2 <0.001

Long-stay1 21.9 21.2 23.3 0.55 16.1 39.6 <0.001 1LOS> 10 days

4.2.3.2 Type and location of myocardial infarction

Characteristics of the infarction are shown in Table 4.6. About half of all infarctions involved

an ST elevation (STEMI) and 22% were anterior in location. Women were less likely to have a

STEMI or a peak CK > 720 U/L, but there was no difference with gender in the location of the

infarction. Prevalence of STEMI, anterior infarction and peak CK > 720 U/L was higher in

cardiology patients.


Table 4.6: Characteristics of myocardial infarction.


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154


STEMI 59.1 64.0 49.8 <0.001 66.6 36.4 <0.001

Anterior MI 22.2 22.9 20.9 0.32 24.8 14.3 0.006

High-CK1 40.1 43.1 34.6 0.036 45.8 22.7 <0.001 1peak CK >720 U/L

4.2.3.3 Cardiac complications

Heart related complications recorded during the admission are listed in Table 4.7. Gender

differences were observed for CHF and pulmonary oedema, both being more frequent in

women. Non-cardiology patients had a greater prevalence of CHF, pulmonary oedema, AF and

cardiac arrest.

Table 4.7: Cardiac complications during hospital course


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154


CHF 20.9 17.5 27.4 <0.001 15.6 37.0 <0.001

Pulmonary Oedema 25.6 19.7 36.7 <0.001 20.8 40.3 <0.001

Cardiogenic shock 1.4 1.2 1.9 0.53 1.5 1.3 1.00

AF 14.2 13.0 16.3 0.27 12.0 20.8 0.007

2o Heart Block 1.3 1.5 0.9 0.56 1.1 2.6 0.24

Complete Heart Block 2.7 2.0 4.2 0.11 3.0 2.0 0.49

Ventricular Tachycardia 7.2 7.4 7.0 0.85 8.1 4.6 0.14

Ventricular Fibrillation 3.1 3.2 2.8 0.78 4.1 - 0.006

Cardiac Arrest 1.6 2.0 0.9 0.33 1.3 2.6 0.27

4.2.3.4 Hospital Investigations and procedures

Hospital investigations and procedures are shown in Table 4.8. A number of gender related

differences were observed with men more likely than women to have undergone investigations

and procedures. Invasive cardiac investigations and procedures were almost exclusively

performed in patients treated in cardiology units.


Table 4.8: Investigations and procedures during hospital admission


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154


Investigations

Angiography 45.1 53.9 28.4 <0.001 59.1 2.6 <0.001

Echocardiography 48.2 48.0 48.4 0.94 50.4 40.9 0.038

Nuclear Scan 19.0 20.2 16.7 0.30 21.8 10.4 0.002

Exercise Stress Test 12.6 15.0 7.9 0.011 16.7 - <0.001

Chest x-ray 68.0 65.8 72.1 0.11 65.5 75.3 0.024

Procedures

Thrombolysis/1° PCI 25.9 30.3 17.7 <0.001 33.4 3.2 <0.001

PCI 19.2 20.4 16.7 0.27 25.5 - <0.001

CABG 4.0 5.9 0.5 0.001 5.1 0.6 0.009

CARP 22.7 25.6 17.2 0.017 30.0 0.6 <0.001

4.2.3.5 Risk factors

Prevalence of risk factors at discharge, including new diagnosis and previous history, is shown

in Table 4.9. No risk factors were present in 10% of patients. Men were more likely to have

hyperlipidemia and to be a current smoker. The prevalence of current or ever smoking was

higher for cardiology patients. There was no difference in the prevalence of hypertension or

diabetes between the different patient groups however there was a higher prevalence of

hyperlipidemia in the cardiology patients.

Table 4.9: Risk factors documented during admission


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=152

Biomedical risk factors Percent χχχχ2 p Percent χχχχ2 p

Hypertension 52.0 49.8 56.3 0.122 52.5 50.6 0.696

Hyperlipidemia 53.1 57.1 45.6 0.006 62.5 26.0 <0.001

Diabetes 27.9 28.1 27.4 0.866 28.5 26.0 0.548

Smoking

Smoker 20.6 24.9 12.6 <0.001 25.0 7.1 <0.001

Ex-smoker 33.8 40.2 21.9 <0.001 38.5 19.5 <0.001

Never Smoked 45.6 35.0 65.6 <0.001 36.4 73.4 <0.001


4.2.3.6 Comorbidity Index

The distribution of the modified Charlson comorbidity index is shown in Table 4.10. There was

no difference in the mean comorbidity index with gender, however there was a trend for females

to have a higher comorbidity index. The mean comorbidity index was greater for non-

cardiology patients compared to cardiology patients, with 65% of cardiology patients having no

comorbidity compared with 35% of non-cardiology patients.

Table 4.10: Mean and distribution of comorbidity index


N=621

Male

N=406

Female

N=215

Cardiology

N=467

Other

N=154

Mean (SD) t-test p Mean (SD) t-test p

0.8 (1.5) 0.8 (1.5) 0.9 (1.4) 0.510 0.6 (1.2) 1.5 (1.9) <0.001

Index Percent Trend p Percent Trend p

0 57.6 60.6 52.1 65.1 35.1

1 25.0 22.9 28.8 23.3 29.9

2 8.4 8.1 8.8 6.6 13.6

≥3 9.0 8.4 10.2 4.9 21.4

0.011 <0.001


4.3 Follow-up cohort

4.3.1 Patient selection

Reasons for excluding patients from the follow-up study are shown in Table 4.11. Of the 621

post-MI patients with a medical record review available 364 were included.

Table 4.11: Reasons for exclusion from follow-up

N

Elderly (>80 years) 144

Serious illness 46

Non-metropolitan 27

Non English Speaking Background 22

Mental Health Issues 11

Deceased prior to early follow-up 4

Other 3

Total exclusions 257

Of the 364 patients in the initial follow-up, 327 (90%) were included in the late follow-up.

Reasons for not including patients in the late follow-up included 17 patients who previously

indicated they did not wish to participate, 11 deceased patients, and 9 patients who were unable

to be contacted at the time of the early follow-up.

4.3.2 Response rate

Response rates to the follow-up questionnaires were 80% (292/364) and 76% (240/327) for the

early and late follow-up respectively. Responses to the late follow-up included 223 patients

who had returned the early questionnaire (80% response rate) and 17 patients who had not

returned the early questionnaire (50% response rate). Reasons for not returning questionnaires

in both surveys are shown in Table 4.12.

Table 4.12: Reasons for non-response to follow-up

Early Late

Unwell 14 0

Not interested 17 12

Leave it with them 17 24

Unable to make contact 24 51

Total 72 87



Of the 292 patients who returned the early follow-up questionnaires 213 (73%) had an

interview. Reasons for not having an interview are shown in Table 4.13.

Table 4.13: Reason for no patient interview

Not interested 60

Unable to contact 11

Cancelled appointment 4

Not at home 1

76

4.3.2.2 GP questionnaire

Of the 292 patients completing the early follow-up questionnaire 265 (91%) provided details

about their general practitioner and consented to them being contacted. Of the 241 patients

completing the late follow-up questionnaire 207 (86%) provided details of the general

practitioner and consented to their being contacted.

The response rate to the early and late general practitioner questionnaire was 90% (238/265) and

83% (172/207) respectively.

4.3.3 Time to follow-up

The time lag from hospital discharge to completion of the questionnaire is shown in Table 4.14.

Most early follow-up questionnaires were completed within four months of hospital discharge

while all late follow-up questionnaires were completed more than 12 months after discharge.

Table 4.14: Time from discharge to completion of patient questionnaire

Mean Quartiles

(days) 25% Median 75%

Early follow-up 109 95 106 123

Late follow-up 391 378 387 400

The mean time from hospital discharge to completion of the to general practitioner

questionnaire was 139 days (range 82-282 days) for early follow-up and 426 days (range 380-

587 days) for the late follow-up.

Table 4.15: Time from discharge to completion of GP questionnaire

N Mean (SD) Quartiles

25% Median 75%

Early follow-up 238 139 (32) 119 132 155

Late follow-up 172 426 (32) 404 419 442


The time lag between completion of the patient and doctor questionnaires are shown in Table

4.16. Half of all general practitioner questionnaires were returned within one month of the

patient completing the follow-up questionnaire.

Table 4.16: Time lag from patient to doctor questionnaire

N Mean (SD) Percentiles

25% Median 75%

Early follow-up 238 29 (26) 16 22 34

Late follow-up 172 37 (28) 20 28 43

4.3.4 Post-discharge care

This section describes the care received after the initial hospital episode by respondents to the

patient follow-up surveys.

4.3.4.1 Cardiac rehabilitation

Attendance at cardiac rehabilitation as either an inpatient or outpatient is shown in Table 4.17.

More than 60% of respondents attended no group education sessions, 12% attended an exercise

program and about one fifth of respondents received a telephone call from the hospital within

the first couple of weeks after discharge.

Table 4.17: Inhospital or post-discharge cardiac rehabilitation

Percent (n)

Group sessions attended

Exercise program 11.6 (34)

Information session about heart disease 24.7 (72)

Information session about risk factors 15.1 (44)

Information session about medications 8.2 (24)

Information session about diet 14.0 (41)

Information session about stress management 12.7 (37)

No sessions 61.6 (180)

Follow-up phone call 19.2 (56)

4.3.4.2 Consultations with health professionals

During the early follow-up period most patients had consulted their general practitioner and

81% reporting seeing a cardiologist, but very few patients had been seen by an allied health

professional since discharge.


Table 4.18: Early follow-up consultations

Percent (n)

Cardiologist 80.8 (236)

Doctor in Outpatients Clinic 20.2 (59)

General Practitioner 83.9 (245)

Dietician 4.4 (13)

Physiotherapist 5.5 (16)

Social Worker 2.4 (7)

Occupational Therapist 3.8 (11)

Cardiac Rehabilitation nurse 4.1 (12)

No one 1.0 (3)

At the late follow-up, 27% (64) of respondents reported seeing a cardiologist within the

previous 3 months and a 24% (58) within the previous 6 months. Of the remainder, 28.8% (69)

had seen a cardiologist since discharge but not within the previous 6 months, and, as at early

follow-up, 20%(64) had not seen a cardiologist since the initial discharge.

Cardiac related healthcare received since the index hospital discharge is shown in Table 4.19.

At the time of the early follow-up about three quarters of all respondents had undergone some

cardiac related tests since discharge with 36% having an invasive cardiac procedure. Almost

one half of respondents had been readmitted to hospital, most for cardiac related reasons. At the

time of the late follow-up these proportions were very similar suggesting that most tests and

procedures were conducted early in the follow-up period.

Table 4.19: Healthcare since index admission

Follow-up

Early Late

Tests Echocardiogram 28.8 (84) 29.2 (70)

Exercise test 33.6 (98) 37.9 (91)

Nuclear Scan 17.5 (51) 15.4 (37)

ECG 48.3 (141) 51.2 (123)

No test 26.7 (78) 29.6 (71)

Procedures Angiogram 21.2 (62) 21.2 (51)

PTCA 10.6 (31) 12.9 (31)

CABG 6.8 (20) 6.7 (16)

Other heart surgery 0.7 (2) 1.2 (3)

No procedures 64.0 (187) 67.1 (161)

Hospital admission Readmission 45.9 (134) 37.5 (90)

Heart related readmission 39.7 (116) 24.6 (59)

Reinfarction 6.7 (16)


4.3.4.3 Patient - general practitioner interaction

Patient responses to the general practitioner satisfaction questionnaire are shown in Table 4.20.

While the level of satisfaction was generally high, the lowest levels of satisfaction were noted

for aspects of the patient-doctor interaction related to discussion of treatment options, patient

encouragement to ask questions and explanations about health problems and what to expect in

the future.

Table 4.20: Patient satisfaction with patient-provider interaction

How is your general practitioner at… Excellent Very

Good

Good Fair Poor Can’t

say

Treating you like you’re on the same level;

not ” talking down” to you or treating you

like a child

59.6 26.7 8.9 2.4 0.3 2.0

Letting you tell your story; listening

carefully; asking thoughtful questions; not

interrupting while you’re talking

53.1 30.8 9.2 4.4 0 2.4

Discussing options with you; asking your

opinion; offering choices and letting you

help decided what to do; asking what you

think before telling you what to do

40.1 28.7 16.4 5.8 3.8 5.1

Encouraging you to ask questions;

answering them clearly; not avoiding the

questions or lecturing you

43.8 27.7 14.7 5.8 4.1 3.8

Explaining what you need to know about

your problems; how and why they occurred

and what to expect next

43.2 27.7 13.7 8.2 3.4 3.8

Using words you can understand when

explaining your problems and treatments;

explaining any technical and medical terms

in plain language

48.3 32.9 13.0 2.4 1.0 2.4


4.3.4.4 Information about medications

At the late follow-up patients overwhelmingly nominated their doctor as the main source of

information about their medications (Table 4.21).

Table 4.21: Providers of information about medications

Percent (N)

My Doctor 75.0 (180)

My Pharmacist 8.8 (21)

Hospital 8.8 (21)

Information inside packet 4.2 (10)

Other 1.7 (4) Internet, Heart study clinic, Library – medical books

4.3.5 Current status

This section describes the status of respondents at the time of each survey and includes a

comparison of health status at early and late follow-up for respondents to both surveys.

4.3.5.1 Current medications

Current cardiac related medications reported by patients are shown in Table 4.22. Use of

secondary prevention therapies is covered in detail in Chapter 7.

Table 4.22: Medications reported at follow-up

Early

N=292

Late

N=240

Drug class Percent (n)

Aspirin 85.6 (250) 84.2 (202)

All Antiplatelets 89.7 (262) 89.6 (215)

Beta-blockers 75.7 (221) 72.5 (174)

Lipid lowering therapy 86.0 (251) 85.8 (206)

ACE inhibitors 62.3 (182) 61.7 (148)

Calcium antagonist 14.4 (42) 13.8 (33)

Angiotensin receptor blockers 6.2 (18) 7.5 (18)

Anticoagulant 8.9 (26) 8.3 (20)

Diuretic 23.9 (70) 27.1 (65)

Antiarrhythmic 9.2 (27) 10.0 (24)

Diabetic medication 21.6 (63) 25.8 (62)

Angina medication 38.4 (112) 33.8 (81)


4.3.5.2 Smoking status

Of the 90 respondents who reported smoking at the time of the index admission, 44 (49%)

subsequently reported stopping (Table 4.23). This was maintained at late follow-up with 30 of

58 smokers (52%) reporting that they had stopped smoking.

Table 4.23: Smoking status at follow-up

Follow-up

Early Late

Percent (n)

Never smoked 28.8 (84) 27.9 (67)

Stopped before MI 38.0 (111) 45.8 (110)

Stopped since MI 15.1 (44) 12.5 (30)

Trying to stop 9.2 (27) 6.2 (15)

Smoking 6.5 (19) 5.4 (13)

Missing 2.4 (7) 2.1 (5)

4.3.5.3 General health

Respondents’ rating of their health compared to 12 months ago (health transition) is shown in

Figure 4.3. At the early follow-up, health was most frequently described as about the same or

somewhat worse than a year before, while at late follow-up, health was most frequently

described as about the same or better than 12 month ago.

Figure 4.3: Patient perception of health compared to 12 months ago

0

10

20

30

40

Percent

Much better Somewhat better Same Somewhatworse

Much worse

Early Late

In a direct comparison of responses for respondents to both early and late surveys, 45% scored

higher and 13% scored lower at late compared with early follow-up (Table 4.24).

Table 4.24: Changes in health transition

N Early Late Mean (SD) t-test p Lower Higher

Mean Difference Percent

Health transition 218 3.1 2.4 -0.67 (1.28) <0.001 45.9 13.3


Results from the remaining SF-36 (Version 2) items are shown in Table 4.25.

Table 4.25: SF-36 Item mean scores

Early

N=292

Late

N=240

Domain Mean (SD)

Physical functioning 67.1 (26.8) 70.2 (26.0)

Role physical 59.5 (31.5) 66.4 (31.3)

Bodily pain 69.8 (27.2) 72.0 (26.4)

General health 59.4 (22.4) 59.2 (26.4)

Vitality 51.2 (22.1) 53.7 (21.8)

Social functioning 73.2 (27.7) 75.0 (27.2)

Role emotional 73.1 (31.2) 76.3 (28.8)

Mental health 70.1 (20.5) 72.9 (19.5)

Direct comparison of responses between the two surveys for respondents to both early and late

surveys showed a significant difference for Role Physical, which improved from the early to

late survey (Table 4.26). Generally more respondents scored higher at late follow-up compared

to the proportion of patients who scored lower.

Table 4.26: Differences in SF-36 scores between surveys

Difference Higher Lower

Domain N mean (SD) t-test p Percent

Physical Functioning 216 1.7 (22.0) 0.266 24.5 16.2

Role Physical 208 6.9 (25.1) <0.001 38.9 17.8

Bodily Pain 209 2.8 (26.8) 0.129 32.5 25.8

General Health 215 -1.4 (16.4) 0.228 27.9 22.8

Vitality 214 1.7 (18.6) 0.188 35.0 26.6

Social Functioning 215 -0.3 (24.9) 0.864 29.8 29.3

Role Emotional 206 1.4 (31.4) 0.512 26.7 23.3

Mental Health 213 0.8 (17.6) 0.484 21.6 18.8


4.3.5.4 Heart failure

The degree of shortness of breath related to the heart is shown Table 4.27. Direct comparison of

between the two surveys for responders to both surveys showed that 26% (56) reported

deterioration of heart function and 33% (71) reported an improvement (Table 4.28).

Table 4.27: Shortness of breath related to the heart

Follow-up

Early

N=292

Late

N=240

Not at all 36.3 (106) 35.4 (85)

Only with strenuous effort 32.5 (95) 35.0 (84)

Only with normal exertion 14.7 (43) 15.4 (37)

On mild exertion 9.6 (28) 8.8 (21)

Even at rest 6.5 (19) 2.9 (7)

Missing (1) 2.5 (6)

Table 4.28: Differences in shortness of breath between surveys

Rating at late follow-up

Same

N=89

Better

N=71

Worse

N=56

Difference

Rating at early follow-up Percent Mean (SD)

Not at all 55.7 - 44.3 -0.63 (0.89)

Only with strenuous effort 45.2 38.4 16.4 0.14 (0.90)

Only with normal exertion 24.2 54.6 21.2 0.42 (0.94)

On mild exertion 5.6 83.3 11.1 1.17 (1.04)

Even at rest 23.4 76.9 - 1.69 (1.38)

4.3.5.5 Angina

Use of angina medication and chest pain within the previous four weeks is shown in Table 4.29.

Less respondents at late follow-up reported chest pain within the last four weeks, although more

patients at late follow-up reported use of angina medications.

Table 4.29: Angina medication use and chest pain.

Early follow-up

N=292

Late follow-up

N=240

Percent (n) χχχχ2 test p

Any medication 21.6 (63) 47.1 (113) <0.001

Non-glyceryl trinitrate (GTN) 10.3 (30) 13.0 (32) 0.246

Chest pain, last 4 weeks 34.0 (100) 25.4 (61) 0.027


Results of the SAQ are shown in Table 4.30 for all respondents reporting angina in the previous

four weeks. Direct comparison of responses between the two surveys for responders to both

surveys showed a significant worsening in Physical Limitation among respondents to both

surveys (Table 4.31).

Table 4.30: Mean scores for each component of SAQ

Early

N=100

Late

N=61

Mean (SD)

Physical Limitation 62.3 (25.2) 53.0 (20.0)

Angina Stability 56.4 (31.8) 51.3 (28.5)

Angina Frequency 63.6 (22.1) 65.9 (20.4)

Treatment Satisfaction 80.6 (20.0) 79.5 (17.1)

Disease Perception 55.4 (23.8) 59.0 (24.0)

Table 4.31: Differences in SAQ scores between surveys

Difference Higher Lower

N Mean t-test p Percent

Physical Limitation 42 -7.0 0.016 14.3 33.3

Angina Stability 43 -7.6 0.261 30.2 44.2

Angina Frequency 44 -0.9 0.800 13.6 22.7

Treatment Satisfaction 41 -3.0 0.226 12.2 22.0

Disease Perception 44 0 1.00 27.3 27.3

4.3.5.6 Social factors

Factors related to living and working arrangements are shown in Table 4.32. This shows that

80% of respondents were living within the family and 25% were working full-time. About one

third of respondents to each survey reported working less than 12 months ago with half as many

reporting working more at the late follow-up compared with 12 months before.

Table 4.32: Sociodemographic factors at follow-up

Early

N=292

Late

N=240

Percent (n)

Living with family 81.2 (237) 80.4 (189)

Working

Working full-time 25.0 (73) n/a

Working more 1.7 (5) 14.2 (34)

Working less 32.5 (95) 39.6 (95)


4.3.6 General practitioner consultations

Table 4.33 shows the number of patient visits reported by the general practitioner. At the early

follow-up, 4 doctors reported that they had not seen the patient at all while 4 reported seeing the

patient 16 times or more. At late follow-up, one doctor reported not seeing the patient at all and

8 reported seeing the patient 27 times or more since the myocardial infarction.

Table 4.33: Number of visits to general practitioner

N Mean (SD) Percentiles

25% Median 75%

Early follow-up 226 5.6 (4.0) 3 5 7

Late follow-up 157 12.3 (8.7) 6 10 16

The frequency of visits to the general practitioner decreased by the late follow-up so that the

number of days between visits had increased to a mean of 60 days at the late follow-up

compared with 41 days at the early follow-up.

Table 4.34: Days between visits

Percentiles

N Mean (SD) 25% Median 75%

Early follow-up 222 41.0 (38.2) 19 28 44

Late follow-up 156 58.9 (63.6) 25 42 70


4.4 Sample validity

This section compares patient characteristics and responses between responders and non-

responders to the patient questionnaires, patient interviews and the availability of general

practitioner questionnaires.

4.4.1 Patient questionnaires

Characteristics of responders and non-responders are compared in Table 4.35. Several

differences were noted. Generally responders were older and had less comorbidity. In

particular, patients responding to the late follow-up were significantly older and were

significantly less likely to have been smokers at the time of infarction. Over 90% of patients

included in the follow-up were treated in a cardiology unit, with no difference between

responders and non-responders. Prescription of drugs at discharge was also very high and

similar between the two groups.


Table 4.35: Comparison of responders and non-responders to the patient surveys

Early follow-up Late follow-up

N=292 N=72 N=240 N=87

Means t-test p Means t-test p

Age 62.6 59.6 0.090 63.4 55.6 <0.001

Comorbidity index 0.4 0.6 0.060 0.4 0.3 0.052


Male 77.7 66.7 0.050 77.5 74.7 0.60

Public patient 80.5 80.6 0.99 78.8 85.1 0.20

Previous MI 16.4 30.6 0.006 15.4 24.1 0.068

Previous CHD 21.6 33.3 0.036 20.4 26.4 0.25

Diabetes 22.6 37.5 0.009 25.4 21.8 0.51

Hypertension 48.0 59.7 0.073 50.8 46.0 0.44

Hyperlipidemia 65.8 65.3 0.94 64.6 67.8 0.59

Heart Failure 20.6 26.4 0.28 21.7 18.4 0.52

Smoker 27.4 31.9 0.44 22.9 44.8 <0.001

Tertiary Hospital 74.7 73.6 0.86 74.6 72.4 0.69

Cardiology 94.5 90.3 0.18 94.2 95.4 0.66

Anterior MI 23.3 22.2 0.85 25.0 24.1 0.87

STEMI 66.4 66.7 0.97 67.5 69.0 0.80

High CK1 44.9 37.5 0.26 45.8 46.0 0.98

Reperfusion 32.2 30.6 0.79 33.8 28.7 0.39

Angiogram 64.7 62.5 0.72 66.2 64.4 0.75

CARP 33.2 27.8 0.38 35.4 31.0 0.46

Cardiologist follow-up 67.1 68.1 0.88 69.2 64.4 0.41

Discharge medications

Antiplatelet agents 94.2 88.9 0.11 93.8 93.1 0.83

Beta-blockers 82.9 86.1 0.50 85.0 82.8 0.62

Statins 82.2 84.7 0.61 82.1 85.1 0.53

ACE inhibitor 61.6 56.9 0.46 60.8 58.6 0.72

Calcium antagonist 13.0 13.9 0.84 12.1 12.6 0.89 1peak CK>720 U/L

4.4.2 Patient interviews

This section compares the group of patients with an interview with other patients participating

in the early follow-up with no patient interview in terms of medical history and the hospital

episode from the medical record review, post-discharge care and current status from the early

patient follow-up.


4.4.2.1 Previous history and hospital episode

Interviewed patients were less likely to have prior history of myocardial infarction and were

more likely to have been treated in a cardiology unit and to have undergone an angiogram than

non-interviewed patients (Table 4.36). There was no difference in the proportion of patients

with follow-up appointments with cardiologists or in the drugs prescribed at discharge.

Table 4.36: Comparison of interviewed and non-interviewed patients

Interview

N=213

No interview

N=79

Mean (SD) t-test p

Age 62.6 (11.2) 62.6 (11.6) 0.994

Comorbidity index 0.39 (0.74) 0.42 (0.90) 0.787

Percent (n) OR (95% CI) χχχχ2 p

Male 77.9 (166) 77.2 (61) 1.04 (0.56-1.93) 0.90

Public patient 79.3 (169) 83.5 (66) 0.76-(0.38-1.49) 0.42

Medical history

Comorbidity index>0 28.2 (60) 29.1 (23) 0.95 (0.54-1.69) 0.87

Previous MI 13.2 (28) 25.3 (20) 0.45 (0.23-0.85) 0.013

Previous CHD 18.8 (40) 29.1 (23) 0.56 (0.31-1.02) 0.056

Diabetic 21.1 (45) 26.6 (21) 0.74 (0.41-1.34) 0.32

Hypertension 49.3 (105) 44.3 (35) 1.22 (0.73-2.05) 0.45

Hyperlipidemia 65.7 (140) 65.8 (52) 1.00 (0.58-1.72) 0.99

Heart Failure 19.7 (42) 22.8 (18) 0.83 (0.44-1.55) 0.56

Smoker 28.2 (60) 25.3 (20) 1.16 (0.64-2.08) 0.63

Hospital episode

Tertiary Hospital 77.0 (164) 68.4 (54) 0.64 (0.36-1.14) 0.13

Cardiology 96.7 (206) 88.6 (70) 3.78 (1.36-10.54) 0.007

Anterior MI 22.1 (47) 26.6 (21) 0.78 (0.43-1.42) 0.42

STEMI 66.7 (142) 65.8 (52) 1.04 (0.60-1.79) 0.89

High-CK1 45.1 (96) 44.3 (35) 1.03 (0.61-1.73) 0.91

Reperfusion 33.8 (72) 27.8 (22) 1.32 (0.75-2.33) 0.33

Angiogram 68.1 (145) 55.7 (44) 1.70 (1.00-2.88) 0.049

CARP 34.3 (73) 30.4 (24) 1.19 (0.68-2.08) 0.53

Cardiologist follow-up 67.1 (143) 67.1 (53) 1.00 (0.58-1.74) 0.99

Discharge medications

Antiplatelets 94.4 (201) 93.7 (74) 1.13 (0.38-3.32) 0.78

Beta-blockers 82.6 (176) 83.5 (66) 0.94 (0.47-1.87) 0.85

Lipid lowering therapy 81.7 (174) 83.5 (66) 0.88 (0.44-1.75) 0.71

ACE inhibitor 59.2 (126) 68.4 (54) 0.67 (0.39-1.16) 0.15

Calcium antagonist 12.7 (27) 13.9 (11) 0.90 (0.42-1.91) 0.78 1 peak CK>720 U/L


4.4.2.2 Post-discharge care

Interview patients were less likely to have attended no cardiac rehabilitation sessions but there

were no differences in consultations, tests and procedures (Table 4.37).

Table 4.37: Comparison of post-discharge care by patient interview

Interview

N=213

No interviewed

N=79

Percent (n) χχχχ2 p

Exercise program 11.3 (24) 12.7 (10) 0.74

Information session Heart disease 26.8 (57) 19.0 (15) 0.17

Risk factors 17.4 (37) 8.9 (7) 0.071

Medications 8.0 (17) 8.9 (7) 0.81

Diet 15.5 (33) 10.1 (8) 0.24

Stress management 13.2 (28) 11.4 (9) 0.69

None 57.3 (122) 73.4 (58) 0.012

Phone call 19.2 (41) 19.0 (15) 0.82

Follow-up Cardiologist 81.2 (173) 79.8 (63) 0.78

Doctor in Outpatients Clinic 19.7 (42) 21.5 (17) 0.73

General Practitioner 85.4 (182) 79.8 (63) 0.24

Dietician 4.7 (10) 3.8 (3) 0.741

Physiotherapist 6.1 (13) 3.8 (3) 0.571

Social Worker 1.9 (4) 3.8 (3) 0.391

Occupational Therapist 3.8 (8) 3.8 (3) 1.001

Cardiac Rehabilitation nurse 3.8 (8) 5.1 (4) 0.741

None 0.9 (2) 1.3 (1) 1.001

Tests Echocardiogram 27.2 (58) 32.9 (26) 0.34

Exercise test 32.9 (70) 35.4 (28) 0.68

Nuclear Scan 17.4 (3&0 17.7 (14) 0.94

ECG 48.4 (103) 48.1 (38) 0.97

No test 27.7 (59) 24.0 (19) 0.53

Procedures Angiogram 21.1 (45) 21.5 (17) 0.94

PTCA 10.8 (23) 10.1 (8) 0.87

CABG 8.4 (18) 2.5 (2) 0.0751

Other heart surgery 0.94 (2) (0) 1.001

No procedures 63.4 (135) 65.8 (52) 0.701

Hospital Readmission 49.3 (105) 36.7 (29) 0.055

Heart related readmission 42.7 (91) 31.6 (25) 0.086 1 Fishers exact test (expected n<5)


Similarly, there was no difference in the proportion with less than optimal satisfaction of the

patient-provider interaction between interviewed and non-interviewed patients (Table 4.38).

Table 4.38: Comparison of patient-provider interaction by patient interview

Interview

N=213

No interview

N=79


Treating you like you’re on the same level; not ” talking

down” to you or treating you like a child 11.0 (23) 14.5 (11) 0.42

Letting you tell your story; listening carefully; asking

thoughtful questions; not interrupting while you’re talking 13.4 (28) 15.8 (12) 0.61

Discussing options with you; asking your opinion;

offering choices and letting you help decided what to do;

asking what you think before telling you what to do

26.6 (54) 29.7 (22) 0.61

Encouraging you to ask questions; answering them

clearly; not avoiding the questions or lecturing you 26.3 (54) 23.7 (18) 0.65

Explaining what you need to know about your problems;

how and why they occurred and what to expect next 26.7 (55) 25.3 (19) 0.82

Using words you can understand when explaining your

problems and treatments; explaining any technical and

medical terms in plain language

16.8 (35) 17.1 (13) 0.94

4.4.2.3 Current status

Table 4.39 compares drug use reported by patients in the early follow-up questionnaire. As with

drugs at discharge there were no significant differences in the use of drugs at early follow-up in

patients with and without an interview.

Table 4.39: Comparison of drug use by patient interview.

Interview

N=213

No interview

N=79


Aspirin 85.4 (182) 86.1 (68) 0.89

Other antiplatelet 8.0 (17) 5.1 (4) 0.391

Antiplatelet 90.1 (192) 88.6 (70) 0.70

Beta-blocker 77.0 (164) 72.2 (57) 0.39

Lipid lowering therapy 86.4 (184) 86.1 (68) 0.94

ACE inhibitor 61.5 (131) 64.6 (51) 0.63

Calcium antagonist 16.9 (36) 8.9 (7) 0.085 1 Fishers exact test (expected n<5)


Smoking prevalence at early follow-up between interviewed (16.9%) and non-interviewed

(12.7%) patients was similar.

Table 4.40 shows the proportion of patients to score high (>1 SD above the mean) and low (>1

SD below the mean) for each domain in the SF-36. Interviewed patients were more likely to

have a high score for the Physical Functioning (OR 2.06; 95% CI 0.99-4.30) and General Health

(OR 2.05; 95% CI 1.01-4.16) domains compared to non- interviewed patients.

Table 4.40: Comparison of SF36 scores by patient interview

High1 score Low2 score

Interview

N=213

No interview

N=79

Interview

N=213

No interview

N=79

Percent (n) χχχχ2 p Percent (n) χχχχ2 p

Domain

Health Transition 7.5 (16) 8.9 (7) 0.70 13.6 (29) 10.1 (8) 0.43

Physical Functioning 23.0 (49) 12.7 (10) 0.050 21.1 (45) 24.0 (19) 0.59

Role Physical 23.5 (50) 21.5(17) 0.72 23.5 (50) 27.8 (22) 0.44

Bodily Pain 29.6 (63) 26.6 (21) 0.62 25.4 (54) 21.5 (17) 0.50

General Health 24.9 (53) 13.9 (11) 0.044 23.5 (50) 17.7 (14) 0.29

Vitality 21.3 (45) 16.5 (13) 0.37 16.9 (36) 17.7 (14) 0.87

Social Functioning (0) (0) - 17.8 (38) 17.7 (14) 0.98

Role Emotional (0) (0) - 23.9 (51) 26.6 (21) 0.64

Mental Health 13.2 (28) 8.9 (7) 0.32 14.6 (31) 17.7 (14) 0.50 1more than 1SD above the mean, 2more than 1SD below the mean

There was also a significant difference in the prevalence of shortness of breath on mild exertion

or rest between interviewed and non-interviewed patients (13.2% versus 24.1%, p=0.02), with a

corresponding odds ratio of 0.48 (95% CI 0.25 to 0.92).

There was no difference in the proportion of patients reporting chest pain, or using anti-anginal

medications (Table 4.41)

Table 4.41: Comparison of antianginal medications by patient interview

Interview

N=213

No interview

N=79


Any medication 23.0 (49) 17.7 (14) 0.33

Non-GTN 11.3 (24) 7.6 (6) 0.36

Chest pain, last 4 weeks 37.1 (79) 29.1 (23) 0.20

Interviewed patients were more likely to be living with family and less likely to be working full-

time than non-interviewed patients.


Table 4.42: Comparison of social factors by patient interview

Patient interview

Yes

N=213

No

N=79


Living with family 84.0 (179) 73.4 (58) 0.039

Working fulltime 21.6 (46) 34.2 (27) 0.027

Working more 2.4 (5) (0) 0.33

Working less 34.3 (73) 27.8 (22) 0.28

4.4.3 GP questionnaires

This section compares patients with and without complete GP questionnaires.

4.4.3.1 Previous history and hospital episode

In terms of baseline characteristics, the two groups of patients were generally comparable

patients although there were several statistically significant differences noted (Table 4.43).

These differences included ST-elevation at the early follow-up and public patients and anterior

infarction at the late follow-up.

4.4.3.2 Post-discharge care

Patients not consulting their general practitioner within the first few months were less likely to

have a GP questionnaire returned. (Table 4.44). There were no other differences, in either

cardiac rehabilitation or consultation of health professions. Nor were there any differences in

test and procedures since discharge at either early or late follow-up (Table 4.45). There was no

association between time since last cardiologist consultation or attendance at an outpatient

cardiac clinic and response to later follow-up by general practitioner (trend p=0.516).

There was also no association between doctors responding to the questionnaire and monitoring

of cholesterol (trend p=0.820) and blood pressure (trend p=0.746) reported by the patients in the

late questionnaire. There were however several marginal differences in the prevalence of less

than optimal responses (good/fair/poor) to questions about the patient-provider relationship with

non-responders more likely to have a lower score (Table 4.46)


Table 4.43: Patient characteristics by availability of GP questionnaire


GP questionnaire GP questionnaire

Yes No Yes No

N=238 N=54 N=172 N=69

Mean (±SD) t-test p Mean (±SD) t-test p

Age 63.1 (11.2) 60.3 (11.6) 0.098 63.9 (10.6) 62.1 (10.6) 0.23

Comorbidity index 0.3 (0.6) 0. 7 (1.2) 0.062 0.4 (0.6) 0.6 (0.9) 0.12


Male 76.0 (181) 85.2 (46) 0.14 79.1 (136) 73.9 (51) 0.38

Public patient 79.0 (188) 87.0 (47) 0.18 75.0 (129) 88.4 (61) 0.021

Medical history

Previous MI 16.0 (38) 18.5 (10) 0.65 15.7 (27) 15.9 (11) 0.96

Previous CHD 21.4 (51) 22.2 (12) 0.90 21.5 (37) 18.8 (13) 0.64

Diabetic 21.0 (50) 29.6 (16) 0.17 25.0 (43) 27.5 (19) 0.68

Hypertension 48.7 (116) 44.4 (24) 0.57 51.7 (89) 47.8 (33) 0.58

Hyperlipidemia 66.0 (157) 64.8 (35) 0.87 64.0 (110) 66.7 (46) 0.69

Heart failure 19.8 (47) 24.1 (13) 0.48 21.5 (37) 21.7 (15) 0.97

Smoker 25.2 (60) 37.0 (20) 0.078 21.5 (37) 26.9 (18) 0.44

Hospital episode

Tertiary Hospital 75.6 (180) 70.4 (38) 0.42 76.7 (132) 69.6 (48) 0.25

Cardiology 95.0 (226) 92.6 (50) 0.49 94.2 (162) 94.2 (65) 1.00

Anterior MI 23.5 (56) 22.2 (12) 0.84 20.9 (36) 34.8 (24) 0.025

STEMI 69.3 (165) 53.7 (29) 0.028 66.9 (115) 69.6 (48) 0.68

High-CK1 46.2 (110) 38.9 (21) 0.33 44.2 (76) 49.3 (34) 0.47

Reperfusion 32.4 (77) 31.5 (17) 0.90 32.6 (56) 36.2 (25) 0.58

Angiogram 66.0 (157) 59.3 (32) 0.35 66.3 (114) 66.7 (46) 0.95

CARP 34.4 (82) 27.8 (15) 0.35 36.0 (62) 34.8 (24) 0.85

Cardiology follow-up 68.1 (162) 63.0 (34) 0.47 66.9 (115) 73.9 (51) 0.28

Discharge drugs

Antiplatelets 95.0 (226) 90.7 (49) 0.23 93.6 (161) 94.2 (65) 1.00

Beta-blockers 83.6 (199) 79.6 (43) 0.48 86.0 (148) 81.2 (56) 0.34

Statins 81.5 (194) 85.2 (46) 0.52 82.6 (142) 81.2 (56) 0.80

ACE inhibitor 59.2 (141) 72.2 (39) 0.078 59.9 (103) 62.3 (43) 0.73

Calcium antagonist 12.6 (30) 14.8 (8) 0.66 13.4 (23) 8.7 (6) 0.31 1peak creatine kinase >720 U/L


Table 4.44: Care in early follow-up period by availability of GP questionnaire

GP questionnaire

Yes

N=238

No

N=54

Cardiac rehabilitation Percent (n) χχχχ2 p

Exercise program 12.2 (29) 9.3 (5) 0.54

Information session about heart disease 24.8 (59) 24.1 (13) 0.91

Information session about risk factors 14.3 (340 18.5 (10) 0.43

Information session about medications 8.4 (20) 7.4 (4) 0.81

Information session about diet 14.3 (34) 13.0 (7) 0.80

Information session about stress management 12.6 (30) 13.0 (7) 0.94

No sessions 60.1 (143) 68.5 (37) 0.25

Follow-up phone call 28.6 (68) 25.9 (14) 0.70

Health professionals

Cardiologist 82.4 (196) 74.1 (40) 0.16

Doctor in Outpatients Clinic 19.3 (46) 24.1 (13) 0.43

General Practitioner 86.6 (206) 72.2 (39) 0.010

Dietician 4.6 (11) 3.7 (2) 0.771

Physiotherapist 5.9 (14) 3.7 (2) 0.741

Social Worker 2.1 (5) 3.7 (2) 0.621

Occupational Therapist 4.2 (10) 1.8 (2) 0.411

Cardiac Rehabilitation nurse 4.2 (10) 3.7 (2) 1.001

No one 0.42 (1) 3.7 (2) 0.0311 1 Fishers exact test (expected n<5)


Table 4.45: Tests and procedures by availability of GP questionnaire



Yes

N=238

No

N=54

Yes

N=178

No

N=70


Tests

Echocardiogram 26.9 (64) 37.0 (20) 0.14 24.2 (43) 40.0 (28) 0.13

Exercise test 32.4 (77) 38.9 (21) 0.36 36.0 (64) 40.0 (28) 0.55

Nuclear Scan 16.0 (38) 24.1 (13) 0.16 15.2 (27) 15.7 (11) 0.91

ECG 47.9 (114) 50.0 (27) 0.78 50.6 (90) 51.4 (36) 0.90

No test 27.3 (65) 24.1 (13) 0.63 32.6 (58) 24.3 (17) 0.20

Procedures

Angiogram 21.4 (51) 20.4 (11) 0.86 20.2 (36) 22.9 (16) 0.65

PTCA 10.1 (24) 13.0 (7) 0.54 12.9 (23) 11.4 (8) 0.75

CABG 5.9 (14) 11.1 (6) 0.23 6.2 (11) 8.6 (6) 0.58

Other heart surgery 0.84 (2) (0) 1.00 (0) 4.3 (3) 0.022

No procedures 65.1 (155) 59.3 (32) 0.42 68.5 (122) 64.3 (45) 0.52

Hospital admission

Readmission 45.8 (109) 46.3 (25) 0.947 40.4 (72) 32.9 (23) 0.27

Heart related readmission 39.5 (94) 40.7 (22) 0.866 27.5 (49) 20.0 (14) 0.22

Reinfarction 7.3 (13) 4.3 (3) 0.57


Table 4.46: Patient-provider interaction by availability of GP questionnaire

GP questionnaire

Yes

N=238

No

N=54


Treating you like you’re on the same level; not “ talking down” to you

or treating you like a child 10.6 (25) 18.0 (9) 0.14

Letting you tell your story; listening carefully; asking thoughtful

questions; not interrupting while you’re talking 12.3 (29) 22.4 (11) 0.062

Discussing options with you; asking your opinion; offering choices and

letting you help decided what to do; asking what you think before

telling you what to do

25.0 (57) 38.8 (19) 0.050

Encouraging you to ask questions; answering them clearly; not avoiding

the questions or lecturing you 24.9 (58) 29.2 (14) 0.54

Explaining what you need to know about your problems; how and why

they occurred and what to expect next 23.7 (55) 38.8 (19) 0.030

Using words you can understand when explaining your problems and

treatments; explaining any technical and medical terms in plain

language

15.7 (37) 22.0 (11) 0.28

4.4.3.3 Current status

A comparison of drugs prescribed at discharge is shown in Table 4.47. Drug use between the

groups was comparable with a high proportion of patients using antiplatelet agents, beta-

blockers and statins at discharge and the rate of ACE inhibitor use also moderately high. There

was a significant difference in the use of antiplatelets at early follow-up however this difference

was not repeated at late follow-up

Table 4.47: Medication use by availability of GP questionnaire



Yes

N=238

No

N=54

Yes

N=172

No

N=69


Antiplatelets 91.6 (218) 81.5 (44) 0.027 89.5 (153) 89.9 (62) 0.93

Beta-blockers 75.6 (180) 75.9 (41) 0.96 70.8 (121) 76.8 (53) 0.34

Statins 85.7 (204) 87.0 (47) 0.80 84.8 (145) 88.4 (61) 0.47

ACE inhibitor 61.8 (147) 64.8 (35) 0.68 62.0 (106) 60.9 (42) 0.87

Calcium antagonist 14.7 (35) 13.0 (7) 0.74 15.8 (27) 8.7 (6) 0.15


There was no difference in the prevalence of smokers at early follow-up between the group of

patients with a general practitioner questionnaire and those with no general practitioner

questionnaire (14.7% versus 20.4%, χ2 p = 0.302). Similarly at late follow-up, 10.7% of patients

with a general practitioner questionnaire were still smokers compared with 14.3% for those with

no general practitioner questionnaire (χ2 p = 0.426)

Table 4.48 shows the proportion of patients with high (>1SD above the mean)” and low (>1SD

below the mean) scores for each domain of the SF-36 by availability of general practitioner

questionnaire. There were no differences between groups at either the early or late follow-up.

.

171 Chapter 4 The study sample

Table 4.48: SF-36 score by the availability of GP questionnaire

General practitioner early questionnaire General practitioner late questionnaire

Yes

N=238

No

N=54

Yes

N=238

No

N=54

Yes

N=178

No

N=70

Yes

N=178

No

N=70

Percent (n) χχχχ2 p Percent (n) χχχχ2 p Percent (n) χχχχ2 p Percent (n) χχχχ2 p

Domain

Health Transition 7.1 (17) 11.1 (6) 0.40 12.6 (30) 13.0 (7) 0.94 12.9 (23) 12.9 (9) 0.99 27.0 (48) 31.4 (22) 0.48

Physical Functioning 20.6 (49) 18.5 (10) 0.73 22.3 (53) 20.4 (11) 0.76 9.0 (16) 8.6 (6) 0.92 18.5 (33) 28.6 (20) 0.083

Role Physical 24.4 (58) 16.7 (9) 0.22 24.0 (57) 27.8 (15) 0.56 28.6 (51) 28.6 (20) 0.99 24.2 (43) 30.0 (21) 0.34

Bodily Pain 29.8 (71) 24.1 (13) 0.40 25.2 (60) 20.4 (11) 0.45 28.6 (51) 34.3 (24) 0.38 26.4 (47) 30.0 (21) 0.57

General Health 22.7 (54) 18.5 (10) 0.50 21.4 (51) 24.1 (13) 0.67 16.3 (29) 12.9 (9) 0.50 23.6 (42) 22.9 (16) 0.90

Vitality 20.6 (49) 16.7 (9) 0.51 16.8 (40) 18.5 (10) 0.76 10.7 (19) 10.0 (7) 0.87 18.0 (32) 28.6 (20) 0.065

Social Functioning (0) (0) - 18.1 (43) 16.7 (9) 0.81 (0) (0) - 16.8 (30) 25.7 (18) 0.11

Role Emotional (0) (0) - 24.0 (57) 27.8 (15) 0.56 (0) (0) - 21.4 (38) 24.3 (17) 0.62

Mental Health 13.0 (31) 7.4 (4) 0.25 15.1 (36) 16.7 (9) 0.77 13.5 (24) 17.1 (12) 0.46 22.5 (40) 24.3 (17) 0.76


Prevalence of shortness of breath on mild exertion or rest was similar for patients with and

without a general practitioner questionnaire at both the early (32.6% versus 42.9%, p=0.546)

and late (10.1% versus 14.3, p=0.350) follow-up. Symptoms and treatment of angina were also

similar (Table 4.49) although at late follow-up more patients with general practitioner

questionnaires available were using an antianginal medication.

Table 4.49: Antianginal medications and chest pain by availability of GP questionnaire



Yes

N=238

No

N=54

Yes

N=178

No

N=70


Any medication 11.2 (10) 21.4 (3) 0.38 47.8 (85) 45.7 (32) 0.77

Non-GTN 9.0 (8) 7.1 (1) 0.82 16.3 (29) 5.7 (4) 0.027

Chest pain, last 4 weeks 33.7 (30) 28.6 (4) 0.70 28.1 (50) 22.9 (16) 0.40

Social factors were similar between group with and without general practitioner questionnaires

available (Table 4.50)

Table 4.50: Social factors by availability of GP questionnaire



Yes

N=238

No

N=54

Yes

N=178

No

N=70


Living with family 81.5 (194) 79.6 (43) 0.75 76.6 (131) 84.1 (58) 0.20

Working full time 23.5 (56) 31.5 (17) 0.22

Working more 2.1 (5) (0) 0.59 15.8 (27) 10.1 (7) 0.26

Working less 33.2 (79) 29.6 (16) 0.75 39.2 (67) 40.6 (28) 0.84


4.5 Discussion

There were marked differences between genders and treatment specialty in the cohort of

patients included in the medical record review. These included age and aspects of medical

history, hospital episode and comorbidities. While many of the gender differences could be

accounted for by the difference in age between males and females, the differences by treatment

speciality suggested two different patient cohorts. The differences between treatment

specialities suggested that non-cardiology patients were older and had more morbidity, and the

myocardial infarction was less severe. These differences need to betaken into account in any

comparison of treatment between cardiology and non-cardiology units to ensure minimal

confounding.

The baseline characteristics of the study cohort in terms of age, sex and previous medical

history at the time of hospital admission were similar to those of the Global Register of Acute

Coronary Events (GRACE) (Steg et al. 2002a), although a past history of PCI was higher in

GRACE.

Overall the incidence of echocardiogram and angiogram prior to discharge was relatively high

in the cardiology group with an echocardiogram in hospital for one half of patients while 60%

had a cardiac angiogram before discharge. About one third of cardiology patients received either

a thrombolytic agent or a primary angioplasty with a total of 25% undergoing a PCI prior to

discharge and another 5% undergoing coronary artery bypass surgery prior to discharge.

Cardiac procedures were almost exclusively associated with treatment in cardiology.

While rates of angiography in the cardiology group were similar to those reported in GRACE

(53% and 55% for STEMI and NSTEMI respectively) rates of PCI in the cardiology group were

lower than those reported elsewhere. For example in their study of patients with ACS admitted

to hospital in France during 1998 Danchin et al found that 49% underwent PCI during the initial

hospital stay (Danchin et al. 2002). In GRACE which also included patients with any ACS,

Steg et al reported PCI rates of 40% with STEMI, 28% with NSTEMI and 18% with other ACS

(Steg et al. 2002a). In their study Venturini et al found overall thrombolysis rate of about 40%,

which was higher than the overall rate reported here but similar for patients treated in

cardiology.

4.5.1 The follow-up cohort

One of the major methodological issues with a follow-up study is whether the study sample is

representative of all patients invited to participate in the study, in this case otherwise well

patients up to 80 years of age discharged from a participating hospital following a myocardial

infarction. Comparison of responders and non-responders suggest that this may not be the case.


In the early survey, differences were noted in a previous history of myocardial infarction and

diabetes, although these were not maintained in the late survey. However in the late survey

responders were significantly older and less likely to be smokers. These differences between

responders and non-responders must be considered in terms of whether or not these variables

impact on the use of medications.

The observation that patients with a previous infarction responded less often to the early survey

is perhaps not surprising, since these patients may be less motivated than patients following a

first infarction. The lack of association at late follow-up may reflect decreased motivation 12

months after an infarction. Alternately it may reflect differences in the eligibility for the late

follow-up, which excluded patients explicitly stating that they did not wish to participate in the

study and patients who died in the period between the early and late follow-up. The extent to

which motivation to participate in a survey may reflect the motivation to continue drug merits

some consideration, particularly with regard to the variables with significant associations.

Factors associated with drug adherence were discussed in Section 2.5.2 and include duration of

treatment, disease severity and lack of symptoms.

Decreased adherence is a common finding in long-term therapy. Given the reduced likelihood

of reinfarction with use of secondary prevention therapies it is likely that adherence was indeed

less than optimal prior to admission in patients with a previous myocardial infarction. However,

it might be expected that following reinfarction patients would have increased motivation to

adhere with the treatment regimen, even where adherence had previously lapsed. This notion is

supported by the observations that adherence increases with increased disease severity and

symptoms. It can be argued that a reinfarction might be interpreted as a “symptom” of CHD or

at least indicate increased disease severity, and therefore it could be expected to result in

adherence with the treatment regimen.

No clear association has been shown between age and adherence with various studies show in

either positive, negative or no association with age. It is arguable that greater participation by

older patients reflects the increased availability of time to participate rather than other

differences that might reflect reduced drug use.

The observation that almost one half of non-responders to the late survey were smokers at the

time of admission is of more concern. A direct comparison of the early and late follow-up

showed that a disproportionate number of those responding to the early but not late follow-up

survey were smokers at the time of the myocardial infarction. It is arguable that a lack of

response to a health related survey by smokers is to be expected. Equally it is arguable that

smokers are less likely to adhere to medical advice, not only regarding smoking but also other

therapies.


Given the observed differences between responders and non-responders, any inferences drawn

from the follow-up study regarding persistence with secondary prevention therapies must be

tempered with the knowledge that patients responding to surveys are more likely to adhere with

medical advice and that characteristics such as age, comorbidities particularly previous CHD,

and smoking might all be expected to influence the use of therapies.

As with the patient questionnaire, several differences were observed between interviewed and

non-interviewed patients that give rise to some concern about the internal validity of the sample

and its’ generizability. Interviewed patients were less likely to have a history of previous MI

than patients completing the early questionnaire but choosing not to be interviewed. Agreeing

to an interview may reflect more motivation and interest in the treatment regimen in patients

with a recent first infarction. Interviewed patients were almost exclusively treated in cardiology

and therefore results of the patient interviews only reflect patients treated in a cardiology unit.

Patients treated in a cardiology unit were more likely to have a severe infarction and exclusively

had invasive tests and procedures, as well as more structured education. Therefore results of the

patient interview must be regarded as representing the group of patients with the greatest

likelihood of adherence with the treatment regimen.

Patients with general practitioner questionnaires completed had frequent contact with the

general practitioner throughout the follow-up period. One half the patients consulted the

general practitioner every 28 days during the early follow-up period but this was extended for

the reminder of the follow-up period. This suggests that general practitioners have ample

opportunity to monitor patients drug use and risk factors.

On the other hand patients with no general practitioner questionnaire completed at early follow-

up were less likely to have reported seeing a general practitioner during the early follow-up

period. There was also an increased proportion of patients dissatisfied with aspects of the

patient-provider relationship. Use of non-GTN angina medications was higher among patients

with a completed general practitioner at late follow-up.

These differences also suggest that patients with completed general practitioner questionnaires

may represent those patients with the greatest opportunity for patient-provider interaction, that

this interaction may be more satisfying for the patient and that the patient may be motivated by

ongoing angina. Furthermore the notion that general practitioners responding to the surveys

may be more interested and better informed in the secondary prevention of CHD cannot be

ignored.


4.6 Conclusions

Baseline characteristics of the study sample were similar to those reported elsewhere in the

literature. Patient management was also similar that reported elsewhere although the rate of

revascularisation procedures in particular was lower than that reported in some studies.

While the response rate to the patient survey, patient interview and general practitioner surveys

were all high, small but significant differences in some variables were observed. These

differences could result in overestimation of the use of secondary prevention therapies in

ambulatory care.

177 Chapter 5: Secondary prevention therapies at discharge

CHAPTER 5

SECONDARY PREVENTION THERAPIES AT DISCHARGE

5.1 Introduction

This chapter examines the prescribing patterns for medications that have been shown to improve

post-MI outcomes. The care plan at hospital discharge represents the first opportunity for the

initiation of a long-term risk reduction strategy following a myocardial infarction, including the

prescription of cardioprotective drugs. This is also the first point in the continuum of patient

care where appropriate secondary prevention therapies may fail to be implemented with a

consequent “treatment gap”.

This treatment gap in the secondary prevention of CHD has been documented many times in

many different settings. The gap is usually attributed to a lack of knowledge, understanding and

interpretation of evidence from clinical trials and the dissemination and implementation of the

relevant practice guidelines. This is supported by a body of evidence showing that initiation of

secondary prevention therapy at hospital discharge has increased with increasing time since the

publication of relevant evidence and guidelines. This literature was extensively discussed in

Chapter 2.3

One reason suggested for lack of prescribing at hospital discharge is the low priority given to

secondary prevention by doctors treating an acute event (Grundy et al. 1997; Feely 1999).

However, the importance of commencing secondary prevention at hospital discharge and the

important role of the cardiologist in prevention is now well understood (Braunwald 2001;

Bairey-Merz et al. 2002). Drug prescription at discharge predicts drug use in long term

management (Fonarow et al. 2001b; Muhlestein et al. 2001; Danchin et al. 2002). Furthermore,

aspirin and beta-blocker prescription at hospital discharge were been shown to influence early

patient outcomes (Chen et al. 1999b). Several studies have also shown the benefit of early

prescription of statins (Schwartz et al. 2001; Thompson 2001a).

This understanding of the importance of prescription at hospital discharge has seen the

implementation of several programs to facilitate the implementation of secondary prevention

prior to hospital discharge in a number of different settings (Fonarow et al. 2000; Scott et al.

2000a; Mehta et al. 2002). No such programs were in place in the setting of this study.

5.1.1 Evolving evidence

While the evidence for the benefits of antiplatelet agents, beta-blockers and statins in the

secondary prevention of CHD is well established there is a constant flow of new evidence to


impact on clinical practice, as discussed in Chapter 2. Some of the new evidence includes the

following:

• New drugs have been developed that provide alternatives for patients where aspirin is not

tolerated or may used in combination with aspirin for high risk patients (CAPRIE Steering

Committee 1996; The Clopidogrel in Unstable Angina to Prevent Recurrent Events (CURE)

Trial Investigators 2001).

• Recommendations for the use of beta-blockers have broadened to include patients with

conditions previously viewed as contraindications (AHA/ACC 1999; Chen et al. 2001). In

particular heart failure is no longer considered a contraindication for beta-blockers, but

rather some beta-blockers are recommended for the treatment of heart failure (Yancy 2001).

• The observed benefits of statins to patients with relatively low lipid levels has seen the

recommended therapeutic targets, particularly for patients with known CHD, decreased

several times (Adult Treatment Panel II 1993; National Heart Foundation of Australia et al.

2001; Adult Treatment Panel III 2002).

Indications for use of ACE inhibitors have expanded considerably since their introduction as an

antihypertensive agent in the early 1980s. The benefits of ACE inhibitors were first noted for

patients with heart failure (The SOLVD Investigators 1991). Evidence of the benefits of ACE

inhibitors in post-MI patients followed, first in short term trials of early benefit in a broad

spectrum of patients and then in long term trials showing long term benefit in patients with

reduced left ventricular function (ACE Inhibitor Myocardial Infarction Collaborative Group

1998; Flather et al. 2000). Although the short-term trials of early ACE inhibitor therapy

showed a benefit across all patient groups, the proportional benefit was greatest in patients at the

highest risk. This led the ACE inhibitor MI Collaborative Group to propose two alternate

strategies. The first strategy involved “starting ACE inhibitor therapy in acute MI in all patients

who do not have clear contraindications. Such treatment should be re-evaluated at discharge or

after a few weeks and should be continued only in patients considered to be at high risk.” The

second strategy involved “initiating therapy only in patients presenting with an anterior

infarction and in certain high risk individuals” (ACE Inhibitor Myocardial Infarction

Collaborative Group 1998). Finally came the evidence of benefits of ACE inhibitors in all

patients at high risk of cardiovascular events (Yusuf et al. 2000; The EURopean trial On

reduction of cardiac events with Perindopril in stable coronary Artery disease Investigators

2003) and the recommendation that long-term ACE inhibitor therapy should be considered for

all post-MI patients without contraindications (Smith et al. 2001a).

Calcium antagonists provide a point of comparison with the secondary prevention therapies.

Although used for the treatment of hypertension and angina, calcium antagonists are not

recommended for routine treatment or secondary prevention of CHD and should only be used in


patients with angina or hypertension not properly controlled by beta-blockers and ACE

inhibitors. Patients unable to tolerate beta-blockers may be treated with verapamil or diltiazem

provided they have good ventricular function (Smith et al. 2001a; National Heart Foundation of

Australia et al. 2003).

5.1.2 Evolving practice

A major challenge in the practice of evidence-based medicine is the incorporation of new

evidence into practice and, updating guidelines to reflect this new evidence (Grimshaw et al.

1993; Shekelle et al. 2001).

Given the long-standing evidence for the benefits of antiplatelets and beta-blockers, prescription

of both these drug classes should be high and most of the variation should be explained by

contraindications. Prescription of statins should also be high with most the variation explained

by lipid levels, although the extent to which current guidelines for target lipid levels are

followed is unclear. In contrast, given the evolving evidence of the benefits of ACE inhibitors

post-MI, prescription of these agents may not be as high and there may be more unexplained

variability in prescribing practices.

5.1.3 Objectives

The objectives of this chapter are to describe prescribing practices for secondary prevention

therapies at hospital discharge post-MI and to determine the extent to which current practice at

hospital discharge reflects the current evidence, and guidelines. This is juxtaposed against the

use of calcium antagonists, which does not have cardioprotective benefits in patients with CHD.


Section 5.2 provides an overview of prescribing patterns observed at hospital discharge.

Sections 5.3 - 5.7 provide a detailed analysis for each drug class including the independent

influence of indications, contraindications and other clinical factors. The first section provides

an overview of prescribing patterns. Section 5.8 discusses the observed prescribing patterns in

terms of current best practice guidelines, at the time of the study. Sections 5.9 and 5.10 provide

a summary and conclusions respectively.


5.2 Overview of drug prescriptions

At the time of discharge from hospital, 88.7% of post-MI patients were prescribed an

antiplatelet agent, 75.0% a beta-blocker, 69.7% lipid lowering therapy, 60.4% an ACE inhibitor

and 15.6% a calcium antagonist. All but one of the patients prescribed lipid-lowering therapy

received an HMGCoA enzyme inhibitor (statin). Therefore the following analysis refers to lipid

lowering therapy as statins.

5.2.1 Demographics

Prescription by gender is illustrated in Figure 5.1. Significant differences by gender were

observed for beta-blockers and statins, where the proportion was greater in males, and calcium

antagonists, where the proportion was greater in females.

Figure 5.1: Drug prescriptions by gender

0

10

20

30

40

50

60

70

80

90

100

Antiplatelet Beta-blocker Statin ACEInhibitor

CalciumAntagonist

Male Female

p =0.461

p =0.015p =0.001

p =0.315

p =0.029

Prescription of antiplatelets, beta-blockers and statins decreased with age while prescription of

calcium antagonists increased with age (Figure 5.2). ACE inhibitor prescription showed a

biphasic trend with age.


Figure 5.2: Percentage prescribed drugs by age

0

10

20

30

40

50

60

70

80

90

100

Antiplatelet Beta-blocker Statins ACEInhibitor

CalciumAntagonist

<60 60-<70 70-<80 80+p <0.001

p <0.001 p <0.001

p =0.581

p =0.008

5.2.2 Enrolment Period

Patterns of discharge medications during the medical review period are illustrated in Figure 5.3.

No difference in prescribing was observed from January 2000 to July 2001 for antiplatelets,

beta-blockers and statins (p=0.069, 0.744, 0.290 respectively). ACE inhibitor prescriptions

increased markedly over the study from 49% in the first quarter to 70% in the last quarter

(p=0.001) with a corresponding reduction in calcium antagonist (p=0.016), reflecting new

evidence that became available during this time (see 5.1.1.4 and 5.1.1.5)


Figure 5.3: Trends in drug prescription (percentage) with annual quarters

0

10

20

30

40

50

60

70

80

90

100

Jan-

00

Apr-0

0

Jul-0

0

Oct-00

Jan-

01

Apr-0

1

Jul-0

1

Antiplatelts

Beta-blockers

Statins

ACE inhibitors

Calcium antagonists

5.2.3 Comorbidity Index

Prescription by comorbidity index is shown in Table 5.1. Prescriptions decreased with

increasing comorbidity for antiplatelets, beta-blockers and statins but increased for calcium

antagonists. There was no association for ACE inhibitors.

Table 5.1: Drug prescription by Comorbidity index

Comorbidity index* Antiplatelet

agents

Beta-blockers Statins ACE inhibitors Calcium

antagonists

0 94.7 84.6 76.8 58.1 11.7

1 83.2 69.0 67.7 65.8 20.0

2 73.1 71.2 53.8 65.4 15.4

≥3 80.4 39.3 44.6 55.4 28.6

Trend p <0.001 <0.001 <0.001 0.660 0.001

* Score derived from a modified Charlson comorbidity index that excluded heart failure

5.2.4 Treatment Specialty

Prescription of drugs at discharge by treatment specialty is shown in Figure 5.4. Greater

proportions of patients treated in a cardiology unit were prescribed antiplatelets, beta-blockers


and statins (p<0.001) but not ACE inhibitors and calcium antagonists. Most notably, statins

were prescribed to 82% of patients treated in a cardiology unit compared with 32% of patients

treated in other units.

Figure 5.4: Drug prescription by treatment specialty

0

10

20

30

40

50

60

70

80

90

100

Antiplatelets Beta-blockers Statins ACE inhibitors Calcium antagonists

Cardiology Other

5.2.5 Cardiologists

Table 5.2 shows the mean percentage of patients prescribed drugs and the variation in

prescribing habits of individual cardiologists (n=11). The range of prescription fractions was

greater for ACE inhibitors than for other drug classes with the χ2 p-value marginally significant

for ACE inhibitors, but not significant for the other drug classes. Using the F-test, the variation

in the prescribing patterns for ACE inhibitors was greater than antiplatelet agents (p=0.022) and

beta-blockers (p=0.046) but not for statins (p=0.208).

Table 5.2: Variation in new prescription rates among cardiologists

Antiplatelet

agents

Beta-blocker Statins ACE inhibitor Calcium

antagonist

Mean (±SD) 93.0 (6.2) 81.2 (7.0) 77.6 (9.4) 56.3 (12.2) 6.93 (6.42)

Variance 38.799 48.592 87.806 149.277 41.224

Max 100.0 95.6 89.5 74.3 21.6

Min 81.2 70.8 64.0 36.4 0

χ2 p 0.312 0.620 0.341 0.061 n/a

Mean/variance 2.40 1.67 0.88 0.38 0.17


5.3 Antiplatelet agents

There were 551 (88.7%) patients prescribed an antiplatelet agent at discharge of which 95.1%

were prescribed aspirin. A reason for not prescribing aspirin was documented in the medical

notes of 33 (5.3%) cases. Reasons given for not prescribing aspirin included: peptic ulcer

disease (16), bleeding (6), use of anticoagulant (2) and allergy to aspirin (10). There were nine

cases noted where the patient was receiving aspirin in hospital but it was not included in the

discharge summary.

5.3.1 Type and dose

The most frequently prescribed antiplatelets were aspirin (84%) and clopidogrel (22%). Less

than 2% of patients were prescribed other antiplatelet agents including dipyridamole,

combination aspirin/dipyridamole, and ticlopidine. Patients were sometimes prescribed more

than one antiplatelet, particularly following PCI.

5.3.1.1 PCI prior to discharge

There were marked differences in the type and dose of antiplatelets prescribed to the 107

patients who underwent PCI prior to discharge. Of patients undergoing the procedure prior to

discharge 84% (90) were discharged with 300mg of aspirin and 75mg of clopidogrel. A further

9% were prescribed some other mix of aspirin and clopidogrel. In the remaining six patients,

five had a record of aspirin only and one had no record of antiplatelet prescription. In patients

with no PCI prior to discharge, 67% were prescribed low dose (100-150 mg) aspirin with a

further 13% prescribed aspirin at a higher dosage or with no dosage specified. Six percent were

prescribed clopidogrel either alone or in combination with other antiplatelet agents and 2% were

prescribed other antiplatelet agents while 12% were prescribed no antiplatelet agent.

5.3.2 Associations with antiplatelet agent prescription

5.3.2.1 Contraindications and indications

There were 172 patients with a relative contraindication to aspirin or other antiplatelet agents,

including 71 with peptic ulcer disease, 55 with a bleeding complication, 10 with an allergy to

aspirin and 66 prescribed anticoagulants at discharge. The prevalence of relative

contraindications among patients not prescribed an antiplatelet was significantly higher than in

patients prescribed an antiplatelet (Table 5.3). Prescription of an anticoagulant was the most

common relative contraindication and included 43% of patients not prescribed an antiplatelet

agent. A relative contraindication was present in all but 19 cases where an antiplatelet was not

prescribed. Excluding patients with a relative contraindication the rate of prescription of an

antiplatelet at discharge was 96%.


Table 5.3: Influence of relative contraindications on antiplatelet prescription.

Antiplatelet agent prescribed

Yes

N=551

No

N=70

Percent (n) χχχχ2 p Unadjusted OR 95% CI

Anticoagulant 6.5 (36) 42.9 (30) <0.001 0.09 0.05-0.17

Bleeding 6.9 (38) 24.3 (17) <0.001 0.23 0.12-0.44

Peptic ulcer disease 10.0 (55) 22.9 (16) 0.001 0.37 0.20-0.70

Allergy - aspirin 1.3 (7) 4.3 (3) 0.059 0.29 0.07-1.14

Any contraindication 22.0 (121) 72.9 (51) <0.001 0.10 0.06-0.18

Compared with patients treated in other units, a greater proportion of patients treated in

cardiology units were prescribed an antiplatelet agent in the presence of contraindications

(Table 5.4). Allergy to aspirin was not analysed separately because of the small number of

cases.

Table 5.4: Influence of relative contraindications by treatment speciality.

Cardiology Other


Anticoagulant 62.8 (32) 26.7 (4) 0.014 4.63 1.3-16.6

Bleeding 86.1 (31) 36.8 (7) <0.001 10.6 2.8-40.1

Peptic ulcer disease 84.6 (44) 57.9 (11) 0.017 4.00 1.2-13.0


5.3.2.2 Other clinical variables

When characteristics of patients prescribed antiplatelets were compared with those not

prescribed antiplatelets it was noted that only one patient who underwent a CARP during the

hospital episode was not prescribed an antiplatelet at discharge. This patient had a bleeding

complication. Given this strong association, all further analyses considered only patients who

did not undergo a CARP.

Basic demographic and clinical variables and the prescription of antiplatelets are listed in Table

5.5. Mean age and comorbidity index were significantly lower in the group prescribed

antiplatelets. Patients prescribed an antiplatelet agent had a higher incidence of treatment in

tertiary hospital, treatment in a cardiology unit, STEMI, having an angiogram, recurrent chest

pain, have a lipid measurement, smoking, beta-blocker and statin prescription. Conversely these

patients had a lower incidence of CHF, AF, VT and LOS>10 days.


Table 5.5: Antiplatelet prescription by demographic and clinical variables

Antiplatelet prescription

Yes No

N=420 N=69

Mean (SD) t-test p

Age 70.2 (14.0) 73.8 (12.4) 0.051

Comorbidity index 0.8 (1.4) 1.5 (2.0) <0.001

Number of discharge drugs 6.9 (2.7) 6.8 (2.5) 0.95


Male 64.0 (269) 60.9 (42) 0.61

Public Patient 81.7 (343) 71.0 (49) 0.040

History of MI 21.9 (92) 21.7 (15) 0.98

History of CARP 11.2 (47) 14.5 (10) 0.43

Antiplatelet prior to admission 43.3 (182) 31.9 (22) 0.074

Current smoker 21.4 (90) 10.1 (7) 0.029

CHF 39.0 (164) 63.8 (44) <0.001

LVD 1 23.3 (98) 31.9 (22) 0.13

AF 18.3 (77) 39.1 (27) <0.001

CVD 15.0 (63) 20.3 (14) 0.26

Hypertension 52.1 (219) 52.2 (36) 1.00

Hyperlipidemia 51.0 (214) 42.0 (29) 0.17

Diabetes 29.3 (123) 34.8 (24) 0.36

Creatinine >300 µmol/L 2.9 (12) 2.9 (2) 1.00

Dementia 3.6 (15) 2.9 (2) 1.00

STEMI 58.8 (247) 44.9 (31) 0.031

Anterior site 19.0 (80) 21.7 (15) 0.60

High-CK3 39.3 (165) 31.9 (22) 0.24

VT 5.7 (24) 15.9 (11) 0.002

Cardiac arrest, including VF 2.9 (12) 7.2 (5) 0.065

Recurrent chest pain 17.9 (75) 11.6 (8) 0.20

Long-stay2 18.1 (76) 40.6 (28) <0.001

Cardiology 71.2 (299) 53.6 (37) 0.003

Tertiary Hospital 67.1 (282) 82.6 (57) 0.010

Angiogram 36.2 (152) 17.4 (12) 0.002

Reperfusion 22.4 (94) 13.0 (9) 0.078

Echocardiogram 46.9 (197) 58.0 (40) 0.088

Lipid profile recorded 67.6 (284) 53.6 (37) 0.023

Beta-blocker 77.4 (325) 58.0 (40) <0.001

Statins 69.5 (292) 49.3 (34) <0.001

ACE inhibitor 60.7 (255) 63.8 (44) 0.63

Calcium antagonist 15.7 (66) 23.2 (66) 0.12 1LVEF<40%, 2 LOS >10 days, 3peak CK>720 U/L,


5.3.3 Independent predictors of antiplatelet agent prescription

When all variables with a χ2 p<0.10 were included in a multivariate logistic regression analysis

there were a number of independent associations with prescription of an antiplatelet agent

(Table 5.6). The greatest influence on antiplatelet agent prescription was use of anticoagulants

and a bleeding complication in hospital, both reducing the odds of antiplatelet prescription by

more than 90%. In addition to the contraindications, evidence of reduced wellbeing, indicated

by a higher comorbidity index or increased length of stay, also reduced the odds of prescription.

Table 5.6: Independent predictors for prescription of antiplatelets

Adjusted OR 95% CI χχχχ2 p

No revascularisation procedure n=489

Anticoagulant 0.04 0.02-0.09 <0.001

Bleeding 0.08 0.03-0.19 <0.001

Comorbidity index 0.81 0.69-0.96 0.015

Beta-blockers 2.07 1.00-4.27 0.049

STEMI 2.21 1.15-4.26 0.017

c-statistic 0.844

Treatment speciality

Cardiology N=336

Anticoagulant 0.06 0.03-0.14 <0.001

Bleeding 0.24 0.06-0.94 0.040


c-statistic 0.797

Non-cardiology N=153

Anticoagulant 0.04 0.01-0.18 <0.001

Bleeding 0.04 0.01-0.17 <0.001

Long-stay1 0.24 0.08-0.76 0.015

Admission antiplatelet 4.4 1.32-14.9 0.015

c-statistic 0.886

Adjusted for age 1LOS >10 days

Although treatment speciality was not associated with antiplatelet prescription in the overall

model, stratifying by treatment specialty resulted in different independent associations. Most

notable was the inclusion of prior use of an antiplatelet agent in the non-cardiology model. The

strong association between STEMI and antiplatelet agent prescription observed in the overall

model was not maintained in the stratified models.


5.3.4 Summary

Prescription of antiplatelet agents was high with relative contraindications present in almost all

patients not prescribed an antiplatelet agent. The types and dosages of antiplatelet agents

differed in patients undergoing PCI prior to discharge. Logistic regression models considered

only patients not undergoing CARP prior to discharge since these latter patients were

universally prescribed antiplatelet agents. The logistic regression analysis confirmed the

bivariate analysis that contraindications had a strong influence on antiplatelet agent prescription.

Significant comorbidities as indicated by a higher comorbidity index also were negatively

associated with antiplatelet agent prescription. Concomitant prescription of beta-blockers and

STEMI were positively associated with antiplatelet prescription.


5.4 Beta-blockers

Beta-blockers were prescribed to 75.0% (466) of patients. A reason for not prescribing a beta-

blocker was documented in the medical record in 48 cases (7.7%). Reasons given for not

prescribing a beta-blocker included: chronic airways limitation (CAL) (12), sinus bradycardia

(9), hypotension (8) and peripheral vascular disease (PVD) (6). Some form of intolerance was

noted in 5 cases. Other reasons given were heart block, aortic stenosis, pulmonary oedema and

renal failure.

5.4.1 Type and dose

The most frequently prescribed beta-blockers were metoprolol (70%), atenolol (26%) and

carvedilol (2%). Other beta-blockers prescribed included propranolol and sotalol.

Prescription of metoprolol usually involved twice a day dosing (96%), while atenolol was

usually prescribed once a day (93%). The most frequent daily doses prescribed were 50 mg

(43%) and 100 mg (33%) for metoprolol and, 50 mg (49%) and 25 mg (34%) for atenolol.

5.4.2 Associations with beta-blocker prescription


There were 152 patients with a relative contraindication to beta-blockers including 102 with

CAL, 68 with hypotension, 66 with bradycardia, 62 with PVD, 24 with second degree or

complete heart block and nine with cardiogenic shock. Prevalence of most relative

contraindications was higher among patients not prescribed a beta-blocker compared with

patients prescribed a beta-blocker (Table 5.7). There was no difference in prevalence for

hypotension and cardiogenic shock. CAL was the most common contraindication in the group

not prescribed beta-blocker. CAL and heart block had the greatest effect on the prescribing of

beta-blockers reducing the odds by 90% for CAL and 75% for heart block.

Of the patients not prescribed a beta-blocker, 73% (111) had a relative contraindication.

Excluding patients with a relative contraindication, the rate of beta-blocker prescription was

89% while the rate of prescription for patients with CAL was 35%.


Table 5.7: Influence of relative contraindications for beta-blocker prescription

Beta-blockers prescribed

Yes

N=469

No

N=152


CAL 7.7 (36) 43.4 (66) <0.001 0.11 0.07-0.17

Hypotension 10.0 (47) 13.8 (21) 0.19 0.69 0.40-1.20

PVD 7.3 (34) 18.4 (28) <0.001 0.34 0.20-0.59

Heart Block, 2o or complete 2.3 (11) 8.6 (13) <0.001 0.26 0.11-0.59

Bradycardia 8.3 (39) 17.8 (27) 0.001 0.42 0.25-0.71

Cardiogenic shock 1.3 (6) 2.0 (3) 0.46 0.64 0.16-2.60


A greater proportion of patients treated in cardiology were prescribed a beta-blocker in the

presence of CAL, hypotension and PVD compared to patients treated in other units as shown in

Table 5.8. No difference was apparent for heart block and bradycardia.

Table 5.8: Influence of relative contraindications by treatment specialty.

Cardiology Other


CAL 47.4 (28) 18.6 (8) 0.003 3.95 1.57-9.94

Hypotension 76.5 (39) 47.1 (8) 0.023 3.68 1.16-11.5

PVD 67.6 (23) 39.3 (11) 0.026 3.23 1.14-9.18

Heart Block, 2o or complete 52.9 (9) 28.6 (2) 0.28 2.81 0.42-18.74

Bradycardia 56.9 (33) 75.0 (6) 0.33 0.44 0.08-2.37



Table 5.9 lists basic demographic and clinical variables with beta-blocker prescription. Mean

age and comorbidity index were significantly lower in patients prescribed beta-blockers.

Patients prescribed beta-blockers had a higher prevalence of treatment in cardiology, STEMI,

high-CK, cardiac related tests, concomitant prescription of antiplatelets and statins,

hyperlipidemia and beta-blockers use prior to admission. Conversely they had lower prevalence

of other heart conditions.


Table 5.9: Beta-blocker prescription by demographic and clinical variables

Beta-blocker prescribed

Yes No

N=469 N=152

Mean (SD) t-test p

Age 66.9 (13.8) 73.4 (13.8) <0.001




Male 68.0 (319) 57.2 (87) 0.015

Public Patient 79.1 (371) 79.0 (120) 0.97

History of MI 19.4 (91) 23.0 (35) 0.33

History of CARP 13.2 (62) 7.9 (12) 0.078

Beta-blocker at admission 28.4 (133) 6.6 (10) <0.001

Current smoker 21.1 (99) 19.1 (29) 0.59

CHF 32.0 (150) 50.7 (77) <0.001

LVD 1 23.2 (109) 23.7 (36) 0.91

AF 15.8 (74) 28.3 (43) <0.001

CVD 9.6 (45) 24.3 (37) <0.001

Hypertension 50.8 (238) 55.9 (85) 0.27

Hyperlipidemia 56.9 (267) 42.8 (65) 0.002

Diabetes 27.9 (131) 27.6 (42) 0.94


Dementia 2.6 (12) 3.9 (6) 0.38

STEMI 63.8 (299) 44.7 (68) <0.001

Anterior site 23.2 (109) 19.1 (29) 0.28

High-CK2 42.6 (200) 32.2 (49) 0.023

VT 7.9 (37) 5.3 (8) 0.28

Cardiac arrest including VF 4.9 (23) 2.6 (4) 0.23


Long-stay3 17.5 (82) 35.5 (54) <0.001

Cardiology 81.7 (383) 55.3 (84) <0.001


Angiogram 49.7 (233) 30.9 (47) <0.001

Reperfusion 30.1 (144) 11.2 (17) <0.001

CARP 24.1 (113) 18.4 (28) 0.15

Echocardiogram 49.2 (231) 42.1 (64) 0.13

Lipid profile recorded 76.3 (358) 55.3 (84) <0.001

Antiplatelets 91.5 (429) 80.3 (122) <0.001

Statins 77.4 (363) 46.0 (70) <0.001

ACE inhibitor 60.8 (285) 59.2 (90) 0.73

Calcium antagonist 10.2 (48) 32.2 (49) <0.001 1LVEF<40%, 2 LOS >10 days, 3peak CK>720 U/L,


5.4.3 Independent predictors of beta-blocker prescription


a number of independent associations with beta-blocker prescription were observed in both the

overall cohort and in the cohort not using a beta-blocker prior to admission (Table 5.10). The

overall model (upper panel) included 10 independent predictors of beta-blocker prescription.

CAL, heart block, bradycardia and PVD were all negatively associated with beta-blocker

prescription, as were concomitant prescription of a calcium antagonist, an increasing

comorbidity index and being aged more than 80 years. Beta-blocker use prior to admission,

reperfusion therapy and concomitant prescription of statins were all positively associated with

beta-blocker prescription. Given the strong influence of prior beta-blocker use it was of interest

to examine independent predictors of beta-blocker prescription in only patients not using beta-

blockers prior to admission (lower panel). This model included three extra variables. A

concomitant prescription of an antiplatelet agent was positively associated with beta-blocker

prescription, while previous MI and hypertension were negatively associated with beta-blocker

prescription.

The logistic regression models by treatment specialty are shown in Table 5.11. Although

treatment in cardiology was not an independent predictor of beta-blocker prescription in the

overall cohorts, there were some differences between the cardiology and non-cardiology model.

The most notable differences were the association with statins, measurement of lipids and

STEMI in the non-cardiology model. This suggested that in non-cardiology units, prescription

of beta-blockers was more restricted than in the cardiology unit. Both models included a marker

of general health status, although the cardiology model included long-stay, while the non-

cardiology model included comorbidity index.


Table 5.10: Independent predictors of beta-blocker prescription


Chronic Airways Limitation 0.14 0.07-0.25 <0.001

Heart block (2° or complete) 0.18 0.06-0.60 0.005

Bradycardia 0.22 0.06-0.59 <0.001

Calcium antagonist 0.25 0.13-0.48 <0.001

PVD 0.46 0.22-0.99 0.049


Age, years

≥80 0.44 0.22-0.90 0.025

70-<80 1.43 0.70-2.92 0.321

60-<70 0.93 0.42-2.03 0.848

<60 Referent

Statins 3.02 1.77-5.15 <0.001

Reperfusion 3.45 1.73-6.90 <0.001

Beta-blocker at admission 9.00 4-21 <0.001

c-statistic 0.887

New prescriptions N=478

Chronic Airways Limitation 0.08 0.04-0.16 <0.001

Bradycardia 0.16 0.07-0.37 <0.001



Previous MI 0.33 0.16-0.70 0.003

Peripheral vascular disease 0.40 0.16-0.96 0.039

Hypertension 0.47 0.27-0.83 0.009

Age, years

≥80 0.37 0.17-0.81 0.013

70-<80 1.68 0.74-3.81 0.214

60-<70 0.79 0.34-1.88 0.600

<60 Referent

Statins 2.72 1.50-4.93 0.001

Antiplatelets 2.86 1.29-6.36 0.010

Reperfusion 4.37 2.05-9.34 <0.001

c-statistic 0.895


Table 5.11: Independent predictors for beta-blocker prescription by treatment specialty


Cardiology N=467



CAL 0.17 0.08-0.37 <0.001

Bradycardia 0.18 0.08-0.39 <0.001

Long-stay 0.36 0.17-0.77 0.008

Age, years

≥80 0.25 0.10-0.64 0.005

70-<80 1.08 0.49-2.35 0.852

60-<70 0.76 0.33-1.76 0.518

Reperfusion 3.53 1.67-7.49 0.001

Beta-blocker at admission 9.00 3-25 <0.001

c-statistic 0.871

Non-cardiology N=154

CAL 0.07 0.02-0.28 <0.001


PVD 0.23 0.05-1.01 0.051


STEMI 3.00 1.1-10.4 0.032

Lipids measured 4.00 1.2-11.4 0.025

Statins 7.00 2-26 0.002

Beta-blocker at admission 11.00 2-51 0.002

c-statistic 0.927

5.4.4 Summary

In the absence of relative contraindications, beta-blockers were prescribed to almost 90% of

post-MI patients although only 35% of patients with CAL were prescribed a beta-blocker.

Relative contraindications and prescription of a calcium antagonist were all independent

negative predictors of beta-blocker prescription. Use of beta-blockers at the time of admission

had a strong positive association with beta-blocker prescription. On the other hand there was a

negative association with previous MI and hypertension in those not using beta-blockers at the

time of admission. Other negative predictors in the overall models included being over 80 years

of age and comorbidity while positive predictors included reperfusion therapy and concomitant

use of statins. Treatment speciality was not associated with beta-blocker prescription in the

overall models however when stratified by treatment specialty differences between the models

were noted.


5.5 Statins

Lipid lowering therapy was prescribed to 69.7% of patients. All but one of these patients were

prescribed a statin, with three patients prescribed gemfibrozil in addition to a statin. Reasons

for not prescribing statins were documented in six cases. These included elevated CK, liver

disease, pins and needles, satisfactory lipid profile, use of alternative therapy and one case

where treatment was stopped, but no clear reason documented.

5.5.1 Type and dose

The most commonly prescribed statins were atorvastatin (34%), pravastatin (32%) and

simvastatin (25%). The remainder were using cerivastatin or fluvastatin (2%) or were taking

part in a RCT involving a statin (7%). Table 5.12 shows the most frequently prescribed doses

and compares mean doses between patients newly prescribed a statin and those using a statin

prior to hospital admission. Only atorvastatin doses differed between the two groups.

Table 5.12: Statin doses (mg) prescribed at discharge

Overall New prescription Ongoing Difference

Dose (mg) t-test p

Pravastatin

N=139 N=92 N=47

10 6% 6% 6%

20 51% 51% 48%

40 41% 42% 43%

Mean (SD) 28.0 (10.8) 27.8 (10.8) 28.3 (10.8) 0.82

Simvastatin

N=105 N=54 N=51

10 16% 13% 20%

20 66% 74% 59%

40 15% 13% 18%

Mean (SD) 22.6 (11.8) 21.3 (8.0) 23.9 (14.8) 0.27

Atorvastatin

N=146 N=81 N=65

10 42% 49% 33%

20 26% 40% 33%

40 16% 10% 23%

Mean (SD) 22.1 (16.8) 17.8 (11.4) 27.5 (20.7) 0.001


5.5.1.1 Changes in drugs from admission to discharge

Very few changes were made to the drug prescribed at discharge (11/169) with no evidence of

systematic change. Statin doses prior to admission were available for only 97 of the 169 cases.

Of these cases the dose was increased in 9 cases (10%) of which five were atorvastatin.

5.5.1.2 Timing of doses

Overall, 69% of patients were prescribed statins at night, 8% the morning and in the remaining

23% the time of administration was unspecified. Where the timing was specified, atorvastatin

was prescribed at night to 72% of patients compared with 98% of those prescribed pravastatin

or simvastatin (p<0.001). A total of 27% of cases prescribed atorvastatin had no time specified

compared with 16% for pravastatin and 20% for simvastatin (p=0.037).

5.5.2 Associations with statin prescription


Liver disease was documented for five patients, of who three were not prescribed statins. With

such a low prevalence of disease no meaningful analysis could be performed. A history of

hyperlipidemia was recorded for 37.5% of patients at the time of admission and a diagnosis of

hyperlipidemia was recorded for 53.1% of patients at discharge.

Lipids

Table 5.13 shows bivariate analysis of statin prescription by lipid measurements, as a

categorical variable. Statin prescription was strongly associated with TC and LDL-C. There

was a weaker association with triglyceride levels and no association with HDL-C levels. Given

the continuous nature of the associations, all future analyses included lipid levels as continuous

variables.


Table 5.13: Unadjusted odds ratio (OR) for statin prescription by lipid levels

Lipid levels Prescription

mmol/L Percent Unadjusted OR 95% CI χχχχ2 p

Total Cholesterol <4 36.7 1.00

≥4 and <5 64.5 3.13 1.58-6.23 0.001

≥5 and <6 77.9 6.06 2.95-12.46 <0.001

≥6 92.6 21.53 6.66-69.53 <0.001

LDL-C <2.5 41.7 1.00

≥2.5 and <3 71.7 3.55 1.96-6.42 <0.001

≥3 and <4 87.1 9.45 3.93-22.74 <0.001

≥4 90.5 13.10 3.23-61.05 <0.001

Triglycerides <2 64.2 1.00

≥2 and <4 82.4 2.60 1.40-4.82 0.002

≥4 88.2 4.18 0.94-18.7 0.060

HDL-C ≥1 67.1 1.00

< 1 73.2 1.34 0.82-2.18 0.24


Characteristics of patients prescribed statins were compared with those not prescribed statins. It

was noted that only four patients using lipid-lowering therapy prior to admission were not

prescribed therapy at discharge. Given this strong association, further analysis was restricted to

patients not using lipid-lowering therapy prior to admission (n=444). Statin prescriptions for

patients not using statins prior to admission are shown in Table 5.14. Mean age and

comorbidity index were lower in patients prescribed statins. More males were prescribed statins

as were patients treated in cardiology units. There was a higher incidence of STEMI, high-CK,

reperfusion, angiogram and CARP. Antiplatelet and beta-blocker prescription were also higher

in patients prescribed statins, as was a complete lipid profile, diagnosis of hyperlipidemia,

smoking and recurrent chest pain. Conversely CHF, AF, CVD, previous MI, long-stay and

calcium antagonist prescription were all lower in patients prescribed statins.


Table 5.14: New statin prescription by demographic and clinical variables

Statin prescribed

Yes No

N=260 N=184

Mean (SD) t-test p

Age 63.6 (13.9) 76.0 (13.1) <0.001




Male 73.5 (191) 54.9 (101) <0.001

Public Patient 79.6 (207) 81.5 (150) 0.62

History of MI 11.2 (29) 18.5 (34) 0.029

History of CARP 5.4 (14) 3.3 (6) 0.29

Current smoker 31.9 (83) 12.5 (23) <0.001

CHF 24.2 (63) 52.2 (96) <0.001

LVD 1 25.4 (66) 21.7 (40) 0.38

AF 10.8 (28) 30.4 (56) <0.001

CVD 7.7 (20) 16.3 (30) 0.005

Hypertension 45.8 (119) 45.6 (84) 0.98

Hyperlipidemia 56.9 (148) 13.6 (25) <0.001

Diabetes 23.5 (61) 22.8 (42) 0.88


Dementia 0.04 (1) 7.1 (13) <0.001

STEMI 69.6 (181) 46.7 (86) <0.001

Anterior site 25.8 (67) 18.5 (34) 0.071

High-CK2 50.4 (131) 29.9 (55) <0.001

VT 6.9 (18) 7.1 (13) 0.95



Long-stay3 15.4 (40) 31.5 (58) <0.001

Cardiology 92.7 (241) 43.5 (80) <0.001


Angiogram 58.8 (153) 21.2 (39) <0.001

Reperfusion 34.6 (90) 15.8 (29) <0.001

CARP 27.3 (71) 12.0 (22) <0.001

Echocardiogram 51.5 (134) 45.1 (83) 0.18

Lipid profile recorded 84.2 (219) 51.1 (94) <0.001

Antiplatelet 95.4 (248) 81.0 (149) <0.001

Beta-blocker 87.7 (228) 57.1 (105) <0.001

Calcium antagonist 10.0 (26) 16.8 (31) 0.034

ACE inhibitor 60.8 (158) 53.3 (98) 0.12 1LVEF<40%, 2peak ck>720 U/L, 3 LOS >10 days,


5.5.3 Independent predictors of new statin prescription


a number of independent associations with new statin prescriptions were observed (Table 5.15).

The upper panel includes all patients and whether there was a cholesterol measurement, but no

lipid levels. The model for patients with a cholesterol measurement is shown in the lower panel.

Table 5.15: Logistic regression model for new statin prescription


Not including lipid levels

N=444

Cardiology 5.82 2.28-12.20 <0.001

Hyperlipidemia 5.64 3.16-10.06 <0.001

Beta-blocker 3.11 1.68-5.77 <0.001

Cholesterol Measurement 2.29 1.06-4.95 0.035

Antiplatelet agent 2.76 1.11-6.85 0.029

AF 0.48 0.24-0.95 0.036

c-statistic 0.872

Including cholesterol

N=349

Cardiology 5.70 2.39-13.6 <0.001

Hyperlipidemia 3.30 1.76-6.20 <0.001

Beta-blocker 2.61 1.28-5.32 0.008

Cholesterol measurement 2.12 1.51-2.99 <0.001

c-statistic 0.849

Age adjusted

In both models treatment in a cardiology unit, a diagnosis of hyperlipidemia and concomitant

beta-blocker prescription were all positively associated with statin prescription. The cholesterol

level was also positively associated with statin prescription with an increase of 1mmol/L

doubling the odds of statin prescription. In the model that did not include cholesterol levels, the

measurement of cholesterol and prescription of antiplatelets were associated with statin

prescription, while atrial fibrillation reduced the odds of statin prescription.

5.5.4 Summary

There was a direct relationship between lipid levels and prescription of statins at discharge. The

overall prescription rate for statins was 70% but this increased to 78% for patients with TC

levels between 5 and 6 mmol/L and 93% for TC levels greater than or equal to 6 mmol/L.

Treatment in cardiology, a diagnosis of hyperlipidemia and concomitant beta-blocker

prescription were independent predictors of statin prescription in patients not using a statin prior

to admission.


5.6 ACE inhibitors

Overall 60.4% of patients were discharged with an ACE inhibitor. Twenty patients (3.2%) had

a documented reason for not prescribing an ACE inhibitor at discharge, including 12 with

contraindications (1 renal failure, 3 aortic stenosis and 8 hypotension) and 4 adverse responses.

Normal LVEF was given as the reason for not prescribing an ACE inhibitor in two cases. In

another case the decision was made to wait for the results of the cardiac catheter before

prescribing an ACE inhibitor and in another case the general practitioner was advised to

commence an ACE inhibitor. Another 5.5% of patients were prescribed an ARB

5.6.1 Changes in prescribing over time

There was a trend of increasing ACE inhibitor prescription over the period (Figure 5.5). There

was an absolute increase of 18% in cardiology units (p=0.002) compared with 7% in non-

cardiology units. The relative increase was 35% in cardiology units and 13% in non-cardiology

units. The increase was even more marked for new prescriptions with an absolute increase of

23% in cardiology (p=0.001) and 6.7% in non-cardiology (p=0.57) units. The relative increase

was 60% in cardiology and 19.5% in non-cardiology units.

Figure 5.5: Changes in ACE inhibitor prescription over the study

20

30

40

50

60

70

80

Early Middle Late

Enrolment period

Per

cen

tag

e

Cardiology

Non-cardiology

Cardiology, new

Non-cardiology, new


5.6.1.1 Intra-cardiology variability

Eleven cardiologists, caring for at least 15 patients (range 19 to 35) were included in this

analysis. Individual prescription rates for cardiologists ranged from 36% to 74% (mean (±SD)

= 56%(±12), χ2p =0.061). Table 5.16 shows the breakdown of cardiologists and the proportion

of patients treated by low, medium and high ACE inhibitor prescribing cardiologists.

Table 5.16: Cardiologist by prescribing rate

Prescribing rate Cardiologists Patients

N Percent

Low 3 25

Intermediate 6 59

High 2 15

The change in prescribing over time for the three groups is shown in Figure 5.6. There was an

increase in prescribing in the intermediate prescribing group (p<0.001), but not in the low

(p=0.766) and high (p=0.546) prescribing groups.

Figure 5.6: Changes in cardiology prescribing of ACE inhibitors

0

10

20

30

40

50

60

70

80

90

100

Early Middle Late

Enrolment period

Per

cen

tag

e

High

Intermediate

Low


5.6.2 Type and dose

The most commonly prescribed ACE inhibitor was ramipril (37.6%) followed by perindopril

(28.8%), trandolapril (9.6%), captopril (6.1%) and enalapril (5.3%). Other ACE inhibitors

accounted for 12.5%.

Table 5.17 shows the most frequently prescribed doses of ACE inhibitors and compares these

between patients newly prescribed an ACE inhibitor and those using ACE inhibitors prior to

hospital admission. Mean doses were significantly higher for ongoing prescriptions compared

with new prescriptions but the differences were relatively small.

Table 5.17: ACE inhibitor doses (mg) prescribed at discharge

Overall New scripts Ongoing scripts Difference

Dose (mg) χχχχ2 p

Ramipril

N=141 N=112 N=29

2.5 43.7 50.9 17.2

5.0 41.6 36.6 58.6

10 12.0 9.8 20.7

Mean (SD) 4.6 (2.5) 4.0 (2.2) 5.5 (2.4) 0.002

Perindopril

N=108 N=67 N=41

2 50.9 58.2 33.3

4 36.6 34.3 46.2

8 4.5 1.5 10.3

Mean (SD) 3.2 (1.6) 2.8 (1.3) 3.8 (1.7) <0.001

Trandolapril

N=36 N=21 N=15

0.5 41.7 61.9 13.3

1.0 30.6 28.6 33.3

2.0 19.4 4.8 40.0

Mean (SD) 1.1 (0.8) 0.1 (0.5) 1.6 (0.9) 0.003

5.6.2.1 Changes in type of ACE inhibitor prescribed over time

The proportion of patients prescribed ramipril at discharge increased from 9% in the first quarter

to 35% in the last quarter, while the proportion of patients prescribed other ACE inhibitors

remained moderately stable varying between 29% and 43% per quarter over the study period.

As a result the relative proportion of ramipril increased from 19% of all ACE inhibitor

prescriptions to 50% of all ACE inhibitor prescriptions (Trend p=0.003) over the study period.


5.6.3 Associations with ACE inhibitor prescription


Aortic stenosis was more prevalent in the group not prescribed ACE inhibitors, however renal

failure and hypotension were not associated with ACE inhibitor prescription (Table 5.18). There

were insufficient patients with raised creatinine levels to provide further analysis.

Table 5.18: Influence of relative contraindications to ACE prescription

ACE inhibitor prescription

Yes No

N=375 N=246


Aortic Stenosis 1.1 (4) 3.7 (9) 0.027

Renal failure 12.0 (45) 12.2 (30) 0.94

Hypotension 11.5 (43) 8.9 (22) 0.32

Creatinine > 300 µmol/L 1.6 (6) 3.2 (8) 0.18

There was a higher prevalence of definite and probable indications for ACE inhibitor

prescription in patients prescribed an ACE inhibitor, shown in Table 5.19.

Table 5.19: Influence of indications on ACE inhibitor prescription

ACE inhibitor prescribed

Yes

N=375

No

N=246

N Percent (n) χχχχ2 p OR (95% CI)

LVD 1 145 30.4 (114) 12.6 (31) <0.001 3.03 (1.96-4.68)

CHF 227 42.1 (158) 28.0 (69) <0.001 1.87 (1.32-2.64)

High-CK2 249 48.3 (181) 27.6 (68) <0.001 2.44 (1.73-3.45)

Diabetes 173 33.1 (124) 19.9 (49) <0.001 1.99 (1.36-2.90)

Anterior site 138 25.9 (97) 16.7 (41) 0.007 1.74 (1.16-2.62) 1LVEF<40%, 2peak CK>720 U/L

Prescription rates by treatment specialty and indication is shown in Table 5.20. ACE inhibitors

were prescribed to a greater proportion of patients treated in cardiology compared with other

units; however, the difference was only significantly different for heart failure.


Table 5.20: ACE inhibitor prescription by indication and treatment speciality

Indication All Cardiology Other

Percent (n) χχχχ2 p OR (95% CI)

LVD 1 78.6 (114) 80.2 (89) 73.5 (25) 0.41 1.45 (0.60-3.56)

CHF 69.6 (158) 75.0 (99) 62.1 (59) 0.037 1.83 (1.03-3.24)

High-CK2 72.7 (181) 73.4 (157) 68.6 (24) 0.56 1.26 (0.58-2.74)

Diabetes 71.7 (124) 72.9 (97) 67.5 (27) 0.50 1.30 (0.60-2.78)

Anterior site 70.2 (97) 72.4 (84) 59.1 (13) 0.21 1.82 (0.71-4.66) 1LVEF<40%, 2peak CK>720 U/L

Table 5.21 compares prescription of ACE inhibitors by the level of indication. ACE inhibitor

prescription was greatest in patients with LVD or heart failure, intermediate in patients with

anterior MI, peak CK>720 or diabetes and lowest in the remaining group of patients.

Table 5.21: ACE inhibitor prescription by indication

Indication ACE inhibitor prescribed OR (95% CI) χχχχ2 p

LVD 1/CHF 70.6 (204) 4.14 (2.70-6.35) <0.001

Anterior site/high-CK2/Diabetes 62.2 (120) 1.46 (0.99-2.15) 0.054

Other 36.7 (51) 1.00 1LVEF<40%, 2peak CK>720 U/L

Table 5.22 shows the proportion of patients with heart failure and LVD prescribed an ACE

inhibitor at discharge. There was an increase in the proportion of patients prescribed an ACE

inhibitor from neither heart failure nor LVD, to heart failure alone, LVD alone and, heart failure

and LVD (trend p<0.001). However, there was no significant difference between heart failure

alone and LVD alone (p=0.104). Furthermore stratified analysis showed no interaction between

heart failure and LVD (χ2 p=0.992).

Table 5.22: Influence of heart failure and LVD on ACE inhibitor prescription

No LVD LVD χχχχ2 p OR (95% CI)

No CHF 51.5 (171) 74.2 (46) 0.001 2.71 (1.47-4.97)

CHF 62.5 (90) 81.9 (68) 0.002 2.72 (1.41-5.22)

χ2 p 0.027 0.261

OR (95% CI) 1.57 (1.05-2.34) 1.58 (0.71-3.50)

Influence of time on ACE inhibitor indications

Table 5.23 shows the influence of indications on changes in ACE inhibitor prescription over the

study. ACE inhibitor prescription increased markedly with an anterior infarction, peak

CK>720 U/L or diabetes, while only small and non-significant increases were observed for

patients other indications. The absolute increase in ACE inhibitor prescription for patients with

an anterior infarction, peak CK>720 U/L or diabetes was 39% with a relative increase of 87%.


Table 5.23: Changes in ACE inhibitor prescription over the study by indication

Indication N Early Period Middle Period Late Period Trend p

All prescriptions

LVD 1/CHF 289 68.5 69.7 73.8 0.46

Anterior site/high-CK2/Diabetes 193 45.0 61.0 84.3 <0.001

Other 139 31.6 38.9 38.3 0.54

Cardiology

LVD 1/CHF 187 73.8 75.6 76.3 0.78


Other 110 28.6 35.0 40.0 0.32 1LVEF<40%, 2peak CK>720 U/L

When the analysis was restricted to patients not using ACE inhibitors prior to admission (Table

5.24), the increase in prescriptions was even greater for the group with anterior infarction, peak

CK>720 U/L or diabetes but no heart failure or LVD. The absolute increase was 51% with a

relative increase of 179% in the complete cohort.

Table 5.24: New ACE inhibitor prescriptions over the study

N Early Period Middle Period Late Period Trend p

All prescriptions

LVD 1/CHF 198 56.9 59.6 65.5 0.350


Other 112 21.2 24.4 23.7 0.81

Cardiology

LVD 1/CHF 128 63.3 67.9 71.4 0.47


Other 93 19.4 26.5 25.0 0.60 1LVEF<40%, 2peak CK>720 U/L


Patient characteristics and ACE inhibitor prescription are shown in Table 5.25. There was no

difference in mean age and comorbidity index; but the mean number of medications at discharge

was greater in patients prescribed ACE inhibitors. In addition to heart failure, left ventricular

dysfunction, high-CK, anterior site and diabetes, other variables with higher prevalence in

patients prescribed ACE inhibitors included STEMI, reperfusion, echocardiogram, statin

prescription, previous MI or CARP and hypertension.


Table 5.25: ACE inhibitor prescription by demographic and clinical variables.

ACE inhibitor prescription

Yes No

N=375 N=246

Mean (SD) t-test p

Age 68.8 (13.1) 68.0 (15.5) 0.46


Number of discharge drugs 7.2 (2.4) 6.1 (2.4) <0.001


Male 66.9 (251) 63.0 (155) 0.32

Public Patient 78.1 (293) 80.5 (198) 0.48

History of MI 22.9 (86) 16.3 (40) 0.043

History of CARP 14.1 (53) 8.5 (21) 0.035

ACE inhibitor at admission 38.7 (145) 4.1 (10) <0.001

Current smoker 20.5 (77) 20.7 (51) 0.95

CHF 42.1 (158) 28.0 (69) <0.001

LVD 1 30.4 (114) 12.6 (31) <0.001

AF 19.7 (74) 17.5 (43) 0.48

CVD 12.3 (46) 14.6 (36) 0.39

Hypertension 56.0 (210) 45.9 (113) 0.014

Hyperlipidemia 55.2 (207) 50.8 (125) 0.28

Diabetes 33.1 (124) 19.9 (49) <0.001


Dementia 2.7 (10) 3.2 (8) 0.67

STEMI 63.5 (238) 52.4 (129) 0.006

Anterior site 25.9 (97) 16.7 (41) 0.007

High-CK2 48.3 (181) 27.6 (68) <0.001

VT 8.0 (30) 6.10 (15) 0.37



Long-stay3 21.9 (82) 21.9 (54) 0.98

Cardiology 77.1 (289) 72.4 (178) 0.18


Angiogram 43.2 (162) 48.0 (118) 0.24

Reperfusion 32.5 (122) 15.8 (39) <0.001

CARP 21.6 (81) 24.4 (60) 0.42

Echocardiogram 58.7 (220) 30.5 (75) <0.001


Antiplatelet 88.0 (330) 89.8 (221) 0.48

Beta-blocker 76.0 (285) 74.8 (184) 0.73

Statin 73.3 (275) 64.2 (158) 0.016

Calcium antagonist 14.1 (53) 17.9 (44) 0.21 1LVEF<40%, 2peak CK>720 U/L, 3LOS>10 days


5.6.4 Independent predictors of ACE inhibitors

Logistic regression models for ACE inhibitor prescription are shown in Table 5.26. The model

for the overall cohort is shown in the upper panel. The model for patients with no heart failure

or LVD is shown in the middle panel. The lower panel shows the model for patients with either

heart failure or LVD.

Table 5.26: Logistic regression model for ACE inhibitor prescription at discharge

Adjusted OR 95%CI χχχχ2 p

All (N=621)

Admission ACE inhibitor 27 12-58 <0.001

Reperfusion Therapy 2.30 1.38-3.85 0.001

LVD 1 1.98 1.11-3.53 0.021

High-CK2 2.05 1.32-3.20 0.001

Echocardiogram 1.81 1.12-2.91 0.014

CHF 1.92 1.16-3.17 0.011

Diabetes 1.63 1.02-2.62 0.043

Month of study 1.06 1.02-1.11 0.002


Recurrent chest pain 0.64 0.40-1.04 0.074

Aortic stenosis 0.07 0.01-0.34 0.001

c-statistic 0.846

No CHF or LVD1 (N=332)


Reperfusion Therapy 3.27 1.70-6.26 <0.001

Anterior MI 2.41 1.17-4.96 0.017

High-CK2 2.38 1.32-4.29 0.004

Diabetes 2.10 1.06-4.16 0.033

Month of study 1.10 1.05-1.17 <0.001

Age, years

≥80 0.37 0.14-1.00 0.052

70-79 1.57 0.78-3.16 0.202

60-69 0.98 0.47-2.02 0.950

<60 Referent

c-statistic 0.854

Heart failure or LVD1 (N=289)


High-CK2 2.61 (1.36-5.01) 0.004

CHF 2.59 0.98-6.80 0.053

LVD 1 2.31 0.98-5.42 0.055



Aortic stenosis 0.06 0.01-0.37 0.002

c-statistic 0.828 Adjusted for age 1LVEF<40%, 2peak CK>720 U/L


The models stratified by indication varied in several important ways. Associations observed in

the NO CHF/LVD group but not CHF/LVD group included month of the study, age of 80 years

and older, anterior infarction, diabetes and reperfusion. Associations observed in the group with

CHF/LVD group but not in NO CHF/LVD group included a positive association with

echocardiogram and a negative association with aortic stenosis recurrent chest pain.

5.6.4.1 New prescriptions

The logistic regression models for patients not using an ACE inhibitor prior to admission are

shown in Table 5.27. The NO CHF/LVD model was similar to that when all prescriptions were

included. However, the model for patients with CHF/LVD included three additional variables.

The new variables included statin prescription that was positively associated with ACE inhibitor

prescription, and comorbidity index and previous MI that both reduced the odds of ACE

inhibitor prescription.


Table 5.27: Logistic regression models for new ACE inhibitor prescription

Adjusted OR 95%CI χχχχ2 p

All (N=466)

Reperfusion Therapy 2.28 1.34-3.89 0.002

LVD 1 2.10 1.13-3.89 0.019

High-CK2 2.15 1.35-3.42 0.001


CHF 2.49 1.43-4.35 0.001

Statin 1.63 0.98-2.71 0.060

Month of study 1.07 1.03-1.12 0.002

Comorbidity Index 0.84 0.70-1.02 0.072


Aortic stenosis 0.06 0.01-0.65 0.021

c-statistic 0.797

No heart failure/LVD1 (N=268)

Reperfusion Therapy 3.60 1.86-6.95 <0.001

Anterior MI 2.34 1.12-4.89 0.023

High-CK2 2.45 1.35-4.47 0.003

Diabetes 2.01 0.99-4.07 0.053

Month of study 1.11 1.05-118 <0.001

Age, years

>=80 0.32 0.11-0.97 0.045

70-<80 1.59 0.78-3.24 0.205

60-<70 0.89 0.45-1.88 0.769

<60 years Referent

c-statistic 0.793

Heart failure/LVD1 (N=198)

CHF 4.3 1.4-13.8 0.013


LVD 1 2.49 0.93-6.68 0.070

High-CK2 2.35 1.12-4.94 0.024

Statins 2.32 1.09-4.94 0.029


Previous MI 0.37 0.15-0.94 0.036


Aortic stenosis 0.05 0.00-0.53 0.014

c-statistic 0.821

Adjusted for age 1LVEF<40%, 2peak CK>720 U/L


The possible interaction between indication and month of enrolment was analysed using logistic

regression. There was significant interaction between the odds of ACE inhibitor prescription

with month of enrolment for patients with a probable indication (Table 5.28). The odds ratio for

ACE inhibitor prescription with a probable indication in the first month of the study was 0.24

(95% CI, 0.10-0.57, p=0.001) times that in patients with a definite indication. However, for

patients enrolled 12 months later there was no difference in the odds of ACE inhibitor

prescription for patients with a definite or probable indication with an OR=0.85 (95% CI, 0.56-

1.30, p=0.449).

Table 5.28: Logistic regression model for ACE inhibitor prescription

OR 95% CI χ2 p

Definite indication 1

Probable indication 0.21 0.08-0.55 0.001

No indication 0.19 0.06-0.55 0.003

Month 1.02 0.96-1.07 0.502

Definite indication*month 1

Relative indication*month 1.12 1.03-1.22 0.007

No indication*month 1.02 0.94-1.11 0.651

5.6.5 Summary

ACE inhibitor prescribing patterns at the time of discharge changed over the study enrolment

period. Changes included an increase in the proportion of patients prescribed an ACE inhibitor

at discharge and changes in the type of ACE inhibitor prescribed. The proportion of ramipril

prescribed increased from about one in five of all ACE inhibitor prescriptions to one in two

ACE inhibitor prescriptions. Increased prescribing in the cardiology units was not uniform

between cardiologists. The changing rate of ACE inhibitor prescription at discharge was limited

to patients with no heart failure or LVD but with an anterior infarction, peak CK>720 U/L or

diabetes. By the late enrolment period of the study there was no difference in prescription rates

between this group and that with heart failure or LVD.


5.7 Calcium antagonists

A calcium channel blocker was prescribed to 15.6% of patients at discharge.

5.7.1 Type and dose

Of the patients prescribed a calcium antagonist at discharge, 38.8% were prescribed diltiazem

and 30.6% amlodipine. The remainder were prescribed nifedipine 17.4%, felodipine 7.1% and

verapamil 6.1%.

5.7.2 Associations with calcium antagonist prescription

5.7.2.1 Indications and contraindications

Patients prescribed a calcium antagonist had a higher prevalence of angina as shown in Table

5.29. While angina was more prevalent in patients prescribed a calcium antagonist more than

one half of the patients prescribed a calcium antagonist did not have a history of angina.

Table 5.29: Influence of indications on calcium antagonist prescriptions

Calcium antagonist

Yes

N=97

No

524

Percent (n) Unadjusted OR 95% CI χχχχ2 p

Angina on exertion 39.2 (38) 14.7 (77) 2.86 1.82-4.50 <0.001

Unstable angina 8.2 (8) 3.0 (16) 2.85 1.19-6.87 0.015

Any angina 43.3 (42) 16.8 (88) 3.78 2.38-6.00 <0.001

Recurrent chest pain 24.7 (24) 20.2 (106) 1.30 0.78-2.15 0.32

Calcium antagonist prescription was reduced in cardiology compared with non-cardiology for

patients with recurrent chest pain in hospital (Table 5.30). While there were no other significant

differences, the trend was towards reduced prescription in cardiology.

Table 5.30: Influence of angina on calcium antagonist prescription

Cardiology Other

Percent (n) Unadjusted OR 95% CI χχχχ2 p

Angina on exertion 30.3 (27) 42.3 (11) 0.59 0.24-1.46 0.25

Unstable angina 31.2 (5) 37.5 (3) 0.76 0.13-4.49 0.76

Any angina 29.9 (20) 39.4 (13) 0.65 0.29-1.49 0.31

Recurrent chest pain 15.5 (18) 42.9 (6) 0.24 0.08-0.79 0.013



Table 5.31 lists basic demographic and clinical variables with calcium antagonist prescription.

Patients prescribed a calcium antagonist were older, had a higher comorbidity index and

received more medications at discharge. Although use of a calcium antagonist prior to

admission was associated with prescription of a calcium antagonist at discharge, one half of the

patients using a calcium antagonist prior to admission were not prescribed one at discharge.

Other factors associated with calcium antagonist prescription included the comorbidities of

hypertension and cerebrovascular disease as well as a history of CHD. Factors negatively

associated with calcium antagonist prescription included STEMI, anterior site of MI,

reperfusion, LVD and high-CK; all markers of a significant infarction. In addition three

process-of-care factors were also negatively associated with calcium antagonist prescription

including prescription of beta-blockers, echocardiogram and angiogram.


Table 5.31: Calcium antagonist prescription by demographic and clinical variables

Calcium antagonist prescription

Yes No

N=97 N=524

Mean (SD) t-test p Age 71.6 (13.2) 67.9 (14.2) 0.019


Number of discharge drugs 8.3 (2.8) 6.5 (2.3) <0.001

Percent (n) χχχχ2 p Male 55.7 (54) 67.2 (352) 0.029

Public Patient 79.4 (77) 79.0 (414) 0.93

Previous MI 34.0 (33) 17.8 (93) <0.001

Previous CARP 21.6 (21) 10.1 (53) 0.001

Calcium antagonist at admission 62.9 (61) 11.6 (61) <0.001

Current smoker 21.6 (21) 20.4 (107) 0.78

CHF 43.3 (42) 35.3 (185) 0.13

LVD 1 12.4 (12) 25.4 (133) 0.005

AF 17.5 (17) 19.1 (100) 0.72

CVD 22.7 (22) 11.4 (60) 0.003

Hypertension 69.1 (67) 48.8 (256) <0.001

Hyperlipidemia 58.8 (57) 52.5 (275) 0.25

Diabetes 35.0 (34) 26.5 (139) 0.085


Dementia 4.1 (4) 2.7 (14) 0.43

STEMI 45.4 (44) 61.6 (323) 0.003

Anterior site 11.3 (11) 24.2 (127) 0.005

High-CK2 29.9 (29) 42.0 (220) 0.026

VT 3.1 (3) 8.0 (42) 0.086

Cardiac arrest including VF 2.1 (2) 4.8 (25) 0.23


Long-stay3 23.7 (23) 21.6 (113) 0.64

Cardiology 69.1 (67) 76.3 (400) 0.13


Angiogram 34.0 (33) 47.1 (247) 0.017

Reperfusion 14.4 (14) 28.0 (147) 0.005

CARP 16.5 (16) 23.8 (125) 0.11

Echocardiogram 34.0 (33) 50.0 (262) 0.004


Antiplatelet 83.5 (81) 89.7 (470) 0.077

Beta-blocker 49.5 (48) 80.3 (421) <0.001

ACE inhibitor 54.6 (53) 61.4 (322) 0.21

Statins 67.0 (65) 70.2 (368) 0.53 1LVEF<40%, 2peak CK>720 U/L, 3LOS>10 days


5.7.2.3 Independent predictors of calcium antagonist non-prescription

The logistic regression model for non-prescription of calcium antagonist is shown in Table 5.32.

Beta-blocker prescription and an LVEF≤40% were positively associated with non-prescription

of a calcium antagonist. A history of previous MI, a history of angina and use of a calcium

antagonist prior to admission were all associated with reduced odds of not being prescribed a

calcium antagonist.

Table 5.32: Independent predictors for no calcium antagonist prescription


Beta-blocker 8.30 4.43-15.52 <0.001

LVD 1 3.75 1.68-8.34 0.001

Previous MI 0.44 0.23-0.82 0.01

Angina 0.36 0.20-0.66 <0.001

Admission calcium antagonist 0.07 0.04-0.12 <0.001

c-statistic 0.878

Age adjusted 1LVEF<40%

New prescriptions

The logistic regression model for patients not using a calcium antagonist prior to admission is

shown in Table 5.33. This model excludes patients with ventricular tachycardia since none of

these patients was prescribed a calcium antagonist. There were only two associations, beta-

blocker prescription and an echocardiogram which both reduced the odds of a new calcium

antagonist prescription.

Table 5.33: Independent predictors for new calcium antagonist prescription


Beta-blocker 12 5-26 <0.001


c-statistic 0.791

Treatment specialty

The logistic regression models for calcium antagonist prescription by treatment specialty are

shown in Table 5.34. The model for cardiology is shown in the upper panel and the model for

non-cardiology units is shown in the lower panel. While only use of a calcium antagonist prior

to admission was associated with reduced odds of non-prescription of a calcium antagonist in

the non-cardiology model, there were seven independent associations in the cardiology model.

In addition to the associations with prescription of beta-blockers, LVD, a previous MI, a history

of angina and use of a calcium antagonist prior to admission observed in the overall model, a

STEMI and VT were also associated with reduced odds of calcium antagonist prescription.


Table 5.34: Independent predictors for calcium antagonist prescription by specialty


Cardiology (N=467)

Beta-blocker 15 7-33 <0.001

VT 15 1-206 0.042

LVD 1 7 2-22 0.001

STEMI 2.16 1.08-4.31 0.028

Angina 0.35 0.16-0.77 0.009

Previous MI 0.30 0.13-0.67 0.003


c-statistic 0.902

Non-cardiology (N=154)


c-statistic 0.806

Age standardised 1LVEF<40%

5.7.3 Summary

Very few patients were prescribed a calcium antagonist at discharge. In logistic regression

analysis beta-blocker prescription and an assessment of ventricular function increased the odds

of not being prescribed a calcium antagonist.


5.8 Discussion

5.8.1 Overview

The chapter provides a descriptive analysis of prescribing patterns at discharge for secondary

prevention therapies in post-MI patients, from a retrospective review of hospital medical

records. This section compares prescribing patterns in the study setting with those observed in

other settings and discusses the extent to which variations in prescribing reflect evidence based

practice.

At the time of commencement of this study antiplatelets, beta-blockers and statins all had well

established guidelines recommending their use post-MI, while the results of the first landmark

trial showing the benefits of ACE inhibitors in patients with CHD had just been published.

Updated guidelines reflecting this new evidence were published at about the same time as the

data collection phase for prescribing patterns at hospital discharge ceased. This difference

between the three former drugs with well-established guidelines and ACE inhibitors with

evolving guidelines was reflected in the observed prescribing patterns.

The prescribing patterns for antiplatelet agents, beta-blockers and statins included relatively

high prescription rates; decreasing prescription with increasing age and comorbidity; increased

prescribing in cardiology units compared with other units; uniform prescribing among

cardiologists and no change in prescribing over the period of the study. This contrasted with the

pattern ACE inhibitors which included lower prescription rates, a biphasic trend in prescribing

with age, no change in prescribing with comorbidity, no difference in prescribing by treatment

speciality, a wide variation in prescribing between cardiologists and increased prescribing over

the study period. The association between drug prescription and age in the current study were

similar to those observed elsewhere (Tran et al. 2004a; Avezum et al. 2005).

Decreased prescribing with age and comorbidity for antiplatelet agents, beta-blockers and

statins probably reflected an increasing concern about the appropriateness of secondary

prevention of CHD in the elderly or unwell. The increased ACE inhibitor prescription with

increasing age noted in patients up to 80 years of age probably reflected the prescription of ACE

inhibitors to treat heart failure, a condition more common with increasing age. The finding for

antiplatelets, beta-blockers and statins of no change in prescribing over the study and the

uniform prescribing by cardiologists reflected the well established guidelines for these agents in

the post-MI setting while the increased prescribing over the study and the variation in

prescribing between cardiologists reflected the evolving evidence for the use of ACE inhibitors

in the post-MI setting.


The prescribing patterns for the recommended therapies was contrasted with prescribing

patterns for calcium antagonists, not recommended routinely in the post-MI setting. This was

reflected in the relatively small proportion of patients prescribed a calcium antagonist at hospital

discharge. Other observed patterns for calcium antagonist prescription included increased

prescription with increasing age and comorbidity, relatively large variability between

cardiologists and decreased prescribing over the study. The pattern of increased prescription in

older and sicker patients was in direct contrast to the case of antiplatelet agents, beta-blockers

and statins and suggests that the use of calcium antagonists may be largely restricted to patients

not considered suitable for secondary prevention of CHD. The decrease in prescribing over the

study, and the wide variability in prescribing between cardiologists suggests that the prescribing

pattern for calcium antagonists in the post-MI setting reflects differences in opinion among

cardiologists and continues to evolve.

In the following sections prescribing patterns for each drug class is discussed individually,

including comparisons with other studies and the appropriateness of the observed patterns given

the evidence and guidelines.


The high rate of antiplatelet agent prescription observed in the study setting was comparable

with other recent studies including EUROASPIRE II from Europe, ACCEPT from the United

States and Brisbane Cardiac Consortium Study (Pearson et al. 1997c; Euroaspire II Study

Group 2001; Scott et al. 2002).

5.8.2.1 Type and dose

The observed differences in prescription of antiplatelet agents in patients with and without PCI

prior to discharge accorded with the evidence and guidelines for the care of patients post-PCI

(Muller et al. 2000; Smith et al. 2001b; Steinhubl et al. 2002). Similarly the prescription of

moderately low doses of aspirin was in keeping with the lack evidence for using higher doses of

aspirin (Antithrombotic Trialists' Collaboration 2002). The low prescription of clopidogrel also

accorded with both the evidence that this was only marginally better than aspirin (CAPRIE

Steering Committee 1996; Antithrombotic Trialists' Collaboration 2002), and the

recommendations that clopidogrel should be considered for patients unable to tolerate aspirin or

for whom aspirin treatment fails (Gorelick et al. 1999; Antithrombotic Trialists' Collaboration

2002; Hung et al. 2003).

5.8.2.2 Predictors of prescription at discharge

Relative contraindications were strong negative predictors of antiplatelet prescription in

bivariate analysis and could explain all but 19 cases where an antiplatelet was not prescribed at

discharge. There were too few cases to allow any analysis of factors associated with this non-


prescription of antiplatelet agents in patients with no contraindications. However, a number of

patients with a relative contraindication were prescribed an antiplatelet agent. It was therefore

interesting to investigate what, if any, factors were associated with antiplatelet prescription,

while adjusting for relative contraindications in patients who did not undergo a revascularisation

procedure.

Excluding patients undergoing CARP limited the sample size to 481 patients. Stratifying by

treatment speciality gave sample sizes of 336 and 153 in the cardiology and non-cardiology

models respectively. Any analysis was therefore limited by a lack of precision related to the

relatively small sample size, particularly given the relatively small number of patients not

prescribed an antiplatelet agent.

In multivariate analysis, the strongest negative association in all the models considered was

prescription of anticoagulants, reducing the odds of antiplatelet agent prescription by a factor of

about 20. Anticoagulants are recommended to prevent thromboembolism in high-risk patients.

While the combined use of warfarin with aspirin is not contraindicated per se, there is an

increased risk of bleeding. Bleeding complications during the hospital episode also had a

negative effect on prescription of antiplatelets. In contrast, the presence of peptic ulcer disease

was not associated with prescription of an antiplatelet agent in multivariate regression, despite

the strong association observed in bivariate analysis. Given both the availability of different

preparations of aspirin and of different antiplatelet agents, particularly clopidogrel, peptic ulcer

disease should not be considered a contraindication to use of an antiplatelet agent and this was

reflected in the prescribing pattern. The finding that comorbidity index was negatively

associated with prescription of antiplatelets accords with the notion that general health status

might reasonably be expected to influence the initiation of preventive therapy for CHD.

Differences between the various regression models suggested that while treatment speciality

was not an independent predictor of antiplatelet prescription in the overall model, there may be

some subtle differences in prescribing practices between specialties. The association with prior

use of an antiplatelet agent use and prescription of an antiplatelet agent at discharge in the non-

cardiology model suggested some reluctance in non-cardiology units to prescribe an antiplatelet

agent to patients not already using antiplatelets prior to admission. The positive association

with beta-blockers and ST-elevation in the overall model but not in either the cardiology or non-

cardiology model may be explained by the reduced precision of the latter models. Alternately

the association with prescription of beta-blockers and ST-elevation may be surrogate markers

for treatment in cardiology with both these factors more prevalent in cardiology units.

In this study a high prevalence of antiplatelet prescription at discharge was observed with few

independent predictors of antiplatelet prescription. Other studies examining independent


predictors of aspirin prescription showed both similarities and differences with the current

study. Comparison with other studies is problematic given different patient samples and

different time frames. Table 5.35 shows factors associated with antiplatelet agent prescription

in the current study and compares these with other studies. Three additional factors, found to be

associated in at least two other studies are also included. As observed by Krumholz et al,

“Aspirin was most strongly associated with a constellation of care patterns”. This included

revascularisation procedures and concomitant prescription of beta-blockers. As in the current

study Krumholz also observed an inverse relationship with overall health status. In contrast to

the other studies there was no relationship with prior use of aspirin in the current study, a

consequence of the almost universal prescription of antiplatelet agents. Two of the earlier

studies also found inverse relationships with heart failure and diabetes. No association between

either heart failure or diabetes with antiplatelet prescription was observed either in the current

study, or in the study by Danchin et al, probably reflecting the more widespread adoption of

antiplatelets in these later groups.

Table 5.35: Comparison of factors associated with aspirin prescription

This study Lamas1 Krumholz2 Spencer3 Danchin4

% Prescribed 89 59 76 20-80 90

Data collected 2000-2001 1987-1990 1992-1993 1986-1997 1998

Variables

Anticoagulant Negative Negative n/a Not included Not included

Comorbidity/LOS Negative Not included Negative Not included Not included

Revascularisation Positive Positive Positive Not included Positive

Beta-blockers Positive Not included Positive Not included Not included

ST elevation Positive Not included Not included Not included Positive

Prior use None Positive Positive Not included Positive

Heart failure None n/a Negative Negative None

Diabetes None Negative Negative None None 1 (Lamas et al. 1992), 2 (Krumholz et al. 1996), 3(Spencer et al. 2001),4(Danchin et al. 2002)

5.8.3 Beta-blockers

The prescription rate for beta-blockers in the study setting was comparable to EUROASPIRE II,

and the Brisbane Cardiac Consortium Study (Euroaspire II Study Group 2001; Scott et al.

2002), while the rate of prescription was somewhat less (58%) in the United States ACCEPT

study (Pearson et al. 1997c). A recent study from the United States found a small but

significant increase in beta-blocker prescription at the time of hospital discharge between 1998-

99 and 2000-01 in post-MI patients (Jencks et al. 2003). This increase, from 72% to 79%

represented the greatest improvement in inpatient care from 22 quality indicators examined.



While the rate of prescription was relatively high, the doses prescribed were relatively low. The

most common dose of metoprolol prescribed was one quarter of the dose used in the landmark

clinical trials, while the most common dose of atenolol prescribed was one half the doses used

in the landmark clinical trials (Yusuf et al. 1979; Hjalmarson et al. 1981). Since the doses at

discharge may not reflect the dosages in long-term care the issue of dosages prescribed is

explored later when examining drug prescription ambulatory care. In the current setting, 26%

of patients prescribed a beta-blocker were prescribed atenolol, a drug for which there is little

evidence of the benefits in the post-MI setting (Freemantle et al. 1999).

5.8.3.2 Predictors of prescription at discharge

While relative contraindications were negatively associated with beta-blocker prescription in

bivariate analysis, many patients with relative contraindications were still prescribed beta-

blockers. Therefore all patients were included in the multivariate analysis to determine

independent predictors of beta-blocker prescription while adjusting for contraindications. While

the presence of relative contraindications particularly chronic airways limitation, heart block

and bradycardia, had a strong negative influence on beta-blocker prescription the strongest

influence on beta-blocker prescription was the use of beta-blockers prior to admission.

When predictors of beta-blocker prescription were considered in those patients not using beta-

blockers prior to admission a previous history of myocardial infarction or a diagnosis of

hypertension were negatively associated with beta-blocker prescription. These associations

initially appeared at odds with indications of beta-blockers both as antihypertensive agents and

their role in post-MI patients. However, these probably reflected patients with an intolerance to

beta-blockers that was known at the time of admission. This suggested that the strong influence

of prior beta-blocker use reflected previously observed intolerance to beta-blockers in patients

prior to the index admission.

The negative association between beta-blockers and calcium antagonists was predictable given

the common indications of hypertension and angina. However, given the known benefits of

beta-blockers post-MI and the lack of evidence of benefit of calcium antagonists post-MI, this

finding would be of concern without appropriate indications for the use of calcium antagonists;

that is, for the treatment of angina refractory to other treatment in the absence of heart failure

(Kizer et al. 2001).

The negative association of beta-blocker prescription with older age has been a consistent

observation in all studies. It has been suggested that there is a reluctance to prescribe beta-

blockers to elderly patients for fear of adverse effects (Howard et al. 2000). The concern over

possible adverse effects must be balanced against the greater benefit in these higher risk patients


(Avezum et al. 2005). The issue of when secondary prevention is appropriate in an elderly

population is complex and involves many moral and financial considerations that are beyond the

scope of this thesis. Similarly, the association with increased comorbidities and long hospital

stay involves a complex discussion about when it is appropriate to prescribe preventive

treatment.

Reperfusion therapy and concomitant statin prescription were also associated with beta-blocker

prescription and reflected the process of care. Treatment speciality was not associated with

beta-blocker prescription in the overall model however, differences between the cardiology and

non-cardiology models suggested possible differences in prescribing patterns with treatment

speciality. The most notable difference was the co-prescription of statins and beta-blockers in

the non-cardiology model and the positive association with lipid measurement. The

measurement of lipid levels and prescription of statins are key elements in post-MI secondary

prevention and suggested that in non-cardiology units the prescription of beta-blockers was

associated with the decision to instigate other preventive therapy. However, it fails to inform on

what these criteria for eligibility for secondary prevention in non-cardiology patients might be.

Similarly, the observation in the non-cardiology model of an association with STEMI and beta-

blocker prescription does not accord with the guidelines but rather suggested that non-

cardiology specialists are either unaware of the guidelines recommending beta-blocker use in

patients or are reluctant to broadly apply the guidelines in their patient group.

In the current study setting there were 10 independent predictors of beta-blocker prescription,

which accounted for a significant proportion of the variation in beta-blocker prescription. This

suggested that in the current setting the decision to prescribe or not prescribe beta-blockers is

based on a limited number of clinical variables. This contrasts with an earlier study by

Krumholz et al found that after excluding patients with contraindications, there were 25

independent associations with beta-blockers (Krumholz et al. 1998).

Other studies to identify predictors of beta-blocker prescription are compared with the current

study in Table 5.36. Comparison between studies is problematic given the different populations

and the wide scope of candidate variables considered. The most striking similarity between the

studies was the influence of age on beta-blocker prescription, although the break point between

the studies was different. In the current study the breakpoint was 80 years while in the Danchin

study the breakpoint was 75 years while the earlier studies by Krumholz and Viskin found a

graded response with increasing age. Similarly Beck et al analysed age as a continuous variable

and found a negative relationship. The most striking difference between the current study and

earlier studies is the lack of negative relationship between heart failure and beta-blocker

prescription. The lack of association between heart failure and beta-blocker prescription in the

current study reflected newer evidence suggesting that beta-blockers are not contraindicated in


patients with heart failure when heart failure treatment has been optimised (Yancy 2001; Foody

et al. 2002; Gheorghiade et al. 2003). The lack of association with other indications for beta-

blockers, namely hypertension and angina, observed in the current study and in the studies by

Beck et al and Danchin et al probably reflected the more widespread use of beta-blockers.


Table 5.36: Comparison of predictors of beta-blocker prescription

This study Viskin1 Krumholz2 Spencer3 Beck4 Danchin5

% Prescribed 75 58 50 50-75 74-78 68

Data collected 2000-2001 1993 1994-95 1986-97 1996-98 1998

Variables

CAL Negative n/a n/a Not included Not included Not included

Heart block Negative n/a n/a Not included Negative Not included

Bradycardia Negative n/a n/a Not included Not included Not included

Calcium antagonist Negative None Negative Not included Not included Not included

PVD Negative Not included Not included Not included Not included Negative

Comorbidity/LOS Negative Not included Negative Not included Not included Not included

Age, Negative Negative Negative Negative Negative Negative

Statins Positive Not included Not included Not included Not included Not included

Reperfusion therapy Positive Not included Positive Not included Not included Not included

Beta-blocker at admission Positive Not included n/a Not included Not included Positive

CHF None Negative Negative Negative Negative Not included

Angina None Not included Positive Positive None None

Hypertension None Not included Positive Positive None None

Male None None None Positive Positive Positive

LVD None Negative Negative Not included Not included Negative

Diuretics Not included Negative Negative Not included Not included Not included

Revascularisation None None Negative Not included Not included Positive 1(Viskin et al. 1995),2 (Krumholz et al. 1999), 3(Spencer et al. 2001), 4(Beck et al. 2001), 5(Danchin et al. 2002)


5.8.4 Statins

The 70% prescription rate for statins observed in this study was higher than that observed in

some recent studies, including 32% in the 1998-1999 data from the NRMI (Fonarow et al.

2001a), 42% in EUROASPIRE II (Euroaspire II Study Group 2001) and 35% in PREVINIR

(Danchin et al. 2002). More comparable results were reported by an intervention study, which

found 67% of post-intervention patients were prescribed lipid lowering therapy (Mehta et al.

2000a). Similarly, a German study of patients discharged from an inhospital rehabilitation

program found a rate of 69% (Willich et al. 2001). Two related Australian studies reported

prescription rates of 56% and 63% respectively (Scott et al. 2000b; Mudge et al. 2001). A more

recent post-intervention study from the same group found a prescription of lipid lowering

therapy in 68% of all patients and 82% in patients with TC greater than 4 mmol/L (Scott et al.

2002). In the current study, 75% of patients with a TC greater than 4 mmol/L were prescribed

therapy. Therefore prescribing practices in the current setting were similar to those in at least

one other Australian setting. Similarly, Fonarow et al following the implementation of the

CHAMP quality improvement initiative found 86% of patients with established CHD were

prescribed a statin prior to discharge (Fonarow et al. 2001b).


In the current setting statins were used almost exclusively for lipid lowering with atorvastatin,

pravastatin and simvastatin accounting for over 90% of all statins prescribed. While pravastatin

and simvastatin have strong clinical evidence to support their use (Scandinavian Simvastatin

Survival Study Group 1994, Sacks, 1996 #188; Long-term Intervention with Pravastatin in

Ischaemic Disease (LIPID) Study Group 1998; Heart Protection Study Collaborative Group

2002), evidence for atorvastatin at the time of the study was limited to one short term trial

(Schwartz et al. 2001). The relatively high use of atorvastatin may have been due to studies

suggesting that atorvastatin is more efficacious at lowering lipid levels than the older statins

(Jones et al. 1998; Malhotra et al. 2001; Asztalos et al. 2002; Hippisley-Cox et al. 2003).

The mechanism of action and pharmacokinetics of statins are such that the recommendation is

for statins to be used in the evenings thus increasing efficacy (Knopp 1999; Martin et al. 2002).

When dosing of simvastatin was changed from night to morning a significant increase in lipid

levels was observed (Wallace et al. 2003). Atorvastatin has a long half life compared with the

older statins (Iliff 2002). This is associated with a prolonged inhibition of cholesterol synthesis

(Naoumova et al. 1997) leading to the conclusion that atorvastatin is equally effective whether

taken morning or night. This may explain the finding in the current study that atorvastatin was

much more likely than other statins to be prescribed in the morning or to have no time specified.


It is possible that at least some of the preference for atorvastatin is explained by this apparent

flexibility in time of dosing.

When statin doses prescribed to patients using a statin prior to admission were compared with

doses for newly prescribed statins no difference was observed for pravastatin and simvastatin

but there was a small, significant increase in the dose of atorvastatin prescribed to patients using

a statin prior to admission. This finding was somewhat surprising given the reports of the

greater efficacy of atorvastatin in reducing lipid levels with a higher proportion of patients

achieving target lipid levels at 10 mg of atorvastatin (Jones et al. 1998; Andrews et al. 2001;

Asztalos et al. 2002; Athyros et al. 2002). This observation was not explained by a change to

atorvastatin for patients using other statins prior to admission. The finding that doses of

pravastatin and simvastatin were similar for patients with new and ongoing scripts prescriptions

suggested that little dose titration had taken place in patients with ongoing scripts of these drugs

while there was some evidence of titration of atorvastatin in at least some patients.

5.8.4.2 Predictors of statin prescription

In the current study very few variables accounted for almost all the variation in statin

prescription. As might be expected a diagnosis of hyperlipidemia was positively associated

with statin prescription as was cholesterol level when this was included. When cholesterol level

was not included, having a cholesterol measurement was associated with statin prescription

probably reflecting the high proportion of patients with cholesterol levels above optimal levels.

In bivariate analysis there was a clear relationship between prescription of lipid lowering

therapy and increasing TC, LDL-C however, there was still significant under treatment based on

the Australian Lipid Management Guidelines (National Heart Foundation of Australia et al.

2001). The gradient observed in bivariate analysis for lipid levels and statin prescription

suggested that the decision to prescribe statins was not based solely on the lipid levels with clear

cut off points, as outlined in the guidelines. This could result from various clinicians working to

different cut points or could result from other factors in the decision making process.

Other variables associated with statin prescription were related to the care received. These

included positive associations with treatment in a cardiology unit and prescription of

antiplatelets and beta-blockers. This constellation of care pattern suggested a group of patients

were either deemed eligible for secondary prevention or only a subset of patients received

appropriate care. The strong influence of being treated in cardiology suggests a more rigorous

approach to lipid lowering by cardiologists and a probable underprescribing of statins in patients

not treated in cardiology. However, given the marked differences between patients treated in

cardiology and other patients, it is also possible that there may be some patient factors that have

not been controlled for.


Previous studies examining predictors of lipid lowering therapy reported many more

independent predictors than found in the current study. For example, a study using NRMI data

from 1998-99 found a variety of clinical, demographic, treatment and process-of-care factors

that significantly influenced treatment use of lipid lowering medication (Fonarow et al. 2001a).

One explanation for the lack of associations in the present study may be the relatively small

sample size compared with the NRMI that included data from more than 100,000 patients.

More likely, however, is the more widespread use of lipid lowering therapy in the present study

compared with the NRMI study, which found that only 32% were prescribed lipid lowering

therapy at discharge compared with 70% in this study.


ACE inhibitors were the least commonly prescribed of the secondary prevention therapies with

just 60% of patients prescribed an ACE inhibitor at hospital discharge, although there was a

significant increase in ACE inhibitor prescribing at hospital discharge over the study. The

evolving role of ACE inhibitors in CHD makes comparison of the current study with earlier

studies somewhat difficult. However, the study by Scott et al conducted during 2000 and 2001

provides comparison with another Australian setting. Scott et al found that 61% of all patients

hospitalised with an acute coronary syndrome were prescribed an ACE inhibitor at hospital

discharge. The proportion increased to 73%, when only patients with an LVEF<40% were

considered, compared to 79% in the current study. Thus it appears that prescribing practices in

the current study setting are similar to those in another Australian setting.

5.8.5.1 Increased prescription of ACE inhibitors

The increased prescribing observed in this study was not uniform across the hospitals, but was

restricted to the cardiology units, perhaps reflecting the well documented observation of a

differential change in clinical practice with specialists more readily adopting new evidence

compared to generalists (Hlatky et al. 1988; Ayanian et al. 1994; Soumerai et al. 1998; Kizer et

al. 1999; Go et al. 2000). The observation of differences in prescribing for ACE inhibitors even

within cardiology was consistent with the evolving role of ACE inhibitors in CHD patients and

suggested differential adoption of new evidence even within a group of cardiology specialists

working within the same institution. It raises the question of the effect of this differential

prescribing on both the junior medical staff working in the cardiology unit under the direction of

multiple cardiologists, as well as the influence on primary care doctors who are responsible for

the ongoing care of these patients following hospital discharge. Local consensus and

correspondence with hospitals and specialists have been shown to be important influences on

primary care physicians (Armstrong et al. 1996; Pryce et al. 1996; Allery et al. 1997; Fairhurst

et al. 1998).


The increase over time observed in the current study represents part of a long-term trend in ACE

inhibitor prescription with evolving evidence. Using data from the Cardiovascular Cooperative

Project from 1992-93, Krumholz et al observed an increase in ACE inhibitor prescription from

40% before publication of the SAVE trial to 47% after the publication of the SAVE trial

(Krumholz et al. 1997). A later study following further evidence of the benefits of ACE

inhibitors post-MI and the release of the AHA/ACC guidelines for the management of MI (1996

guidelines) found an increase in ACE inhibitor prescription in post-MI patients from 25% in

1994 to 31% in 1996 (Barron et al. 1998a).

The timing of the current study, commencing just after the release of the results of the HOPE

study, raised the question of the direct influence of this study on ACE inhibitor prescribing

patterns in the current setting. The principal finding of the HOPE study was that ACE inhibitors

reduced the risk of cardiovascular events in all patients at risk patients even with no known left

ventricular dysfunction (Yusuf et al. 2000). Therefore, the observation of a 10% increase in the

odds of ACE inhibitor prescription for every month since the start of the study in patients with

known heart failure or LVD suggested an influence of the HOPE study. However, ACE

inhibitor prescription was not uniform throughout this group as might be expected from the

HOPE study, but rather was restricted to patients with an anterior location MI, a large infarction

or diabetes, all recognised as indications for ACE inhibitors prior to the HOPE study. This bias

towards patients with indications for ACE inhibitors as defined prior to the HOPE study

suggested ongoing secular increase in ACE inhibitor prescription rather than a direct influence

of the HOPE study. It is probable however, that the finding of the HOPE study, while not

impacting on the prescription of ACE inhibitors across the board, did reinforce the benefits of

ACE inhibitors in the highest risk patients.

In their study, Barron et al found that when patients were divided into three mutually exclusive

groups based on the expected absolute benefit from ACE inhibitor therapy, prescriptions

increased in all three groups although prescription within the groups was proportional to the

expected benefit, decreasing from 43% for patients with an LVEF≤40% or evidence of heart

failure to 26% for patients with an anterior infarction to 16% in the remainder (Barron et al.

1998a). This contrasted with the current study where there was no increase in prescription of

ACE inhibitors in the group with an absolute benefit and a differential increase in the remainder

strongly influenced by the size and location of the myocardial infarction. This suggested a

“level of saturation” has been reached for patients with heart failure or LVD.


There were two important observations regarding the type and dose of ACE inhibitors

prescribed. Firstly, the relative increase in the proportion of ramipril prescribed and, secondly


the relatively low dosages of ACE inhibitors prescribed in patients who were using ACE

inhibitors prior to admission.

The increase in the relative proportion of ramipril, the drug used in the HOPE study, suggested

an influence of this study. Two recent Canadian studies using administrative data have also

noted a marked increase in the proportion of ramipril prescribed, which was ascribed to the

HOPE study (Hemels et al. 2003; Tu et al. 2003). The increase in the relative proportion of

ramipril observed by Hemels et al from 9% to 33% of all ACE inhibitor prescription filled from

1999 to 2001 was very similar to the changes observed in the current study (Hemels et al.

2003). If the increase in ACE inhibitors is just a continuum of an ongoing increase of ACE

inhibitors rather than a specific response to the HOPE study, then the increase in the relative

proportion of ramipril prescribed suggests an influence of therapeutic marketing following the

HOPE study on the choice of ACE inhibitor, but no change in the criteria used to prescribe ACE

inhibitors.

While the doses of ACE inhibitors prescribed to patients using ACE inhibitors prior to hospital

admission were significantly higher than doses for newly prescribed ACE inhibitors the ongoing

dosages of ACE inhibitors were still substantially less than those used in the various clinical

trials. For example, only 21% of ongoing scripts for ramipril for 10mg, the dose used in all the

ramipril trials. The findings were similar for perindopril and trandolapril. The issue of dosages

used is explored further in Chapter 7.

5.8.5.3 Predictors of ACE inhibitor prescription

The role of ACE inhibitors in post-MI patients changed over the period of the study. At the

time of commencing the medical record review, guidelines strongly recommended use of ACE

inhibitors in post-MI patients with heart failure or left ventricular dysfunction, although also

recommending ACE inhibitors at least in the short term for other high risk patients (ACE

Inhibitor Myocardial Infarction Collaborative Group 1998; AHA/ACC 1999). At the time of

finishing the medical record review guidelines had been updated to recommend ongoing use of

ACE inhibitors in all post-MI patients (Smith et al. 2001a). It was therefore of interest to

include all patients in the logistic regression analysis to determine what factors were associated

with ACE inhibitor prescription, while adjusting for indications and contraindications,

particularly when the analysis was stratified by various levels of indications. Although the

stratified analysis resulted in relatively small sample sizes and was therefore limited by a lack of

precision the stratified analysis was useful in demonstrating the changes in prescribing patterns.

In the overall analysis symptomatic heart failure, known LVD, anterior infarction, high peak

CK, diabetes and month of the study were all independent predictors of ACE inhibitor

prescription. The observation that in the stratified analysis, month of the study was only


associated with ACE inhibitor prescription in the group with NO CHF/LVD confirmed the

observations in the bivariate analysis that showed no increase in prescriptions over the

enrolment period in patients with CHF/LVD. Similarly the positive association with anterior

infarction, high peak CK, diabetes and ACE inhibitor prescription in the group with NO CHF

/LVD suggested that in the absence of this definite indication for ACE inhibitors the presence of

anterior infarction, high peak CK and diabetes influence the decision to prescribe ACE

inhibitors. The interaction between month of the study and the presence of anterior infarction,

high peak CK and diabetes suggested that the decision to prescribe based on the presence of

anterior infarction, high peak CK and diabetes increased over the enrolment period.

In the CHF/LVD model both symptomatic heart failure and known LVD were independent

predictors of ACE inhibitor prescription with no evidence of interaction between heart failure

and LVD in either bivariate or multivariate analysis. This suggested a simple additive effect

and underuse in either symptomatic heart failure with no known LVD or known LVD with no

symptomatic heart failure.

Although bivariate analysis suggested that overall prescription of ACE inhibitors increased in

cardiology units, but not other units, this association was not maintained in logistic regression

analysis. However, this may have been due more to a lack of precision in the logistic regression

models rather than a lack of association with treatment speciality, because the differences

observed in bivariate analysis were unlikely to be explained by changing patient characteristics

over time. The association with reperfusion therapy and ACE inhibitor prescription suggested

some differences in patterns of care. Since reperfusion therapy was almost exclusively reserved

for patients treated in cardiology, reperfusion therapy would to some extent be a proxy for

treatment in cardiology.

5.8.6 Calcium antagonists

The inclusion of calcium antagonists in this analysis provided a counterpoint to the

recommended secondary prevention therapies. While calcium antagonists are cardiac drugs

used both in the treatment of hypertension and angina there is no evidence that these drugs

reduce the risk of cardiac events in post-MI patients and, therefore, are recommended only for

patients with angina unable to use beta-blockers. In particular, there is some concern about the

use of nondihydropyridines in patients with poor ventricular function (Kizer et al. 2001). The

relatively low proportion of patients prescribed a calcium antagonist at discharge and the trend

of decreasing use over the study accord with the current guidelines for use of drugs in post-MI

patients, which suggest that beta-blockers should be used as first line therapy for hypertension,

and beta-blockers as first line therapy for angina. Also, in accord with these guidelines, were


the observations that patients prescribed calcium antagonist were more likely to have angina and

less likely to have left ventricular dysfunction.

5.8.7 Limitations

The main limitation of this study was the possible lack of sensitivity in determining independent

predictors of drug prescription due to the relatively small sample size, particularly in stratified

analyses. The high proportion of patients prescribed secondary prevention therapies;

particularly antiplatelet agents and beta-blockers, exacerbated the problem of relatively small

sample sizes. Although this indicated a near optimal prescribing pattern, it limited the

discriminative power of the multivariate models. Finally, while the rationale for data collection

was to allow for adjustment of all factors that might impact on prescription of secondary

prevention therapies, it is possible that some unobserved variables impacted on prescribing

patterns.


5.9 Summary

This chapter provided a descriptive analysis of prescribing patterns at hospital discharge for

drugs recommended in the secondary prevention of CHD in post-MI patients. The main

findings included:

• An antiplatelet agent was prescribed to 89% of all patients increasing to 96% of patients

with no contraindication.

• In addition to the negative influence of contraindications on antiplatelet prescription

increasing comorbidity and a long hospital stay (>10 days) also negatively influenced

prescription while the co-prescription of beta-blockers and a STEMI were positively

associated with antiplatelet agent prescription.

• Beta-blockers were prescribed to 75% of all patients increasing to 89% of patients with no

relative contraindications. CAL, bradycardia, heart block, calcium antagonist prescription,

increasing comorbidity and being 80 years or older were all negatively associated with beta-

blocker prescription. Concomitant statin prescription and reperfusion therapy were both

positively associated with beta-blocker prescription.

• Statins were prescribed to 70% of all patients but the proportion increased with increasing

lipid levels up to 93% with TC ≥6 mmol/L.

• Statins were prescribed to 82% of cardiology patients compared with 32% of patients

treated in other units.

• In addition to the influence of lipid levels and treatment in cardiology, co-prescription of

beta-blockers also increased statin prescription.

• An ACE inhibitor was prescribed to 60% of all patients increasing to 70% in patients with

symptomatic heart failure or known LVD.

• ACE inhibitor prescription increased significantly over the period of the study from 49% in

the first quarter to 70% in the last quarter.

• The increase in ACE inhibitor prescription was restricted to patients with no symptomatic

heart failure or LVD but with at least one of; peak CK greater than four times normal,

anterior infarction or diabetes.

• In contrast to the recommended secondary prevention therapies calcium antagonists were

prescribed to only 16% of post-MI patients.


5.10 Conclusions

Prescribing patterns at discharge in post-MI patients suggested that in the study setting, practice

generally followed the guidelines for the treatment of post-MI patients. A notable exception

was the prescription of statins where a significant proportion of patients not prescribed therapy

at discharge had less than optimal lipid levels and prescribing practices were significantly

different between cardiology and other units. ACE inhibitor prescription increased over the

study period, however this appeared to reflect an ongoing increase in ACE inhibitor use in

higher risk patients rather than the specific influence of recent trials, which suggested that ACE

inhibitors would benefit all patients with CHD.

233 Chapter 6: Discharge planning and transition of care

CHAPTER 6

DISCHARGE PLANNING AND TRANSITION OF CARE

6.1 Introduction

While the long-term management of post-MI patients lies with the patient and the primary care

provider, the hospital medical team can influence this through the treatment regimen instigated

at the time of the discharge and, by enabling appropriate transition of care through effective

communication with the patient and general practitioner. This chapter is concerned with how

effectively the treatment plan is communicated to the patient and the general practitioner.

Concern that medication changes made in hospital are not maintained in the community are

reflected in the Australian Pharmaceutical Advisory Council (APAC) national guidelines to

achieve the continuum of quality use of medicines between hospital and community (Australian

Pharmaceutical Advisory Council 1998). These guidelines outline seven principles

recommending medication discharge planning and specific communications with patients and

their general practitioners. A study suggested that these guidelines have been less than

optimally implemented (Mant et al. 2001), while a program attempting to increase adherence

with the guidelines met with limited success (Mant et al. 2002).

6.1.1 Objectives

The primary objective of this chapter was to describe current practices in discharge planning

and transition of care and to identify gaps in optimal communication of the care plan to both the

patient and the primary care provider in the study setting.


Section 6.2 describes discharge planning and transition of care from the patient perspective

using data from the early patient questionnaire which provided details of education and

counselling prior to discharge. Section 6.3 describes the transition of care from the GO

perspective using data from the early general practitioner survey that provided information on

the completeness and quality of the transition of care from the hospital to the primary care

provider. Section 6.4 describes the strategies and barriers to best practice for discharge planning

and the transition of care provided by hospital staff through focus group and interviews. All

these findings are discussed in Section 6.5. Sections 6.6 and 6.7 provide a summary and

conclusions respectively.


6.2 Patient perspective

Cardiac rehabilitation programs should include educational and supportive elements to facilitate

lifestyle change, adherence to advice and long-term maintenance of change in order to promote

secondary prevention of CHD (Gobble et al. 1999). Cardiac rehabilitation should be

commenced in hospital and continued with ambulatory outpatient rehabilitation ultimately

leading to a lifestyle maintenance phase. In addition to early mobilisation, other elements of

inpatient cardiac rehabilitation relate to three elements of secondary prevention. Education,

discussion and counselling, should include information about medications and identification and

modification of risk factors. Discharge planning, includes provision of patient information

about medications and details of who to contact with questions. Finally, patients should be

referred to an outpatient rehabilitation program.

The data in this section come from the early (3-month) patient follow-up questionnaire. As

reported in Chapter 4, 292 of 364 questionnaires were completed (80% response rate).

Differences between responders and non-responders noted in Chapter 4 included lower

prevalence of prior MI or CHD and diabetes among responders. While patient self-reports may

not reflect what actually happened between the patient and the provider these responses provide

a measure of the effectiveness of any information provided and may be a good indication of the

salience of the information provided to the patient.

6.2.1 Prescriptions at discharge

Patient reported drugs prescribed at discharge are shown in Table 6.1 together with the

sensitivity and specificity of the patient questionnaire to collect information about drug

prescriptions at discharge.

Table 6.1: Medications at discharge reported in the early patient survey

Questionnaire compared with hospital record

Drug class Percent (n) Sensitivity Specificity

Aspirin 85.6 (250) 92.1 84.0

All Antiplatelet agents 89.4 (261) 93.8 82.4

Beta-blockers 79.8 (232) 92.6 84.0

Statins 81.2 (237) 95.9 80.8

ACE inhibitors 58.6 (171) 92.2 95.5

Calcium antagonists 13.4 (39) 81.6 96.8

Angiotensin receptor blockers 3.8 (11) 100.0 99.6

Anticoagulants 9.6 (28) 84.6 98.5

Diuretics 21.6 (63) 89.6 96.3

Antiarrhythmics 9.2 (27) 95.6 98.5

Diabetic medications 21.2 (62) 87.5 99.2


Angina medications 49.6 (145) 74.5 93.8

6.2.2 Information about medications

Information provided to patients about new medications is shown in Table 6.2. Doctors and

nurses were the most common source of information about medications while only 13% cited

the clinical pharmacist as a source of information. There were significant differences between

the two hospitals with more patients at the affiliate hospital receiving no education about

medications and fewer patients receiving information about medications from a nurse compared

with the tertiary hospital.

Very few respondents (7%) reported receiving no information. While about 80% of respondents

reported being told about the purpose of the medication and when to take it, only 30% reported

being given information about the side effects of medications. Only 12% had a discussion about

strategies for remembering to take medications. Significantly more patients at the tertiary

hospital were given information about when to take their medicines compared to the affiliate

hospitals with a trend in the same direction for strategies to remember their medication.

Table 6.2: Information provided about medications in hospital

Hospital

All Tertiary Affiliate

Percent (n) Percent χχχχ2 p

Health professional N=292 N=218 N=74

Doctor 47.3 (138) 49.1 47.2 0.788

Nurse 46.9 (137) 54.7 29.2 <0.001

Pharmacist 13.0 (38) 15.1 8.3 0.145

Other health professional 11.6 (34) 13.7 6.9 0.128

Not otherwise specified 5.8 (17) 6.1 5.6 0.857

None 7.2 (21) 4.2 16.7 <0.001

Type of information N=271 N=209 N=62

Purpose of medication 81.0 (213) 82.3 76.7 0.332

When to take medication 79.5 (209) 83.2 66.7 0.005

Strategies for remembering 12.2 (32) 14.3 5.0 0.053

Side effects of medication 29.7 (78) 30.5 26.6 0.564

Nothing 1.9 (5) 2.0 1.7 0.880

Forty-nine patients (17% of all respondents) provided some comment on the information

provided about medications. This included 14 (28% of all comments) with positive comments

using words such as “excellent” and “helpful” particularly with regard to the written information

and discharge medication list. Comments about the lack of explanation about the purpose of the

medicine suggested that some patients, at least, wanted a higher level of explanation “protect my


heart” - a bit paternalistic”, “ not given any specific explanation… only that they were to reduce

blood pressure and control heart beat” and “just told it was for my heart”.

Lack of information about side effects was reflected in some comments provided “Not much

said about long term effects”, “ Would like to know what if any long term effects of medications”,

“ I’m not sure of the side effects”, “ Limited information about side effects; effects of the

combination of medicines not explained”

In two instances comments related to changes in medication dosages that were not explained.

There were also several comments about alternative sources of information including the

community pharmacist, general practitioner and information inside the packets. Other more

general comments included “did not get any”, “ not given much information at all” and “just

given scripts”.

6.2.3 Risk factor modification

Table 6.3 compares risk factor interventions by hospital type. The highest rate of intervention

was for smoking (in smokers) followed by cholesterol levels and inactivity. Risk factor

interventions are explored further in Chapter 8.

Table 6.3: Proportion of patients reporting interventions about risk factors

Discussion Discussion with no other intervention

Hospital Hospital

All Tertiary Affiliate All Tertiary Affiliate


Smoking 90.0 89.1 92.3 0.64 42.2 35.9 57.7 0.058

Hyperlipidemia 64.0 67.0 55.4 0.073 8.0 8.2 7.3 0.85

Blood pressure 45.2 47.7 37.8 0.14 8.3 7.7 10.7 0.61

Blood glucose 21.6 22.5 18.9 0.52 25.4 26.5 21.4 0.70

Overweight 24.7 27.1 17.6 0.10 22.2 23.7 15.4 0.51

Inactivity 53.1 57.8 39.2 0.006 21.9 19.0 34.5 0.07

6.2.4 Written Information

The proportion of patients with written information provided at discharge is shown in Table 6.4.

A discharge medication list and a discharge summary were reported by 80% and 75% of

patients respectively. Significantly more respondents from the tertiary hospital reported

receiving a discharge medication list, a copy of the discharge summary and a contact number for

the hospital.


Table 6.4: Written information provided at discharge

Hospital

All

N=292

Tertiary

N=218

Affiliate

N=74


Discharge medication list 80.1 (234) 88.5 55.4 <0.001

Information about risk factors 50.7 (148) 52.8 44.6 0.22

Information about medications 47.6 (139) 49.5 41.9 0.26

Details about support group 25.3 (74) 27.5 18.9 0.14

A contact phone number at the hospital 37.7 (110) 42.2 24.3 0.006

Other information 5.8 (17) 6.4 4.0 0.45

Copy of discharge summary 74.7 (218) 78.4 63.5 0.016

6.2.5 Outpatient cardiac rehabilitation

Reported referrals at discharge are shown in Table 6.5. Overall 26% of patients reported a

referral to some follow-up program and 20% were referred to an allied health professional for

follow-up. Significantly more patients from the tertiary hospital reported referral to an exercise

program and a dietician.

Table 6.5: Reported referrals at discharge

Hospital

Referral

All

N=292

Tertiary

N=218

Affiliate

N=74


Follow-up program

Cardiac rehabilitation program 11.3 (33) 12.8 6.8 0.15

Exercise program 13.0 (38) 16.1 4.0 0.008

Other program 2.0 (5) 2.3 1.4 0.62

No program 74.0 (216) 70.6 83.8 0.026

Allied health referrals

Occupational therapist 2.7 (8) 3.7 0 0.21

Physiotherapist 3.8 (11) 4.6 1.4 0.30

Social worker 1.7 (5) 2.3 0 0.34

Dietician 8.6 (25) 11.0 1.4 0.010

Cardiac Rehabilitation Nurse 3.1 (9) 3.2 2.7 0.83

No allied health follow-up 80.5 (235) 77.5 89.2 0.029


6.2.6 Knowledge about medications

Approximately one third (93) of respondents at early follow-up reported concern about the

purpose of medications with no difference between discharging hospitals (33% for the tertiary

hospital compared with 30% for the affiliate hospital). Only one third of respondents at early

follow-up nominated specific drug classes as a cause of concern (Table 6.6). Concerns about

the purpose of beta-blockers and ACE inhibitors were most frequent. At late follow-up only 5%

(13) of respondents were not confident about the purpose of their medications.

Table 6.6: Concern about purpose of medication


Percent (n) (n)

Beta-blocker 5.1 (15) (2)

ACE inhibitor 3.8 (11) (1)

Statin 1.7 (5) (1)

Angina 1.4 (4) (3)

All 2.4 (7) (3)

Other 1.4 (4) (2)

Not specified 19.5 (57) (1)

Concern about when to take medications was reported in 22% (64) of questionnaires. Only two

comments were provided; one concerned “what to do about missed medications” and the other

questioned related to the treatment regimen “taking metoprolol twice a day in addition to a

calcium antagonist”.

Comments at late follow-up were provided by five respondents and included “don’t know how

long I have to take it” while two indicated that they had altered the timing of medications from

that prescribed “I did not like taking 5 tablets in the morning” and “doctor changed the time on

the prescription from morning till night, but didn't mention it to me. Pharmacist advised to go

on taking it in the morning but the script says take at night”.

6.2.7 Patient satisfaction

The level of satisfaction with the inhospital communication was generally high although levels

of satisfaction were lowest with the explanations provided about the treatment plan (Table 6.7).

In particular, only 41% indicated that the purpose and side effects of medications had definitely

been explained in a way that they could understand. A greater proportion of tertiary hospital

patients were “definitely” satisfied with most aspects of inhospital care, although not with

regard to the purpose and side effects about medications.


Table 6.7: Reported satisfaction with care received in hospital

Definitely satisfied

Definitely Somewhat No N/A Tertiary Affiliate

Percent Percent Trend p

Did you get enough information about your condition and treatment while you were in hospital? 72.3 21.2 5.5 1.0 77.2 60.8 0.002

When you had questions about your condition and treatment did you get answers you could

understand? 67.8 23.3 4.4 4.4 74.2 61.4 0.039

Did you get enough encouragement to ask questions you wanted to ask about your condition and

treatment? 61.3 18.8 13.7 6.2 68.0 57.4 0.018

Was the purpose of tests explained to you in a way you could understand? 72.3 17.5 7.5 2.7 77.0 66.2 0.022

Were the results of tests explained to you in a way you could understand? 64.0 23.3 8.9 3.8 69.7 57.1 0.011

Was enough effort made to discuss the benefits and risks of your treatment with you? 59.2 21.9 12.7 6.2 66.0 53.8 0.068

Did anyone explain the purpose and potential side effects of medicines you were to take at home in

a way you could understand? 41.4 23.3 31.8 3.4 43.9 40.0 0.430

Was enough information about your condition and treatment given to your family or someone close

to you? 48.0 21.6 25.0 5.5 53.6 42.0 0.108

Were you given enough information on how to manage your condition/recovery at home? 59.9 26.4 11.3 2.4 65.1 50.7 0.026


6.3 General practitioner perspective

The notion that general practitioners cannot be expected to be familiar with management

guidelines in all areas of practice and that they justifiably rely on the management regimen

determined by the hospital-based team underpins the emphasis on a reliable communication

plan from hospital to general practitioner. The REACT study assessed the acceptance of

guidelines and implementation of CHD prevention guidelines and concluded “in terms of

secondary prevention, communication between primary and secondary care is also a major

issue” (Hobbs et al. 2002). The importance of the interaction between the cardiovascular

specialist and the primary physician is underscored by Grundy et al when they say that

“Interaction between the cardiovascular specialist and primary care physician will further assure

that cholesterol management is initiated and continued” (Grundy et al. 1997). Confusion by

both patients and general practitioners about the respective roles of primary and secondary care

was reported by Feder et al who proposed “a more systematic approach to the secondary

prevention of CHD, with explicit agreement between primary and secondary care about

respective responsibilities in an integrated programme of care after a coronary event” (Feder et

al. 1999). Others have suggested that primary care doctors may interpret lack of

implementation of a risk reduction strategy as the cardiologist not believing that it is necessary

(Grundy et al. 1997; Feely 1999).

Data in this section come from the 3-month survey of general practitioners. As reported in

Chapter 4, 238 of 265 questionnaires were completed, a response rate of 90%.

6.3.1 Type of communication

A discharge summary was received by 229 (96%) doctors but only 60 (25%) reported a

telephone call from the hospital at the time of the patient’s discharge.

6.3.2 Transition of care

Comments about the transition of care from the hospital back to the community were provided

in 99 cases (42%). Comments could be divided into three almost equal groups; no problems

(30), happy with transition of care (32) and unhappy with some aspect of the transfer in

particular or had general suggestions for how the process could be improved (37). In the first

group, comments included words such as “satisfactory”, “ no problems”, “ no complaints” and

“OK”. The second group used words such as “good’, “excellent”, “ informative”, “ well

documented” and “helpful”. The third group used words such as ‘no transition of care”, “ poor

communication” and ”very little commitment to general practitioner communication”.

Specific comments from the third group about poor transition of care are shown in Table 6.8.

Many comments related specifically to the discharge summary, referring to “legibility”,


“ timeliness” and “level of detail”. Other comments referred to the generally poor level of

communication. Preference was expressed for being contacted at the time of admission as well

as discharge and preference for faxed rather than mailed discharge summaries. Several doctors

also expressed a preference for a telephone call in addition to the written discharge summary.

Where general practitioners tried to refer back to the hospital, for more detail, they had

problems getting in touch with appropriate staff. Another issue with transition of care was

treatment by multiple doctors, including ongoing follow-up at the hospital.

Table 6.8: General practitioner comments about transition of care

Theme (n) Specifically identified issues

Discharge summary (17) Legibility “4th carbon copy”

“Hand written, usually illegible”

Timeliness “Late”

“Did not get, may have been given

to patient”

“Fax is better”

“Prefer notification of admission”

Level of detail “Use of abbreviations”

“Details of procedures performed”

“Specify treatment received”

“Discharge medications”

“Details of ongoing management”

“Advice on changes to medication

doses”

Poor communication (12) Difficulty contacting hospital

“Advice re ongoing management”

“Clarification about medications”

“No discharge summary”

Conflicting documentation “confusion between letters from

intern and cardiologist”

Diffuse management (12) Patient difficulties “Rehabilitation program required”

Care by multiple doctors “No general practitioner follow-up”

Change of doctors “No communication”


6.4 Cardiology staff perspective

Even with the best intentions by all hospital staff involved in patient education and discharge

planning, structural problems within the healthcare system can act as barriers to communicating

the care plan. These barriers need to be identified and systems modified to facilitate optimal

transition of care.

This section presents the results of discussions with cardiology staff through both individual

interviews of key informants and focus groups with cardiology nurses. Six key informants were

interviewed including the cardiac rehabilitation nurse, two staff development nurses, the

pharmacist, and two resident medical officers, working on the cardiology ward. A total of 13

nurses, ranging from probationary nurses to Clinical Nurse Specialists participated in the one of

two focus groups.

6.4.1 Communication with patients

Hospital staff identified three patient-directed strategies aimed at optimal continuity of care

(Table 6.9). These included: education, provision of written materials and patient review prior

to discharge. There was little discrepancy between staff about the different strategies and who

was responsible for each aspect. Ultimately, it was the responsibility of the nurse reviewing the

patient prior to discharge to make sure that all paperwork has been prepared and provided to the

patient and that the patient has an appropriate understanding of the management plan, including

medications to be taken at home.

Barriers to the delivery of education to patients prior to discharge revolved around time

constraints (Table 6.10). Time constraints related to a shortage of nurses able to provide

education that in turn placed more time pressure on those able to deliver the education. A

change in patient acuity, resulting from increasing numbers of outlying patients requiring more

“nursing” meant that nurses had less time for patient education. Time was also an issue for the

pharmacist, with a bed load of 90 per pharmacist. Other demands on patient time, including

tests and procedures also limited the time available for education. Other barriers to education

included the patient’s lack of interest, while inhospital drug substitution was problematic for

bedside education at the time of drug administration. One group patient education session

covering a different aspect of heart disease was conducted daily, Monday to Friday. Although

staff described these sessions as “very good”, attendance was very poor with estimates of 2 to 8

per session. Poor attendance was attributed to competing interests for the patient’s time,

including being confined to bed awaiting a procedure. The relatively short hospital stay also

limited the possibility of patients attending each session while an inpatient.


Table 6.9: Patient-directed strategies

Education Bedside

Formal role for nurse and pharmacist, restricted role for doctors

Group Sessions

Organised by cardiac rehabilitation nurse. Pharmacist delivers medications talk.

Written materials Life Guide

Core education tool for nurses. Includes “Heart condition”, “Health plan”,

“Medications”, “Risk factors” and “Community resources”

Medication list

Shared role for pharmacist and RMO

Review Formal role for nurse

Modifiable cardiac risk factor assessment

Education

Patient Education Checklist (completed on day of discharge)

“Patient is able to identify

• discharge drugs, actions and major side effects

• identify own risk factors and actions to modify”,

Ensure all prescriptions and appointments required are provided

Allied health services required and discharge plan

Referral to Cardiac rehabilitation nurse or pharmacist

Table 6.10: Barriers to education strategies

BEDSIDE EDUCATION

Time constraints Shortage of appropriately experienced nurses

Increased patient acuity (due to outliers)

Patient/pharmacist ratio

Other demands on patient time

Patient lack of interest “Some people just don’t want to know”

“My wife gives me my tables”

“Patients fake it”

Inhospital drug substitution Brand substitution, strength discrepancies

GROUP EDUCATION SESSIONS

Time constraints Other demands on patient time

Short hospital stay

Patient lack of interest

Two types of barriers were identified with regard to written materials provided (Table 6.11).

These included barriers in the availability of written materials and the quality of the information

provided.


Table 6.11: Barriers to providing appropriate writt en materials

LIFE GUIDE

First admission only Additional leaflets for new drugs may be provided on subsequent admissions.

DISCHARGE MEDICATION LIST

Last minute

preparation/ timing

of discharge

Pharmacist not available

- needs notice prior to discharge

-duties outside the ward

-after hours

Medication list not available

-Used in patient education/review

-Nurses often need to remind RMO

Time constraints

“Don’t have time to do”, “ When busy then not as diligent”, “Suddenly five

patients going home “

Medication list

format

Hand written, legibility problems

Not sufficient space to provide all necessary information

“No documentation on how long to take, to increase dose or maximal dose,

what to do if not tolerated”, “ Box too small to put in explanation”

Inadequate or

inaccurate

information

“Depends on RMO”

“Pharmacist puts strength of tablet and number of tablets, RMOs write dose”

“Alternate brand names not included”

“Discrepancies in the drugs used in hospital and what patient uses at home”

“Decisions at ward rounds, discussed but not documented”

Limited information

for RMO

Transfers (CCU to ward) not comprehensive.

“Only told current medications and sometimes then not complete list”,

“Sometimes don’t know what exactly being used for. Could have had a heart

attack but already on beta-blockers for high blood pressure”, “ Sometimes

they come over (to the ward from CCU) and discharged quickly, I don’t even

know why they are taking it”

Lack of consensus

about information to

provide

“Not filled in very well”, versus “A few key words will remind them”,

“problems when given prophylactically they write “heart”” versus “Don’t

think need to get too technical, as long as they know it is for the heart”

Leaflets for the Life Guide were thought to be of a high quality. There was little concern that

patients might not receive a Life Guide on first admission or that not all appropriate leaflets

were added. However, Life Guides were issued only on the first admission. There was an

expectation on subsequent admissions, that patients (or families) would bring the Life Guide to

the hospital to be updated. Where this did not occur additional leaflets for new medications

were given to the patient with the expectation that the patient would remove leaflets for any

ceased drugs and add new leaflets, thus maintaining an up to date reference.


There was some lack of consensus about responsibility for the preparation of the discharge

medical list. This hand written list should be completed at the time of discharge and include

brand names, strength of tablet and number of tablets to take, the time of day to be taken and the

reason for taking it. The pharmacist described this as a key role for them; junior medical staff

were unclear whether it was part of their role, while nurses said the junior medical staff usually

prepared the list, although the pharmacist did a better job. Barriers to the timely availability of

discharge medication lists revolved around the practice of last minute preparation. While this

allows for possible last minute changes to medications, it provides other problems particularly

in the case of unplanned discharges. These include the unavailability of the pharmacist to

prepare the list and the unavailability of the list at the time of patient review prior to discharge.

This practice also provides time pressure, which may also compromise the quality of the

documentation. Other quality-related issues revolved around the format of the medication list,

which did not provide enough space for all the necessary information and different practices

between individuals. These included the use of doses versus tablet strengths and numbers of

tablets and, the degree of information provided about the rationale for the various medications.

Another issue that compromised the quality of the information provided was the knowledge

available to the resident medical officer preparing the discharge medication list. This related to

knowledge about available strengths of tablets available and alternate names as well as a lack of

knowledge about changes made to patients treatment regimes since admission and reasons for

these changes.

The review prior to discharge should check the patient’s understanding of the treatment plan and

that all referrals for risk factor management have been attended to. Where the nurse (or other

member of the clinical team) has concerns about the patient’s understanding of the management

plan the patient should be referred to the cardiac rehabilitation nurse for follow-up.

Barriers to an effective review prior to discharge revolved around unplanned discharge initiated

either through a need for hospital beds or a change in the patient’s management plan. The

haphazard nature of consultant ward rounds were also a problem often resulting in discharges

occurring at times problematic for the nurses including times when nurses are absent from the

ward.


Table 6.12: Barriers to an effective review prior to discharge

Time constraints “No education done at the time of discharge”

Unplanned or untimely discharge “Nurses on break or at hand over time”

Lack of patient understanding

about the discharge process:

“Patients eager to leave, will not wait for nurse”

Lack of understanding by doctors

about the discharge process

“Doctors need to pay more heed to the discharge process”

“If doctors could speak to nurses and say I think this patient

can go home, then could get onto education”

Unavailability of written materials “Need to ask for mediations lists etc”

The role of the cardiac rehabilitation nurse was limited to patients referred for follow-up

because of concerns by other members of the clinical team. In such cases the rehabilitation

nurse must access medical notes from medical records after the patient has been discharged.

The medical record includes a copy of the discharge summary but not the discharge medication

list.

6.4.2 Communication with general practitioner

Communication with general practitioners was a role for the junior medical staff (Table 6.13).

This included the preparation of the discharge summary, a copy of which is mailed to the

general practitioner with another given to the patient at the time of discharge. Junior medical

staff also reported a telephone call to general practitioners. While admitting that this did not

occur for all patients, post-MI patients were specifically targeted.

Table 6.13: Correspondence with the patient’s nominated general practitioner.

DISCHARGE SUMMARY

Illegibility “Hand written carbon copy”

Lack of detail “Very limited room to provide reasons for medications changes,

more details about tests and follow-up plan”

TELEPHONE CALL

Time constraints “Only for patients with myocardial infarction”

“Usually no problem speaking to general practitioner”


6.5 Discussion

This chapter examined the transition of care from the hospital back to primary care from the

perspective of the patient, the general practitioner and hospital staff. The analysis was limited

in several ways. First, it was hypothesis-generating rather than hypothesis-testing. The patient

perspective relied on patient recall. Furthermore the general practitioner perspective did not

include specific questions about the usefulness or quality of the transition of care, but was

limited to general comments, which were provided by less than one half of the general

practitioners responding to the early follow-up survey. The hospital staff perspective was

limited to that from the cardiology department at the tertiary hospital, which cared for just over

one half of all patients. Nonetheless it was apparent from all perspectives that the transition of

care is at least in some cases less than optimal.

6.5.1 The patient perceptive

Almost all patients reported receiving education about their medications particularly at the

tertiary hospital where less than 5% reported receiving no education. This accorded well with

the reports from hospital staff that education about medications was an important aspect of

discharge planning. Based on hospital reports, nurses and pharmacists have a formal role in

educating patients about their medications while doctors have only an informal role. However

based on patient reports, doctors and nurses provided the most information about medications,

while only 15% of respondents from the tertiary hospital reported receiving information from

the pharmacist. It cannot be inferred that the pharmacist did not provide the information, but

may result from the pharmacist not being identified as such. Differences between the tertiary

and affiliate hospital regarding education about medications particularly the difference in nurse

delivered education probably reflected a more formal role for nurses in patient education at the

tertiary hospital compared with the affiliate hospital.

Information about the side effects of medications was apparently rarely provided or provided in

an ineffectual manner. Only about 30% of respondents reported being given information about

side effects, while only two in five respondents reported being definitely satisfied that “the

purpose and side effects of the medications had been explained in a way you could understand”.

This contrasts with the hospital staff reports that either the nurse, pharmacist or both went

through the drugs explaining the purpose and side effects of the medications. It is of some

concern that the level of communication in hospital was apparently least satisfactory in the area

of discharge planning, particularly information about medications. In terms of chronic diseases,

it is arguable that communication about the long-term treatment plan is the most important

information for the patient to receive following an acute event. Better drug knowledge and

compliance together with a reduction in unplanned visits to the doctor and re-admissions was


found in one study that examined the benefits of an inhospital intervention, which included

counseling about medications and the provision of a discharge medication list (Al-Rashed et al.

2002).

While reports about discharge medication lists from respondents treated in cardiology at the

tertiary hospital concurred with staff reports that all patients should be given a discharge

medication list, about one in ten patients still did not recall receiving a list. The effectiveness of

other written material, particularly the material contained within the Life Guide is more

questionable. Only about one half of the respondents at the tertiary hospital reported receiving

other written information including information about risk factors and medications, with even

less respondents reporting information provided at discharge about support groups and a contact

telephone number, although these were all included in the “Life Guide”. Nursing staff reported

that the Life Guide was the core educational tool, with leaflets provided for each medication and

each risk factor. One problem with the Life Guide was that it was provided only on the first

admission, with an expectation that it would be updated at subsequent admissions. This may

explain some of the shortfall in the reported information provided. Another explanation is that

while respondents were provided with a Life Guide containing potentially valuable information,

this was not effective for many respondents.

About one third of respondents to the early follow-up had some concerns about the purpose of

their medications. Beta-blockers and ACE inhibitors were the most frequently specified.

Although beta-blockers and ACE inhibitors have multiple indications compared with the statins

and antiplatelet agents, this should not translate into confusion or concern about the specific

rationale for the use of each drug. Providing rationale for treatments is one factor in patient

adherence (Miller et al. 1997). Comments provided by some respondents indicated that in some

cases at least, patients would have liked more information than was provided. This was coupled

with a level of disagreement between hospital staff as to the level of information that should be

provided. Clearly the information provided should be tailored to the individual patient,

something that appears to not always occur. The difference between staff beliefs about the type

of information that should be provided was exacerbated by an apparent lack of explanation and,

therefore, knowledge about the reasons for the use of certain drugs by medical staff. This was

particularly a problem in the case of beta-blockers and ACE inhibitors with multiple indications

including prophylactic use post-MI. It is arguable that consensus is needed about the types of

explanations that should be provided to patients for each drug class and indication and these

should be included in practice guidelines for all those involved in patient education. The

National Prescribing Service’s “Easy Guide to Good Prescribing” suggests that the answer to

the patient’s question “why am I taking this medication” is the therapeutic goal (National

Prescribing Curriculum). In the case of secondary prevention of CHD the answer to this


question would be “to prevent cardiovascular events”. Clearly there are patients whom this may

not be sufficient and more explanation about mechanisms and evidence may be required.

6.5.2 General practitioner perspective

In the current study setting almost all doctors reported getting a copy of a discharge summary,

although this did not always arrive in a timely manner. In most cases the only summary

received was a carbon copy of a hand written one page summary. No specific questions about

the usefulness of the summary were included, in the interests of brevity. However more than

40% of respondents made some comments which were distributed relatively evenly between

three groups ranging from “good” to “no problem” to “could be improved”. In trying to

quantify the level of satisfaction it can be argued that in the best-case scenario all respondents

unhappy with the transition of care provided some comment. In this case about 15% of all

respondents were unhappy with the transition of care. However if the proportion of respondents

providing a comment reflected all respondents then more than one third of all respondents felt

that the transition of care process could be improved. Many of the comments related

specifically to the discharge summary, reflecting the importance of this document in the

transition of care, particularly when only one quarter of respondents reported receiving a

telephone call from the hospital. Comments about the discharge summary revolved around

three main themes, legibility, timeliness and usefulness. In a later study carried out in a general

medical ward of the same tertiary hospital almost one third of general practitioners scored

legibility poorly, about one quarter scored timeliness poorly and almost one third scored the

usefulness of the discharge summary poorly (Williamson et al. 2004).

Concerns about the quality of the transition of care in general and the discharge summary in

particular are well documented. In a survey of general practitioners, Bolton et al found that

timeliness, follow-up required and treatment provided in hospital and discharge medications

were the most highly rated criteria for assessing the quality of discharge communications

(Bolton et al. 1998). Pantilat et al found that information about discharge medications and

discharge diagnosis were deemed very important by more than 90% of respondents.

Furthermore, they found that only 56% of primary doctors were satisfied or somewhat satisfied

with communication with the hospital team and only 33% reported that the discharge summary

arrived in a timely manner (Pantilat et al. 2001). Wilson et al compared discharge summaries

with medical notes in an Australian general public hospital (Wilson et al. 2001). They found

inaccuracies in 36% of summaries with about one third of inaccuracies noted in the list of

discharge medications. These included incorrect medications recorded, medications omitted

and omission of dose and frequency. In one quarter of summaries there were no medications

recorded, but it was unclear whether this meant that there was no variation in medications or

that no medication was needed. Only 35% of general practitioners reported receiving the


discharge summary and most were delivered by the patient. The quality of the summaries was

graded by the general practitioner for timeliness (66%), usefulness (74%) and legibility (77%).

The apparent dependence on the discharge summary to effect a seamless transition of care

reported by the general practitioners contrasted with the resident medical officer (RMO), who

reported almost always ringing the general practitioner in the case of a myocardial infarction.

The reasons for the discrepancy are unclear. It may be due to over reporting by RMOs, under

reporting by general practitioners or telephone calls that were made but were not effective.

Several general practitioners commented on the difficulty of getting access to hospital doctors

when they had questions about a patient’s management plan. This contrasted with the RMOs

who reported little difficulty in making contact with the general practitioners.

The importance of the availability and the quality of the discharge summary and transition of

care has been demonstrated in several studies, which examined the relationship between aspects

of the transition of care and patient outcomes. van Walraven et al examined the effect of timely

receipt of a discharge summary on hospital readmission rates (van Walraven et al. 2002). After

controlling for possible confounding factors they found a trend towards a lower likelihood of

readmission for patients who were seen in follow-up by a doctor who had received a discharge

summary prior to the patient visit (RR 0.74; 95% CI 0.05-1.10). Another study examined the

effects of discontinuity of care on patient outcomes (Moore et al. 2003) where no discharge

summaries were sent to the primary care doctor. Errors found in this study suggested that

relevant information concerning the intended discharge plan were not adequately transmitted

from the hospital to the primary care provider. Three types of errors were documented:

medication continuity errors, test follow-up errors and work up errors. Although medication

continuity errors were the most common, multivariate analysis showed that only work up errors

were associated with increased rehospitalisation within three months (OR 6.2; 95% CI 1.3-

30.3). There was no association between medication continuity errors and rehospitalisation

within three months. As noted by the authors it is likely that medication errors were not serious

enough to affect outcomes within three months. Nonetheless this study has shown that at least

some errors in the continuity of care from hospital to primary care can have adverse effects on

patient outcomes.

6.5.3 The system

While appropriate strategies regarding inpatient education and discharge planning have been

adopted in the Cardiology unit of the tertiary hospital, a number of barriers within the system

present challenges to hospital staff in achieving these goals. Many of these problems, related to

the timeliness, completeness and usefulness of discharge summaries would be ameliorated with

the inevitable implementation of electronic medical records and electronic medication


management. However other aspects such as the barrier to providing appropriate education and

review prior to discharge will require other changes.

Providing education on an ongoing basis during the admission was increasingly difficult due to

the decreased times that patients spend on the ward, the increased use of agency staff unable to

provide education and the increased acuity of the ward due to the presence of outlying medical

patients requiring nursing. The latter two problems are system-wide problems that can be

resolved only at the health care system level. However, the limited time available to educate

patients may be addressed within cardiology. This should involve commencing education,

while the patient is still on the coronary care unit, and more importantly by more comprehensive

cardiac rehabilitation post-discharge, something moderately rare in the current system. The

National Heart Foundation of Australia Policy Statement on Cardiac Rehabilitation recommends

that all patients with cardiac conditions, including myocardial infarction, should be referred to

an outpatient cardiac rehabilitation program (National Cardiac Rehabilitation Advisory

Committee 1998).

One of the biggest problems noted by hospital staff was that of unplanned and untimely

discharges. This was especially difficult where no education had been delivered prior to the

time of discharge. These discharges also made it less likely that the pharmacist would write the

discharge medication list, and that the nurse would have the opportunity to review the written

information provided and the patient’s understanding of medications prior to discharge. At least

part of this problem arose from the practice of haphazard consultant ward rounds. Furthermore,

while the importance of the nurse’s role in preparing the patient for discharge was believed by

nurses to be understood by consultants and junior medical staff, this was not passed on to

patients who believed that when the consultant says they can go home that is the final word.

Consultants need emphasise to patients the importance of having a clear understanding about

the treatment and management plans prior to leaving the hospital and the need to receive certain

paperwork prior to leaving. It is arguable that a formal discharge process requiring the patient

to sign a discharge document, including what information has been received and drugs

prescribed should be initiated.

Lack of interest by the patient was a commonly cited problem, both in terms of wanting to

understand about medications and other aspects of the disease and treatment, as well being

prepared to wait for a nurse to complete the review prior to discharge. There is a growing

understanding of the need for patients to take an active role in the treatment plan. This is

acknowledged in initiatives such “Speak Up” of the Joint Commission on Accreditation of

Healthcare Organisations (Joint Commission on Accreditation of Healthcare Organisations) and

in the “10-tips for safer health care” of the Australian Council on Safety and Quality in Health

Care (Australian Council on Safety and Quality in Health Care 2003).


6.6 Summary

This chapter provides insights into communication about the treatment plan from the

perspective of the patient and the general practitioner. It also provides details of the hospital

strategies in place to facilitate the continuity of care from home to ambulatory care and some of

the barriers to a seamless continuum of care. Findings included:

• Most patients were told about the purpose of medications and when they should be taken

but less than one third of patients were told about side effects.

• Only 41% of patients felt they definitely had the purpose and side effects of medications

explained to them in a manner they could understand.

• A discharge medication list was provided to most patients but few patients were provided

with other information about medications.

• Three months post discharge one third of patients had concern about the purpose of their

medications, particularly beta-blockers and ACE inhibitors.

• A discharge summary was received by almost all general practitioners however only one

quarter received a telephone call.

• One third of the comments about the transition of care indicated room for improvement,

with most comments relating specifically to the timeliness, legibility and level of detail

provided in the discharge summary.

• Patient directed strategies described by hospital staff included education, provision of

written materials and review prior to discharge.

• Barriers to education and review prior to discharge revolved around time constraints. The

quality of the written information, particularly the discharge medication list, was described

as a barrier to the usefulness of the written information.

• The written discharge summary provided to the general practitioner was acknowledged by

hospital staff to lack both legibility and appropriate level of detail.

6.7 Conclusions

Concerns about the transition of care were noted from all perspectives. The majority of patients

did not feel they received appropriate information about the purpose and side effects of

medications and this was reflected in their concerns about the purpose of medications,

particularly beta-blockers and ACE inhibitors. General practitioners also had concerns about

the transition of care particularly the completeness of information provided. Hospital staff

identified time constraints, including unplanned discharges, as a major barrier to effective

discharge planning. Staff were also concerned about the quality of the hand written discharge

medication list and discharge summary.

253 Chapter 7: Long term secondary prevention therapies

CHAPTER 7

LONG TERM SECONDARY PREVENTION THERAPY

7.1 Introduction

In this chapter, drug use in the ambulatory care setting is examined. Prescription of post-MI

secondary prevention therapies at discharge was examined in Chapter 5. This showed a

relatively high level of prescription for antiplatelet agents, beta-blockers and statins and, to a

lesser extent, ACE inhibitors. Prescription at discharge however, is only one step towards

optimal long-term prevention of cardiovascular events in patients with CHD. One barrier to

optimal long-term treatment is the transition of care from the hospital back to the community.

Aspects of the transition of care from the perspective of the patient, the general practitioner and

hospital staff involved in the discharge process were examined in Chapter 6. Drug use in

ambulatory care represents the net effect of prescribing at hospital discharge and other factors

related to the patient and general practitioner, including the transition of care process. These

factors may influence the ability and willingness of the patient to adhere to the treatment or the

doctor’s prescribing practice. Use of a drug does not necessarily imply effective use of the

drug, which requires the regimen prescribed and the patient’s adherence to be such that effective

doses are taken.

7.1.1 Objectives

The primary objective of this chapter is to describe the long-term use of the four secondary

prevention medications namely antiplatelet agents, beta-blockers, statins and ACE inhibitors,

including the treatment regimen prescribed by general practitioners and the degree of patient

adherence with the treatment regimen. The secondary objective is to determine factors

associated with long-term use.


Section 7.2 examines the prevalence of drug use in ambulatory care. This includes an

examination of drug use prior to admission in eligible patients as well as use during the follow-

up period. This is followed in Section 7.3 with a description of the treatment regimen, including

doses prescribed by general practitioners during the follow-up period. Section 7.4 examines

patient adherence with the prescribed treatment regimen and Section 7.5 examines independent

predictors of long-term secondary prevention drug use. Section 7.6 discusses these results while

Sections 7.7 and 7.8 provide the summary and conclusions for the chapter


7.2 Prevalence of drug use

This study provided two opportunities to examine the use of drugs for the secondary prevention

of CHD in ambulatory care. These included use prior to admission in eligible patients and use

during the post-MI follow-up period. Both estimates have weaknesses and strengths.

In the case of use prior to admission it was not possible to differentiate between non-

prescription and non-adherence of therapy. Furthermore, since use of secondary prevention

therapies reduces the risk of infarction, patients with a history of CHD presenting to hospital

with myocardial infarction would represent an underestimation of drug use among patients with

CHD in the community. This can be adjusted by applying the Relative Risk Reduction benefits

derived from the landmark RCTs. Furthermore, the effective “over sampling” of non-use of

secondary prevention therapies provided an opportunity to examine factors associated with non-

use of secondary prevention therapies.

Use of therapies during the follow-up period following myocardial infarction provided a

measure of persistence with therapy since drug prescription at discharge is known. The main

weakness of follow-up data however, as discussed in Chapter 4, is the potential of response bias,

which might be expected to overestimate drug use in ambulatory care.

In this section the use of secondary prevention therapies is juxtaposed with the use of calcium

antagonist, not routinely recommended in post-MI patients.

7.2.1 Use of medications prior to hospital admission

In patients with established CHD three quarters were using an antiplatelet agent, while about

one half were using each of the other protective agents and one third used a calcium antagonist

(Table 7-1). Figure 7.1 shows the frequency distribution for the number of cardioprotective

drugs used prior to admission. Only 10% of the CHD cohort was using no cardioprotective

therapies and 48% were using at least three of the four protective therapies (Figure 7.1).

Table 7-1: Medication use prior to admission

Total cohort

N=621

Percent (95% CI)

CHD cohort

N=155

Percent (95% CI)

Antiplatelet agent 39 (35-43) 76 (69-83)

Beta-blocker 23 (20-26) 53 (45-61)

Lipid lowering therapy 28 (24-32) 53 (45-61)

ACE inhibitor 25 (22-28) 44 (36-52)

Calcium antagonist 20 (17-23) 30 (23-37)


Figure 7.1: Use of cardioprotective therapies

05

1015202530354045

Per

cen

tag

e

None One Two Three FourNumber of protective therapies

All patients Prior CHD

7.2.1.1 Missed opportunities for secondary prevention

The proportion of patients with a prior history of CHD and not using a therapy at admission that

was prescribed at discharge varied from more than three quarters for antiplatelet agents to less

than one half for statins and ACE inhibitors (Table 7-2). The sum of patients using therapy

prior to admission and new prescriptions at discharge provided an estimate of patients with prior

history of CHD eligible for each therapy. While almost all patients with CHD were eligible for

an antiplatelet agent, only about three-quarters of all patients with CHD were eligible for a beta-

blocker or lipid lowering therapy and even less were eligible for ACE inhibitors. Underuse of

secondary prevention therapies, estimated as the proportion of eligible patients not using

therapy prior to admission, ranged from 20% for antiplatelet agents to 36% for ACE inhibitors.

Use of ACE inhibitors prior to admission increased with the number of indications (Table 7-3).

Table 7-2: Missed opportunity for secondary prevention of CHD

Non-users New prescription Estimated percent

Percent of CHD cohort(n) Percent non-users (n) Eligible Underuse

Antiplatelet agent 24.5 (38) 79.0 (30) 94.8 20.4

Beta-blocker 47.1(73) 52.0 (38) 77.4 31.7

Lipid lowering 47.1 (73) 46.6 (34) 74.8 29.3

ACE inhibitors 56.1 (87) 44.8 (39) 69.0 36.4


Table 7-3: ACE inhibitor use by previous history

Prior history of CHD No prior history of CHD

ACE inhibitor ACE inhibitor

N Percent N Percent

Neither 84 35.7 357 14.3

Diabetes only 39 48.7 73 28.8

CHF only 19 52.6 22 36.4

Diabetes and CHF 13 69.2 14 50.0

Trend-p 0.012 <0.001

Calcium antagonists in patients with a prior history of CHD

Use of a calcium antagonist was ceased in one third (15/46) of patients with established CHD

using a calcium antagonist prior to admission, while therapy was initiated in 9% (10/109) of

patients with established CHD not using a calcium antagonist prior to admission.

7.2.1.2 Estimates of community wide secondary prevention

The prevalence of secondary prevention drug use in the community of patients with CHD was

estimated by applying the relative benefit of each therapy in reducing the risk of an event

(Yusuf 2002) to the prevalence of secondary prevention therapy prior to admission in the CHD

cohort. The number of patients taking various combinations of risk reduction therapies in the

study cohort was used to estimate the number of people with CHD in the community using each

drug combination (Table 7-4). Thus although 10% (16 of 155) of the cohort with CHD were not

using any risk reduction strategies prior to admission, the estimated proportion of patients with a

history of CHD not using any risk reduction therapies was 4.8%. Similarly, while 15% (23 of

155) of the study cohort with CHD was using all four therapies, it was estimated that 24% of the

wider community with CHD were using all four therapies.


Table 7-4: Population estimates of drug use in patients with a history of CHD

Study sample Population

N Event rate1 Estimated N Percentage

None 16 8% 200 4.8%

One drug

Antiplatelet agent 16 6% 267 6.4%

ACE inhibitor 5 6% 83 2.0%

Beta-blocker 3 6% 50 1.2%

Statin 2 5.6% 36 0.9%

Two drugs

Antiplatelet agent + Beta-blocker 12 4.5% 267 6.4%

Antiplatelet agent + ACE inhibitor 12 4.5% 267 6.4%

Antiplatelet agent + statin 7 4.2% 167 4.0%

Beta-blocker + statin 3 4.2% 71 1.7%

Beta-blocker + ACE inhibitor 2 4.5% 44 1.0%

Statin + ACE inhibitor 3 4.2% 71 1.7%

Three drugs

Missing ACE inhibitor 28 3.0% 933 22.3%

Missing beta-blocker 12 3.1% 387 9.3%

Missing statin 7 3.4% 206 4.9%

Missing antiplatelet agent 4 3.1% 129 3.1%

All four drugs 23 2.3% 1000 23.9%

Total 155 4178 1 Estimated two-year rates determined by Yusuf (Yusuf 2002)

Differences between the estimated proportion of patients in the population with CHD using each

secondary prevention therapy and the proportion of patients prescribed each therapy at the time

of discharge were small with relative differences highest for beta-blockers ACE inhibitors

(Table 7-5).

Table 7-5: Comparison of estimates with prescriptions at discharge post-MI.

Estimated use

% of population with CHD

Prescription at discharge1

% of discharges

Relative

difference

(%)

Antiplatelet agent 84 89 5.6

Beta-blocker 64 75 14.7

Statin 64 70 8.6

ACE inhibitor 52 60 13.3 1 Prescriptions at discharge determined in Chapter 5


7.2.2 During follow-up

This section used data collected during the early and late follow-up patient surveys. It examined

trends in the prevalence of drug use over the follow-up study, including the influence of the

period of enrolment. At the individual level, it examines the number of patients initiating and

discontinuing treatment during the follow-up period.

7.2.2.1 Prevalence of drug use

Table 7-6 compares drug use at discharge and follow-up for both the early and late follow-up

cohorts. There was a significant decrease in the prevalence of aspirin and beta-blocker use at

both early and late follow-up compared with prescriptions at discharge. There were small non-

significant increases in the prevalence of statins, ACE inhibitors and calcium antagonists at

early and late follow-up compared with prescriptions at discharge.

Table 7-6: Comparison of drug use at follow-up with prescriptions at discharge

Early follow-up

N=292

Late follow-up

N=240

Discharge Follow-up Discharge Follow-up


Aspirin 91.4 (267) 85.6 (250) 0.027 90.4 (217) 84.2 (202) 0.040

All antiplatelet agents 94.2 (275) 89.7 (262) 0.048 93.8 (225) 89.6 (215) 0.099

Beta-blockers 82.9 (242) 75.7 (221) 0.032 85.0 (204) 72.5 (174) <0.001

Statins 81.2 (237) 85.3 (249) 0.184 80.8 (194) 85.4 (205) 0.18

ACE inhibitors 61.6 (180) 62.3 (182) 0.865 60.8 (146) 61.7 (148) 0.85

Calcium antagonist 13.0 (38) 14.4 (42) 0.630 12.1 (29) 13.8 (33) 0.59

The influence of enrolment period on drug use in ambulatory care for both the early and late

follow-up cohorts is shown Table 7-7. There was a significant association between enrolment

period and use of ACE inhibitors at both the early and late follow-up and a significant

association between enrolment period and use of antiplatelet agents, but not aspirin at the early

follow-up.


Table 7-7: Influence of period of enrolment on drug use at follow-up

Enrolment period

Early Middle Late Trend p

Early follow-up (n=292)

Aspirin 80.2 (81) 90.6 (106) 85.1 (63) 0.267

All antiplatelet agents 84.2 (85) 91.4 (107) 94.6 (70) 0.021

Beta-blocker 75.2 (76) 73.5 (86) 77.0 (57) 0.826

Statin 81.2 (82) 88.0 (103) 89.2 (66) 0.114

ACE inhibitor 53.5 (54) 65.8 (77) 68.9 (51) 0.030

Calcium antagonist 18.8 (19) 9.4 (11) 16.2 (12) 0.500

Late follow-up (n=240)

Aspirin 80.5 (62) 91.0 (91) 77.8 (49) 0.778

All antiplatelet agents 87.0 (67) 92.0 (92) 88.9 (56) 0.669

Beta-blocker 75.3 (58) 71.0 (71) 71.4 (45) 0.588

Statin 88.3 (68) 84.0 (84) 85.7 (54) 0.630

ACE inhibitor 53.2 (41) 63.0 (63) 69.8 (44) 0.042


Restricting the analysis to only those patients participating in both the early and late follow-up

(n=223), the only trend observed was a significant downward trend in the prevalence of beta-

blocker use from hospital discharge to late follow-up (Table 7-8).

Table 7-8: Trends in drug use from hospital discharge to late follow-up

Discharge Early follow-up Late follow-up Trend p

Antiplatelet 94.2 (210) 88.8 (198) 89.7 (200) 0.100

Beta-blockers 84.8 (189) 76.7 (171) 71.8 (160) 0.001

Statin 82.1 (183) 85.2 (190) 85.2 (190) 0.364

ACE inhibitors 61.0 (136) 61.4 (137) 62.3 (139) 0.770


7.2.2.2 Changes in drug regimen

While there were few changes in the prevalence of drug use over the follow-up period, a

number of changes in drug use at the individual level were reported. Some patients not

prescribed a drug at discharge initiated therapy during the follow-up period. Conversely, some

patients prescribed a drug at discharge discontinued use during the follow-up period. This

analysis was restricted to the cohort responding to both surveys.


Initiation of therapy

Table 7-9 shows drug use during the follow-up period in patients in whom, a drug was not

prescribed at the time of hospital discharge. For example, of the 87 patients not prescribed an

ACE inhibitor at the time of discharge, 24 (28%) commenced an ACE inhibitor during the

follow-up period. Just over one half of these (14) were taking an ACE inhibitor at early follow-

up, with the remainder commencing ACE inhibitor use after the early follow-up.

Table 7-9: Initiation of therapy in 223 respondents to both surveys

Antiplatelet Beta-blocker Statin ACE inhibitor Calcium

antagonist

No discharge prescription

N

13

34

40

87

197

Percent (n)

Commenced 30.8 (4) 35.3 (12) 42.5 (17) 27.6 (24) 7.1 (14)

Early follow-up 7.7 (1) 26.5 (9) 37.5 (15) 16.1 (14) 5.1 (10)

Late follow-up 23.1 (3) 8.8 (3) 5.0 (2) 11.5 (10) 2.0 (4)

Started/stopped - 2.9 (1) 2.5 (1) 1.1 (1) 1.5 (3)

Never used 69.2 (9) 61.8 (21) 55.0 (22) 71.3 (62) 91.4 (180)

With relatively few patients not prescribed recommended therapies at discharge, no measurable

differences in the odds of commencing treatment during the follow-up period were found (Table

7-10). In contrast, the odds of commencing calcium antagonist therapy during the follow-up

period were significantly reduced.

Table 7-10: Odds of initiating therapy compared to odds of initiating statins

Antiplatelet Beta-blocker Statin ACE inhibitor Calcium

antagonist

No discharge prescription

N

13

34

40

87

197

Commenced (n) 4 12 17 24 14

Never used (n) 9 21 22 62 180

Odds (100) 44.4 57.1 77.3 38.7 7.8

OR 0.58 0.74 1.00 0.50 0.10

95% CI 0.15-2.19 0.28-1.91 0.23-1.10 0.04-0.23


Drug discontinuation

Table 7-11 shows drug use during the follow-up period where a drug was prescribed at

discharge. For example, of the 189 patients with a beta-blocker prescription at discharge, 77%

(145) continued to use a beta-blocker throughout the follow-up period. However 22% (41)

discontinued beta-blocker therapy during the follow-up period, most during the early follow-up

period (25) and the remainder (16) after the early follow-up.

Table 7-11: Discontinuation of therapies in 223 respondents to both surveys

Antiplatelet Beta-blocker Statins ACE inhibitor Calcium

antagonist

Prescription at discharge

N

210

189

183

136

26

Percent (n)

Continuous use 90.5 (190) 76.7 (145) 91.8 (168) 83.8 (114) 57.7 (15)

Discontinued 6.6 (14) 21.7 (41) 5.5 (10) 15.5 (21) 34.6 (9)

Early follow-up 3.3 (7) 13.2 (25) 2.2 (4) 9.6 (13) 26.9 (7)

Late follow-up 3.3 (7) 8.5 (16) 3.3 (6) 5.9 (8) 7.7 (2)

Stopped/restarted 2.8 (6) 1.6 (3) 2.7 (5) 0.1(1) 7.7 (2)

The odds of discontinuation were similar for statins and antiplatelet agents but greater for beta-

blockers and ACE inhibitors (Table 7-12). The odds of discontinuation were greatest for

calcium antagonists.

Table 7-12: Odds of discontinuation compared` to the odds of discontinuing statins

Antiplatelet Beta-blocker Statins ACE inhibitor Calcium

antagonist

Discharge prescription

N

210

189

183

136

26

Stopped 14 41 10 21 9

Continued 190 145 168 114 15

Odds (100) 7.37 28.3 5.95 18.4 60.0

OR 1.24 4.75 1.00 3.09 10.1

95% CI 0.54-2.86 2.30-9.82 1.40-6.82 3.5-28.6

Reasons for drug discontinuation

Patients reported only 53 of the 80 apparent discontinuations at early follow-up. Of these most

were attributed to the doctor rather than being patient initiated. Adverse effects accounted for

only 16 of the 53 reported discontinuations (Table 7-13). Of the limited information available

about reasons for drug discontinuations at the time of the late follow-up, adverse effects

accounted for 9 of the 22 discontinuations.


Table 7-13: Reasons reported for drug discontinuations

Antiplatelet agent Beta-blockers Statin ACE inhibitors

Early follow-up

Discontinued 16 35 10 19

Patient reported 8 25 10 10

Reported reason

Doctor Not needed 4 11 5 3

Adverse effect 4 6 3 3

Drug change 0 6 1

Patient Not needed 0 1 0 0

Adverse effect 0 1 1 1

Other 0 1 2

Late follow-up

Discontinued 7 19 6 12

Reason available 4 10 3 5

Reported reason

Drug change 2 1 2

Adverse effects 1 3 2 3

Doctor (NOS) 6

Patient (NOS) 1 1


7.3 Treatment regimens in follow-up care

This section uses data collected from general practitioners at early and late follow-up surveys.

For each drug class, it examines the prevalence of specific drugs and doses prescribed, as well

as changes in drug prescriptions at the individual level.


Prescription of antiplatelet agents from hospital discharge to late follow-up is shown in Table

7-14. There was no difference in the prevalence of prescriptions for antiplatelet agents at the

three time points. There was however, a significant, albeit small, shift away from the

prescription of aspirin towards the prescription of clopidogrel alone. Although the use of

clopidogrel alone increased, the overall use of clopidogrel decreased.

Table 7-14: Prescription of antiplatelet agents in primary care

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Percent (n) of study sample Trend p

Any antiplatelet agent 93.2 (343) 93.7 (223) 90.7 (156) 0.37

Percent (n) of patients prescribed antiplatelet agents

Aspirin 97.1 (333) 96.9 (216) 92.3 (144) 0.022

Clopidogrel 32.1 (110) 19.7(44) 14.1 (22) <0.001

Clopidogrel only 2.3 (8) 3.1 (7) 6.4 (10) 0.029

Other (4) (1) (0)

7.3.1.1 Doses prescribed

Table 7-15 shows the daily dosages of aspirin prescribed in the three groups. The mean dosages

decreased over the study, reflecting a shift from 300 mg daily to 100 mg daily.

Table 7-15: Daily dosages of aspirin prescribed

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Mean (SD) χχχχ2 p

178.0 (71.7) 164.5 (64.3) 153.5 (58.5) <0.001

Dose Percent (n) of patients prescribed aspirin Trend p

100 mg 16.9 (56) 21.3 (46) 28.5 (41) 0.004

150 mg 58.0 (192) 61.1 (132) 58.3 (84) 0.82

300 mg 24.2 (80) 16.7 (36) 11.8 (17) <0.001


7.3.1.2 Changes at the individual level

There were 11 cases where all antiplatelet agents were stopped during the follow-up period.

This included four cases attributed to commencement of warfarin. One was attributed to nausea

and sweats and another followed consultation with a naturopath. There were 12 instances

during the follow-up period where an antiplatelet agent was added to the regimen including four

cases where PCI was cited as the reason and one case where warfarin was stopped.

There were seven cases where aspirin was replaced with another antiplatelet agent. In five cases

the change was to clopidogrel. A reason was provided for only one of these cases with further

angina cited as the reason for the change. The two non-clopidogrel changes were made as

planned at discharge.

7.3.2 Beta-blockers

Prescription of beta-blockers from hospital discharge to late follow-up is shown in Table 7-16.

There was a steady decrease in beta-blocker prescription over the study. Metoprolol and

atenolol accounted for almost all beta-blocker prescriptions during follow-up, with metoprolol

prescribed in about two thirds of all cases. There was a small shift towards prescription of

atenolol rather than metoprolol over the study.

Table 7-16: Prescription of beta-blockers in primary care

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172


Any beta-blocker 83.4 (307) 77.7 (185) 73.8 (126) 0.005

Percent (n) of patients prescribed beta-blockers

Metoprolol 71.3 (219) 67.0 (124) 63.5 (80) 0.095

Atenolol 26.1 (80) 31.4 (58) 34.9 (44) 0.052

Other 2.6 (8) 1.6 (3) 1.6 (2)


Table 7-17 shows the daily dosages of beta-blockers prescribed in the three groups. Although

there was no measurable change in the mean dosages prescribed for either beta-blocker, there

was a marginally significant increase in the proportion of patients prescribed very low (25mg

daily) doses of metoprolol.


Table 7-17: Daily dosages of beta-blockers prescribed

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Metoprolol Mean (SD)

87.2 (49.3) 83.5 (47.5) 82.7 (49.4) 0.69

Dose Percent (n) of patients prescribed metoprolol

25 mg 5.9 (13) 9.7 (12) 12.8 (10) 0.046

50 mg 42.9 (94) 41.1 (51) 39.7 (31) 0.60

100 mg 33.8 (74) 33.9 (42) 30.8 (24) 0.67

>100 mg 17.4 (38) 15.3 (19) 16.7 (13) 0.79

Atenolol Mean (SD) χχχχ2 p

49.7 (24.4) 46.4 (23.1) 50.0 (33.5) 0.732

Dose Percent (n) of patients prescribed atenolol Trend p

25 mg 32.5 (26) 39.3 (22) 41.5 (17) 0.30

50-75 mg 52.5 (42) 50.0 (28) 46.3 (19) 0.52

≥100 mg 15.0 (12) 10.7 (6) 12.2 (5) 0.59


There were 35 cases (15%) of general practitioner reported cessation of a beta-blocker.

Reported reasons included non-specified adverse side effects (8), low heart rate (3), replaced

with other drug class (3), stopped at 12 months (1). Heart failure was given as the reason for

stopping in one case. Two cases were attributed to patient decisions and seven cases were

attributed to a specialist or the hospital. No reason was specified for 10 cases. There were eight

cases where a beta-blocker was added to the regimen. Reasons for initiating beta-blockers were

provided in only three cases one citing blood pressure control, another angina, and one

attributed the change to the cardiologist.

There was relatively little volatility in the type of beta-blocker prescribed with only 14 instances

where the beta-blocker prescribed was changed. The majority of change was from metoprolol

to atenolol (9 cases compared with 3 cases of atenolol to metoprolol). Metoprolol was replaced

with carvedilol in one case. Reasons for the change were provided in only two cases, both with

metoprolol replaced by atenolol. One case cited a “compliance problem” as the reason for

changing and the other “depression”.


7.3.3 Statins

Prescription of statins from hospital discharge to late follow-up is shown in Table 7-18. There

was a non-significant increase in the proportion of patients prescribed statins over the follow-up

period. Pravastatin, atorvastatin and simvastatin together accounted for 90% of all lipid-

lowering therapy with no change in proportions over the study period. Gemfibrozil was the only

non-statin prescribed.

Patients taking statins as part of a RCT were included in “other statins”. This included 28

patients at hospital discharge, 9 patients at early follow-up and 4 patients at late follow-up who

were reported as taking the Pravastatin Acute Coronary Treatment (PACT) study drug. The

PACT study drug was initiated during the hospital episode and was taken for 28 days after

which the doctor was to treat as appropriate (Thompson et al. 2004).

Table 7-18: Prescription of lipid lowering therapy in primary care

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172


Any therapy 82.6 (304) 84.9 (202) 86.6 (149) 0.22

Statin 81.5 (300) 84.0 (200) 86.0 (148) 0.17

Gemfibrozil 1.6 (6) 1.3 (3) 1.2 (2) 0.64

Percent (n) of patients prescribed statins Trend p

Pravastatin 32.7 (98) 36.0 (72) 35.1 (52) 0.53

Atorvastatin 33.7 (101) 34.5 (69) 36.5 (54) 0.57

Simvastatin 22.3 (67) 21.5 (43) 24.3 (36) 0.70

Other statins 11.3 (34) 8.0 (16) 4.7 (7) 0.018


The mean daily dosage increased over the follow-up period for all statins (Table 7-19).

However, 74% (165/220) of patients prescribed a statin at discharge had no change in statin

regimen over the study period. This included 74% (100/139) of cases where a statin was newly

prescribed following the MI. The proportion was similar for all statins.


Table 7-19: Daily doses of statins prescribed

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Pravastatin Mean (SD) χχχχ2 p

28.4 (10.6) 30.4 (10.3) 33.3 (12.5) 0.045

Dose Percent (n) of patients prescribed pravastatin Trend p

10 mg 5.1 (5) 2.8 (2) 5.8 (3) 0.98

20 mg 49.0 (48) 41.7 (30) 25.0 (13) 0.006

30 mg 1.0 (1) 2.8 (2) 3.8 (2) 0.25

≥40 mg 43.9 (43) 51.4 (37) 59.6 (31) 0.063

Atorvastatin Mean (SD) χχχχ2 p

22.3 (16.2) 22.8 (16.3) 31.0 (22.9) 0.015

Dose Percent (n) of patients prescribed atorvastatin Trend p

10 mg 39.6 (40) 30.4 (21) 22.2 (12) 0.025

20 mg 36.6 (37) 47.8 (33) 33.3 (18) 0.93

≥40 mg 22.8 (23) 18.8 (13) 35.2 (19) 0.15

Simvastatin Mean (SD) χχχχ2 p

20.9 (10.4) 24.9 (13.5) 29.2 (17.0) 0.010

Dose Percent (n) of patients prescribed simvastatin Trend p

10 mg 17.9 (12) 16.3 (7) 8.3 (3) 0.22

20 mg 71.6 (48) 55.8 (24) 55.6 (20) 0.074

≥40 mg 10.4 (7) 27.9 (12) 36.1 (13) 0.002


Statins were discontinued in 15 cases. Five were attributed to adverse effects; two were patient

initiated and the remainder unspecified. Statins were added to the treatment regimen in 24 cases

including 47% (23 of 49) of cases where statin was not prescribed at discharge.

The type of statin prescribed was changed following discharge in 26 cases (12%). These

included five cases of ceased cerivastatin, which was withdrawn from the market during the

course of this study. In another five cases side effects were cited. There were 13 cases where

the statin was changed from pravastatin to another statin; including seven cases where the

reason was that lipid levels were not adequately controlled. There was one case where

gemfibrozil was replaced with a statin. Over the follow-up period only 39 patients had the dose

of statin increased including 22 patients that were newly prescribed therapy at the time of

discharge.



There was no difference in the proportion of patients prescribed ACE inhibitors over the follow-

up period (Table 7-20. There was a small, marginally significant, increase in the proportion of

ramipril prescriptions from hospital discharge to late follow-up.

Table 7-20: ACE inhibitor prescription in primary c are

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172


Any ACE inhibitor 61.1 (225) 63.0 (150) 62.8 (108) 0.66

Percent (n) of patients prescribed statins

Ramipril 43.6 (98) 49.3 (74) 53.7 (58) 0.071

Perindopril 22.7 (51) 20.0 (30) 14.8 (16) 0.10

Trandolapril 10.2 (23) 11.3 (17) 12.0 (13) 0.60

Other 14.4 (53) 12.2 (29) 12.2 (21) 0.42


The mean dosage of ramipril, but not perindopril and trandolapril, increased over the follow-up

period (Table 7-21). Prescribed doses of ACE inhibitors were unchanged during follow-up in

74% (119/160) of cases, including 73% (78/107) of patients where an ACE inhibitor was newly

prescribed therapy post-MI. There was no difference between individual ACE inhibitors.


Table 7-21: Daily dosages of ACE inhibitors prescribed in primary care

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Ramipril Mean (SD) χχχχ2 p

4.46 (2.43) 5.01 (2.67) 5.66 (2.77) 0.024

Dose Percent (n) of patients prescribed ramipril Trend p

≤2.5 mg 44.9 (44) 36.5 (27) 27.6 (16) 0.030

5 mg 39.8 (39) 43.2 (32) 46.6 (27) 0.40

10 mg 14.3 (14) 20.3 (15) 25.9 (15) 0.07

Perindopril Mean (SD) χχχχ2 p

3.22 (1.63) 3.26 (1.79) 3.33 (1.68) 0.97

Dose Percent (n) of patients prescribed perindopril Trend p

<2 mg 52.0 (26) 54.8 (17) 50.0 (9) 0.96

4 mg 40.0 (20) 32.3 (10) 38.9 (7) 0.78

≥6 mg 8.0 (4) 12.9 (4) 11.1 (2) 0.59

Trandolapril Mean (SD) χχχχ2 p

0.89 (0.58) 0.94 (0.55) 1.08 (1.04) 0.74

Dose Percent (n) of patients prescribed trandolapril Trend p

0.5 mg 54.6 (12) 41.2 (7) 61.5 (8) 0.82

1 mg 31.8 (7) 47.1 (8) 15.4 (2) 0.45

≥2 mg 13.6 (3) 11.8 (2) 23.1 (3) 0.51


ACE inhibitors were stopped in 16 cases including three attributed to cough, one to low blood

pressure and two changed to an angiotensin receptor blocker. An ACE inhibitor was added to

the treatment regimen in 24% (26 of 109) of cases with no prescription at discharge. Reasons

were cited in only four cases including three cases where the change was attributed to the

hospital or cardiologist and in one case the ACE inhibitor replaced another drug class.

There were 10 instances of changes to the type of ACE inhibitor prescribed. In four cases the

ACE inhibitor was substituted with an ACE inhibitor/diuretic combination with better blood

pressure control and reducing the number of medications cited as reasons. Side effects were

cited as the reason for the change in two cases and no reason was specified in four cases.

Dosages were changed in 39 patients including 22 cases where the dose was increased and 17

cases where the dose was decreased.


7.3.5 Calcium antagonists

There was no measurable difference in the proportion of patients prescribed calcium antagonists

over the study, although there were changes in the types of calcium antagonist prescribed (Table

7-22).

Table 7-22: Prescription of calcium antagonists

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172



Percent (n) of patients prescribed calcium antagonists

Diltiazem 44.9 (22) 35.0(14) 31.0 (9) 0.20

Amlodipine 24.5 (12) 37.5 (15) 58.6 (17) 0.003

Other 30.6 (15) 27.5 (11) 10.3 (3) 0.057


In the 35 patients with follow-up data and a calcium antagonist prescription at discharge,

treatment was discontinued in seven cases. There were 17 cases where a calcium antagonist

was added to the treatment regimen, including 12 cases during the early follow-up period.

Reasons provided for commencing a calcium antagonist included: angina in two cases, blood

pressure control in one case and two cases were attributed to the cardiologist. In one case where

angina was cited as the reason, it was noted that the patient had an adverse reaction to a beta-

blocker. Another case cited IHD as the reason and another case cited the reason “has been on

for several years”. A significant proportion of patients using a calcium antagonist (17/46)

started therapy during the follow-up period.

The association between initiation of a calcium antagonist in follow-up care and use prior to

hospital admission for patients not prescribed a calcium antagonist at discharge is shown in

Table 7-23. The odds of being prescribed a calcium antagonist in follow-up care were

significantly increased if the patient was using a calcium antagonist prior to admission,

particularly in the early follow-up period.

Table 7-23: Initiation of calcium antagonist during follow-up

Initiated early follow-up Initiated late follow-up

Use prior to admission N Percent (n) N Percent (n)

Yes 21 28.6 (6) 14 21.4 (3)

No 187 3.2 (6) 126 1.6 (2)

OR (95% CI) 12.1 (3.5-42.0) 6.8 (1.04-45.0)

χχχχ2 p <0.001 0.023


7.3.6 Prescription of effective doses

Effective doses were defined as those doses used in the landmark clinical trials, which showed

these agents to be effective in the secondary prevention of CHD (Table 3.9). Changes in the

proportion of patients prescribed effective doses at hospital discharge and in follow-up care are

shown in Table 7-24. Statins were the only drug class where the proportion of patients

prescribed an effective dose increased over the follow-up period.

Table 7-24: Proportion of patients prescribed an effective dose

Effective dose prescribed

Discharge

N=368

Early follow-up

N=238

Late follow-up

N=172

Dose (mg) Percent Trend p

Beta-blocker 10.0 8.3 9.2 0.70

Metoprolol ≥200 8.2 7.3 7.7 0.82

Atenolol ≥100 15.0 10.7 12.2 0.59

Statin 59.4 63.5 72.7 0.040

Pravastatin ≥40 43.9 51.4 59.60 0.063

Simvastatin ≥20 82.1 83.7 91.7 0.22

ACE inhibitor 32.4 32.0 35.3 0.66

Ramipril ≥10 14.3 20.3 25.9 0.072

Perindopril ≥4 48.0 54.2 50.0 0.96

Trandolapril ≥1 45.4 58.8 38.5 0.82


7.4 Adherence with treatment regimen

Patients may diverge from the prescribed regimen in a number of different ways and for various

reasons, both intentional and unintentional. Completely discontinuing a drug is only one form

of non-adherence. Much more common is partial adherence with the treatment regimen, by

either sporadically or routinely missing or varying doses. Patterns of patient use of medications

were covered in the literature review (Chapter 2.5.2).

7.4.1 Survey-drug inventory concordance

Comparison of reported drug use between the early follow-up questionnaire and the drug

inventory at the time of the patient interview provides some measure of the usefulness of self-

reported drug use by questionnaire. There were few deviations between the drug inventory at

the time of interview and the regimen reported in the early follow-up survey (Table 7-25).

There were four instances, including two for aspirin, where a drug was not reported on the

questionnaire but was presented at the home visit. There were five instances where a drug was

reported on the questionnaire but was not presented at the home visit. All five cases involved

statins with two instances where no mention was made of statins and three cases where

cessation of statins within the last week was reported.

Table 7-25: Drug inventory at interview compared with questionnaire

Percent (n) Concordant Discordant

Interview

N=213

Survey

N=292

Using Not using Interview Survey

Aspirin 86.4 (184) 85.4 (182) 182 29 2 0

All Antiplatelets 91.1 (194) 90.1 (192) 192 19 2 0

Beta-blockers 77.5 (165) 77.0 (164) 164 48 1 0

Statins 84.5 (180) 86.4 (184) 179 28 1 5

ACE inhibitors 61.5 (131) 61.5 (131) 131 82 0 0

Calcium antagonist 16.9 (36) 16.9 (36) 36 177 0 0

7.4.2 Patient-doctor concordance

Central to the issue of appropriate use of medications in ongoing care is the notion that doctors

have accurate information about patients’ current treatment regimens. Of particular concern in

the current setting, would be the case where the doctor believes the patient is taking appropriate

medications that the patient is not taking, since this could represent a missed opportunity. This

section examines agreement between patient and general practitioner reported drug use.


There were a small number of discordant pairs at the drug class level with similar proportions at

early and late follow-up (Table 7-26). Doctor-only discordant pairs were more common than

patient-only discordant pairs (68 versus 40, χ2p=0.004). Within individual drug classes this

difference was only significant for beta-blockers (χ2p=0.02).

Table 7-26: Discordant pairs by drug class

Early follow-up

N=238

Late follow-up

N=171

Reported by

Discordant pairs

Percent

Discordant pairs

Percent

Patient

N

Doctor

N

Antiplatelet agents 5.4 4.7 7 14

Beta-blockers 6.3 4.7 6 17

Statins 5.4 5.3 11 11

ACE inhibitor 6.3 7.0 11 16

In 53% of cases where the doctor reported a drug class not reported by the patient, the patient

had reported stopping use of that drug class (Table 7-27).

Table 7-27: General practitioner discordant pairs

General practitioner

reported use

N

Patient

reported discontinuation

N

Percent

Antiplatelet agents 14 6 43

Beta-blocker 17 11 65

Statins 11 4 36

ACE inhibitors 16 9 56

Total 58 30 53

When all drug classes and specific drugs and doses were included to the comparison at late

follow-up, there were only 34 (20%) cases with no discordant pairs for all drugs and 50% with

no discordant pairs for secondary prevention drugs. There were 381 discordant pairs noted

among 137 (80%) of patients (Table 7-28). Almost one half of all discordant pairs resulted

from doctor only reporting (181/381) with patient only reporting accounting for about one third

(124/381). One quarter of cases (76/381) involved a dose discrepancy.


Table 7-28: Concordance by drug group at late follow-up

Pairs

Concordant Discordant Ratio

Doctor Patient Dose Total Discordant/Concordant

Antiplatelet agent 133 14 5 18 37 0.28

Statins 113 16 13 10 39 0.34

Beta-blockers 93 9 4 18 31 0.33

ACE inhibitor 86 10 7 6 23 0.27

Calcium antagonist 23 4 3 0 7 0.30

Diuretic 22 4 6 2 12 0.54

Hypoglycaemic 21 7 4 5 16 0.76

PUD/GORD 21 23 12 1 36 1.71

Angina 14 9 7 6 22 1.57

NSAID 5 13 10 1 24 4.80

Two common discrepancies were noted for antiplatelet agents, including eight cases where

aspirin and clopidogrel were both reported by the doctor but the patient reported aspirin only;

and 15 cases where the patient reported aspirin 100-150 mg but the general practitioners

reported aspirin 300 mg.

The drug discrepancies included 30 cases where both patient and doctor reported the same drug

class but a different drug. Statins accounted for 9 of these cases.

7.4.3 Patient interview

In this section, data from the patient home visit are used to qualitatively examine the extent to

which patients adhere with their treatment regimens. The patient interview comprised two

parts. In the first part, a semi-structured format was used to obtain information about missed

drugs, stopped drugs and routines around the use of medications and intentional changes in the

drug regimen. This was followed by a drug inventory where the respondent was asked about

the dose, timing and purpose of each drug. This allowed the discovery of unintentional

deviations from the prescribed regimen as well as the patient’s understanding of the rationale for

use of each drug.

7.4.3.1 Sporadic deviations

Sporadic deviations from the prescribed regimen usually involved missed medications, although

some dose related errors were also noted. These errors were largely unintentional in nature.

Forgetting to take medications was reported in 82 cases (38%). In about one quarter of these

cases pills were taken late, usually a delay of a couple of hours, rather than missed completely.

There was a general awareness that missed tablets should not be taken later, however one


patient described taking two tablets in one day to make up for a missed tablet the previous day

“took in the morning then again in the evening as usual”. The frequency of missed medications

was usually said to be “rarely”, “ every couple of weeks” or “once a month”. There were

however a small number of cases where medications were forgotten relatively frequently;

“about 3 times a week”, “ about twice a week” and “often forget at bedtime”. Missed

medications through forgetfulness occurred more often in the evening or night than in the

morning; “more likely to forget in the evening”, “ mainly at night”, “ out of routine in the

evening, never forget morning” and “mornings are best -never forget”.

Circumstances under which drugs were more likely to be forgotten included the immediate post-

discharge period “starting to get into pattern, forgetting less often”, “ first month all over the

place” and “when first came out of hospital was quite confused”. Another frequently cited

reason was a change of routine: “away for the weekend”, “ travelling”, “having takeaway food”,

“running late” and in one case “doing exams, been a bit forgetful”. In several cases there were

ongoing problems with remembering medications due to “very erratic life” and “shift work so

routine is upset”. Running out of tablets was another common reason for missing tablets:

“occasionally miss when run out of scripts on week end or public holiday”, “ Ran out, was

without for 5 days”, “ ran out yesterday - been away for a couple of days” and “need to go to the

general practitioner for a script”. Financial constraints were also mentioned in a few cases:

“ finances (car getting fixed) - cut down on pills” and “take every second day to get through to

pay day if going to run out before pay day”. One case of missed medications occurred during

hospital readmission 2 days post-PCI where clopidogrel was not provided during the hospital

episode.

Some sporadic errors involved wrong doses. These included two cases where changes to

dosages were made in hospital but not conveyed effectively to the patient. In both cases the

respondents reported continuing with the old dosages until corrected by the general practitioner.

Other cases of incorrect dosages were noted at the time of the interview. In one case there was

an apparent dispensing error, nicorandil 10mg dispensed in the place of 20mg, resulting in use

of half the prescribed dose. In another case “finishing off old tablets”, meant that while aspirin

100mg was reported 300mg was presented at the drug inventory.

7.4.3.2 Systematic deviations

At the time of the interview most patients volunteered they did not like taking tablets and many

indicated that they would like to stop taking the medications. However respondents generally

said they would not stop taking medications without first speaking to their doctor. When

medications were stopped, they were not usually cardiac medications but were most commonly

medications related to pain, particularly gastrointestinal. There were however a few patients


who had stopped or altered doses of cardiac medications without first speaking with their

doctor.

Stopped medications usually represented an intentional deviation from the prescribed

medication regimen. An adverse effect was the most common reason given for stopping

medications without first speaking to the doctor. Sometimes this was only temporary “stopped

because of side effects, but doctor told me to start again” and “stopped metoprolol because of

bad dreams, missed a couple of days before seeing GP who prescribed atenolol”. In one case

two medications were stopped with the explanation “forgot to take (statin) twice, noticed aches

and pain not so bad so stopped to see if (pain) got better, will test cholesterol again. Also

stopped night metoprolol – taking too many tablets and heart rate too low”. Two other

respondents also stopped statin use: “feeling heavy" and “feeling squeamish”. In one case where

aspirin had been stopped because of “stomach problems” aspirin 300mg had been incorrectly

used long-term post-PCI.

Stopped medications did not always represent intentional deviation from the treatment regime.

In the most serious case of unintentional deviation from the prescribed regimen, the respondent

had stopped all medications. In this case, some tablets, but no prescriptions or effective

explanation that these tablets were to be ongoing was provided at discharge. This error was

corrected when the respondent consulted the general practitioner several weeks after ceasing all

medications. This respondent was awaiting a PCI but was “feeling good”. There were several

other cases where medications had been ceased, although it was doubtful this had been the

intention of the treating doctor. This usually involved hospital readmissions where drugs used

prior to admission had not been included in the most recent discharge summary, although no

specific instruction to stop the medication was given: “Using trandolapril prior to admission,

no ACE inhibitor prescribed at discharge. Subsequently prescribed by cardiologist.” and

”Taking ramipril when admitted for CABG but this was not included on medication list when

discharged following CABG so longer taking. Not sure if should be taking.”

Most systematic deviations in dosing and frequency were unintentional with a lack of

understanding about the treatment regimen usually responsible for deviations from the

prescribed regimen. The most common deviations in prescribed treatment regimen included the

dose of aspirin used, the frequency of metoprolol dosing and the timing of statin doses.

Of the 184 patients taking aspirin, 21 patients were not taking “as directed”. Of these, one was

taking less than directed, taking 150 mg only every second day. Another patient was taking 300

mg every second day rather than 150mg daily. The rest were all taking 300 mg daily, including

one patient who was taking 150 mg twice a day. Fourteen patients using 300 mg reported

undergoing a PCI more than one-month prior with most apparently not understanding that the


dose should be halved after one month. However some deviations were intentional including

“can’t be bothered breaking the tablets”. Concern about the long-term effects of aspirin in one

case meant that a patient systematically missed aspirin “sometimes give aspirin a miss I've taken

too many aspirin in my life”.

Of the 110 patients taking metoprolol, 11 patients were using it once a day. This included one

case that had been told to take 25 mg twice daily, but had decided to take 50mg in the evening

instead, another case that had recently decided to stop the evening tablet and one case that had

stopped the evening tablet mistakenly thinking this was appropriate one month post-PCI, rather

than halving the aspirin dose. Eight of the 11 patients had been prescribed metoprolol twice

daily including; five prescribed 25 mg twice daily but now taking 25 mg once daily; two

prescribed 50mg twice daily but now taking 50 mg once daily and one prescribed 12.5 mg twice

daily but now taking 12.5 mg once daily. The last case reported becoming hypotensive at

higher doses. Metoprolol was initiated during the follow-up period in two of the 11 taking 50

mg once daily.

Of the 179 patients using statins, 27 patients were taking it in the morning, including 21 taking

atorvastatin, and three each taking simvastatin and pravastatin. This included one patient where

the discharge summary specified “mane”, and another where the general practitioner had

instructed the patient to take all tablets in the morning. One patient changed from night to

morning at the pharmacist’s suggestion after complaining about “sleeplessness”. Another

patient had been taking at night as instructed, but then read that it should be taken at least three

hours after food once daily so changed to morning since goes to bed straight after dinner. There

was also some confusion about whether tablets should be taken with the evening meal or at

bedtime. This included a couple of patients who had been taking it at bedtime but had changed

to taking with their evening meal because they often forgot to take it at bedtime. Another two

patients noticed during the interview that the discharge medication list stated bedtime rather

than with dinner.

Not being convinced about the need for lipid lowering was also cited in several cases as reasons

for intentionally missing statins “take erratically, I don’t thing I need it - cholesterol was 5 in

hospital” and “only take 2-3 days a week”.

7.4.3.3 Factors influencing partial adherence

The patient interview highlighted a number of factors that may lead patients to less than optimal

adherence. These included the routines adopted by patients and their understanding of the

rationale for the treatment regimen. However a number of system-wide factors were also

identified that could lead to medication errors.


Routines in taking medications

Medications were generally taken at about the same time every day, usually associated with

meals or bedtime. In several cases regimens more complicated than those prescribed were

adopted because “I don’t like to take too many tablets at once”.

Pill-dispensing boxes were used in 15% (n=32) of cases, although these were not always used

appropriately. In the worst cases this involved putting all of the tablets to be taken in any one

day into the same compartment commenting that “I know when to take what” and “I pick out the

morning ones”.

A common reminder strategy involved reference to the discharge medication list (15% of cases)

“keep discharge list with tablets” or “check medication list”. However, the most common

strategy was to leave the medications somewhere visible, typically, “keep medicines on the table

– under my nose”, “ near toothbrush” and “bedside table”. If not leaving the medications clearly

visible then other visual cues were used including; “medication list on the fridge” and “keep

glass of water next to the tablets as a reminder”. One strategy for remembering medications,

especially by men, was to rely on the spouse with comments including, “my wife reminds me”,

“my wife makes sure my pills are out each morning” and “wife prepares each evening for next

day”.

In a number of cases tablets were removed from packets and bottles well ahead of taking them.

These included, “keep morning tablets for one week in a separate labelled bottle and the

evening ones in a separate bottle”, “ when taking morning tablets also take out evening tablets

and put them in a bottle”, “ put all tablets for the day in a bowl”, “ get tablets together once a

day, two piles –put into little box”, “ at night prepare night and morning tablets (take morning

tablets to work)”, “ get morning tablets ready the night before ”, “ I have three cups; one each for

morning, noon and night” and “I take all the tablets out in the morning and leave the evening

tablets in a glass on the table”. In a couple of cases there was an attempt to keep tablets out of

the air “put in some foil” and “put them in a film canister”; however, in many cases the pills

were left out for a considerable time. Although calendar packs are used extensively, less than

10% of cases followed the days of the week.

Although very few patients mentioned cost as a reason for missed tablets, a number did

comment that the cost of prescriptions was an issue: “pretty expensive” “ money is a problem”,

“need to make sure I buy the tablets before I run out of money” and “financial strain”.

There were two instances where the names on tablets shown did not correspond with the name

of the patient with explanations of: “My mother buys the aspirin on her healthcare card” and

“Mother-in-law was using same medications, but not taking any more so I am taking them”.


Other inappropriate habits included “both take blood pressure medicines, got them mixed up”

and “share with wife”.

Understanding medication regimen

Most respondents were able to say that antiplatelet agents interfered with the formation of blood

clots although eight respondents (4%) could not say what the purpose of taking the antiplatelet

agent was. Three quarters of respondents associated antiplatelets with “thinning the blood”,

15% of cases were more specific in describing “prevention of blood clots” and “platelet

aggregation”. A few respondents mentioned the heart, “preventing a heart attack” (3 patients)

or that it was “for the heart” (2 patients).

Reasons for using beta-blockers reported by patients generally coincided with one of the

indications for beta-blockers, although 41 respondents (25%) could not say what the purpose of

taking the beta-blocker was and in one case an inappropriate indication, “thins the blood” was

provided. Lowering of blood pressure (30%) and heart rate (24%) were most commonly cited.

Angina was cited as the reason for using a beta-blocker in four cases, while another four cases

described “dilating blood vessels”, “increasing blood flow” and “increasing oxygen to the

heart”, all related to the relief of angina symptoms, making a total of about 5%. Twenty-seven

respondents (16%) gave a non-specific reason “for the heart” and five cases (3%) indicated that

beta-blockers reduce the risk of a heart attack. Of the four respondents using carvedilol one said

it was for “heart failure”, another for “shortness of breath” a third simply said “heart” while the

fourth said it was for “blood pressure”.

Eighty five percent of respondents were able to correctly state that the purpose of the statin was

to decrease cholesterol; however, 12% could not say what the purpose of the medication was.

In the remaining cases reasons stated included “preventive”, “to heal the heart” while two

patients gave inappropriate answers of “blood pressure” and “calcium”.

The majority of respondents gave a reason for using an ACE inhibitor that coincided with one

the indications for ACE inhibitors; however, almost 30% (37 cases) could not give a reason for

using the ACE inhibitor and 3% (4 cases) gave an inappropriate answer “slows heart rate”.

Lowering blood pressure was most frequently cited (42%). About 10% (13 cases) indicated that

the ACE inhibitor was prescribed for heart failure and left ventricular dysfunction including

three cases who said it was “fluid” and another three cases who said it was to “decrease work

load”. A further 12% said that the ACE inhibitor was “for the heart”. Finally eight respondents

(6%) said the ACE inhibitor was to reduce the risk of heart attack.

Of the 36 respondents using a calcium antagonist almost half (17 cases) reported that it was to

lower blood pressure. One third of respondents (11 cases) could not say why they were taking a


calcium antagonist. Of the remaining patients, six said they used a calcium antagonist for

angina and three said it was for the heart. One patient said it was to prevent coronary spasm.

A number of respondents cited lowering blood pressure as the reason using both beta-blockers

and ACE inhibitors, following this with a comment such as “but I don’t have high blood

pressure”. This notion that these two drug classes might be interchangeable was exemplified in

the patient who first halved the atenolol dose when ramipril was added and then did not increase

the dose of ramipril as directed because “Was feeling so good thought I would stick with half”.

System-wide factors

The problem of generic drug names versus proprietary names was a common source of

confusion for patients. Comments included “Drugs have different names- you wonder if they

are the same”, “ Twice gone (to the pharmacist) for one medication and come home with

another – from the same script”, “ Very confusing with different names for different preparations

of the same drug”. Similarly, “brand choice”, the substitution with a cheaper generic for the

more expensive drug also contributed to patient confusion. “pharmacist suggests generics but I

prefer to stick to what doctor wrote”.

A number of errors or potential errors were described during the interviews. These did not

always result in medications being used inappropriately, but all had the potential to do so.

These included problems at the hospital discharge process, problems in the continuity of care

and prescription and dispensing errors.

Problems at hospital discharge included:

• Discharged with neither tablets nor prescriptions “Was not given any tablets or scripts when

discharged from hospital. Fortunately I was able to contact my doctor after hours to get

prescriptions” and “No prescription for pravastatin at discharge, therefore missed tablet

until saw general practitioner to get script the next day”.

• Incomplete, inconsistent and unhelpful written information was also common “Aspirin was

not included on discharge medication list. Received a telephone call from patient educator

who went through the list of medications and told me I should be taking aspirin”,

“Discharge medication list illegible. Daughter wrote one I could read”, “ Conflicting

information about when to take atorvastatin. Medication list specifies morning but

directions say evening”, “ Metoprolol not on discharge medication list and not given a

prescription”, “ Post–PCI was not made clear to take aspirin 300mg of until spoke with

general practitioner”, “ given discharge medication list then received another one in the

post with different explanations for metoprolol and ramipril”, “Not clear from discharge

medication list that clopidogrel should be stopped and aspirin halved after one month.


General practitioner wrote repeat script for clopidogrel that was queried by pharmacist

who went back to general practitioner who went back to hospital”.

• Readmission for procedures sometimes led to lack of clear information about medication:

“Poor communication post CABG about what medications to continue. Given a bundle of

scripts including one for trandolapril with no repeats. Discharge summary did not

recommence beta-blocker or statin. Statin subsequently recommenced by cardiologist.

Current medications are aspirin and atorvastatin only.”

Problems with the continuity of care included misunderstandings about the treatment regimen

and lack of transfer of information: “Went to general practitioner for scripts but doctor knew

nothing, had not received discharge summary”, “ Nifedipine was added by specialist. It was not

clear to me whether other medications should be continued had to check with general

practitioner”, “ Conflicting instructions about when to take lipitor, was originally told in the

morning but cardiologist said to take at night”, “ did not know how long to take medications,

asked general practitioner who told me to go and see the cardiologist”, “Using amlodopine and

irbesarten/hydrochlorothiazde prior to admission for control of blood pressure. At discharge

was prescribed only aspirin, metoprolol and atorvastatin. Both amlodopine and

irbesarten/hydrochlorothiazde have since been resumed.”

Prescription and dispensing errors included “General practitioner did not increase dose of

ramipril, subsequently increased by specialist”. “Prescribed 5mg of ramipril. Dispensed 2.5 mg

with instructions to take 2 tablets.” “Once given wrong dose of captopril – could tell from the

colour”, “Prescribed enalapril 15mg twice daily but given script for 5mg – this meant new

packet every 5 days” and “Was given 40mg pravastatin instead of 20mg – so taking half. ”


7.5 Predictors for use of secondary prevention therapy

This section examines factors associated with the use of cardioprotective therapies prior to

admission and factors associated with discontinuation of therapy during the follow-up period.

7.5.1 Use prior to admission

Section 7.2.1.1 suggested some underuse of secondary prevention therapies prior to admission

in patients with a prior history of myocardial infarction or revascularization (CHD cohort).

Given the protective benefits of the secondary prevention therapies it would be expected that

underuse of therapies would be over represented in a cohort of patients with myocardial

infarction. This “over sampling” of patients with less than optimal treatment regimen therefore

provided an opportunity to examine factors that may be associated with the use of secondary

prevention therapies.

The initial bivariate analysis examined the complete cohort and the subgroup with a prior

history of CHD. Subsequent multivariate analysis examined associations for each drug in the

complete cohort, as well as an examination of the associations with “underuse” of secondary

prevention therapies in the subgroup with a prior history of CHD.


Demographic variables

Drug use prior to admission by gender is shown in Table 7-29 for the complete cohort and the

subgroup with prior history of CHD. Secondary prevention drug use did not vary with gender

in the complete cohort, although calcium antagonist use was more prevalent among females. In

the group with a prior history of CHD, use of an antiplatelet agent was more prevalent among

females with no other associations by gender.

Table 7-29: Drug use prior to admission by gender

Antiplatelet agent Beta-blocker Statin ACE inhibitor Calcium antagonist

Complete cohort (n=621)

Male 37.4 21.9 28.1 23.4 16.8

Female 42.3 25.1 29.3 27.9 25.1

χ2p 0.235 0.368 0.748 0.217 0.012

Subgroup with prior CHD (n=155)

Male 70.2 50.9 53.5 45.6 29.0

Female 90.2 58.5 51.2 39.0 31.7

χ2p 0.010 0.400 0.801 0.466 0.740

Figure 7.2 shows drug use prior to admission by age. In the complete cohort, there were

significant increases in drug use with increasing age (trend p<0.001) for all drug classes except


statins. Statins showed a biphasic trend with an initial increase with age (<60 years compared

with 60-70 years, χ2 p=0.012) followed by a decrease with increasing age (trend p=0.003). In

the CHD subgroup, only calcium antagonists showed an increasing trend with increasing age

(trend p<0.001), although use of antiplatelet agents in the CHD subgroup increased in patients

80 years and older compared to younger patients (χ2p=050) and use of ACE inhibitors increased

in patients older than 60 years compared with younger patients (χ2p=0.026). In contrast, there

was an inverse trend for statins (trend p<0.001). There was no association with age for beta-

blocker use

Figure 7.2: Drug use prior to admission by age

0102030405060708090

Per

cen

tag

e

Antiplatelet Beta-blocker

Statin ACEInhibitor

Calciumantagonist

Complete cohort

<60 60-<70 70-<80 >=80

0102030405060708090

Per

cen

tag

e

Antiplatelet Beta-blocker

Statin ACEInhibitor

Calciumantagonist

Subgroup with prior history of CHD


Trends in drug use prior to admission by enrolment period are shown in Table 7-30. There were

no measurable changes in the use of the cardioprotective therapies prior to admission in the

complete cohort, although use of calcium antagonists decreased over the study. In the subgroup

with a prior history of CHD, the use of antiplatelet agents prior to admission increased with

calendar period.

Table 7-30: Drug use prior to admission by period of study



Early 36.3 24.0 26.3 24.0 25.7

Middle 36.9 21.3 29.5 24.6 18.7

Late 45.0 24.7 29.1 26.4 15.4

Trend p 0.087 0.853 0.566 0.601 0.015

Subgroup with prior history of CHD (n=155)

Early 63.4 51.2 48.8 41.5 36.6

Middle 76.7 52.0 52.0 43.8 30.1

Late 85.4 56.1 58.5 46.3 22.0

Trend p 0.021 0.889 0.663 0.906 0.147

Contraindications and indications

Use of anticoagulants was negatively associated with use of antiplatelet agents in both the

complete cohort (21.9% versus 40.1%, p=0.040) and CHD subgroup (46.2%, versus 78.2% χ2p

=0.010). Similarly, chronic airways limitation (CAL) was negatively associated with beta-

blocker use in the complete cohort (8.8% versus 25.8%, p<0.001) and CHD subgroup (22.7%

versus 57.9%, χ2p <0.002). A history of angina was positively associated with use of calcium

antagonists in the complete cohort (33.5% versus 14.4%, p<0.001) and CHD subgroup (42.7%

versus 17.5%, χ2p <0.001).


Smoking

Drug use by smoking status is shown in Table 7-31. In the complete cohort, drug use was

significantly lower in smokers. Drug use was also consistently lower in smokers in the CHD

subgroup, but this only reached statistical significance for ACE inhibitors.

Table 7-31: Smoking and medication use with CHD

Current smoker Non-smoker


N 128 493

Percent χχχχ2p

Antiplatelet agent 24.2 43.0 <0.001

Beta-blocker 12.5 25.8 0.002

Lipid lowering therapy 17.2 31.4 <0.002

ACE inhibitor 9.4 29.0 <0.001

Calcium antagonist 13.3 21.3 0.042


N 26 129

Percent χχχχ2p

Antiplatelet agent 61.5 78.3 0.070

Beta-blocker 38.5 55.8 0.11

Lipid lowering therapy 38.5 55.8 0.11

ACE inhibitor 23.1 48.1 0.019

Calcium antagonist 15.4 32.6 0.080

Previous medical history

There was a strong association between previous medical history and drug use prior to

admission in the complete cohort (Table 7-32). Use of antiplatelet agents and beta-blockers was

highest in association with CHD, while use of statins was highest in association with

hyperlipidemia and ACE inhibitor use was highest in association with heart failure.

In the group with prior history of CHD, few associations with other cardiac related conditions

were maintained (Table 7-33). Hyperlipidemia was associated with increased use of

antiplatelets, beta-blockers and statins, but negatively associated with calcium antagonists.

Hypertension was positively associated with beta-blockers and statins, while cerebrovascular

disease was positively associated with antiplatelet agents. Heart failure was positively

associated with ACE inhibitors but negatively associated with use of beta-blockers and lipid

lowering therapy.


Table 7-32: Drug use prior to admission by previous medical history

History

Yes No

Drug use

Percent χχχχ2p

Antiplatelet agent CHD1 75.5 27.0 <0.001

Cerebrovascular disease 72.8 34.1 <0.001

Ischaemic heart disease 67.2 21.7 <0.001

Heart Failure 58.8 36.7 <0.001

Hyperlipidemia 52.5 30.9 <0.001

Hypertension 51.5 27.8 <0.001

Diabetes 49.6 36.1 0.004

Atrial Fibrillation 53.6 37.7 0.020

Beta-blocker CHD 52.9 13.1 <0.001



Hyperlipidemia 33.0 16.9 <0.001


Diabetes 27.3 21.8 0.17

Cerebrovascular disease 27.2 22.4 0.34

Heart Failure 25.0 22.8 0.68

Statin Hyperlipidemia 64.0 6.8 <0.001

CHD 52.9 20.4 <0.001


Diabetes 44.6 23.9 <0.001





ACE inhibitor Heart Failure 50.0 21.9 <0.001

CHD 43.9 18.7 <0.001


Diabetes 40.3 20.5 <0.001




Hyperlipidemia 29.7 22.1 0.034

Calcium antagonist Diabetes 30.9 16.4 <0.001



CHD 29.7 16.3 <0.001




Atrial Fibrillation 17.9 19.8 0.72 1prior history of MI or revascularisation procedure


Table 7-33: CHD subgroup1 drug use prior to admission by previous medical history

History

Yes No

Drug use

Percent χχχχ2p

Antiplatelet agent Cerebrovascular disease 95.0 72.6 0.030


Hypertension 80.9 68.2 0.069


Diabetes 76.9 74.8 0.77


Beta-blocker Hyperlipidemia 67.4 34.8 <0.001



Diabetes 51.9 53.4 0.86



Statin Hyperlipidemia 74.4 26.1 <0.001




Diabetes 55.8 51.5 0.61


ACE inhibitor Heart Failure 59.4 39.8 0.047


Diabetes 53.8 38.8 0.075




Calcium antagonist Diabetes 32.7 28.2 0.56





Hyperlipidemia 18.6 43.4 <0.001 1 prior history of MI or revascularisation procedure

Concomitant therapy

In the complete cohort there was a strong association (p<0.001) between the proportion of

patients using any drug and the number of secondary prevention therapies used (Table 7-34).

Thus while 18% of patients using no beta-blocker, statin or ACE inhibitor were using an

antiplatelet agent, 86% of patients taking a beta-blocker, a statin and an ACE inhibitor were also

using an antiplatelet agent. In the subgroup with prior history of CHD, the strong association

was maintained for antiplatelets, beta-blockers and statins but not for ACE inhibitors and

calcium antagonists.


Table 7-34: Drug use with number of concomitant secondary prevention therapies


Number of therapies

Percent (n)


0 18.1 (56) 8.6 (24) 13.0 (38) 11.5 (33) 9.1 (23)

1 47.8 (87) 23.0 (38) 28.5 (45) 30.6 (52) 23.8 (36)

2 74.5 (70) 41.1 (51) 49.2 (64) 40.4 (40) 29.7 (33)

3 85.7 (30) 55.6 (30) 73.2 (30) 46.2 (30) 32.0 (24)

4 - - - - 20.0 (6)


0 50.0 (16) 15.8 (3) 11.1 (2) 23.8 (5) 18.8 (3)

1 75.6 (31) 42.5 (17) 35.1 (13) 44.7 (17) 42.3 (11)

2 85.4 (47) 63.9 (39) 62.9 (44) 51.1 (23) 30.8 (12)

3 85.2 (23) 65.7 (23) 76.7 (23) 45.1 (23) 33.3 (17)

4 - - - - 13.0 (3)

In a bivariate analysis of the CHD subgroup, three factors were significantly associated with the

number of secondary prevention therapies used (Table 7-35). There was a positive association

with hyperlipidemia and hypertension and a negative association with smoking. These

associations were independent of the inclusion of ACE inhibitors in the analysis.

Table 7-35: Trend analysis for number of drugs used in the CHD cohort

None One Two Three Four

N=16 N=26 N=39 N=51 N=23

Percent Trend p <60 years 50.0 15.4 10.3 29.4 21.7 0.52

Male 93.8 69.2 74.4 64.7 82.6 0.39

Smoking 37.5 26.9 12.8 13.7 4.4 0.003

Hyperlipidemia 43.8 23.1 43.6 70.6 87.0 <0.001

Hypertension 25.0 50.0 48.7 72.6 69.6 <0.001

Heart failure 0 46.2 20.5 17.7 13.0 0.40

Cerebrovascular disease 0 7.7 15.4 19.6 8.7 0.16

Diabetes 25.0 30.8 33.3 35.3 39.1 0.33

Excluding ACE inhibitors N=21 N=38 N=45 N=51

Percent Trend p <60 years 38.1 13.2 15.6 31.4 0.75

Male 90.5 71.0 71.1 70.6 0.18

Smoking 33.3 21.0 11.1 11.8 0.021

Hyperlipidemia 42.9 15.8 57.8 88.2 <0.001

Hypertension 28.6 47.4 64.4 70.6 <0.001

Heart failure 19.0 31.6 26.7 7.8 0.056

Cerebrovascular disease 0 15.8 11.1 17.6 0.12

Diabetes 28.6 42.1 22.2 39.2 0.78


7.5.1.2 Multivariate Analysis

The logistic regression models for use of each of the study drugs in the complete cohort are

shown in Table 7-36 to Table 7-40. In predicting the use of these therapies the c-statistic varied

from 0.91 for statins to 0.81 for ACE inhibitors, while the c-statistic for calcium antagonist use

was 0.76.

There was no clear association with gender for any of the study drugs, including calcium

antagonists when controlling for other variables; however, the positive association with age was

maintained for antiplatelet agents and ACE inhibitors. The negative association with calendar

period was maintained for calcium antagonists and, there was a positive association with

calendar period and use of an antiplatelet agent. Contraindications (anticoagulants for

antiplatelet agents and chronic airways limitation for beta-blockers) were strong negative

predictors for the respective drugs. Cardiac related medical history remained a strong predictor

of drug use. CHD was associated with increased use of all four secondary prevention therapies

but not with the use of calcium antagonists. Heart failure and diabetes were negatively

associated with beta-blocker use. In contrast, diabetes was positively associated with use of

lipid lowering therapy, ACE inhibitors and calcium antagonist, but there was no association

with antiplatelet agents. Hypertension was positively associated with antiplatelet agents, beta-

blockers, ACE inhibitors and calcium antagonists. Hyperlipidemia was positively associated

with antiplatelet agents and lipid lowering therapy, with a very high odds ratio for the latter.

Cerebrovascular disease was associated with increased use of antiplatelet agents and lipid

lowering therapy. The negative association observed with smoking in bivariate analysis was

maintained in multivariate analysis for beta-blockers, lipid lowering therapy and ACE

inhibitors, reducing the odds of drug use by about half, although 95% confidence intervals all

included unity. The number of concomitant secondary prevention therapies used was

significantly associated with use of each secondary prevention therapy but was not associated

with calcium antagonist use when controlling for other factors.


Table 7-36: Independent predictors of antiplatelet use

Adjusted OR 95% CI p-value

Gender, Male 1.02 0.63-1.64 0.95

Age, years

≥80 years 4.03 2.06-7.89 <0.001

70-<80 2.39 1.28-4.46 0.006

60-<70 1.85 0.93-3.67 0.079

<60 1.00

Calendar period 1.39 1.04-1.85 0.026

Cerebrovascular disease 7.4 3.8-14.2 <0.001

CHD 3.30 1.63-6.66 <0.001

Ischaemic heart disease 2.58 1.40-4.76 0.002

Atrial fibrillation 2.24 0.90-5.60 0.084

Hyperlipidemia 1.84 1.12-3.04 0.017

Hypertension 1.47 0.93-2.32 0.098

Anticoagulant 0.03 0.01-0.11 <0.001

Number of drugs 2.20 1.62-2.98 <0.001

c-statistic 0.88

Table 7-37: Independent predictors of beta-blocker use


Gender, Male 0.77 0.46-1.30 0.32

Age, years

≥80 years 1.15 0.57-2.32 0.70

70-<80 0.96 0.50-1.87 0.91

60-<70 0.71 0.34-1.48 0.36

<60 1.00

Ischaemic heart disease 4.35 2.22-8.52 <0.001

Hypertension 3.54 2.15-5.86 <0.001

CHD 2.24 1.16-4.33 0.017

Heart failure 0.45 0.22-0.95 0.036

Diabetes 0.61 0.36-1.05 0.073

Chronic airways limitation 0.14 0.06-0.33 <0.001

Number of drugs 1.54 1.19-2.00 0.001

Smoking 0.57 0.28-1.17 0.13

c-statistic 0.86


Table 7-38: Independent predictors of lipid lowering therapy use


Gender, Male 0.64 0.36-1.12 0.12

Age, years

≥80 years 0.60 0.25-1.43 0.25

70-<80 0.72 0.36-1.47 0.37

60-<70 1.57 0.74-3.33 0.24

<60 1.00

Hyperlipidemia 30 17-53 <0.001

Cerebrovascular disease 2.25 1.07-4.75 0.033

Diabetes 2.10 1.20-3.68 0.010

Atrial fibrillation 2.07 0.85-5.01 0.11

CHD 1.91 1.03-3.54 0.041

Number of drugs 2.16 1.58-2.95 <0.001

Smoking 0.56 0.28-1.13 0.11

c-statistic 0.92

Table 7-39: Independent predictors of ACE inhibitor use


Gender, Male 1.10 0.70-1.74 0.68

Age, years

≥80 years 2.78 1.38-5.62 0.004

70-<80 3.51 1.82-6.79 <0.001

60-<70 3.33 1.62-6.83 0.001

<60 1.00

CHD 1.97 1.19-3.27 0.008

Hypertension 3.03 1.93-4.75 <0.001

Heart failure 2.71 1.49-4.92 0.001

Ischaemic heart disease 1.92 1.20-3.06 0.006

Diabetes 1.73 1.09-2.73 0.019

Smoking 0.51 0.26-1.04 0.064

Number of drugs 1.35 1.07-1.71 0.011

c-statistic 0.81


Table 7-40: Independent predictors of calcium antagonist use


Gender 0.74 0.46-1.17 0.20

Age, years

≥80 years 1.88 0.96-3.66 0.064

70-<80 1.79 0.96-3.35 0.066

60-<70 1.07 0.52-2.21 0.86

<60 1.00

Hypertension 3.35 2.10-5.34 <0.001

Angina 2.10 1.27-3.46 0.004

Diabetes 1.86 1.16-3.00 0.010

IHD 1.57 0.95-2.59 0.077

Enrolment period 0.69 0.51-0.92 0.011

c-statistic 0.76

Underuse of secondary prevention therapies with prior history of CHD

In this analysis underuse was defined as both “no therapies” and “less than two therapies”.

Table 7-41 shows logistic regression models for predictors of underuse of secondary prevention

therapy using each definition. Underuse of therapies was negatively associated with older age

and, the presence of cardiac related comorbidities and positively associated with smoking.

Table 7-41: Predictors of underuse of cardioprotective therapies

No therapies Less than two therapies

Adjusted

OR

95% CI

χ2 p

Adjusted

OR

95% CI

χ2 p

Male gender 1.39 0.87-2.21 0.17 1.23 0.76-1.99 0.40

Age, years

≥80 0.21 0.11-0.41 <0.001 0.36 0.17-0.74 0.005

70-<80 0.26 0.14-0.48 <0.001 0.54 0.28-1.04 0.066

60-<70 0.35 0.19-0.67 0.001 0.49 0.25-0.99 0.047

<60 1.00 1.00

CHD 0.26 0.12-0.60 0.002 0.17 0.09-0.34 <0.001

Hyperlipidemia 0.18 0.11-0.29 <0.001 0.22 0.14-0.36 <0.001

Hypertension 0.28 0.18-0.43 <0.001 0.27 0.17-0.43 <0.001

CVD 0.19 0.09-0.40 <0.001 0.28 0.15-0.52 <0.001

IHD 0.32 0.17-0.60 <0.001 0.39 0.22-0.71 0.002

Smoking 1.66 0.95-2.90 0.073 2.12 1.10-4.11 0.025

c-statistic 0.872 0.882


7.5.2 Drug discontinuation

This section compared the group of respondents to the follow-up surveys who discontinued at

least one secondary prevention drug during the follow-up period, with the group that continued

all secondary prevention drugs prescribed at discharge. The aim of this analysis was to

determine care related factors that might be associated with drug discontinuation, while

controlling for other factors.

Discontinuations are based on drugs prescribed at the time of discharge, but not reported as

being used by the patient at follow-up. Comparisons are based on characteristics at discharge

and patient responses to the follow-up surveys. Response to the late follow-up survey was

independent of whether a drug was discontinued by early follow-up (78% versus 76%,

p=0.708). Some of the medications discontinued at the early follow-up were recommenced by

the late follow-up. Very few respondents discontinued more than one drug (Table 7-42)

Table 7-42: Number of drug discontinued

Drugs discontinued Total Antiplatelet agent Beta-blocker Statin ACE inhibitor

Early follow-up N=292 N=16 N=35 N=10 N=19

None 78% - - - -

One 17% 75% 63% 50% 58%

Two 4% 19% 31% 30% 37%

Three 1% 6% 6% 20% 5%

Late follow-up N=240 N=14 N=44 N=10 N=26

None 70% - - - -

One 24% 64% 68% 30% 65%

Two 4% 29% 20% 30% 15%

Three 2% 1% 11% 40% 19%


Baseline characteristics at discharge

Table 7-43 compares baseline characteristics by discontinuation of at least one drug.

Discontinuation of at least one therapy was negatively associated with male gender and

positively associated with beta-blocker prescription at discharge. There was a marginal

negative association between hyperlipidemia prior to admission and discontinuation of at least

one therapy.


Table 7-43: Drug discontinuation by characteristics at hospital discharge

Early Late

Discontinued Discontinued

No

N=228

Yes

N=64

No

N=199

Yes

N=41


<60 years 40.4 43.8 0.62 38.2 34.2 0.63

Male 80.7 67.2 0.022 79.9 65.8 0.050

Tertiary hospital 75.0 73.4 0.80 75.9 68.3 0.31

Public patient 79.8 82.8 0.59 79.4 75.6 0.59

Cardiology 93.9 96.9 0.54 94.5 92.7 0.66

Smoker 27.6 26.6 0.86 22.1 26.8 0.51

Revascularisation 35.1 26.6 0.20 36.2 31.7 0.57

Hypertension 49.6 42.2 0.30 50.8 51.2 0.96

Hyperlipidemia 68.4 56.2 0.070 66.8 53.7 0.11

Diabetes 24.1 17.2 0.24 26.1 22.0 0.58

Comorbidity index>0 29.8 23.4 0.32 32.2 29.3 0.72

Discharge prescriptions

Antiplatelet 93.9 95.3 0.66 93.5 95.1 1.00

Beta-blockers 79.4 95.3 0.003 82.9 95.1 0.046

Lipid lowering 83.8 76.6 0.18 81.9 82.9 0.88

ACE inhibitor 61.8 60.9 0.90 59.3 68.3 0.28

Risk factor history

Drug discontinuation by risk factor history reported at early follow-up is shown in Table 7-44.

There was a marginal negative association with hyperlipidemia requiring medication prior to

admission.

Table 7-44: Drug discontinuation by medical history on admission

Discontinued drug

No

N=228

Yes

N=64

Percent χχχχ2 p

Hypertension requiring medication 41.2 32.8 0.22

Hyperlipidemia requiring medication 39.5 26.6 0.058

Overweight 42.1 40.6 0.83

Inactive 48.7 50.0 0.85

Diabetes requiring medication 11.8 12.5 0.88

Smoker on admission 30.3 32.8 0.70


Inhospital experience

Generally, less verbal communication was associated with drug discontinuation, whether this

related to the provision of advice about risk factors or communication related to aspects of care

(Table 7-45). Composite variables for risk factor counselling and satisfaction with

communication had even stronger associations. Using a composite variable to indicate less

verbal communication that included both less counselling about risk factors and dissatisfaction

with at least one aspect of inhospital communication, the association was even stronger. Not

receiving a discharge medication list was also (marginally) associated with drug

discontinuation. However there was no association with the provision of other written

materials, or with attendance at group cardiac rehabilitation sessions or a single follow-up

telephone call. The summary variables for risk factor counselling, and satisfaction with

communication about care were combined with not receiving a discharge medication list into

one variable to indicate less discharge planning. Less discharge planning was defined as having

at least two of “no counselling for 3 or more risk factors”, “definitely not satisfied with or more

aspect of communication in hospital” and “no discharge medication list”. Almost one half of all

respondents to the early follow-up survey (124/292) were classified as having poor

communication including two thirds (40/64) of patients who discontinued at least one drug and

just over one third (84/228) of those who continued with medications prescribed at discharge

(p<0.001).


Table 7-45: Drug discontinuation by inpatient experience

Discontinued drug

No

N=228

Yes

N=64

Percent χχχχ2 p

No education about medications 7.0 7.8 0.83

No risk factor intervention:

Cholesterol 35.5 37.5 0.77

Blood Pressure 54.0 57.8 0.58

Diabetes 78.1 79.7 0.78

Weight 72.8 84.4 0.058

Physical Activity 44.7 54.7 0.16

No counselling for 3 or more risk factors 59.2 70.0 0.021

Definitely not satisfied:

Enough information 4.4 9.4 0.13

Good answers 2.6 10.9 0.010

Able to ask questions 12.7 17.2 0.36

Tests explained 6.6 10.9 0.24

Results explained 8.8 9.4 0.88

Treatment discussed 13.2 10.9 0.64

Medicines explained 29.8 39.1 0.16

Family informed 22.4 34.4 0.050

Recovery explained 12.3 7.8 0.32

Definitely not satisfied with 1 or more aspect 45.6 59.4 0.052

Less verbal communication 31.1 48.1 0.010

Written materials

No discharge medication list 17.5 28.1 0.061

No medication information 46.9 50.0 0.66

No risk factor information 51.3 42.2 0.20

No contact telephone number 36.8 40.6 0.58

Follow-up telephone call 29.4 23.4 0.35

Exercise program 11.0 14.1 0.50

Medication session (in hospital or follow-up) 8.3 7.8 0.89

No sessions (in hospital or follow-up) 61.0 64.1 0.65

Less discharge planning 36.8 62.5 <0.001


Post-discharge treatment

The extent of post-discharge treatment had little influence on drug discontinuation (Table 7-46).

The notable exception was CABG after the index admission, which was associated with drug

discontinuation although a cardiac related readmission was marginally negatively associated

with drug discontinuation.

Table 7-46: Drug discontinuation by post-discharge treatment



No

N=228

Yes

N=64

No

N=199

Yes

N=41


ECG 46.9 53.1 0.38 50.2 48.8 0.86

Echocardiogram 26.8 35.9 0.15 30.6 22.0 0.26

Exercise stress test 34.6 29.7 0.46 39.2 31.7 0.37

Radionuclide test 17.5 17.2 0.95 15.1 17.1 0.75

No tests 28.1 21.9 0.32 29.6 29.3 0.96

Readmission 44.7 50.0 0.46 39.7 26.8 0.12

Heart related readmission 39.0 42.2 0.65 27.1 12.2 0.043

Reinfarction n/a n/a n/a 7.5 2.4 0.32

Cardiac angiogram 19.7 26.6 0.24 22.1 17.1 0.47

PCI 11.8 6.5 0.20 14.1 7.3 0.24

CABG 4.8 14.1 0.010 6.0 9.8 0.49

Any revascularisation 16.7 20.3 0.50 19.6 17.1 0.71

No invasive procedure 66.2 56.2 0.14 65.8 73.2 0.36

Follow-up with

Cardiology 86.0 93.8 0.094 50.8 51.2 0.96

Dietician 4.4 4.7 0.92

Social worker 2.2 3.1 0.67

Occupational therapist 2.6 7.8 0.054

Rehabilitation Nurse 4.8 1.6 0.24


There was also no association between drug discontinuation up to the early follow-up and the

patient-general practitioner relationship at early follow-up (Table 7-47).

Table 7-47: Drug discontinuation by patient-general practitioner relationship

Early follow-up Discontinued drug

No

N=228

Yes

N=64

Percent χχχχ2 p

Dissatisfied with aspect of general practitioner care

Not talking down 11.3 14.1 0.54

Listens 14.5 12.5 0.69

Discusses treatment 27.1 28.6 0.82

Encourages questions 27.2 20.3 0.27

Explains 25.7 28.6 0.65

Uses plain language 17.1 15.9 0.82

Unhappy with 4 or more aspects 33.7 28.1 0.39

Risk factor monitoring

There were no associations with monitoring of individual risk factors and drug discontinuation

(Table 7-48).

Table 7-48: Drug discontinuation by risk factor monitoring

Early follow-up Discontinued drug

No

N=228

Yes

N=64

Percent χχχχ2 p

No follow-up monitoring

Cholesterol 37.7 37.5 0.97

Blood pressure 2.2 6.2 0.10

Blood sugars 64.9 62.5 0.72

Weight 71.0 73.4 0.71

Physical activity 46.9 42.2 0.50

Late follow-up Discontinued drug

No

N=199

Yes

N=41

Percent χχχχ2 p

Cholesterol measure <12 months 87.9 90.2 0.66

High cholesterol level 23.6 29.3 0.44

Blood pressure measurement<12 months 93.5 92.7 0.85

High Blood pressure 23.1 24.4 0.86


Current status

Concomitant therapies

Use of each drug was significantly less frequent in the group of patients with at least one

discontinued drug, with the relative proportions reflecting discontinuation rates of the various

drugs (Table 7-49).

Table 7-49: Drug discontinuation by concomitant therapies



No

N=228

Yes

N=64

No

N=199

Yes

N=41

Current drugs Percent χχχχ2 p Percent χχχχ2 p

Antiplatelet agent 94.7 71.9 <0.001 92.0 78.0 0.008

Beta-blockers 85.5 40.6 <0.001 80.9 31.7 <0.001

Statins 92.1 65.6 <0.001 89.4 68.3 <0.001

ACE inhibitor 69.3 37.5 <0.001 66.8 34.2 <0.001

Confidence about medications

Purpose 65.8 76.6 0.10 94.0 97.6 0.70

Timing 76.8 82.8 0.30 97.5 100.0 0.59

Social factors

There was little influence of social factors on drug discontinuation (Table 7-50), although there

was a trend for smoking to be associated with drug discontinuation, particularly at the early

follow-up.

Table 7-50: Drug discontinuation by current status



No

N=228

Yes

N=64

No

N=199

Yes

N=41


Living with family 81.1 81.2 0.98 80.4 70.7 0.17

Working full-time 27.2 17.2 0.10 n/a n/a

Working less 33.8 28.1 0.39 39.7 39.0 0.96

Smoker 13.2 21.9 0.085 10.6 17.1 0.28


Health status

The symptoms of shortness of breath and chest pain were not associated with drug

discontinuation (Table 7-51). Nor were there any associations with scores in the Seattle Angina

Questionnaire (SAQ) at early follow-up (Table 7-52). However at the late follow-up there was

a direct association between the physical limitation score and drug discontinuation.

Table 7-51: Drug discontinuation by heart related health



No

N=228

Yes

N=64

No

N=199

Yes

N=41

χ2 p


Shortness of breath

No shortness of breath 34.2 43.8 0.16 34.2 41.5 0.37

Rest or with mild exertion 31.6 28.1 0.60 12.1 9.8 0.80

Chest pain

Chest pain <4 weeks 41.2 34.4 0.32 25.1 26.8 0.82

No angina medications, including GTN 76.8 84.4 0.19 52.3 56.10 0.65

Completed SAQ 46.0 39.1 0.32 n/a n/a

Table 7-52: Drug discontinuation by Seattle Angina Questionnaire scores1

Discontinued drug Discontinued drug

No Yes No Yes

Score>80 Score<60

Early follow-up N=105 N=25 N=105 N=25


Physical limitation 66.7 68.8 0.75 23.2 17.2 0.30

Angina stability 66.7 71.9 0.43 26.8 23.4 0.59

Angina frequency 64.9 73.4 0.20 14.9 7.8 0.14

Treatment satisfaction 77.2 87.5 0.071 11.8 6.2 0.20

Disease perception 64.5 68.8 0.52 25.9 25.0 0.88

Late follow-up N=50 N=11 N=50 N=11


Physical limitation 4.0 27.3 0.037 76.0 36.4 0.010

Angina stability 12.0 18.2 0.63 74.0 72.3 0.93

Angina frequency 10.0 9.1 1.00 30.0 27.3 1.00

Treatment satisfaction 46.0 45.4 0.97 28.0 27.3 1.00

Disease perception 26.0 0.0 0.10 54.0 36.4 0.34 1Scores for each domain calculated according to the scoring instruction (Spertus 1993)


Similarly, there were no associations between general health status as measured by the SF36

scales and drug discontinuation at early follow-up, but there were some associations at late

follow-up (Table 7-53). These included the SF36 items of Bodily Pain, Vitality, Emotional

Role and Mental Health. However only Bodily Pain score was associated with drug

discontinuation consistently with high scores (less pain) associated with reduced drug

discontinuation and low scores (more pain) associated with increased drug discontinuation.

Table 7-53: Drug discontinuation by general health status

Ongoing Stopped Ongoing Stopped

Early follow-up N=228 N=64

Percent χχχχ2 p

Better health than 12m ago 38.6 39.1 0.95

Score>(mean+SD) Score<(mean-SD)

Physical functioning 19.3 23.4 0.47 17.1 21.9 0.38

Physical role 21.9 26.6 0.44 25.0 23.4 0.80

Bodily pain 27.6 32.8 0.42 24.6 23.4 0.85

General health 21.5 23.4 0.74 21.5 23.4 0.74

Vitality 20.2 18.8 0.80 17.1 17.2 0.99

Social functioning 38.16 34.4 0.58 18.0 17.2 0.88

Emotional role 39.9 37.5 0.73 22.8 31.2 0.17

Mental health 10.5 17.2 0.15 13.6 21.9 0.10

Late follow-up N=199 N=41

Percent χχχχ2 p

Better health than 12m ago 88.4 78.0 0.075

Score>(mean+SD) Score<(mean-SD)

Physical functioning 9.6 7.3 0.65 17.6 24.4 0.31

Physical role 30.6 24.4 0.42 23.1 24.4 0.86

Bodily pain 34.7 14.6 0.011 22.6 36.6 0.060

General health 16.6 12.2 0.48 21.1 19.5 0.82

Vitality 12.6 2.4 0.058 17.1 24.4 0.27

Social functioning 41.2 36.6 0.58 16.1 19.5 0.59

Emotional role 48.2 31.7 0.052 18.6 24.4 0.39

Mental health 14.6 17.1 0.68 18.1 31.7 0.049

7.5.2.2 Multivariate analysis

When all variables with χ2 p<0.20 were included in a multivariate logistic regression analysis

there were a number of independent associations with drug discontinuation in the early and late

follow-up cohorts. Many of these associations were maintained in a multivariate analysis for

the cohort of patients that responded to both the early and late follow-up surveys. These

included both positive and negative predictors of drug discontinuation, including aspects of


baseline characteristics, inhospital care, follow-up care and current status (Table 7-54). There

was a consistent negative association with drug discontinuation and male gender, a diagnosis of

hyperlipidemia and beta-blocker prescription at discharge. Drug discontinuation was also

associated with a composite variable for less discharge planning, which included not receiving a

medication list, dissatisfaction with at least one aspect of inhospital communication and less risk

factor counselling. A consultation with an occupational therapist early after discharge was

positively associated with drug discontinuation while a heart related readmission during the

follow-up period was negatively associated. A low Physical Limitation score on the SAQ at the

time of late follow-up was negatively associated with drug discontinuation.

Other aspects of the current status were independent predictors of drug discontinuation. At the

early follow-up these included increased drug discontinuation with a high Treatment

Satisfaction on the SAQ and a high Mental Health score while full time employment was

associated with reduced drug discontinuation. At the late follow-up a high score for the Bodily

Pain component of the SF36 was associated with reduced drug discontinuation.

Consultation with a cardiologist or a cardiology outpatient clinic during the early follow-up

period was associated with drug discontinuation at early follow-up, however this association

was not maintained when only patients responding to the both the early and late surveys were

included.


Table 7-54: Multivariate logistic regression model for drug discontinuation

Adjust OR (95% CI) χχχχ2 p

Early follow-up

Baseline characteristics Age <60 years 2.13 (1.01-4.52) 0.048

Male gender 0.43 (0.21-0.90) 0.025

Hyperlipidemia 0.47 (0.24-0.89) 0.021

Inhospital Beta-blocker at discharge 7.08 (1.98-25.4) 0.003

Less discharge planning 3.31 (1.74-6.31) <0.001

Follow-up Cardiologist/outpatient clinic 4.21 (1.23-14.4) 0.022

Occupational therapy 7.02 (1.68-29.3) 0.008

Current High Mental score, SF36 2.35 (0.94-5.89) 0.068

High treatment satisfaction, SAQ 3.01 (1.20-7.58) 0.019

Full-time employment 0.38 (0.15-0.95) 0.038

c-statistic 0.785

Late follow-up

Baseline characteristics <60 years 0.83(0.37-1.84) 0.64

Male 0.38(0.17-0.87) 0.021

Hyperlipidemia 0.44 (0.20-0.94) 0.035

Beta-blocker at discharge 4.76 (1.00-22.6) 0.049

Follow-up Heart related readmission 0.22 (0.08-0.63) 0.005

Current Low physical limitation score, SAQ 0.32 (0.10-1.05) 0.059

High Bodily pain score, SF36 0.24 (0.09-0.64) 0.004

c-statistic 0.765

Early and late follow-up

Baseline characteristics Age <60 years 0.58 (0.29-1.18) 0.14

Male gender 0.38 (0.18-0.80) 0.011

Hyperlipidemia 0.34 (0.18-0.67) 0.002

Inhospital Beta-blocker at discharge 4.11 (1.23-13.7) 0.022

Less discharge planning 3.91 (1.46-10.5) 0.007

Follow-up Occupational therapy 9.30 (2.13-40.6) 0.003

Heart related readmission 0.38 (1.7-0.86) 0.021

Current Low physical limitation score, SAQ 0.30 (0.10-0.92) 0.036

c-statistic 0.773


7.6 Discussion

The focus of this chapter was on the actual use of secondary prevention drugs in ambulatory

care. The gap between the evidence and actual practice is discussed in the first section and the

second section discusses factors that were associated with the use of these therapies in the

current setting.

7.6.1 The treatment gap

Less than optimal long term treatment of patients with known CHD can be the result of a failure

to prescribe at hospital discharge, doctor or patient-initiated inappropriate discontinuation,

prescription of a less than effective dose or by partial adherence with the treatment regimen by

the patient. Prescriptions at discharged were described in Chapter 5. This chapter focused on

long term drug use in ambulatory care (Section 7.5.1.1), the extent to which prescribed

treatment regimes were optimal (Section 7.5.1.2) and patient adherence with the treatment

regimen (Section 7.5.1.3).

7.6.1.1 Long term use

Drug use prior to admission in patients with a prior diagnosis of CHD provided the first

estimate of long-term drug use. The finding that in patients with previous history of MI or

CARP, 76% were taking an antiplatelet and 53% beta-blockers, reflects a marked increase in

evidence based treatment in the past decade in the study setting. Earlier data available for

patients presenting to hospital with reinfarction in Perth, Western Australia, showed that in 1990

48% of patients were using aspirin and 40% were using beta-blockers (Thompson et al. 1992).

This earlier data was comparable with earlier overseas studies that found results ranging from

53% to 65% for aspirin and 29% to 44% for beta-blockers (Phillips et al. 1996; Kizer et al.

1999; McCormick et al. 1999a). Despite the increase in evidence-based practice, it was

estimated that for antiplatelet agents, beta-blockers and statins about one in five patients with a

history of CHD prior to admission and no contraindication to therapy were not using the therapy

prior to admission. This estimate assumed optimal prescribing at discharge with any under

prescribing at discharge leading to an underestimate of the problem of underuse in ambulatory

care. Estimates of underuse of ACE inhibitors was more problematic because of evolving

evidence for a possible anti-atherogenic role for ACE inhibitors resulted in changing prescribing

practice at discharge over the time of the study. Changes in the prevalence other indicators for

ACE inhibitors (heart failure and left ventricular dysfunction) pre and post the myocardial

infarction further complicated estimates of ACE inhibitors underuse. The level of use of ACE

inhibitors in patients with a history of CHD and heart failure prior to admission was comparable

with the earlier study of Putnam at al (Putnam et al. 2004).


While prevalence of drug use prior to admission in patients with a prior history of CHD

provides a point of comparison with other studies, it does not provide an estimate of drug use in

ambulatory care because use of secondary prevention therapies reduces the risk of a cardiac

event. Applying the protective effects of these drugs to the measured prevalence prior to

hospital admission provided estimates of use in ambulatory care. These estimates assumed that

the secondary prevention therapies were as effective in clinical practice as in the RCTs. There

is however, evidence to suggest this may not be the case. Frolkis et al, for example, found

significantly less reduction in LDL-C than expected from the results of the statin clinical trials,

arguing that this was the result of less than optimal patient adherence (Frolkis et al. 2002).

Other studies, including the current study, found that drugs, particularly beta-blockers and ACE

inhibitors, are prescribed at doses less than those demonstrated to be effective in the clinical

trials (Viskin et al. 1995; Hillis et al. 1996; Barron et al. 1998b; Luzier et al. 1999; Roe et al.

1999). A point of comparison for prophylactic cardiac drug use in patients with CHD in the

current setting was provided by a 1999 follow-up study of patients who underwent CABG in

Western Australia between 1980 and 1993 (Bradshaw et al. 2004). Comparisons varied with

drug class.

In the case of antiplatelet agents, the strong agreement with the finding in the Bradshaw study

suggested that the estimates for these agents were valid. The finding of only minor differences

between estimated use in the community and prescriptions at discharge suggested that

prescribing practices in primary care were similar to those at hospital discharge with minimal

discontinuation of these drugs. The minimal discontinuation of antiplatelet agents was

confirmed in the follow-up study.

The findings for statins were similar and led to similar conclusions; that the estimates were valid

and that prescribing practices for statins in primary care were similar to those at hospital

discharge, with minimal discontinuation of these drugs. Minimal discontinuation of statins was

confirmed by the unchanging level of statin use over the follow-up period and was consistent

with a study that found that the high levels of statins prescribed at discharge were maintained in

follow-up (Fonarow et al. 2001b). This contrasted with a number of other studies that found

moderately low statin use at discharge that increased during follow-up (Silagy 1996; Pearson et

al. 1997c; Brotons et al. 1998; Euroaspire II Study Group 2001; Muhlestein et al. 2001; Dalal et

al. 2003; Simpson et al. 2003). On the other hand, a study with a high rate of prescription at

discharge observed a moderate but significant reduction in use at 12 months compared with

discharge (69% to 62%, p<0.001) (Willich et al. 2001).

In the case of beta-blockers, use of beta-blockers determined by Bradshaw was low (36%)

compared with both the observed use prior to admission and the estimated use in all patients

with CHD. Bradshaw et al attributed the low use of beta-blockers to decreased use over time


and changes in post-CABG practice since their respondents underwent CABG. It is probable

that different prescribing practices in CHD in general, and post-CABG patients in particular,

may account for most of the beta-blocker differences between the two studies. The differences

between estimated use in the community and prescriptions at discharge for beta-blockers

suggested some combination of discontinuation and differences in prescribing practices between

hospital and primary care. Significant discontinuation of beta-blockers was confirmed by the

follow-up study.

ACE inhibitor use in the Bradshaw study (46%) was similar to use prior to admission for

patients with a history of CHD but less than the estimated use in the community. One possible

explanation for this difference is a lower effectiveness of ACE inhibitors in clinical practice.

Estimated use of ACE inhibitors in patients with known CHD was less than prescriptions at

discharge. As with beta-blockers this suggested some combination of drug discontinuation and

differences in prescribing practices between hospital and primary care. In the case of ACE

inhibitors, this probably resulted from differences in prescribing practices between hospital and

primary care reflecting the evolving evidence for the role of ACE inhibitors. Increased

prescribing of ACE inhibitors at discharge over the study period was described in Chapter 5.

There was however, no increase in ACE inhibitor use over the follow-up period (from discharge

to early and late follow-up). The different prescribing practices between the hospital and

primary care were illustrated by the influence of the enrolment period on use at the early and

late follow-up. Initiation of therapy in primary care for patients in the earlier enrolment periods

not prescribed an ACE inhibitor at discharge would have neutralised the increased prescription

with enrolment period at discharge. Differential uptake of new drugs between specialists and

generalists has been well documented ((Hlatky et al. 1988; Ayanian et al. 1994; Chin et al.

1997; Go et al. 2000; Majumdar et al. 2001)). On the other hand, there was no evidence of

reduced use of ACE inhibitors over the follow-up period. One contemporaneous study of post-

MI patients found ACE inhibitor use increased from discharge to follow-up (Dalal et al. 2003)

although the rate of prescription at discharge was less than in the current setting.

The use of recommended therapies in ambulatory care was juxtaposed with the use of calcium

antagonists, not routinely recommended in post-MI patients. The finding that the odds of

initiating calcium antagonist therapy during the follow-up period was significantly less than for

the recommended drugs, was consistent with current guidelines. However, the finding of a

markedly increased likelihood of commencing a calcium antagonist post-discharge in patients

using a calcium antagonist prior to admission, but not prescribed a calcium antagonist at

discharge is of some concern. One possible explanation for this observation is incomplete

communication of the care plan to the general practitioner. Unless it is clearly stated that a drug

has been discontinued, doctors may assume that medications prior to admission continue as


before. An alternate explanation is the inappropriate cessation of the calcium antagonist during

the hospital episode, which may have been avoided by better communication with the general

practitioner, who has better knowledge of the patient’s history.

Drug discontinuation during follow-up

Discontinuation rates for cardioprotective therapies in the current study varied from about 5%

for antiplatelet agents and statins through to 15% for ACE inhibitors and 20% for beta-blockers.

Similar levels of discontinuation for these medications in post-acute coronary syndrome patients

were also noted at 6 months in a multinational study (Eagle et al. 2004).

While there are a number of legitimate reasons for discontinuing drugs, other discontinuations

may result from misunderstandings on the part of either the patient or the primary care doctor or

may reflect a patient preference. Although patients were asked to report drugs discontinued

since discharge at early follow-up only about one half of all apparent discontinuations were

reported. This lack of reporting may reflect a patient decision to not report discontinued drugs

or that therapy was never commenced, both suggesting a deviation from the regimen prescribed

at discharge. There was no evidence from the drug inventory taken during the home visit that

patients forgot to list medications they were taking.

Beta-blockers were unique in the current study as the only drug class where use decreased

significantly over the follow-up period. Decreased use of beta-blockers over time has been

reported in other follow-up studies (Czarn et al. 1992; Silagy 1996; Brotons et al. 1998;

Euroaspire II Study Group 2001; Willich et al. 2001; Butler et al. 2002; Mitra et al. 2002;

Underwood et al. 2002). However, the finding has not been universal with some studies finding

beta-blocker use maintained in follow-up care (Pearson et al. 1997c; Dalal et al. 2003; Simpson

et al. 2003).

The extent to which decreased use of beta-blockers in the current setting reflects the evidence

base that is strongest in the early post-infarction period is unclear. However, this is not

consistent with current guidelines that recommend ongoing use of beta-blockers. Anecdotally,

discontinuation of beta-blockers is attributed to adverse effects, although there is little evidence

in the literature to support the rates of discontinuation observed. Most studies showed only

small differences in adverse events between beta-blockers and placebo (Beta-Blocker Heart

Attack Trial Research Group 1982; Freemantle et al. 1999; Ko et al. 2002; Poole-Wilson et al.

2003). In the current study, adverse drug effects accounted for only one third of reasons for

stopping beta-blockers provided by patients and less than one half of reasons reported by

doctors. Patient initiated discontinuation of beta-blockers was suggested by the discrepancy

between beta-blocker use reported by patients and doctors. This included three times more

doctor-only than patient-only reports of beta-blocker use and the observation that in more than


one half of the doctor-only reports the patient reported discontinuing beta-blocker therapy. Both

beta-blocker prescribing in ambulatory care and improved patient adherence were found in an

educational intervention directed to doctors of post-MI patients (Zuckerman et al. 2004).

7.6.1.2 Treatment regimen prescribed

To date the discussion had centred on whether or not a particular drug class was used in long-

term care. This section examines specific aspects of the treatment regimen including the

specific drugs and doses used in ambulatory care.

Specific drugs

There were few overall changes in specific drugs prescribed during the follow-up period. The

exception was antiplatelet agents where there was a small but significant increase in the

proportion of patients with clopidogrel as the sole antiplatelet agent prescribed with a

corresponding decrease in the use of aspirin.

These changes probably reflected the evolving evidence for the use of clopidogrel alone or in

combination with aspirin in preventing secondary cardiac events (CAPRIE Steering Committee

1996; The Clopidogrel in Unstable Angina to Prevent Recurrent Events (CURE) Trial

Investigators 2001; Steinhubl et al. 2002). Any discussion on the appropriateness of these

changes must include the relative efficacy, safety and cost of each treatment regimen. While

clopidogrel alone or in combination with aspirin was shown to be beneficial compared to aspirin

alone, concern about the cost of clopidogrel and the increased risk of bleeding associated with

use of both agents has resulted in recommendations for only limited use of clopidogrel in

specific groups of patients. These include those unable to use aspirin, those using aspirin at the

time of an event and those at highest risk (Gorelick et al. 1999; Hung et al. 2003; Marshall

2003). With the small numbers involved in the current study it is unclear whether the change

represents a secular increase in clopidogrel prescribing over time since the publication of results

or if it represents an increase in clopidogrel prescription as patients develop symptoms over time

after the index infarction. Both are likely to be true. A recent Australian study of compliance

with clopidogrel prescribing guidelines found that clopidogrel use for one in three patients was

outside the prescribing guidelines (Kubler et al. 2004). Although the increase in clopidogrel

prescriptions was small in absolute terms, the change in relative terms was more than 100%.

Based on the dispensed price in Australia, clopidogrel treatment costs $3.00 per day compared

with aspirin which costs of about 6 cents per day (100 mg) or 3.6 cents per day (half of a 300

mg tablet)(Pharmaceutical Benefits Scheme 2005). Given the cost implications, there is a clear

need to monitor the ongoing use of clopidogrel.


The overall decrease in clopidogrel use over the follow-up period reflected the reduction in

combined therapy, which at the time of the study, was recommended only in the first month

following PCI. (personal communication, PLT)

Drug doses

Doses of beta-blockers, statins and ACE inhibitors prescribed in the current study were

markedly lower than the doses used in the landmark clinical trials. On the other hand, some

patients were prescribed higher doses of aspirin than recommended (Antithrombotic Trialists'

Collaboration 2002).

Aspirin

While higher doses of aspirin were recommended (locally) in the month immediately following

PCI (personal communication, PLT), concern about gastric bleeding in particular and increased

risk of bleeding in general suggests that the lowest effective dose should be used

(Antithrombotic Trialists' Collaboration 2002). However at late follow-up more than 10% of

cases were reported by general practitioners to be using aspirin 300mg. This finding did not

reflect the number of patients undergoing PCI in the previous month. Comparison between

doses of aspirin reported by patients and doctors at late follow-up showed that in most of these

cases patients were using 100-150 mg. This over-reporting of aspirin 300 mg suggested that

general practitioners were unclear on the treatment plan post-PCI and assumed patients

continued on the higher dose prescribed at hospital discharge following PCI. This highlights the

need for better communication between the hospital and to the general practitioner, particularly

where the treatment plan is for changes to drugs and doses in ambulatory care, as in the case of

the post-PCI regimen.

Beta-blocker

Compared with the doses of beta-blockers used in the landmark trials, dosages prescribed in the

current study were very low with only 10% of patients prescribed the doses used in the trials.

Low doses of beta-blockers have also been reported by others (Viskin et al. 1995; Barron et al.

1998b). Barron et al also examined outcomes of beta-blocker use in their setting and found that

treatment with lower doses of beta-blocker (≤50% of the effective dose) were associated with at

least as great a reduction in mortality as patients treated with higher doses. This finding

suggested that doses of beta-blockers required for risk reduction are less than those originally

used in the landmark clinical trials. However, Barron et al reported for doses 50% or less of the

effective dose, while doses 25% or less of the effective dose were used by more than one half

the patients in both the current study and the study of Viskin et al. Whether the benefit of beta-

blockers in the secondary prevention of CHD is still conferred at the doses of metoprolol or

atenolol commonly prescribed in the current study is unclear. Use of ineffective doses of beta-


blockers confers an unnecessary, albeit relatively small, cost on both the patient and the health

system, and it adds one more drug to what may well already be a complex treatment regimen for

no benefit.

Statins

The increased mean doses observed for all three commonly prescribed statins suggested an

attempt at dose titration to achieve target lipid levels. The extent to which this resulted in

achievement of appropriate lipid levels is discussed in Chapter 8. Corresponding with the

increased mean doses was an increase in the proportion of patients prescribed an “effective

dose” from the time of discharge to late follow-up. Nonetheless a significant but small

proportion of patients continued to be prescribed doses less than those used in the landmark

trials. This contrasted with the finding in a follow-up of the British regional heart study that

found 41% of patients using simvastatin and no patients using pravastatin were using the

appropriate doses (Whincup et al. 2002). Nonetheless, the relatively low doses prescribed are

of particular concern given the recent evidence showing the intensive lipid lowering using

atorvastatin 80mg was more effective than the modest lipid lowering observed with pravastatin

40mg (Cannon et al. 2004; Nissen et al. 2004b).

ACE inhibitors

Low doses of ACE inhibitors were sustained throughout the follow-up period. Although there

was a marginal increase in the proportion of patients prescribed ramipril 10mg at late follow-up

compared with hospital discharge, only one quarter of patients were prescribed 10mg at late

follow-up and there was no change in the dosages prescribed for perindopril or trandolapril

throughout the study. Similar low doses of ACE inhibitors have been reported in both patients

with heart failure and post-MI (Hillis et al. 1996; Roe et al. 1999; Underwood et al. 2002).

Reasons for the low doses used are unclear. Tolerance to target doses of ACE inhibitors in

clinical trials was high (The Heart Outcomes Prevention Evaluation Study Investigators 2000;

Lonn et al. 2001; Lau et al. 2002; The EURopean trial On reduction of cardiac events with

Perindopril in stable coronary Artery disease Investigators 2003).

One explanation for the use of low doses is that patients are continued on low doses with no

attempt to achieve the target dose. Whether this results from poor communication from the

hospital to the general practitioner and patient, or a reluctance to prescribe the higher

recommended doses is unclear. In a comparison of generalist and specialist physician

knowledge and use of ACE inhibitors in congestive heart failure, Chin et al found that

compared to generalists, cardiologists were more likely to increase ACE inhibitors to target

doses, although even cardiologists did so less than one half the time. Chin et al also noted that

cardiologists were more tolerant of a systolic blood pressure of 90 mm Hg (Chin et al. 1997).


Whether or not the lower doses frequently prescribed in the current study provided the level of

secondary prevention for coronary events observed in the landmark trials is unknown. However

some evidence of a dose response effect for ACE inhibitors has been demonstrated (Lonn et al.

2001; Marre et al. 2004; Rochon et al. 2004). The doses prescribed may have a significant

impact on the effectiveness of these drugs to prevent cardiovascular events and, by corollary,

impact on the burden of cardiovascular disease. The worst of all possible scenarios is the use of

ineffective doses that do not confer a benefit, but nonetheless confer a cost on the patient and

health system. Research needs to be carried to determine the lowest doses at which the

secondary prevention benefit is conferred. Until this research is available it is important that

doses of ACE inhibitor be titrated up to the maximum tolerable dose as used in the clinical

trials.

7.6.1.3 Adherence with treatment regimen

The observation that at late follow-up there was at least one discrepancy between doctor and

patient-reported drug use in about four in five patients was consistent with the findings in other

studies (Atkin et al. 1998; Bedell et al. 2000). While some of these discrepancies can be

attributed to patient non-adherence with the prescribed treatment regimen, others will result

from breakdown in communication between the various doctors involved in patient care as well

as between the patient and the doctor. In the context of secondary prevention of cardiovascular

events a doctor believing a patient is using a preventive drug the patient is not taking, represents

the greatest risk to less than optimal care. This was particularly the case for beta-blockers

where in a significant number of doctor-only reports the patient had reported discontinuing the

drug.

Drug discontinuation is the easiest type of non-adherence to measure. However, evidence from

the literature suggests that drug discontinuation represents only a fraction of non-adherence.

Estimates of the proportions of patients taking less than 80% of medications reported in the

literature have varied between about one half and one quarter of all patients (Rudd et al. 1993;

Rudd 1995; Svarstad et al. 1999). Estimates of missed doses vary from 13% to 25% (Svarstad

et al. 1999; Cramer 2002). In this study it was not possible to measure partial adherence

quantitatively, although some qualitative measure was available from the patient interviews.

This indicated both sporadic and systematic deviations from the prescribed treatment regimen.

Some of these deviations were intentional while others were unintentional. Most types of non-

adherence were observed ranging from the occasional missed pill, to drug holidays, to reduced

frequency and reduced dose. However the evidence from the home visit suggested that, where

patients were taking a drug, few patients were taking less than 80% of tablets. Although, this

must be taken in the context of volunteers who agreed to complete questionnaires and have a

home visit.


Most recent studies that have examined the proportion of prescribed tablets used by patients

involved the use of administrative data. In their study of post-MI patients, Simpson et al

defined high persistence as the proportion of patients who filled a discharge prescription and

whose prescriptions covered at least 80% of days in the year after discharge. Proportions varied

from 80% for statins to 69% for ACE inhibitors (Simpson et al. 2003). Three studies looked

specifically at the degree of adherence with statin prescription (Avorn et al. 1998; Benner et al.

2002; Jackevicius et al. 2002). All three studies found that regardless of the definition used,

adherence was increased with known CHD. Defining adherence as filling a prescription for 100

tablets at least every 120, days Jackevicius et al found that in a cohort of elderly patients almost

25% with ACS were non-adherent for statins by six months increasing to 40% at two years

(Jackevicius et al. 2002). Varying the number of days between prescriptions from 120 to 180,

the proportion of adherent patients increased from 40% to 62%. This suggested significant

partial adherence (50-80% of drugs used) in patients who continued to fill prescriptions. Using

a definition of non-adherence of Proportion of Days Covered (PDC) <20%, the proportion of

non-adherent patients increased from 29% at 6 months to 56% at 5 years (Benner et al. 2002).

The proportion of partially adherent patients (PDC=20-79%) also declined with time from 40%

at 3 months to 29% at 6 months to 18% at 5 years. An important observation of Benner et al

was that those initiating therapy in later years (1996-1998) were 21-25% less likely to stop or

reduce statins compared with therapy initiated in earlier years. This suggested that with the

increasing evidence for the benefits of statins, both complete discontinuation and partial non-

adherence are reduced. It is difficult to reconcile the findings of these studies with the

qualitative data from patient interviews that suggested that very few patients took less than 80%

of their tablets, including statins.

To date it has not been possible to access administrative data to repeat this type of analysis in

Australia, although this should soon be possible (personal communication, John Bass). There

have been few studies of drug discontinuation in Australia. In an early pharmacy-based

Australian study, 60% of patients prescribed lipid-lowering therapy had discontinued treatment

within 12 months, with one half occurring within three months. However, concurrently using

other cardiovascular drugs, reduced the risk of discontinuation by 31% (Simons et al. 1996). A

later study by the same group using prescription records, found a discontinuation rate of 30%

(Simons et al. 2000). This was very similar to the 29% non-adherence rate reported by Benner

et al (Benner et al. 2002).

Factors associated with non-adherence

While the home visit did not allow measurement of the degree of adherence it provided useful

information about the reasons for systematic deviations from the treatment regimen, which is of

greatest concern. This type of deviation was usually associated with a misunderstanding about


the treatment regimen, either in terms of what was expected or the rationale for the treatment

regimen. Speaking openly with patients about medication habits and convincing them of the

long-term benefits is an important factor in patient adherence (LaRosa et al. 2000).

Information, counselling and reminders have all been shown to be effective in increasing

adherence usually in combination (Haynes et al. 2002). Zuckerman et al showed that

information to doctors about factors contributing to adherence problems and actions needed to

increase adherence resulted in increased patient adherence (Zuckerman et al. 2004). In-patient

pharmaceutical counselling, linked to a medication and information discharge summary and a

medicine reminder card, contributed to better drug knowledge and compliance together with

reduced unplanned visits to the doctor and re-admissions (Al-Rashed et al. 2002). Discharge

medication lists have been shown to increase patients’ knowledge of their treatment regimen as

well as increase adherence (Raynor et al. 1993).

Discharge medication lists were recognised by patients as an important resource. However in

the current setting there was the potential for a number of errors in the medication list

particularly with regard to planned treatment changes and the rationale for medications. Having

a clear understanding of the rationale for treatment is seen as one the important steps towards

better patient adherence (Miller et al. 1997). There was some evidence of this in the current

study. The rationale for beta-blockers and ACE inhibitors were less clear for patients than

antiplatelets and statins. This was apparent both from the early follow-up survey and patient

interview. There was a corresponding increase in drug discontinuation for beta-blockers and to

a less extend ACE inhibitors. The answer to the question “why am I taking this medication?”

should be answered in terms of therapeutic goal (National Prescribing Curriculum). When no

symptoms are being treated, as is often the case in post-MI patients, then the therapeutic goal is

to prevent further cardiovascular events. Furthermore it is important to explain to the patient

that each of the prophylactic cardiac drugs achieves its therapeutic goal independently of other

drugs and that the effect is additive. Even in the case of statins where most respondents

indicated that these lowered cholesterol levels, there appeared to be a lack of understanding in

some patients, at least, about the therapeutic goal and particularly the concept of “the lower the

better”. A number of patients mentioned adjusting or ceasing medications because they were

“feeling well”, suggesting a lack of understanding that while at least some of these drugs may

have a role in symptom relief, they also have a prophylactic role beneficial even in the absence

of symptoms.

Fear of taking too many tablets and not liking to take tablets was a consistent theme. In some

cases this led to patients completely stopping a medication, taking a medication sporadically or

altering the recommended treatment regimen to spread the drugs out over the day. Patients need

to be reassured about the safety of taking multiple tablets at the same time and of the relative


risk and benefits of taking each of the prophylactic therapies. There is clearly a need for a

discharge process that provides clear information to patients about the treatment regimen,

particularly any planned changes to the treatment regimen. In the case of post-PCI patients, a

follow-up telephone call one-month post-PCI would ensure appropriate changes were made.

7.6.2 Predictors of long-term drug use

In terms of drug use prior to admission logistic regression models were able to explain most of

the variation. This suggested a clear pattern of care with moderately little random variation in

drug use. Clinical independent predictors of drug use accorded with the indications for each

drug including a history of CHD for antiplatelet agents, beta-blockers, lipid-lowering therapy

and ACE inhibitors but for not calcium antagonists. Similar associations with the number of

concomitant prophylactic therapies also accorded with the evidence that calcium antagonists are

not a secondary prevention therapy for CHD.

Analysis of the CHD cohort suggested that a history of CHD per se was not sufficient to ensure

the use of prophylactic therapies. Use of a greater number of prophylactic cardiac therapies was

associated with other cardiac related comorbidities and accorded both with other indications for

these agents as well as the notion that patients with more disease are more likely to adhere to

treatment. On the other hand the negative association between smoking and the number of

prophylactic therapies used has no clinical basis, but can only be explained by lack of adherence

in smokers.

Changes in drug use on admission over the study were observed for antiplatelet agents and

calcium antagonists. The increased use of antiplatelets may be explained by the introduction of

new preparations of aspirin and new antiplatelet agents suitable for patients unable to use older

preparations of aspirin. The negative association of enrolment period with calcium antagonist

use suggested an ongoing relinquishment of this treatment, reflecting a concern for the safety

and efficacy of this drug class in CHD. In a study of relinquishment of calcium antagonists,

Majumdar et al found no difference in relinquishment by specialty although generalists were

slower to adopt effective therapies (Majumdar et al. 2001). The slower adoption of effective

therapies probably explains the lack of increase in ACE inhibitor use prior to admission, which

contrasts with the increased prescribing at discharge described in Chapter 5.

Examination of the number of secondary prevention therapies used by the CHD cohort revealed

a small group of patients not using any therapies prior to admission, despite their increased risk

of cardiac events. Given the level of underuse of these therapies this small group of patients

using no therapies could explain about one half of the underuse.


Smoking was consistently associated with reduced odds of using risk reduction therapies, both

within the CHD cohort and in the wider cohort when adjusting for medical history. This

highlights a small group of patients at great risk of cardiac events not only through smoking, but

also through less than optimal use of risk reducing therapies. This points to a need for intense

management of smokers, particularly those with other risk factors, not only to assist with

smoking cessation but also to ensure ongoing adherence with treatment regimens.

7.6.2.1 Predictors of drug discontinuation

The aim of this analysis was to test the hypothesis that the health care system and health care

providers influence drug discontinuations. Ideally a separate analysis would have been carried

out for each drug class, because some factors associated with discontinuation would be expected

to drug specific. However the relatively small number of discontinuations precluded analysis

within individual drug classes, therefore the analysis was restricted to discontinuation of any

secondary prevention drug.

Some aspects of inpatient care including the extent of risk factor counselling, provision of a

discharge medication list and satisfaction with communication were associated with drug

discontinuation in bivariate analysis. There was no measurable association with aspects of the

patient-provider relationship in primary care.

In multivariate analysis, the positive association between drug discontinuation and less

discharge planning measured by a combination of; counselling about risk factors, patient

satisfaction with inhospital communication and, provision of a discharge medication list

supported the hypothesis. The relationship between the quality of communication with patients

as well as interpersonal aspects of care have been shown to influence a variety of health related

behaviours (DiMatteo 1994; Bultman et al. 2000; Culos-Reed et al. 2000). Another study

showed a negative association with aspects of care such as patient education and discharge

planning and long-term outcomes (Fremont et al. 2001). Fremont et al did not collect

information about adherence with medications. However, the authors note that at least part of

the reason for their findings may be related to the influence of communication with patients and

more interpersonal aspects of patient care on health related behaviour, which may influence

long-term outcomes including adherence with the medication regimen.

The finding that the relationship with the general practitioner was not associated with drug

discontinuation was surprising. A study of Bultman et al that showed that the physician’s

follow-up communication style was predictive of better medication adherence. The lack of

association between the general practitioner-patient relationship and drug discontinuation

observed in the current study may reflect the involvement of cardiology specialists in their care,

which could override the general practitioner-patient relationship.


Associations with other aspects of post-discharge care were unexpected. While the finding of

an association between early drug discontinuation and, a cardiology consultation and

consultation with an occupational therapist supported the hypothesis of an influence of the

health care system, it was not in the expected direction. The relatively small number of patients

seen by an occupational therapist suggested that the increased discontinuation within this group

may reflect characteristics of patients referred to occupational therapists rather than the

influence of the occupational therapist. The association with the occupational therapist was

maintained in the analysis of the combined surveys suggesting that this observation may not

have been a chance occurrence. In contrast to occupational therapists with very few

consultations, the majority of patients had at least one cardiology consultation in the early post-

discharge period. The observation that patients who had a cardiology consultation were more

likely to have discontinued a medication is counterintuitive to the notion that patients reviewed

by specialists and hospital clinics receive more appropriate treatment or, that patients given

more intense follow-up will be less likely to discontinue medications. It may however, reflect

less satisfactory encounters with cardiologists and cardiology clinics. Another explanation is

that the association reflected “appropriate” drug discontinuations, while general practitioners

may be reluctant to make changes to hospital/specialists instituted drug regimens. (Armstrong et

al. 1996; Pryce et al. 1996; Allery et al. 1997; Tomlin et al. 1999). Alternately patients

perceived to be at most risk either of requiring modification to the regimen or of non-adherence

were referred for cardiology follow-up. However, neither the possibility that this was a chance

association, nor the possibility that a cardiology consultation may increase patient drug

discontinuation can be discounted.

The negative association between drug discontinuation and a heart-related readmission to

hospital may not reflect contact with the health system per se but rather accords with the notion

that patients with more disease, or at least more consequences of disease, will be more adherent

with the recommended treatment regimen. However, a hospital readmission does provide

another opportunity to explain and reinforce the treatment regimen and to reinstate any

discontinued drugs.

There is a general notion that adherence to medical regimen tends to be lower in asymptomatic

patients and higher in those who have severe or frequent symptoms (Haynes et al. 1979).

Aspects of patient health including symptoms of heart failure and angina, as well as general

health and well being, were collected to enable control of health related factors. The influence

of health on patient adherence and indeed the influence of drug discontinuation on health

outcomes is complex and beyond the scope of this thesis.

In the current study there was some evidence of underuse of medications prior to admission in

the youngest group of patients with a history of CHD. A similar association was apparent at the


early follow-up survey, but this relationship was not maintained for the late follow-up survey or

the combined surveys. The relationships between ongoing drug use and age have varied

between studies including; increased adherence with increasing age (Monane et al. 1996;

Simons et al. 1996), no association (Butler et al. 2002) and an association between older age

and poor long term persistence (Benner et al. 2002).

Female gender was associated with drug discontinuation in the follow-up study. This contrasted

with the lack of association between gender and drug use prior to admission in patients with a

history of CHD. A negative association between compliance and female gender was noted by

Sung et al in their study of antihyperlipidemic medications (Sung et al. 1998). Similarly, Eagle

et al found that male gender was associated with better adherence to ACE inhibitor therapy, but

there was no association for aspirin or beta-blockers (Eagle et al. 2004). Butler et al on the

other hand, found no association with ongoing beta-blocker use and gender (Butler et al. 2002).

Similarly Monane et al also found no relationship between compliance and gender for

antihypertensive therapy (Monane et al. 1996).

Beta-blocker prescription at discharge was consistently associated drug discontinuation. This

reflected the increased discontinuation of beta-blockers compared with other prophylactic drugs.

However, it may also reflect increased discontinuation of an ACE inhibitor in the presence of

beta-blockers.

Despite the relatively small numbers in the current study, the c-statistic in the multivariate

logistic regressions of about 0.78 suggested that a moderate amount of the variation in

discontinuation was explained by these models, which included aspects of inhospital education

and counselling and follow-up care. This contrasted with the study of Eagle et al which included

only medical history, diagnosis and aspects of inhospital treatment and could explain very little

in the variation in adherence with individual drugs with c-statistics around 0.50 (Eagle et al.

2004).


7.7 Summary

This chapter tested the hypothesis that there was an underuse of secondary prevention therapies

in the long-term care of patients with CHD and, that changes to the healthcare system and the

patient-provider interaction could improve long-term drug use. Findings included:

• Estimated underuse of secondary prevention therapies prior to admission in patients with a

prior history of CHD of ranged from 20% to 25%. Being young (<60 years) and smoking

were associated with use of less than two secondary prevention therapies in the CHD group.

• More than 12 months post-MI prevalence of drug use was similar to prescription at

discharge for antiplatelet agents, statins and ACE inhibitors at 90%, 85% and 62%

respectively. However use of beta-blockers declined steadily over the follow-up period

from 85% prescription at discharge to 72% at late follow-up.

• Beta-blockers and ACE inhibitors were discontinued more frequently than statins and

antiplatelets.

• Less discharge planning was associated with a greater likelihood of drug discontinuation.

• Compared with the doses used in the landmark clinical trials, 90% of patients were using

low doses of beta-blocker and 65% were using low doses of ACE inhibitor. These

proportions did not change over the follow-up period. In the case of statins, the proportion

of patients prescribed a dose, at least equivalent to those used in the trials, increased from

60% at discharge to 73% at late follow-up.

• Almost all patients reported taking drugs on at least 80% of days. There were, however,

examples of unintentional systematic deviations that resulted from a lack of understanding

of the prescribed treatment regimen.

• Although the medication list was recognised as a useful resource by patients there was the

potential for a number of errors in this medication list as well as unclear explanations both

about the treatment plan and the reason for use of a particular medication.

7.8 Conclusions

Long-term use of secondary prevention therapies in known CHD was relatively high in the

current setting, but evidence of underuse remains. Underuse included:

• discontinuation of beta-blockers, and to a lesser extent ACE inhibitors, over the follow-up

period; and

• prescription of doses lower than those shown to be effective in secondary prevention,

particularly in the case of ACE inhibitors.

The observed association between drug discontinuation and less discharge planning supports the

hypothesis that the healthcare system and health care providers can influence patient adherence

in the study setting.

319 Chapter 8: Risk factor management

CHAPTER 8

RISK FACTOR MANAGEMENT

8.1 Introduction

The primary focus of this thesis is the use of drugs known to be effective in preventing cardiac

events in people with known CHD independent of risk factors, symptoms and comorbidities.

However, recommendations for the management of risk factors are also included in all

guidelines for the secondary prevention of CHD. In the current context, management of lipids

is particularly relevant. Guidelines for the management of lipids in patients with CHD include

advice on healthy eating as well as the use of statins to achieve the lipid goals. Management of

blood pressure is also of interest given that beta-blockers, ACE inhibitors and calcium

antagonist are all common antihypertensive agents. Treatment goals for lipids and blood

pressure continue to be revised downward (see Box). The management of diabetes and other

lifestyle risk factors including smoking, body weight and physical activity are also important

factors in risk reduction.

Lipids Blood Pressure

Lipids Goal1

(mmol/L) Category

Goal2

(mm Hg)

Systolic Diastolic

Total cholesterol <4.0 Optimal <120 <80

LDL- C <2.5 Normal <130 <85

HDL- C >1.0 High normal <140 <90

Triglycerides <2.0 High >140 >90

1(National Heart Foundation of Australia et al. 2003), 2(National Blood Pressure Advisory Committee 1999)

8.1.1 Objectives

The objective of this chapter is to examine the management of risk factors within the study

setting with particular reference to the monitoring of risk factors, the use of drugs to manage

risk factors and the achievement of treatment targets.


Management of lipids prior to admission and during the follow-up period are examined in

Section 8.2. Management of other risk factors during the follow-up period are examined in

Section 8.3. The implications of the findings are discussed in Section 8.4. Section 8.5 and

Section 8.6 provide the summary and conclusions for the chapter.


8.2 Lipid management

This section contains three parts. The first part examines the management of lipids prior to

hospital admission by examining inhospital lipid measurements and use of lipid lowering

therapy prior to admission. The second part examines inpatient monitoring and management of

lipids. The third part examines lipid management in the follow-up period.

8.2.1 Management of lipids prior to admission

Lipid measurements recorded in hospital are shown in Table 8.1. Overall, 58% had TC<5

mmol/L, varying from 77% of patients using statins to 50% of patients not using statins. In the

subgroup with prior history of CHD and using statins, the proportion with TC <4 mmol/L was

47% compared with 17% for the group with prior history of CHD and not using statins.

Similarly the proportion of the CHD subgroup with optimal LDL-C (<2.5 mmol/L) was 68%

and 35% in the group using and not using statins respectively.

Table 8.1: Lipid levels (mmol/L) at the time of admission

Overall Hyperlipidemia CHD

All Statin All Statin All Statin

Yes No Yes No Yes No

Sample (N) 496 147 349 236 151 85 120 68 52

mmol/L Percent Percent Percent

Total cholesterol <4 21.0 37.4 14.0 27.4 37.2 10.7 34.2 47.1 17.3

≥4 - <5 36.7 39.5 35.5 33.3 39.5 22.7 35.0 33.8 36.5

≥5 - <6 29.6 17.0 35.0 27.0 16.3 45.3 25.8 14.7 40.3

≥6 12.7 6.1 15.5 12.3 7.0 21.3 5.0 4.4 5.8

LDL-C <2.5 34.2 58.9 24.0 46.0 60.0 21.9 53.9 67.9 34.9

≥2.5 - <3.5 44.6 35.5 48.3 36.2 34.6 39.1 37.2 28.8 48.8

≥3.5 - <4.5 15.8 4.0 20.7 13.2 3.6 29.7 6.9 1.7 14.0

≥4.5 5.4 1.6 7.0 4.6 1.8 9.4 2.0 1.7 2.3

Triglycerides <2 70.8 71.5 70.4 63.7 71.6 50.0 68.4 66.7 70.6

≥2 - <4 23.9 22.2 24.6 29.8 22.1 43.2 26.5 27.3 25.5

≥4 5.3 6.2 4.9 6.5 6.3 6.8 5.1 6.1 3.9

HDL-C ≥1 53.8 59.7 52.4 54.1 61.4 42.0 46.3 44.3 48.9

<1 46.2 40.3 47.6 45.9 38.6 58.0 53.7 55.7 51.1

In the subgroup with a prior history of CHD (Table 8.2), hyperlipidemia was associated with

higher statin use (74.4% versus 26.1%, χ2p<0.001). Conversely underuse, estimated as the

proportion of patients prescribed a statin at discharge but not using a statin prior to admission,

was significantly greater in the group with no prior hyperlipidemia (48.6% versus 21.0%,

χ2p=0.003).


Table 8.2: Missed opportunity for treatment with statins with prior CHD

Statin prior to

admission

Statin

added at

Sample Yes No discharge Eligible Underuse

(N) Percent (n) Percent (n) Estimated percent

CHD 155 52.9 (82) 47.1 (73) 46.6 (34) 74.8 29.3

Hyperlipidemia 86 74.4 (64) 25.6 (22) 77.3 (17) 94.2 21.0

No hyperlipidemia 69 26.1 (18) 73.9(51) 33.3 (17) 50.7 48.6

8.2.2 Inpatient monitoring and management of lipids

The section examines the inpatient monitoring of lipid levels and strategies used for lowering

lipid levels including counselling about managing lipid levels and statin prescription.

8.2.2.1 Lipid monitoring

A complete lipid profile was recorded for 71% (442) of patients during the hospital episode,

while another 9% (54) had only a cholesterol level recorded. There was a marked difference in

the proportion of patients with recorded lipid profiles treated in cardiology compared with non-

cardiology (83% and 36% respectively, χ2p<0.001). These proportions increased to 93% and

40% when patients with only a cholesterol level recorded were included. Of those with only a

TC level recorded, 69% were treated at the affiliate hospital. Cholesterol only measurement

represented 30% of patients with any lipid measure at the affiliate hospital compared with less

than 5% in the tertiary hospital (χ2p<0.001).

Patient characteristics by availability of a complete lipid profile are shown in Table 8.3.

Patients with complete lipid profiles were younger with less comorbidity. They were more

likely to be male, treated at the tertiary hospital and, treated in a cardiology unit. Other

characteristics associated with complete lipid profiles included a primary diagnosis of

myocardial infarction, chest pain on admission, ST-elevation, a high peak CK and reperfusion.

These patients were also more likely to have a history of hyperlipidemia, but there was no

difference in lipid lowering therapy prior to admission. Conversely, heart failure, atrial

fibrillation, cerebrovascular disease, Creatinine >300 µmol/L and dementia were all negatively

associated with having a lipid profile recorded.


Table 8.3: Bivariate analysis of patient characteristics and complete lipid profile

Lipids measured

Yes

N=442

No

N=179

Mean (SD) t-test p

Age 65.8 (13.6) 75.0 (13.2) <0.001



Male 70.1 (310) 53.6 (96) <0.001

Tertiary hospital 80.3 (355) 63.7 (114) <0.001

Cardiology 87.6 (387) 44.7 (80) <0.001

Primary diagnosis 93.4 (413) 77.1 (138) <0.001

Chest pain on admission 75.3 (333) 40.2 (72) <0.001

ST-elevation 64.9 (287) 44.7 (80) <0.001

High-CK1 44.8 (198) 28.5 (51) <0.001

Reperfusion 31.2 (138) 12.8 (23) <0.001

Congestive heart failure 30.5 (135) 51.4 (92) <0.001

Dementia 1.4 (6) 6.7 (12) <0.001

Cerebrovascular disease 9.7 (43) 21.8 (39) <0.001

Atrial fibrillation 16.1 (71) 25.7 (46) 0.005

Hyperlipidemia, history 41.4 (183) 29.6 (51) 0.006

Anterior site 24.9 (110) 15.5 (28) 0.012

Creatinine >300 1.4 (6) 4.5 (8) 0.018

Admission lipid lowering therapy 29.2 (129) 26.8 (48) 0.55 1peak creatine kinase >720 U/L

In multivariate logistic regression the positive association with tertiary hospital, cardiology unit

and chest pain on admission were maintained while only being aged more than 80 years was

negatively associated with a lipid profile (Table 8.4).

Table 8.4: Multivariate analysis for predictors of lipid profile recorded

OR 95% CI χχχχ2 p

Cardiology 5.96 3.44-10.33 <0.001

Tertiary hospital 4.37 2.71-7.09 <0.001

Chest pain at admission 3.07 1.98-4.78 <0.001

Age, years

≥80 0.52 0.27-0.99 0.046

70-<80 0.80 0.44-1.45 0.47

60-<70 0.92 0.47-1.79 0.80

<60 1.00

c-statistic 0.819


8.2.2.2 Lipid management

A discussion about lipids prior to discharge was reported by 64% of respondents (Table 8.5).

Although 70% of respondents reported being prescribed a new lipid lowering medication, less

than one quarter said a doctor had spoken to them about lowering lipid levels. Less than one

half of respondents reported any dietary counselling and less than one third of respondents

reported any counselling about exercise.

Table 8.5: Inpatient management of lipids

Health professional Percent (n)

Doctor 22.6 (66)

Nurse 29.1 (85)

Other health professional 20.2 (60)

Not otherwise specified 17.1 (50)

None 36.0 (105)

Type of intervention Percent (n)

New medication 69.5 (135)

Diet advice 46.0 (86)

Reading Material 42.8 (80)

Exercise advice 31.6 (59)

Other 0.5 (1)

None 8.0 (15)

In the group not using lipid lowering therapy at the time of myocardial infarction, significantly

higher mean TC (p<0.001), LDL-C (p<0.001) and triglycerides (p<0.001) were associated with

statin prescriptions at discharge (Table 8.6). HDL-C levels were marginally lower in those

prescribed statins. A statin was prescribed to 75% of patients with total cholesterol ≥4 mmol/L

and 78% of patients with LDL-C ≥2.5 mmol/L and not using a statin prior to admission. In

those not prescribed therapy, 55% had an LDL-C ≥2.5 mmol and 70% had a TC level ≥4

mmol/L.


Table 8.6: Lipid concentrations (mmol/L) by newly prescribed statin

Statin prescribed

All

N=349

Yes

N=243

No

N=106

mmol/L Mean (SD)

Total cholesterol 4.96 (1.01) 5.19 (0.96) 4.42 (0.89)

LDL-C 3.05 (0.88) 3.27 (0.84) 2.56 (0.79)

Triglycerides 1.73 (1.16) 1.87 (1.26) 1.41 (0.76)

HDL-C 1.11 (0.35) 1.08 (0.30) 1.17 (0.43)

Percent (n)

Total Cholesterol <4 14.0 (49) 7.4 (18) 29.2 (31)

≥4 - <5 35.5 (124) 32.9 (80) 41.5 (44)

≥5 - <6 35.0 (122) 39.1 (95) 25.5 (27)

≥6 15.5 (54) 20.6 (50) 3.8 (4)

LDL-C <2.5 24.0 (72) 14.5 (30) 45.2 (42)

≥2.5 - <3 .5 48.3 (145) 50.2 (104) 44.1 (41)

≥3.5 - <4.5 20.7 (62) 26.1 (54) 8.6 (8)

≥4.5 7.0 (21) 9.2 (19) 2.2 (2)

Triglycerides <2 70.4 (243) 64.7 (156) 83.6 (87)

≥2 - <4 24.6 (85) 29.0 (70) 14.4 (15)

≥4 4.9 (17) 6.2 (15) 1.9 (2)

HDL-C ≥1 52.4 (164) 50.2 (110) 57.4 (54)

< 1 47.6 (149) 49.8 (109) 42.6 (40)

In multivariate analysis, with lipid measurements entered as continuos variables TC, LDL-C and

HDL-C were all independently associated with statin prescription (Table 8.7). Each increase of

1 mmol/L in TC increased the odds of statin prescription by 74%.

Table 8.7: Lipid levels as predictors of statin prescription

OR 95% CI χχχχ2 p

Total cholesterol 1.74 1.48-2.04 <0.001

LDL-C 1.43 1.11-1.84 0.006

HDL-C 0.37 0.21-0.67 0.001

c-statistic 0.808


8.2.3 Monitoring and management of lipids in follow-up care

This section includes information from the patient and general practitioner surveys. It examines

the monitoring of lipids after hospital discharge and whether therapeutic goals were achieved.

8.2.3.1 Patient survey

No cholesterol check since leaving hospital was reported by 37.7% (110 of 292) of respondents

to the early patient survey. This included 32.8% (44 of 134) of respondents newly commenced

on therapy at discharge. At late follow-up, most respondents had a lipid measurement within

the previous 12 months (Table 8.8). Less than one half of respondents reported optimal

cholesterol levels at the time of the last measurement with almost 20% of respondents unsure of

their cholesterol level. A more recent lipid measurement was associated with an increased

proportion with cholesterol <5.5 mmol/L (trend p<0.001).

Table 8.8: Last lipid measurement at late follow-up

Time lag Cholesterol level Percent (n) Time lag <5.5 mmol/l

Percent (n) (mmol/L) Percent (n)

≤3 months 48.8 (117) <4.5 41.2 (99) ≤3 months 84.2 (96)

≤6 months 21.7 (52) 4.5 –<5.5 27.9 (67) ≤6 months 76.9 (40)

≤12 months 17.9 (43) ≥5.5 7.5 (18) ≤12 months 61.0 (25)

>12 months 1.7 (4) Not sure 17.1 (41) >12 months 25.0 (1)

Missing 10.0 (24) Missing 6.2 (15)

8.2.3.2 General practitioner survey

Some measure of post-discharge lipid levels was available for 149 (87%) patients including 134

(77%) patients with complete lipid profiles. These proportions were similar for patients using

statins (87%, 78%) and not using statins (83%, 75%). The median time since the last lipid

measurement was 130 days (quartile 59-211 days). There were seven cases where it had been

more than 12 months since the last lipid test and 28 cases where the date of the lipid test was

after the date of completion of the patient questionnaire.

Mean lipid levels

TC levels ranged from 2.5 to 7.2 mmol/L with a mean (95% CI) of 4.50 (4.37-4.64) mmol/L.

LDL-C levels ranged from 1.2 to 4.7 mmol/L with a mean (95% CI) of 2.57 (2.46-2.69)

mmol/L. HDL-C levels ranged from 0.50 to 2.90 with a mean (95% CI) of 1.22 (1.16-1.28)

mmol/L. At late follow-up there was no difference in mean lipid levels between those using and

not using statins (Table 8.9).


Table 8.9:Mean lipid levels (mmol/L) at follow-up by statin use

Statin at follow-up N Mean SD Min Max t-test p

Total cholesterol Yes 130 4.51 0.86 2.5 7.2

No 19 4.46 0.74 3.3 5.9

0.82

LDL-C Yes 117 2.57 0.68 1.2 4.7

No 17 2.58 0.57 1.5 3.8

0.98

HDL-C Yes 117 1.23 0.36 0.5 2.9

No 18 1.13 0.32 0.6 1.7

0.28

Changes in lipid levels

The absolute and percentage change in lipid levels from the time of myocardial infarction to

follow-up for patients with new statin prescriptions is shown in Table 8.10.

Table 8.10: Direct comparison of lipid levels following statin prescription

Absolute change (mmol/L)

N Mean SD Median 25% 75%

Total cholesterol 77 -0.564 0.763 -0.600 -1.1 -0.1

LDL-C 62 -0.661 0.659 -0.700 -1.1 -0.3

HDL-C 65 0.140 0.303 0.100 0 0.21

Percent change

N Mean SD Median 25% 75%

Total cholesterol 77 -10.40 15.72 -11.4 -21.0 -2.2

LDL-C 62 -19.38 21.15 -21.8 -33.3 -11.3

HDL-C 65 15.36 33.21 8.3 20.2 0

While TC, LDL-C and HDL-C changed significantly from the time of MI to late follow-up in

patients newly prescribed statins, levels did not change in the complete cohort (Table 8.11). In

patients newly prescribed statins, the proportion of patients achieving therapeutic goals

increased from 10 to 27% for TC, 20 to 53% for LDL-C and from 50 to 63% for HDL-C,

though this last difference was not statistically significant.


Table 8.11:Changes in lipids from MI to late follow-up in all patients

Overall New prescriptions

MI Follow-up MI Follow-up

Sample 159 149 t-test p 91 81 t-test p

Total cholesterol Mean (95% CI) 4.63 (4.49-4.78) 4.50 (4.37-4.64) 0.20 4.98 (4.78-5.17) 4.35 (4.16-4.53) <0.001

mmol/L Percent χχχχ2 p Percent χχχχ2 p

<4 20.8 23.5 0.56 9.9 27.2 0.003

≥4-<5 42.8 50.3 0.18 38.5 54.3 0.037

≥5-<6 28.9 20.8 0.10 38.5 14.8 <0.001

≥6 7.6 5.4 0.44 13.2 3.7 0.028

Trend p 0.11 <0.001

N 140 134 t-test p 78 75 t-test p

LDL-C Mean (95% CI) 2.72 (2.59-2.86) 2.57 (2.46-2.69) 0.095 3.09 (2.91-3.27) 2.49 (2.33-2.64) <0.001


<2.5 37.1 47.8 0.075 20.5 53.3 <0.001

≥2.5-<3.5 45.7 42.5 0.60 50.0 41.3 0.28

≥3.5-<4.5 14.3 9.0 0.17 24.4 4.0 <0.001

≥4.5 2.9 0.8 0.19 5.2 1.3 0.19

Trend p 0.23 <0.001

N 146 135 t-test p 82 75 t-test p

HDL-C Mean (95% CI) 1.11(1.06-1.16) 1.22 (1.16-1.28) 0.006 1.08 (1.01-1.14) 1.20 (1.12-1.28) 0.018


>1 56.2 64.4 0.16 50.0 62.7 0.110

≤1 43.8 35.6 50.0 37.3


Therapeutic goal

A TC level (<4 mmol/L) was achieved by 23% (95%CI 17-30%) of the cohort, while 48%

(95%CI 39-57%) achieved LDL-C target levels (<2.5 mmol/L). Target HDL-C levels (>1

mmol/L) were achieved by 64% (95%CI 39-56%) of the cohort. Conversely, 26% of patients

still had a TC level ≥5 mmol/L and 29% still had an LDL-C ≥3 mmol/L.

Table 8.12 examines factors associated with achieving therapeutic goals in bivariate analysis. A

TC <4 mmol/L was associated with increasing age and decreasing baseline (time of myocardial

infarction) cholesterol level. Target LDL-C was associated with decreasing baseline LDL-C,

while a change in statin regimen during follow-up and use of a dose greater than that used in the

clinical trials were negatively related to the achievement of the therapeutic goal.

Conversely, Table 8.13 shows variables associated with high levels of TC and LDL-C in

bivariate analysis. Use of a statin prior to admission and a change in statin regime during

follow-up were both associated with increased odds of a TC level of at least 5mmol/L. A higher

dose of statin and a change in statin regimen were associated with increased odds of LDL-C of

3mmol/L or greater. Neither baseline level of TC or LDL-C was significantly associated with

the higher lipid levels.


Table 8.12: Factors associated with achieving therapeutic goals

Total cholesterol<4 mmol/L

Yes

N=35

No

N=114

Mean (SD) t-test p

Age 67.2 (14.2) 62.9 (12.5) 0.032


Male 25.2 (30) 16.1 (5) 0.29

Baseline cholesterol <4 mmol/L 43.3 (13) 13.9 (15) <0.001

≥4 - <5 mmol/L 50.0 (15) 42.6 (46)

≥5 mmol/L 6.7 (2) 43.5 (47)

Statin Prior to MI 15.7 (8) 27.3 (27) 0.11

Follow-up 22.9 (30) 26.3 (5) 0.74

Change in statin 28.6 (10) 36.5 (42) 0.39

Test ≤90 days 15.2 (9) 28.6 (26) 0.060

Type of statin Pravastatin 24.4 (11)

Simvastatin 21.9 (7) 0.79

Atorvastatin 21.7 (10) 0.76

Dosages >”effective dose” 24.0 (6) 40.9 (38) 0.13

<”effective dose” 16.0 (4) 16.1 (15) 0.99

LDL-C <2.5 mmol/L

Yes

N=64

No

N=70

p-value

Mean (SD) t-test p

Age 65.0 (10.4) 61.6 (9.3) 0.061

Percent (n)

Male 49.1 (53) 42.3 (11) 0.54

Baseline LDL <2.5 mmol/L 46.3 (26) 21.8 (12) 0.008

2.5-<3.5 mmol 48.2 (27) 56.4 (31)

≥3.5 mmol/L 5.4 (3) 21.8 (12)


Follow-p 47.9 (56) 47.1 (8) 0.95

Change in statin 26.6 (17) 45.7 (32) 0.022

Test≤90 days 42.9 (24) 51.3 (40) 0.34

Follow-up statin Pravastatin 58.5 (24)



Dosages >”effective dose” 26.0 (13) 46.4 (26) 0.031

<”effective dose” 18.0 (9) 16.1 (9) 0.79


Table 8.13: Bivariate analysis for factors associated with having high lipid levels

Total cholesterol≥5 mmol/L

Yes

N=39

No

N=111

Mean (SD) t-test p

Age, 63.3 (10.4) 64.1 (10.5) 0.64

Percent (n)

Male 23.5 (28) 35.5 (11) 0.18

Baseline TC <4 mmol/L 11.1 (4) 23.5 (24) 0.15

≥4 - <5 mmol/L 41.7 (15) 45.1 (46)

≥5 mmol/L 47.2 (17) 31.4 (32)


At follow-up 26.7 (35) 21.0 (4) 0.60

Change in statin 48.7 (19) 29.7 (33) 0.032

Test ≤90 days 32.2 (19) 22.0 (20) 0.16




Dosage >”effective dose” 41.9 (13) 35.6 (31) 0.53

<”effective dose” 19.4 (6) 14.9 (13) 0.57

LDL-C ≥3.0 mmol/L

Yes

N=39

No

N=95

Mean (SD) t-test p

Age 61.2 (9.9) 64.0 (10.5) 0.072

Percent (n)

Male 29.6 (32) 26.9 (7) 0.78

21.9 (7) 39.2 (31) 0.12

Baseline LDL-C <2.5 mmol 56.2 (18) 50.6 (40)

≥2.5 - <3.5 mmol/L 21.9 (7) 10.1 (8)

≥3.5 mmol/L


At follow-up 29.9 (35) 23.5 (4) 0.59

Change in statin 53.8 (21) 29.5 (28) 0.008

Test ≤90 days 37.5 (21) 23.1 (18) 0.070




Dosage >”effective dose” 58.1 (18) 28.0 (21) 0.004

<”effective dose” 19.4 (6) 16.0 (12) 0.68


Logistic regression models for achieving therapeutic goals are shown in Table 8.14. Prior statin

use and lipid levels at baseline were both negatively associated with achieving therapeutic goals.

In addition, changes in the statin prescribed during follow-up and a test within the previous 90

days were associated with reduced odds of achieving the LDL-C goal.

Table 8.14: Logistic regression model for achieving therapeutic goals

OR (95%CI) χ2 p

Total cholesterol < 4 mmol/L

N=109

Statin prior to MI 0.09 (0.02-0.39) 0.002

Cholesterol at MI 0.10 (0.04-0.30) <0.001

c-statistic 0.838

LDL-C <2.5 mmol/l

N=89

Statin prior to MI 0.05 (0.01-0.23) <0.001

Baseline LDL-C 0.10 (0.03-0.30) <0.001

Change in statin 0.33 (0.11-1.00) 0.049

Test<90 days 0.34 (0.12-1.00) 0.051

c-statistic 0.808

Conversely, prior statin use, baseline lipid levels and a change in statin prescription during

follow-up were independently associated with high lipid levels (Table 8.15).

Table 8.15: Logistic regression model for high lipids

OR (95%CI) χ2 p

Total cholesterol ≥ 5 mmol/L

N=109

Statin prior to MI 12 (4-40) <0.001

Cholesterol at MI 3.30 (1.42-7.61) 0.005

Change in statin 3.10 (1.13-8.53) 0.028

c-statistic 0.800

LDL-C ≥3.0 mmol/l

N=89

Statin prior to MI 14 (3-59) <0.001

LDL-cholesterol at MI 4.4 (1.7-11.6)) 0.003

Change in statin 3.3 (1.12-9.79) 0.030

c-statistic 0.804


8.3 Management of other risk factors

This section examines the management of blood pressure and hyperglycaemia, as well as the

monitoring of the lifestyle risk factors of smoking, weight and physical activity.

8.3.1 Blood pressure

Information about blood pressure management was available from the early and late follow-up

surveys of patients and the late follow-up survey of general practitioners.

8.3.1.1 Inpatient blood pressure management

A discussion about blood pressure prior to discharge was reported by less than one half of

respondents although, almost 80% of respondents reported being prescribed a new medication

to lower blood pressure (Table 8.16).

Table 8.16: Inpatient management of blood pressure


Doctor 21.6 (63)

Nurse 20.2 (59)



None 54.8 (160)



Monitoring Blood Pressure 34.8 (46)



Stress management 12.9 (17)

Other 3.0 (4)

None 8.3 (11)

8.3.1.2 Blood pressure management during follow-up

Patient

At early follow-up, 96.9% of respondents reported a blood pressure measurement since hospital

discharge, while 85.4% of respondents reported a blood pressure measurement within the

previous three months at late follow-up (Table 8.17). Three quarters of all respondents reported

good blood pressure at the last measurement, although almost 10% were not sure about their

blood pressure.


Table 8.17: Last blood pressure measurement at late follow-up

Time period Percent (n) Blood Pressure level Percent (n)

1 month 63.3 (152) Good 76.7 (184)

3 months 22.1 (53) A bit high 12.5 (30)

6 months 5.0 (12) High 0.42 (1)

12 months 2.1 (5) Low 0.42 (1)

>12 months 4.6 (11) Not sure 7.1 (17)

None 3.1 (7) Missing 2.9 (7)


A blood pressure measurement during the follow-up period was provided in 96% (166 of 172)

of the late follow-up general practitioner surveys. The medium time to the last measurement

was 35 days (quartiles 12-76 days). In 15 cases the blood pressure had been measured on the

same day the questionnaire was completed. There were only 11 cases where more than 6

months had lapsed since the last blood pressure measurement.

Blood pressure levels

The mean systolic blood pressure for this cohort was 128 mm Hg with a range of 90 to 180 mm

Hg. The mean diastolic blood pressure was 76 mm Hg with a range of 55 to 100 mm Hg. Table

8.18 shows the distribution of patients into the categories of blood pressure as defined as the

Australian Heart Foundation (National Blood Pressure Advisory Committee 1999). Based on

this classification 32% of the cohort were hypertensive and another 21% were at the high end of

normal. Only 21% of patients had an “optimal” blood pressure at follow-up.

Table 8.18: Distribution of blood pressure at follow-up

Percent (n) Systolic blood pressure Diastolic blood pressure

Optimal (<120/80) 21.1 (35) 23.5 (39) 51.2 (85)

Normal (<130/85) 25.3 (42) 24.1 (40) 34.9 (58)

High normal (<140/90) 21.7 (36) 22.3 (37) 7.2 (12)

High 31.9 (53) 30.1 (50) 6.6 (11)

The prevalence of hypertension was similar in patients prescribed any drug that lowers blood

pressure (31.6%) and those not prescribed any of these drugs (36%). However, the number of

patients with none of these drugs was small (11 patients, 6.6%). Prescription of individual

antihypertensive medications was not significantly different between the hypertensive and

normotensive group (Table 8.19).


Table 8.19: Prescription of BP lowering medications by blood pressure

BP≥140/90 mm Hg

Drug prescribed Yes

N=53

No

N=113

N Percent Percent χ2 p

Beta-blocker 121 66.0 76.1 0.17

ACE inhibitor 105 58.5 65.5 0.38

Calcium antagonist 28 24.5 13.3 0.071

Diuretic 34 18.9 21.2 0.72

Any BP lowering drug 155 92.4 93.8 0.74

There was no association between the number of blood pressure lowering medications

prescribed and good blood pressure control (OR 0.88; 95% CI 0.58-1.34, for each additional

medication prescribed).

8.3.2 Management of blood glucose

8.3.2.1 Inhospital monitoring and management of blood glucose

Blood glucose was measured in 80% (500/621) of patients during the hospital admission

including 88% (122/139) of patients with known diabetes. Glycated haemoglobins (HbA1c)

were measured in 47% (66/139) of patients with known diabetes. There was evidence of less

than optimal blood glucose control in 75% (92/122) of patients with a known history of

diabetes.

Table 8.20: Blood glucose during hospital admission

History of diabetes No history

N=139 N=482

Blood Glucose N=102 N=374

<6 mmol/L 14.7 47.6

6-7 mmol/L 10.8 23.8

>7 mmol/L 74.6 28.6

HbA1c N=66 N=26

<7% 24.2 84.6

≥7% 75.8 15.4

No measurement 12.2 21.6


Inhospital interventions reported in early follow-up patient surveys are shown in Table 8.21.

Table 8.21:In hospital blood glucose intervention


Doctor 8.9 (26)

Nurse 8.2 (24)



None 78.4 (229)

Intervention Percent (n)

Diet 46.0 (29)


Exercise 23.8 (15)

Advice on monitoring 22.2 (14)

Further tests 9.5 (6)

Referred to specialist 7.9 (5)

Other 1.6 (1)

Nothing 25.4 (16)

8.3.2.2 Blood glucose management in follow-up care

Patient

At the early follow-up survey 64.4% of respondents reported no blood glucose monitoring since

discharge, including 33% of those with diabetes recorded in the medical record. This included

one of six patients newly diagnosed with diabetes.

At the late follow-up, almost two thirds of the 39 respondents who reported diabetes or IFG

reported a blood test within the previous three months with 90% reporting a test within the last

12 months (Table 8.22). One half of these reported good glycaemic control at the last test.

Table 8.22: Blood glucose monitoring in follow-up care

Last measured Percent (n) Blood sugar level Percent (n)

3 months 61.5 (24) Good 48.7 (19)

6 months 17.9 (7) A bit high 38.5 (15)

12 months 10.2 (4) High 1 (2.6)

Missing 10.2 (4) Not sure 7.7 (3)

Missing 2.6 (1)



There were 42 patients with diabetes or IFG in the cohort based on the doctor report. In this

group of diabetic or glucose intolerant patients some measure of glycaemic control was

provided in 36 cases (86%), including 28 (67%) blood glucose levels and 30 (71%) glycated

haemoglobins (HbA1c). The medium time of the last test was 79 days (quartiles 24-158 days).

Blood glucose levels

The therapeutic goal of HbA1c<7% was achieved in only 40% of patients (Table 8.23).

Table 8.23: Blood glucose and HbGA1 levels

Quartiles

N Mean (SD) 25% 50% 75%

Blood glucose 28 7.6 (3.1) 5.6 6.7 8.2

HbA1c 30 7.5 (1.4) 6.4 7.3 8.1

No hypoglycaemic medications were prescribed for 13 diabetic patients. Of these, five had no

HbA1c recorded and two had HbA1c ≥7%. Thus of patients controlled by diet alone, 46%

(6/13) were known to be well controlled. Of the remainder of the diabetic patients, using at

least one hypoglycaemic medication, 21% did not have a HbA1c recorded and 55% had a

HbA1c ≥7% with only 24% known to be well controlled.

8.3.3 Smoking

Of the 90 respondents to the early follow-up survey who were smokers at the time of admission

only 10% reported no counselling regarding stopping smoking while an inpatient (Table 8.24).

This included two thirds of respondents who reported that a doctor had spoken to them about

smoking. However, very few respondents reported referral to a smoking cessation program,

nicotine replacement or a follow-up appointment about smoking. At the early follow-up, 35 of

the 90 smokers at the time of admission reported that no one had talked with them about

smoking since discharge.


Table 8.24: Smoking intervention


Doctor 65.6 (59)

Nurse 51.1 (46)



None 10.0 (9)


Reading material 35.6 (32)

QUIT program 10.0 (9)

Nicotine replacement 8.9 (8)

Follow-up 5.6 (5)

Other 4.4 (4)

None 42.2 (38)

The smoking status at follow-up is shown in Table 8.25. Of the 90 respondents who reported

smoking at the time of the index admission, 44 (49%) had subsequently stopped smoking. This

was maintained at late follow-up with 30 of 55 smokers (54%) reporting smoking cessation.

Table 8.25: Smoking status at follow-up

Follow-up

Early Late

Never smoked 28.8 (84) 27.9 (67)

Stopped before MI 38.0 (111) 45.8 (110)

Stopped since MI 15.1 (44) 12.5 (30)

Trying to stop 9.2 (27) 6.2 (15)

Smoking 6.5 (19) 5.4 (13)

Missing 2.4 (7) 2.1(5)

General practitioners reported 14 known smokers (8.1%) at late follow-up. This contrasted with

the patient questionnaire for the matching group of patients where 19 patients reported smoking.

Direct comparison showed that there were six cases where the doctor failed to report smoking

that was reported by the patient and one case where the doctor reported smoking not reported by

the patient. This represents a 31.6% (6/19) rate of missed reporting of smoking by the general

practitioner.


8.3.4 Weight management and physical activity

Although about one half of the patients reported being overweight at the time of hospital

admission, only about one quarter of patients reported being advised about their weight in

hospital (Table 8.26). In the early follow-up survey 71.6% of respondents reported no

monitoring or advice on weight management since hospital discharge.

Table 8.26: Weight management interventions


Doctor 10.6 (31)

Nurse 11.0 (32)



None 75.3 (220)





Program for weight loss 16.7 (12)

Follow-up 9.7 (7)

Other 2.8 (2)

Nothing 22.2 (16)

Almost one half of respondents had no physical activity-related counselling during the hospital

episode (Table 8.27). In the early follow-up survey 45.9% of respondents reported no

monitoring or advice on physical activity since hospital discharge.

Table 8.27: Physical activity interventions


Doctor 21.9 (64)

Nurse 23.0 (67)



None 46.9 (137)



Exercise program 16.8 (26)


Other 0.6 (1)

Nothing 21.9 (34)


8.4 Discussion

This chapter examined the management of biomedical and lifestyle risk factors in the study

setting, which included relatively high use of cardioprotective drugs. Management of lipid

levels was of particular interest given the role of statins in achieving therapeutic goals for lipids.

Similarly beta-blockers, ACE inhibitors and calcium antagonists are all recommended for the

treatment of hypertension. In a study of doctors beliefs, diabetes was described as the most

important risk factors for CHD followed by hypertension and raised lipids (Hobbs et al. 2002).

8.4.1 Lipids

This chapter focused on the monitoring of lipid levels and achievement of therapeutic goals.

Prescription of statins at hospital discharge and use of statins following a myocardial infarction

were described in Chapters 5 and 7 respectively. While use of lipid lowering therapy, and in

particular statins, are an important component of lipid management, diet and exercise are also

important factors, reflected in the guidelines (National Heart Foundation of Australia et al.

2003). However, patient reports of inpatient interventions for lipid levels suggested an

emphasis on the prescription of medications with much less attention to diet and exercise.

Patient reports may not accurately reflect the intervention delivered in hospitals but do provide

the patient’s perspective.

8.4.1.1 Monitoring of lipid levels

Measurement of cholesterol levels, particularly LDL-C are considered a necessary first step in

the appropriate treatment of patients admitted with MI and other ACS and should be measured

preferably within 24 hours of hospital admission (Adult Treatment Panel III 2002). Reported

measurement of LDL-C varies from 89% of patients not using lipid lowering therapy on

admission for MI or revascularisation (Lacy et al. 2002) to 55% of patients with an MI related

DRG (LaBresh et al. 2000). In this study setting, a complete lipid profile was available for only

71% of patients although a TC level was available for 80% of patients. This is very similar to

the findings of another Australian study where 82% of patients had a TC measurement

performed in hospital (Mudge et al. 2001).

Being treated in the tertiary hospital and cardiology unit were both strong independent

predictors of cholesterol measurement in hospital. However, patients not treated in cardiology

differed in many ways from patients treated in cardiology and there may have remained

unobserved differences that explained the non-measurement of cholesterol levels in these

patients. In particular, patient characteristics related to a delay in diagnosis of MI or late

presentation by the patient may have resulted in a missed opportunity for early lipid

measurement. This is supported by the finding that chest pain on admission was an independent


predictor of lipid measurement. The only other patient factor independently associated with

cholesterol measurement was being aged 80 years and over. This observation was consistent

with numerous studies showing under prescription of statins in the elderly and suggested that

modification of lipid levels is not a priority in the elderly (McAlister et al. 1999; Bennett et al.

2002). The difference in lipid measurements both by treatment specialty and hospital suggested

the presence of systematic factors facilitating early lipid measurement. While generally

accepted that lipid levels decrease immediately following an acute MI, and that lipid

measurements made after the first 24 hours are not valid, it has been shown that lipid ratios

remain constant following MI and, therefore, remain a valid measure even after 24 hours

(Wattanasuwan et al. 2001).

Monitoring of lipids during the follow-up period was less than ideal in the study setting. About

one third of respondents to the early follow-up survey had no monitoring of lipids, including

those newly prescribed statins at discharge. Some measure of lipid levels was available for

most respondents at the late follow-up, however several factors pointed to less than ideal

monitoring. This included the observation that a change in the statin regimen or a lipid test

within the previous 90 days was negatively associated with therapeutic goals. Furthermore,

about 20% of lipid tests reported at late follow-up were performed after the patient has

completed the late follow-up questionnaire, suggesting the possibility that the study influenced

the ordering of tests. It was a limitation of the current study that no data was collected on the

number of times that lipids were tested during the follow-up period.

8.4.1.2 Therapeutic goals

Achievement of therapeutic goals was less than optimal at each point in the continuum of care.

At the time of hospital admission just over one third of patients with a previous diagnosis of

CHD were at the recommended therapeutic goal. This increased to about one half at the late

follow-up survey. The considerable gap between therapeutic goals recommended in clinical

guidelines and lipid levels observed in follow-up care were very similar to those found in

another Australian study (Vale et al. 2002a). Vale et al showed that the Australian results were

considerably better than other studies. A number of factors have been implicated in this so

called “treatment gap”. These include non-prescribing, inadequate treatment, the effectiveness

of statins and non-adherence by patients.

Non-prescription of statins was not a significant problem during the follow-up period. There

was no difference in mean lipid levels with statin use, and statin use was not an independent

predictor of achieving the therapeutic goal. This contrasts with several other studies, which

found that patients not prescribed statins, were less likely to achieve therapeutic goals (see Box).


The reason for this difference is unclear. It is not explained by the proportion of patients

prescribed statins, which was also high in L-TAP and in the study by Vale et al.

Proportion of patients at target by statin prescription

% at target

% prescribed Target no statin with statin

EUROASPIRE II (AMI diagnosis)1 60 TC<5 mmol/L 28 53

L-TAP (CHD)2 93 LDL <2.6 mmol/L 8 19

Vale3 87 TC <4 mmol/L

TC <5 mmol/L

LDL <2.5 mmol/L

9

35

18

29

69

50

This study 86 TC<4 mmol/L

TC <5 mmol/L

LDL<2.5 mmol/L

26

79

47

23

73

48 1(Euroaspire II Study Group 2001), 2(Pearson et al. 2000), 3(Vale et al. 2002a)

Inadequate treatment, including failure to regularly monitor lipid levels and adjust treatment as

required has been documented in several studies. Previous studies found that patients that did

not attain the treatment goal had been on the same dose for at least one year (Marcelino et al.

1996) or were still on a starting dose (Sueta et al. 1999). Marcelino et al also noted that very

few patients that had not attained the treatment goal were at the maximal recommended dose

(Marcelino et al. 1996). A low incidence of increased statin doses over the follow-up period

was also observed in the current setting. Furthermore, the finding that changes in the statin

regimen during the follow-up period were associated with higher lipid levels suggests that even

where regimen change occurred in response to poorly controlled lipids there was an inadequate

level of lipid monitoring and dose titration. An insufficiently aggressive approach to controlling

lipid levels is also suggested by the negative association between lipid levels at the time of

infarction and achievement of therapeutic targets. At late follow-up, statin use prior to the

infarction was negatively associated with achieving the therapeutic goal. This suggested a need

for more rigorous management in this group, rather than the unchanged treatment regimens

prescribed. In their comparison of lipid management between a multidisciplinary lipid clinic

and primary physician management Harris et al found that 52% of clinic patients, but only 34%

of those treated by their primary physician reached the target cholesterol goal (Harris et al.

1998). The increased effective use of medications resulted from both use of multiple

medications and the use of doses larger than the starting dose.

Failure to adequately monitor lipids levels and make appropriate adjustment to treatments, may

be explained, at least in part, by the well documented barriers to preventive medicine in primary

care. However, different lipids levels tolerated by doctors in different settings may explain the

difference between studies. In an editorial entitled “Targets are fine, unrealistic”, Toop argued


that while most general practitioners accept the desirability of working towards systematic

evidence-based management of patients with established IHD, the targets are unrealistic (Toop

et al. 2001). Clearly, doctors not only need to be aware of therapeutic targets, but also must

accept them and actively work with the patient to achieve them. Pearson et al found that while

95% of doctors indicated that they were aware of guidelines and followed them in practice only

a small proportion of patients reached therapeutic goals (Pearson et al. 2000). This suggested

that factors other than knowledge and attitude play a role. Based on the lipid levels at follow-up

in the current study, either the doctors are unaware of the current guidelines or they, like the

doctors in Pearson’s study, are aware of the guidelines but fail to implement them for other

reasons.

Lack of effectiveness of statins is unlikely to account for the failure to achieve treatment goals

in more than a small number of patients in the present study. The efficacy of statins in reducing

total and LDL-C in the majority of patients has been adequately demonstrated in the clinical

trial setting. Furthermore, a number of studies have demonstrated that statins can be titrated to

achieve the therapeutic goal in the clinical setting (Barter et al. 2000; Andrews et al. 2001;

Athyros et al. 2002). In the present study only 48% of patients had achieved the treatment goal

for LDL-C after a median follow-up of 419 days. While all the above studies found a

differential effectiveness between statins, no such association was noted in the current study.

One probable explanation for this may be that changes in the treatment regimen involved a

change in the statin prescribed rather than by increased dosages of the same statins.

Patient non-adherence with the treatment regimen is another possible contributor to the

treatment gap. Reported use of statins by patients was similar to that reported by general

practitioners, suggesting that complete non-adherence with the treatment regimen is unlikely to

have contributed significantly to the treatment gap. However, partial non-adherence could be an

important factor in not achieving lipid treatment goals.

As previously discussed in Chapter 7 a number of studies using administrative databases found

evidence of significant partial adherence with statins (Avorn et al. 1998; Benner et al. 2002;

Jackevicius et al. 2002; Simpson et al. 2003). Patient non-adherence was suggested in one

study that found the reduction in LDL-C was less than might be expected from the clinical trials

(Frolkis et al. 2002). This was based on the observation of a wide variation in the LDL-C

reductions observed and the observation that unlike the clinical trials where the LDL-C response

was normally distributed, in the clinical setting the LDL-C response to statin therapy was not

normally distributed. While limited by the small sample size in the present study, it is clear that

the percent change following the prescription of statins fell far short of the percent reduction

that might be expected from the large trials.


A rebound effect in lipid levels in the long-term has been reported in the clinical setting but not

in the landmark clinical trials (Barter et al. 2000; Andrews et al. 2001). This has been attributed

to decreased patient compliance in the clinical setting compared with clinical trials where

patients are better monitored and supported. In the current setting, use of statins prior to

admission was associated with higher lipid levels. This was independent of baseline lipid levels

at the time of MI. This may reflect the rebound of lipid levels following long-term statin use,

suggesting that patients using a statin prior to the infarction were less adherent with the regimen

during follow-up. In patients already established on a statin regimen there may be a less

aggressive approach to monitoring lipid levels. It is arguable that this group of high-risk

patients, where treatment failed to avert a coronary event, require more rather than less

aggressive treatment and monitoring.

Further evidence of the influence of patient adherence on achievement goals come from two

intervention studies. A randomised control trial of “coaching” patients with CHD to achieve

target cholesterol levels found that a similar proportion of patients in the intervention and

control group were using therapy and, there was no difference in the doses prescribed however,

patients in the intervention group were more likely than patients in the usual care group to

achieve the target cholesterol level (31% versus 10%) (Vale et al. 2002b). The effectiveness of

this intervention was explained by better adherence to both drug therapy and to dietary advice.

Similarly, a pharmacist conducted educational and monitoring intervention improved the

outcomes of lipid lowering therapy (Peterson et al. 2004).

Failure to achieve therapeutic goals has been suggested as one indicator that patients may not be

completely adherent with the treatment regimen for some reason and should provide a cue for

the doctor to ask the patient about statin use, including the frequency and timing and doses.

Therefore even if the ineffectiveness of the statins is explained by patient factors there is still a

role for the doctor in achieving appropriate lipid levels.

8.4.2 Other risk factors

8.4.2.1 High blood pressure

Based on measurements provided by the general practitioners at late follow-up, one third of

patients had high blood pressure. This compared favourably with EUROASPIRE II where

almost one half of patients with a diagnosis of MI had high blood pressure at follow-up. Both

the prevalence of antihypertensive therapy and the incidence of hypertension among patients not

using any antihypertensive therapy were similar between the two studies. However, in

EUROASPIRE II the incidence of hypertension in patients using at least one antihypertensive

agent was 48% compared with 32% in the current study. This could indicate either more

aggressive antihypertensive treatment or better patient adherence in the current study. The most


frequently cited reason for no initiation or change in blood pressure therapy in one study related

to the primary care doctor being satisfied with the blood pressure. (Oliveria et al. 2002).

The finding that a calcium antagonist, not routinely recommended in post-MI patients, was

almost twice as likely to be prescribed to patients with high blood pressure may indicate some

attempt to control high blood pressure. However, this contrasts with the observation that half

the patients prescribed neither a beta-blocker nor an ACE inhibitor were hypertensive and, the

low doses of beta-blockers and ACE inhibitors prescribed. Better use of beta-blockers and ACE

inhibitors may increase blood control as well as provide a better level of prophylactic benefit.

8.4.2.2 Diabetes

Only three quarters of the patients with diabetes or IFG had a blood test during the follow-up

period. Control was known to be adequate in about one half of patients not using medications

and one quarter of patients using hypoglycaemic medications.

The correlation between the number of hypoglycaemic medication prescribed and blood glucose

level or HbA1c suggests some attempt to control blood sugar levels by use of medications. It is

beyond the scope of this thesis to explore factors relating to adequate control of diabetic

patients. It is, however, clear that in the present setting diabetic patients are not adequately

controlled and that prescription of drugs in isolation is unlikely to result in better control.

8.4.2.3 Smoking and other lifestyle risk factors

The finding that at the time of the late follow-up, about one third of self-reported smokers were

reported as non-smokers by the general practitioner suggested doctors had not discussed

smoking with the patient and by implication have not provided any advice, prescription or

referral for smoking cessation. An alternate explanation is that while the patient felt

comfortable admitting their smoking status in a questionnaire, the doctor-patient relationship

was not conducive to disclosure of smoking status to the general practitioner.

It is generally recognised that doctors are less comfortable counselling patients about lifestyle

changes than in prescribing medications. Given the importance of smoking cessation to risk

reduction this would appear to be one area where doctors may need help to assist them

counselling patients about stopping patients and other lifestyle factors (Bairey-Merz et al.

2002).

This is also illustrated for weight management and physical activity where there were limited

interventions either in hospital or in early follow-up care. However, other reasons for failure to

discuss risk factors and lifestyle changes include lack of time (42%), workload (27%) and

feeling that patients do not listen or understand (21%). (Hobbs et al. 2002)


8.4.3 Limitations

Ideally blood lipids, blood pressure and blood glucose levels would have been measured in a

clinic situation knowing the drug regimen at that time. In this study there was the possibility for

a disconnection between drug therapy and measurement of risk factors. The last reported risk

factor measurement could have been prior to the latest change in drug regimen, particularly with

lipid levels. Changes in the statin regimen reported by the doctor may have ultimately resulted

in target lipid levels. The association observed between changes in statin regimen and lipid

levels supports this notion. A further limitation is that asking doctors about risk factors may

have encouraged them to monitor these risk factors. The relatively large proportion of tests

dated after the patient questionnaire had been completed supports this. This may have resulted

in an inflated estimate of the proportion of patients whose lipids would otherwise have been

monitored.


8.5 Summary

This chapter examined the management of risk factors in a setting of relatively high use of

cardioprotective drugs. Major findings included:

• 36% of patients with a history of hyperlipidemia were not using lipid-lowering therapy at

the time of admission, including 25% of patients who also had a previous diagnosis of CHD

and 42% with no prior history of CHD. At the time of admission the use of lipid lowering

therapy was positively associated with optimal lipid levels.

• The monitoring of lipid levels during the hospital admission was significantly less in non-

cardiology units even after controlling for patient factors.

• Based on patient report:

• Lipid levels had not been monitored by the time of the early follow-up in one third of

patients newly prescribed statins at the time of the MI.

• Most had at least one test prior to the late follow-up.

• There was an inverse relationship between time since the last lipid measurement and

TC ≤ 5.5 mmol/L.

• There was a marked reduction in lipid levels at late follow-up in patients newly prescribed

statins at discharge, although these differences were relatively small and, one half of LDL-C

levels were >2.5 mmol/L.

• High lipid levels at late follow-up were associated with statin use prior to the myocardial

infarction, baseline lipid levels and a change in statin regimen.

• Optimal blood pressure levels were reported for only one in five patients while almost one

in three had high blood pressure.

• At late follow-up most diabetic patients had a glycated haemoglobin measurement in the

previous 12 months, however only one quarter of patients using at least one hypoglycaemic

medication were known to have well-controlled diabetes.

8.6 Conclusions

Despite the relatively high levels of drug use in the current study, the monitoring and

management of risk factors was less than ideal. Failure to attain the therapeutic goal for lipid

levels was not associated with non-use of statins, but rather was associated with less than

optimal monitoring of lipid levels with appropriate dose titration. Similarly, while some of the

failure to achieve optimal blood pressure levels may be explained by non-use of

antihypertensive therapies including beta-blockers and ACE inhibitors, the high proportion of

patients using these therapies with high blood pressure suggested the need for better monitoring

and adjustment of treatment as well as monitoring of patient adherence. Poor monitoring and

management of smoking and blood glucose levels were also evident.

347 Chapter 9: Final discussion

CHAPTER 9

FINAL DISCUSSION

This thesis began with the working hypothesis that there was underuse of cardioprotective

medications in patients with CHD. The hypothesis went on to say that this was attributable to

under prescription of these therapies at both hospital discharge and in primary care.

Furthermore, patient preferences or a patient’s inability to follow the prescribed treatment plan

further compromised optimal therapy. The objectives of this work were to quantify the

treatment gap, to identify the barriers to optimal therapy at various points in the continuum of

patient care in the study setting, and then provide the evidential basis to recommend changes to

the health care system to reduce these barriers. Section 9.1 provides an overview of the findings

of the study discussing use of each drug group across the continuum of care. Section 9.2

discusses possible future work and addresses some questions raised by the study and

recommends strategies to remove the barriers to optimal care identified by this research.

9.1 Overview of study

In this study setting, there was evidence of a relatively small gap between the evidence and

actual practice in terms of the use of cardioprotective medications. This accorded with other

recently published studies. The PEACE study investigators reported near optimal therapy in

patients recruited to their study with 90% using an antiplatelet agent, 60% a beta-blocker and

70% a lipid lowering drug (Braunwald et al. 2004). Similarly, high rates of prescription and

only minor drug discontinuation were observed in a recently published large multinational

registry (Eagle et al. 2004).

Some shortfall in the management of risk factors was noted throughout the continuum of care in

the current setting. This shortfall was similar to that noted in the PEACE study (Braunwald et

al. 2004). In the PEACE study about two in five patients had a diastolic blood pressure ≥ 90

mm Hg or systolic blood pressure ≥140 mm Hg compared with about one in three patients in the

current study. The mean concentration of cholesterol at baseline in PEACE was 192 mg/dl (~5

mmol/L) compared with 4.5 mmol/L in the current study. The prevalence of smoking in the

current study also compared favourably with the PEACE study which noted 14% at recruitment

compared with about 5% in the current setting (Braunwald et al. 2004).

The remainder of this section summarizes the findings for each drug class.



Variation in antiplatelet agent prescription at hospital discharge could almost all be explained by

the presence of a contraindication. Antiplatelet agents prescribed at hospital discharge generally

reflected recommendations prevalent at the time, which included aspirin 300 mg and

clopidogrel 75 mg immediately post-PCI otherwise aspirin 100-150 mg. An analysis of the

CURE trial of aspirin and clopidogrel published after the present study suggested that 75 mg to

100 mg was an optimal aspirin dose with or without clopidogrel (Peters et al. 2003) and

subsequently led to local recommendations for the use of lower doses of aspirin in the

immediate post-PCI period (personal communication PLT). This subsequent change in post-

PCI prescribing practices should reduce the problems noted with failure to effectively

communicate planned changes to aspirin doses.

The appropriateness of aspirin doses used in primary care was less clear with a number of

general practitioners reporting long-term use of aspirin 300 mg at both early and late follow-up,

although the benefit of lower doses of aspirin had been clearly defined a decade before the study

was conducted (Antiplatelet Trialists' Collaboration 1994). Use of higher than recommended

doses increase the risk of bleeding complications and gastrointestinal side effects, and therefore

do not represent optimal care. Indeed, the occurrence of gastrointestinal side effects could result

in complete cessation of aspirin. Reported use of aspirin 300 mg was almost exclusively in

post-PCI patients suggesting that some general practitioners were not familiar with the post-PCI

treatment regimen and, that the long-term treatment plan was not effectively communicated to

general practitioners. Communication with general practitioners must include clear instructions

about planned changes in the treatment plan that the general practitioner is expected to

implement.

Small but significant changes in the mix of antiplatelet agents prescribed from discharge to late

follow-up were observed. These changes probably refected the evolving evidence for the use of

clopidogrel and aspirin, alone and in combination, in preventing secondary cardiac events

(CAPRIE Steering Committee 1996; The Clopidogrel in Unstable Angina to Prevent Recurrent

Events (CURE) Trial Investigators 2001; Steinhubl et al. 2002). At the time of this study long-

term clopidogrel was recommended only for patients at very high risk or in patients using

aspirin at the time of the infarction (Hung et al. 2003). With only small numbers of patients

using long-term clopidogrel it is impossible to comment on the appropriateness of the increased

use of clopidogrel as the sole antiplatelet agent over the follow-up period, however other studies

suggest that at least some of this use would be outside recommended indications (Kubler et al.

2004). The decision about which antiplatelet agent to prescribe in patients with CHD, and other

high risk patients, has a large potential impact on the health system because of the price

difference between agents (Gorelick et al. 1999; Gaspoz et al. 2002; Marshall 2003). It is


therefore important that guidelines informing this decision are provided to all doctors in an

effective manner. Prescribing practices should be closely monitored to prevent an unnecessary

significant increase to the health system from inappropriate prescribing of clopidogrel in

relatively low risk patients.

Few patients discontinued antiplatelet therapy inappropriately during the follow-up period

although adherence with the treatment regimen was not always optimal. Of greatest concern

was the use of aspirin 300mg daily instead of the lower recommended doses. This was

explained either in terms of misunderstanding of the long-term treatment plan following PCI or

patients choosing the convenience of taking a whole rather than half a tablet. As already noted

this practice did not compromise the risk reduction benefits conferred by aspirin but did increase

the possibility of bleeding complications and other adverse effects that may ultimately lead to

complete cessation of aspirin. More effective communication with the patient about the long-

term treatment plan, particularly any changes required, is essential to ensure optimal long-term

care. A discussion between doctor and patient about why a low dose of aspirin should be used,

including alternative preparations of aspirin, could avoid use of unnecessarily high doses.

9.1.2 Beta-blockers

Prescription of beta-blockers at hospital discharge was near optimal with non-prescription

largely explained by the presence of contraindications, notably chronic airways limitation, heart

block and bradycardia. Doses of beta-blockers prescribed however were low compared with the

original clinical trials. The extent of the risk reduction benefit conferred by doses one quarter

the strength of those used in the original trials is unclear. There is a need to compare outcomes

in terms of mortality, reinfarction and cardiac-related readmissions by the doses of beta-blocker

prescribed.

The use of very low doses of beta-blockers persisted in primary care. In addition there was a

significant discontinuation of beta-blockers during the follow-up period, which was not

explained by clinical factors including adverse effects. The significant difference in reporting of

beta-blocker use by doctors and patients also pointed to patient-initiated cessation representing

non-adherence with the prescribed regimen. Cessation of beta-blocker therapy in long-term

care was also suggested by the low estimates of beta-blocker use in the wider community of

patients with CHD compared with prescribing practices at discharge. Reasons for drug

discontinuation during the follow-up period are unclear. However the observation that patients

were least clear about the reasons for beta-blocker use provides one possible explanation. This

uncertainty about the treatment rationale is consistent with the uncertainty about the mechanism

of benefit in the post infarction patient (Yusuf et al. 1985), and may reflect inconsistent and

inaccurate explanations provided to patients. Related to the possible association between


discontinuation of beta-blockers and poor understanding of the treatment rationale is the

observation that less discharge planning, including provision of a discharge medication list,

interventions for risk factors and good communication, was associated with drug

discontinuation.

Partial adherence with the treatment regimen did not appear to be a significant problem although

a small proportion of patients made systematic intentional deviations from the treatment

regimen, usually by not taking the evening dose of metoprolol. This also suggested the need for

better communication with patients about the rational for the treatment regimen.

9.1.3 Statins

Treatment in a cardiology unit increased the odds of statin prescription at hospital discharge

more than five-fold, suggesting under prescription of statins in non-cardiology units. Reasons

for this difference are unclear, however this corresponds with less likelihood of monitoring of

lipids in the non-cardiology patients. This probably results from a greater focus on acute, rather

than preventive care in the non-cardiology units. Other evidence of underuse in the study

setting came from the observation that one half of patients not prescribed statins had lipids

above the suggested treatment threshold levels and the observation that almost one half of

patients not prescribed a statin at discharge initiated treatment during the follow-up period. The

linear association between cholesterol levels and statin prescription suggested poor adherence to

treatment thresholds.

Compared with the landmark statin trials of the 1990s, doses prescribed at hospital discharge

were low. Although the mean doses of statins used increased from hospital discharge to late

follow-up, this increase resulted from relatively few changes in the treatment regimen.

Importantly one half of patients using statins had not achieved treatment goals at the time of the

late follow-up. This probably resulted from less than optimal monitoring of lipids, with

appropriate treatment adjustment as required. The observation that achievement of treatment

goals was negatively associated with changes in the statin regimen, and, a lipid measurement

within the previous 90 days suggested that monitoring was too infrequent to achieve treatment

goals over more than 12 months. The importance of achieving significant lipid reductions early

was highlighted in a recent paper which found an association between shot term effectiveness

and long term adherence (Benner et al. 2005). Reasons for less than optimal monitoring are

unclear, but probably resulted from a combination of a lack of understanding or agreement with

treatment gaols, and a focus on the treatment of acute disease. Recent evidence of the benefits

of statins independent of lipid lowering (Nissen et al. 2005; Ridker et al. 2005) and strong

evidence that intensive statin therapy should be prescribed to lower lipids well below traditional

therapeutic goals (Cannon et al. 2004; Nissen et al. 2004b) suggest that more intense statin


therapy may be warranted. However, the extent to which this might be achieved is not clear.

There is a clear need for good unbiased information to be provided to primary care providers.

At least some of the reason for failure to achieve treatment goals may be explained by partial

adherence with the prescribed regimen (Frolkis et al. 2002; Vale et al. 2002b). Evidence of

partial adherence in the current study included the erratic use of statins and the inappropriate

timing of statin doses that may affect the efficacy of the drug. This behaviour resulted from a

belief that statin therapy was not needed because lipid levels were sufficiently low and a poor

understanding of when to take the medications respectively. Improved communication

regarding the rationale for therapy and treatment goals and a clear explanation about when to

take the medication is needed. Furthermore the observation that adherence was associated with

early and frequent follow-up, particularly lipid monitoring (Benner et al. 2004), indicates a

further role for the primary healthcare provider in ensuring optimal adherence.


The increased prescription of ACE inhibitors at hospital discharge over the study period

coincided with evolving evidence and changing guidelines governing the use of ACE inhibitors

in post-MI patients. However these changes in prescribing practices did not reflect the new

evidence and guidelines, but rather reflected earlier evidence of benefits of ACE inhibitors.

Thus, while the prescription of ACE inhibitors increased in patients with an anterior infarction

or high CK peak (in the absence of heart failure and left ventricular dysfunction) it remained

low in patients with no evidence of any of the above. Some impact of the HOPE study may

have been reflected in the positive association between diabetes and ACE inhibitor prescription.

The HOPE study showed both reduced risk of cardiac events in diabetes and confirmed the

reduced risk of renal complications of diabetes (Heart Outcomes Prevention Evaluation Study

Investigators 2000). There was a wide variation in ACE Inhibitor prescribing practices even

within cardiology and changes in prescribing practices did not extend to primary care.

Therefore, patients in the early part of the study not prescribed an ACE inhibitor at discharge

did initiate therapy during the follow-up period. This observation confirmed the well

documented differential rate of uptake of new evidence between specialists and hospitals and on

the one hand and primary care on the other (Kizer et al. 1999; Go et al. 2000).

Further potential for underuse of ACE inhibitors was evident in the doses prescribed. Although

the significantly higher doses prescribed at hospital discharge in the group using an ACE

inhibitor prior to hospital admission suggested some dose titration; doses were still relatively

low compared with the doses used in landmark clinical trials. There was very little evidence of

dose titration during the follow-up period. Failure to use target doses of ACE Inhibitors in

clinical practice is well documented, although reasons for this reluctance are unclear. At least


part of the reluctance to prescribe target doses may result from concern about adverse effects.

In their speciality-related comparison of differences in knowledge and use of ACE inhibitors,

Chin et al found that cardiologists prescribed target doses more often than generalists and that

cardiologists were more likely than generalists to tolerate systolic blood pressures lower than 90

mm Hg (Chin et al. 1997). In the study setting only about one in four patients had a systolic

blood pressure less than 120 mm Hg and one half of the patients using an ACE Inhibitor had

high blood pressure. Thus concern about hypotension was unlikely to explain the low doses

used. Guidelines and recommendations need to emphasise the doses demonstrated to lower

mortality and morbidity in the trials.

9.1.5 Calcium Antagonists

The inclusion of calcium antagonists in this study provided evidence that the rates of use of the

drugs of interest in this study did not represent indiscriminate high levels of drug use. The

contrast in the findings between calcium antagonists and the other agents in fact confirmed the

evidence-based nature of practice in the study setting.

Overuse of calcium antagonists in primary care was evident with a number of cases of calcium

antagonist cessation during the hospital episode. There was, however, a greater likelihood of

these patients recommencing calcium antagonist use during the follow-up period. It was not

possible to determine to what extent the recommencement of therapy in these patients was

appropriate, and to what extent it reflected a failure to effectively communicate changes made to

the treatment plan.

9.1.6 Summary

While prescription of secondary prevention therapies was relatively high in the study setting,

some evidence of a treatment gap remained.

In the case of antiplatelet agents there was little evidence of underuse. There was however

evidence of use of inappropriately high doses of aspirin in some patients, resulting from an

apparent lack of understanding of the recommended treatment regimen by some general

practitioners and patients.

The significant number of patients discontinuing beta-blocker therapy early in the follow-up

period suggested some underuse of beta-blockers during the follow-up period. Use of very low

doses of beta-blockers may also represent an underuse of beta-blockers. Reasons for the

inappropriate cessation of beta-blockers are unclear. One possible reason suggested by the data

is poor communication between the hospital and patient about the treatment plan. However,

cessation of beta-blockers was also reported by general practitioners and may indicate concern


about side effects or a poor understanding about the benefits of beta-blockers in post-MI

patients, particularly long-term.

There was some evidence of under prescription of statins at hospital discharge particularly in

non-cardiology units. Even where statins were prescribed and used during the follow-up period,

treatment was less than optimal with only one half of patients achieving treatment goals at the

end of the follow-up period. Failure to achieve treatment goals was probably explained by the

relatively low doses of statins prescribed and probably associated with less than optimal

monitoring and dose titration, although intentional and unintentional partial adherence to the

prescribed regimen may also have contributed to poor lipid management.

ACE inhibitor prescribing in the current study suggested that changes in prescribing practices

continue to lag behind the evidence and that change is slower in the primary care setting than in

the hospital setting. Even when ACE inhibitors were prescribed, the doses were lower than

those shown to be effective in clinical trials and may therefore compromise the effectiveness of

ACE inhibitors.

Some of the treatment gap could be attributed to details of the prescriptions at the time of

discharge particularly, the doses prescribed. However, improvement in communication from

hospitals to patients and primary care providers about the rationale for treatment and the

planned treatment regimen is also required to achieve optimal long-term secondary prevention

of CHD.


9.2 Limitations of the study

Quantification of the treatment gap in ambulatory care relied on survey responses. The

potential for biased responses leading to an overestimation of use cannot be ignored. In the

worst-case scenario all non-responders to either survey had discontinued drug use during the

follow-up period. However, given the similarity in early discontinuations between responders

and non-responders to the late follow-up survey this is unlikely to be the case. Furthermore, the

finding that 50% on non-responders to the early follow-up survey responded to the late follow-

up survey also suggested that non-response was for many reasons and unlikely to be related

specifically to adherence with the treatment regimen. Any overestimation of drug use is likely

to be much less than the rate of non-response to the surveys. Furthermore while some

differences between baseline characteristics between responders and non-responders were

noted, there was no evidence in the current study that these characteristics were associated with

drug discontinuation.

Concordance between the drug inventory at the time of the patient interview and patient’s

questionnaires at the early follow-up indicated accurate reporting of current drug use by

patients. However it was impossible to quantify the degree of adherence with the treatment

regimen. Furthermore while the qualitative data from the patient interview suggested that very

few patients would be missing more than 20% of their tablets, this observation was also limited

by possible response bias. In the worst-case scenario, all respondents to the early questionnaire

who did not wish to have a home visit were poor adherers. In this case up to 25% of patients

could be expected to poor adherers. Thus while there was little evidence of poor adherence, it

cannot be discounted that up to 25% were poor adherers.

Given the limited source of patients in this study, the findings of this study may not be

representative of the Australian health setting in general. Patients came from one metropolitan

tertiary hospital and an affiliate metropolitan hospital, both with a cardiology unit attended by

the same group of cardiologists. There was no association between the type of hospital and

drug prescription, however there was an association between statin prescription and the

treatment specialty. Therefore, in the case of statins at least, the results may not be

generalisable to the whole Australian healthcare setting where peripheral and rural hospitals

may not have specialist cardiology units. However, public patients requiring cardiac

catheterisation and other cardiac procedures would ultimately be treated in a tertiary hospital.

Almost all the patients in the follow-up study were treated in a cardiology unit, reflecting the

older age and greater morbidity of post-MI patients treated in non-cardiology units. Therefore,

the findings of this study with regard to long-term drug use and drug discontinuation can only

be applied to patients treated in cardiology units. In terms of long-term drug use there was no


association with hospital type. However, based on patients’ responses, patient education and

discharge planning occurred more frequently at the tertiary hospital reflecting the more formal

processes in place at the tertiary hospital. This raises the possibility that the level of drug

discontinuation observed in this study and, shown to be associated with less patient education

and discharge planning, may under represent discontinuation rates in general. However the

important observation in this study is not the rate of drug discontinuation per se, but rather the

association between patient education/discharge planning and drug discontinuation.

9.3 Future work

The findings of this study open two avenues for further work. The first involves the

determination of the effectiveness of current prescribing practices while the second involves

strategies to improve the long-term treatment of patients hospitalised with a myocardial

infarction and resultant long-term outcomes.

9.3.1 Effectiveness of current prescribing practices

It was beyond the scope of the current study to examine outcomes of treatment post-MI. There

was instead an underlying assumption that where drugs shown to be effective in reducing the

risk of cardiovascular events were prescribed, and used as prescribed, a risk reduction benefit

similar to that shown in the RCTs would be conferred. However, observations in the current

study suggest that this assumption may not be well-based. The doses of beta-blockers, statins

and ACE inhibitors prescribed were low compared with the available evidence. As noted in a

recent editorial referring to ACE inhibitors, but equally applicable to all preventive therapy, “in

the setting of mortality reduction there is no way to know the effectiveness of dosing regimens

other than those used in clinical outcome trials” (Hennessy et al. 2004). Furthermore, in the

case of statins where doses could be titrated to achieve treatment goals, there were only

moderate lipid reductions and more than one half of patients did not achieve therapeutic goals.

It is therefore important to determine whether the current prescribing practices for beta-

blockers, statins and ACE inhibitors result in similar risk reductions to those observed in the

RCTs. Recent studies have examined outcomes with different drugs regimen (Jabbour et al.

2004; Hippisley-Cox et al. 2005) but none have addressed the issue of dose.

The need for ongoing monitoring of outcomes is also suggested by a number of recent studies,

which highlight the complexity of providing optimal treatment. While both the HOPE and

EUROPA studies showed beneficial effects of ACE Inhibitors in patients with CHD, these

findings were not supported by the PEACE study. The PEACE study found that in their cohort

of near-optimally treated patients including use of antiplatelet agents, beta-blocker and statin

and well-managed risk factors; the addition of an ACE inhibitor to the treatment regimen did

not improve outcomes. Furthermore they found that the risk in the control group was similar to


the risk in the treatment group for HOPE and EUROPA. In the current study, use of antiplatelet

agents, beta-blockers, statins and risk factor management was comparable to the PEACE study.

The results of the PEACE Study are echoed in a study by Hippisley-Cox et al which found the

greatest risk reduction with the combination of aspirin, beta-blockers and statins (83%, 95% CI

71% to 88%) with no added benefit with the addition of an ACE inhibitor (Hippisley-Cox et al.

2005). If the conclusions of these studies are correct, then it is arguable that in otherwise

optimally managed patients, including those in the current setting, no benefit is derived from the

addition an ACE Inhibitor.

A recent study by Pilote et al suggested that the benefits of ACE inhibitors were not uniform

across all ACE inhibitors (Pilote et al. 2004). While the validity of the conclusions by Pilote et

al were questioned due to possible bias, the study at least suggests that outcomes with different

ACE inhibitors and different doses need to be examined more rigorously (Hennessy et al. 2004).

The study by Hippisley-Cox et al (Hippisley-Cox et al. 2005) examining the efficacy of various

drug combinations was also limited by lack of information about doses and types of drugs,

particularly ACE inhibitors used.

More evidence of the complexity of deciding optimal treatment comes from two studies, which

examined blood pressure treatments in patients with CHD (Pepine et al. 2003; Nissen et al.

2004a). In particular, the CAMELOT study showed additional benefits of reducing blood

pressure below what are normally considered to be “normal” (Nissen et al. 2004a). Both studies

found that a regimen that included a calcium antagonist; either Verapamil SR-trandolapril

(Pepine et al. 2003) or amlodipine (Nissen et al. 2004a) was better than atenolol-

hydrochlorothiazide and enalapril respectively. Furthermore Nissen et al showed that the

greater benefits of amlodipine compared with enalapril could be attributed to reduced

atherosclerotic progression with amlodipine but not enalapril despite similar blood pressure

reductions in the two groups (Nissen et al. 2004a). These two studies suggest that there may be

a role for calcium antagonists in patients with CHD beyond their role in the treatment of angina

refractory to beta-blockers or when beta-blockers cannot be tolerated.

Observational studies using administrative data provide one means of examining outcomes in

the “real world”. Such studies have been used to measure effectiveness of therapies in the

clinical setting (Pilote et al. 2004; Hippisley-Cox et al. 2005) as well as providing a better

understanding of adverse events from widely prescribed drugs (Hudson et al. 2005; Levesque et

al. 2005). Until recently this type of study was not possible in Australia. There is now the

ability to link information about drugs dispensed under the Pharmaceutical Benefits Scheme

(PBS) with hospital administrative data and mortality data. Therefore it is now possible to use

this “data-linkage” to examine the effectiveness, and safety, of the treatment regimen prevalent

in the study setting. However, many of the more established drugs cost less than the cost to the


patient under the PBS and are therefore not dispensed under the PBS, limiting the use of this

data. This is particularly relevant in younger patients without health concession cards, and for

beta-blockers in particular. Despite this limitation, it is important to monitor outcomes in

particular settings and this provides a relatively easy method to monitor a large number of

patients.

9.3.2 Strategies to improve long-term treatment of patients following AMI

While use of preventive therapies was moderately high, opportunities for improved use remain.

The emphasis of the current study was the processes and practices in place in hospitals to ensure

optimal long-term care for post-MI patients. This included the prescription of appropriate

therapies at hospital discharge and ensuring good discharge planning and transition of care.

Effective communication with the patient about their long-term treatment plan is an important

part of enabling the patient to adhere with the treatment regimen. Similarly, effective

communication with the general practitioner about the long-term treatment plan would also be

expected to increase the likelihood of optimal long-term care. In this section possible strategies

to improve long-term care are discussed under three broad headings: improving prescribing at

hospital discharge; improving communication with patients; and improving the transition of

care between the hospital and general practitioners.

9.3.2.1 Improving prescribing practices

Changing prescribing practices, largely dependent on the actions of a single physician, is

relatively easy compared with many other behaviour changes required within the health care

system to achieve optimal long-term therapy (Burwen et al. 2003). In the area of the

“secondary prevention of CHD” there is now evidence from a number of sources that in terms

of the prescription of therapies, practice has improved significantly over the past 20 years and

may be approaching optimum. In many cases this followed extensive quality improvement

interventions particularly discharge medication programs (Fonarow et al. 2001b; Scott et al.

2002; Lappe et al. 2004). At the time of the current study there were no specific quality

improvement interventions and no discharge medication program in place in the study setting;

however, prescription rates in the study setting were comparable with these intervention studies.

This probably reflects the study setting where three quarters of patients were treated in a

cardiology unit and a similar proportion treated in a hospital with cardiac catheter facilities.

Treatment by a cardiologist and hospital characteristics have been associated with greater

adoption of evidence (Schreiber et al. 1995; Chen et al. 1999b; Willison et al. 2000; Steg et al.

2002b). It must also be acknowledged that while no national programs were in place in

Australia, awareness of programs such as the GAP program (Eagle 2003) and the Get With The

Guidelines (GWTG) Program (Get with the guidelines) could have influenced the practice of

cardiologists working in a tertiary hospital in Australia. Nonetheless, in the current setting it is


arguable that specific interventions to improve prescription rates of these therapies should be

directed specifically towards non-cardiology units and secondary hospitals with no cardiology

services. There are, however, several prescribing related areas that need to be addressed

throughout the healthcare system including dosage issues and promulgation of guidelines.

Dosage issues

There was a marked gap between the evidence base and the doses of beta-blockers, statins and

ACE inhibitors prescribed in the current setting. The low doses prescribed at hospital discharge

were not explained by use of low starting doses, since doses were generally low even when

patients had ongoing prescriptions. Furthermore, few changes in treatment regimen during the

hospital episode were noted in patients with ongoing treatment. This general failure of doctors

to prescribe target doses may be explained by a lack of understanding about the doses used in

the clinical trials. Recommendations and guidelines have generally been silent on the doses

required. The possible exception was statins where treatment thresholds and goals were

provided. Reluctance by doctors to alter treatment regimen may explain some of the observed

failure to modify doses. However, since all study patients were hospitalised following

myocardial infarction, despite the treatment regimen at the time, an increase in an otherwise low

dose might seem reasonable. The findings of this and other studies, that doses prescribed are

significantly lower than those shown to be effective, suggest a need for more detail to be

provided in guidelines, particularly with regard to dosages.

Promulgation of guidelines

Changes in the guidelines per se, however, would not alter the nuances of prescribing unless

these guidelines were effectively implemented. The inevitable introduction of electronic

prescribing with the adjunct decision support systems should move a long way towards the

effective implementation of guidelines (Garg et al. 2005; Kawamoto et al. 2005). Any decision

support system must include information about appropriate doses and treatment goals, where

appropriate.

About one quarter of all patients in the study were not treated in a cardiology unit, but were

treated in either another speciality or general medicine unit. Many baseline characteristics

differed significantly between cardiology and non-cardiology patients. However when these

characteristics were controlled for by multivariate analysis, treatment specialty was not an

independent predictor of drug prescription for any therapy other than statins. In the setting of

myocardial infarction, evidence for the early benefits of statins is quite recent (Aronow et al.

2001a ; Schwartz et al. 2001 ; Thompson et al. 2004). Evidence has also been emerging about

the benefits of lower treatment thresholds (National Heart Foundation of Australia et al. 2003).

This suggests that the difference in prescribing practices may be explained, at least in part, by a


lack of knowledge or acceptance of the evolving evidence and recommendations. In terms of

equity, all patients eligible for therapy on the basis of indications and contraindications should

be provided with therapy independent of the treatment unit. Use of hospital-wide, rather than

treatment specialty guidelines, should increase the likelihood of all patients receiving equal

treatment regardless of the treatment speciality. The introduction of system-wide electronic

prescribing and diagnosis-based decision support may be part of the solution.

9.3.2.2 Improving communication with patients

Anecdotal evidence from patient interviews suggested that non-adherence with prescribed

treatment regimens was usually associated with either a lack of understanding of the long-term

treatment plan or a lack of understanding about the rationale for the treatment plan. The former

was usually associated with unintentional deviation from the treatment plan, while the latter

resulted in intentional deviations from the treatment plan.

At interview, patients were least clear about the reasons for taking beta-blockers and ACE

inhibitors. This confirmed results from the patient questionnaire where beta-blockers and ACE

inhibitors were most often mentioned as having concern about the purpose of medications.

Discontinuation of beta-blockers and, to a lesser extent ACE inhibitors, was significantly greater

than for antiplatelet agents and statins. Given the known association between understanding the

rationale for drug use and adherence with treatment, it is likely that these two observations were

related. This suggests that ineffective communication with patients about the rationale for each

drug prescribed may increase the odds of discontinuation. Support for this hypothesis was also

provided by the logistic regression analysis of factors associated with drug discontinuation. In

this analysis, less discharge planning (defined as any two of: no counselling for three or more

risk factors; being dissatisfied with at least one aspect of communication in hospital; and not

receiving a discharge medication list) was associated with increased likelihood of drug

discontinuation during the early follow-up period. These observations suggested the need for

systems to be in place to ensure patients received effective discharge planning.

Interviews with staff from the cardiology unit, where cardiac rehabilitation is formalised,

provided information about a number of barriers to effective cardiac rehabilitation and discharge

planning. These included time constraints resulting from a lack of suitably qualified nurses,

high pharmacist to patient ratios and, competing interests on the time of junior doctors.

Unplanned discharges due to bed shortages were also blamed for some patients being

discharged without appropriate discharge planning. There was also some uncertainty about who

was responsible for some aspects of discharge planning particularly the preparation of the

discharge medication list and, what information should be provided. There was also a lack of

consensus among hospital staff about the type of explanations that should be provided to


patients about the rationale for the treatment plan. This was exacerbated by a lack of

understanding by junior doctors about the patient’s medication history and the reasons why

drugs were prescribed. There was also a lack of policy and standards regarding the discharge

process, with patients leaving the ward without the appropriate nurse review.

A legible and complete discharge medication list including appropriate rationale for treatment

and highlighting new drugs commenced and any drugs discontinued should be provided to all

patients. This should also include clear instructions about planned changes in the treatment

plan. One advantage of electronic prescribing is the ability to provide computer generated

discharge medication lists. This should result in standardisation of the medication list, including

use of generic and proprietary names, strengths and numbers of tablets to be taken. It would

also allow for standard rationale to be provided for use of each medication, based on primary

and secondary diagnoses.

Despite barriers to effective patient education in the cardiology unit of the tertiary hospital,

procedures and process were in place. This contrasted with elsewhere in the study setting where

no formal education was provided. Given that only one half of the patients in the current study

were treated within the cardiology unit of the tertiary hospital, there is a large gap in the

provision of cardiac rehabilitation in the study setting. Given the high rates of prescription of

preventive therapies in these patients, it would also be appropriate for these patients to receive

inhospital cardiac rehabilitation. The use of routine follow-up telephones calls in the period

immediately following discharge to ensure a good understanding of the treatment regimen for

all patients is also effective (Dudas et al. 2001). With more elderly and complex patients a

home visit by a suitably qualified health professional may be effective (Stewart et al. 1999).

Although beyond the scope of this thesis, a number of effective strategies to maintain optimal

long-term treatment regimen in ambulatory care have been identified. These include nurse led

clinics (Murchie et al. 2003; Raftery et al. 2005), programs involving community pharmacists

(Tsuyuki et al. 2002) and long term “coaching” via the telephone (Vale et al. 2002b). These

strategies offer cost–effective alternatives to reliance on hospital staff or the primary care

provider.

9.3.2.3 Improving transition of care

Each “transition of care” from the community to hospital, transfer within the hospital and from

the hospital back to the community is recognised as a point of potential error in the medication

regimen. The reconciliation of medications at each transition point is an important element to

safe and effective medical care. In the current context, effective communication between

providers within the hospital and between the hospital and the community are the primary focus

for the seamless transition of care.


Before patients can be provided with the appropriate information, it is necessary that those

involved in discharge planning have complete and accurate information about the patient’s

medications prior to admission and the rationale for all drug changes made during the hospital

episode. This was not always the case in the study setting where patients were usually

transferred from the high dependency coronary care unit to the cardiology ward prior to

discharge. In this setting, junior doctors responsible for the preparation of the discharge

materials reported that the brief time patients spent on their ward made it difficult to have a

good understanding about patients’ medication history. This pointed to a need for better

documentation within the medical record to enable ready reckoning of medication history.

Drugs on admission are currently recorded by the doctors, nurses and pharmacists in various

locations within the medical record. These are often difficult to find and there are often

discrepancies between lists. One unique list of drugs on admission, which is known to be

accurate and complete, would be ideal. This issue has been addressed to some degree in a

national medication chart currently being piloted within Australia. The front page of this

medication record contains a list of medications prior to admission, including the indication for

each drug. However to be truly useful this list should have been reconciled by communication

with primary care providers or community pharmacists. Such reconciliation can be time

consuming and may require the use of a dedicated staff (Pronovost et al. 2003; Rozich et al.

2004). The requirement that an indication be provided for each on the medication chart should

also assist the inhospital transition of care as well the preparation of discharge summaries and

medication lists.

General practitioners in the early follow-up survey provided examples of gaps in the transition

of care back to the primary care provider. However these gaps were also evident in the

treatment regimen reported by general practitioners. This usually involved failure to adjust

doses as planed at the time of discharge, including reducing doses of aspirin in post-PCI patients

and increasing starting doses of ACE Inhibitors.

It was beyond the scope of this thesis to examine the barriers for general practitioners providing

optimal preventive care to patients with a history of myocardial infarction. However, it was

apparent that in at least some cases the transition of care was less than optimal with the use of

illegible and incomplete discharge summaries, no telephone call from the hospital and

difficulties experienced by general practitioners trying to contact hospitals for further

information. The extent to which more effective communication by the hospital would result in

improved long-term care is unclear. However, it is clear from the literature that general

practitioners do rely to a large degree on hospital doctors and specialists to inform them

regarding appropriate treatment regimens (Tomlin et al. 1999; Pantilat et al. 2001).


Improvements in the timeliness and quality of discharge summaries would improve transition of

care. Handwritten “interim” discharge summaries are often the only summaries provided to

general practitioners. These summaries are prone to illegibility, compounded by the use of

carbon copies, inaccuracies and incompleteness. Furthermore they often fail to reach the

general practitioner in a timely manner. In the present context, explanations of changes made to

the treatment regimen in terms of explanations about drugs commenced and drugs discontinued

are rare. In recognition of these problems, all tertiary hospitals in Perth have developed an

electronic discharge summary. However, these electronic discharge summaries are not

connected to other databases containing information and test results and procedures or drugs

prescribed. Therefore, the doctor preparing the summary must manually enter information or at

least cut-and-paste test results. These problems will be overcome with the inevitable

introduction of electronic patient records including electronic medication management, which

should enable the generation of an automatic discharge summary containing accurate

information about drugs prescribed in hospital, including indications for use, as well as

information about test and procedures. Other information technology solutions currently being

explored in Australia including, universal health records and a system that allows the sharing of

information about drug prescriptions between community pharmacists and hospitals, should

improve the exchange of information about treatment regimes.

9.4 Importance of the study

This study examined the use of pharmacotherapies in the secondary prevention of CHD from

the time of hospital discharge to more than 12 months post-MI. It collected specific clinical

information from medical records. Questionnaires were used to collect information from

patients about their hospital experience, current drug use and the treatment received following

hospital discharge. Qualitative information was collected from patients about their drug use and

their understanding of the rationale for their treatment regimen. Questionnaires to GPs collected

information about the transition of care and treatment regimen during the follow-up period.

This information allowed examination of the factors associated with optimal drug use at various

points in the continuum of patient care in an Australian setting and was an important first step in

developing strategies to improve long-term care of patients with CHD in particular and in

patients with chronic diseases in general – within the Australian healthcare setting.

One key finding with regard to prescribing rates at hospital discharge in post-MI patients was

that this was near optimal. This finding was similar to more recent overseas studies following

quality improvement interventions. Australia lags behind many overseas countries in the

implementation of quality improvement initiatives. However, based on the findings of this

study, interventions with the specific aim of increasing prescribing rates in eligible patients

would be expected to be of limited value in Australia, particularly in cardiology units. Greater


improvements could be achieved by interventions aimed at encouraging the use of doses shown

to be effective at reducing the risk of cardiovascular events.

A second key finding was that drug discontinuation was relatively low and usually limited to

one drug, most frequently beta-blockers. This contrasts with a study from the United States that

found greater discontinuation of the more expensive statins rather than the relatively

inexpensive beta-blockers (Federman et al. 2001). This conflicting result may be explained by

the Australian PBS that limits drug costs for patients, with little differentiation in costs between

drugs for most patients.

The third key finding was that there is scope to improve long-term management of post-MI

patients through changes to the care provided in hospital and in long-term management. This

was highlighted by the significant discontinuation of beta-blockers during the follow-up period

and the failure to achieve optimum lipid levels by one half of the follow-up cohort.

The discontinuation of beta-blockers in one quarter of all patients prescribed beta-blockers at

hospital discharge was in the context of:

• Adverse effects accounting for only a minority of reasons for discontinuation reported by

patients and GPs.

• Significantly more doctor-only reported beta-blocker use than patient-only reported use.

Furthermore, in one half of the doctor-only reported cases the patient reported ceasing use.

• Responses to the questionnaires and patient interviews indicated that of all the secondary

prevention therapies, patients were least clear about the rationale for beta-blocker use.

• Less discharge planning as described by patients in terms of counselling about risk factors,

satisfaction with inhospital communication and receiving a discharge medication list was

significantly associated with drug discontinuation, particularly early drug discontinuation.

This suggested a treatment gap that could be reduced by more rigorous discharge planning,

including better explanations about the reasons for drug use.

Lipid levels reported by the GP at late follow-up indicated that optimal lipid levels were not

achieved in one half of all patients. This was in the context of a high prevalence of statin use

suggesting that monitoring of lipid levels and subsequent management of the treatment regimen

were less than optimal. This was supported by a number of observations:

• There was no difference in the mean doses of pravastatin and simvastatin prescribed at

hospital discharge in patients with ongoing statin use compared to patients newly prescribed

statins.

• At late follow-up, statin doses reported by GPs were lower than the doses used in the RCTs

in one quarter of cases.

• A complete lipid profile at late follow-up was missing in about one quarter of cases.


• A high proportion of tests were performed within the previous 3 months, with a negative

association observed between achieving LDL-C <2.5 mmol/L and having a test within the

previous 90 days.

• A change in the type of statin prescribed was also negatively associated with achieving

LDL-C <2.5 mmol/L.

• There was a negative association between baseline LDL-C and achieving LDL-C <2.5

mmol/L.

• There was a negative association between statin use prior to the MI and achieving LDL-C

<2.5 mmol/L.

These observations point to a treatment gap in the long-term care and point to a need for

aggressive monitoring and management of lipid levels in the period immediately post-MI. This

may be most important in patients with where statin use prior to the infarction, where poor

patient adherence may also be a factor.

The timing of this study allowed an examination of changes in prescribing patterns for ACE

inhibitors following the findings of a major study of ACE inhibitors in patients at high risk of

cardiovascular events. While other studies using administrative data showed increased use of

ACE inhibitors, this study showed that increased prescription of ACE inhibitors was limited to

the hospital setting. Furthermore, the increase was limited to patients with no definite indication

for ACE inhibitors (CHF or LVD) but with a relative indication (anterior infarction, high peak

CK or diabetes) where evidence of the benefits in the group of patients has been available for

some years.

9.5 Concluding comments

The genesis of this study came from an interest in patient outcomes and the practice of

evidence-based medicine. At a time of rapid increases in the provision of revascularisation

procedures, I asked the question “With this enthusiasm for invasive evidence-based medicine,

are the use of pharmacotherapies in the secondary prevention of CHD also evidence-based?”.

At the end of this process I surmise that the use of these pharmacotherapies in the secondary

prevention of CHD is evidence-based, but only at a superficial level. If one considers the doses

prescribed, and the proportion of patients that achieve ideal treatment goals, a significant

treatment gap remains. Beyond the prescription of secondary prevention therapies, the quality

of long-term care is governed to some degree by happenstance in the completeness of the

communication with the patient and the information provided the general practitioner. This

does not result from a lack of enthusiasm or expertise, but by virtue of a lack of proper

resources and systems that must be addressed as a priority.

365

References

Abraham, W. T. (2000). "Beta-blockers: the new standard of therapy for mild heart failure." Arch. Intern.

Med. 160(9): 1237-47.

ACE Inhibitor Myocardial Infarction Collaborative Group (1998). "Indications for ACE Inhibitors in the

Early Treatment of Acute Myocardial Infarction." Circulation 97: 2202-2212.

Acute Infarction Ramipril Efficacy (AIRE) Study Investigators (1993). "Effect of ramipril on mortality

and morbidity of survivors of myocardial infarction with clinical evidence of heart failure." Lancet

342(821-28).

Adult Treatment Panel II (1993). "Summary of the Second Report of the National Cholesterol Education

Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in

Adults." JAMA 269(23): 3015-23.

Adult Treatment Panel III (2002). Third Report of the National Cholesterol Education Program (NCEP)

Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults, National

Institutes of Health, National Heart, Lung and Blood Institute (NIH Publication No. 02-5215).

Agusti, A., J. M. Arnau and J. R. Laporte (1994). "Clinical trials versus clinical practice in the secondary

prevention of myocardial infarction." Eur. J. Clin. Pharmacol. 46(2): 95-9.

AHA Consensus Panel Statement (1995). "Preventing heart attack and death in patients with coronary

disease." Circulation 92: 2-4.

AHA/ACC (1999). Guidelines for the Management of Patients With Acute Myocardial Infarction.

http://www.americanheart.org/Scientific/statements/1999/AMI, AHA/ACC.

Alexander, K. P., E. D. Peterson, et al. (1998). "Potential impact of evidence-based medicine in acute

coronary syndromes: insights from GUSTO-IIb. Global Use of Strategies to Open Occluded Arteries in

Acute Coronary Syndromes trial." J. Am. Coll. Cardiol. 32(7): 2023-30.

Allen Maycock, C. A., J. B. Muhlestein, et al. (2002). "Statin therapy is associated with reduced mortality

across all age groups of individuals with significant coronary disease, including very elderly patients." J.

Am. Coll. Cardiol. 40(10): 1777-1785.

Allery, L. A., P. A. Owen and M. R. Robling (1997). "Why general practitioners and consultants change

their clinical practice: a critical incident study." BMJ 314(7084): 870-874.

Allison, J. J., C. I. Kiefe, et al. (2000). "Relationship of hospital teaching status with quality of care and

mortality for Medicare patients with acute MI." JAMA 284(10): 1256-62.

Al-Rashed, S. A., D. J. Wright, N. Roebuck, W. Sunter and H. Chrystyn (2002). "The value of inpatient

pharmaceutical counselling to elderly patients prior to discharge." Br. J. Clin. Pharmacol. 54(6): 657-64.

American Board of Internal Medicine (1999). Using Patients and Physician Peers in Performance Based

Assessment. Philadelphia.

366

Andrade, S. E., A. M. Walker, et al. (1995). "Discontinuation of antihyperlipidemic drugs--do rates

reported in clinical trials reflect rates in primary care settings?" N. Engl. J. Med. 332(17): 1125-31.

Andrews, T. C., C. M. Ballantyne, J. A. Hsia and J. H. Kramer (2001). "Achieving and maintaining

National Cholesterol Education Program low-density lipoprotein cholesterol goals with five statins." Am.

J. Med. 111(3): 185-91.

Antiplatelet Trialists' Collaboration (1988). "Secondary prevention of vascular disease by prolonged

antiplatelet treatment. Antiplatelet Trialists' Collaboration." BMJ 296(6618): 320-31.

Antiplatelet Trialists' Collaboration (1994). "Collaborative overview of randomised trials of antiplatelet

therapy--I: Prevention of death, myocardial infarction, and stroke by prolonged antiplatelet therapy in

various categories of patients." BMJ 308(6921): 81-106.

Antithrombotic Trialists' Collaboration (2002). "Collaborative meta-analysis of randomised trials of

antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients." BMJ

324(7329): 71-86.

Antman, E., J.-P. Bassand, et al. (2000). "Myocardial infarction redefined--a consensus document of The

Joint European Society of Cardiology/American College of Cardiology committee for the redefinition of

myocardial infarction: The Joint European Society of Cardiology/ American College of Cardiology

Committee." J. Am. Coll. Cardiol. 36(3): 959-969.

Antman, E. M., D. T. Anbe, et al. (2004). "ACC/AHA guidelines for the management of patients with

ST-Elevation myocardial infarction--executive summary: A report of the American College of

Cardiology/American Heart Association Task Force on practice guidelines (writing committee to revise

the 1999 guidelines for the management of patients with acute myocardial infarction)." J. Am. Coll.

Cardiol. 44(3): 671-719.

Armstrong, D., H. Reyburn and R. Jones (1996). "A study of general practitioners' reasons for changing

their prescribing behaviour." BMJ 312(7036): 949-952.

Aronow, H. D., E. J. Topol, et al. (2001a). "Effect of lipid-lowering therapy on early mortality after acute

coronary syndromes: an observational study." Lancet 357(9262): 1063-8.

Aronow, W. S. (1996). "Prevalence of use of beta blockers and of calcium channel blockers in older

patients with prior myocardial infarction at the time of admission to a nursing home." J. Am. Geriatr. Soc.

44(9): 1075-7.

Aronow, W. S. (1998). "Underutilization of lipid-lowering drugs in older persons with prior myocardial

infarction and a serum low-density lipoprotein cholesterol > 125 mg/dl." Am. J. Cardiol. 82(5): 668-9,

A6, A8.

Aronow, W. S. and C. Ahn (2002). "Incidence of new coronary events in older persons with prior

myocardial infarction and serum low-density lipoprotein cholesterol > or = 125 mg/dl treated with statins

versus no lipid-lowering drug." Am. J. Cardiol. 89(1): 67-9.

Aronow, W. S., C. Ahn and I. Kronzon (2001b). "Effect of beta blockers alone, of angiotensin-converting

enzyme inhibitors alone, and of beta blockers plus angiotensin-converting enzyme inhibitors on new

367

coronary events and on congestive heart failure in older persons with healed myocardial infarcts and

asymptomatic left ventricular systolic dysfunction." Am. J. Cardiol. 88(11): 1298-300.

ASPIRE Steering Group (1996). "A British Cardiac Society survey of the potential for the secondary

prevention of coronary disease: ASPIRE (Action on Secondary Prevention through Intervention to

Reduce Events)." Heart 75(4): 334-42.

Asztalos, B. F., K. V. Horvath, et al. (2002). "Comparing the effects of five different statins on the HDL

subpopulation profiles of coronary heart disease patients." Atherosclerosis. 164(2): 361-9.

Athyros, V. G., A. A. Papageorgiou, et al. (2002). "Treatment with atorvastatin to the National

Cholesterol Educational Program goal versus 'usual' care in secondary coronary heart disease prevention:

The Greek atorvastatin and coronary-heart-disease evaluation (GREACE) study." Curr. Med. Res. Opin.

18(4): 220-228.

Atkin, P. A., R. S. Stringer, et al. (1998). "The influence of information provided by patients on the

accuracy of medication records." Med. J. Aust. 169(2): 85-8.

Australian Council on Safety and Quality in Health Care (2003). 10 tips for safer health care. What

everyone needs to know. A Guide to becoming more actively involved in your health care.

http://www.safetyandquality.org.

Australian Institute of Health and Welfare (2003). Health Expenditure Australia 2001-02. AIHW Cat No

HWE-24 (Health and Welfare Expenditure Series No. 17). Canberra, AIHW.

Australian Institute of Health and Welfare (2004a). Health expenditure Australia 2002-03. AIHW Cat No

HWE-27 (Health and Welfare Expenditure Series No. 20). Canberra, AIHW.

Australian Institute of Health and Welfare (2004b). Heart, stroke and vascular diseases- Australian facts

2004. AIHW Cat. No. CVD-27 (Cardiovascular Disease Series No 22). Canberra, AIHW and National

Heart Foundation of Australia.

Australian Pharmaceutical Advisory Council (1998). National Guidelines to achieve the continuum of

quality use of medicines between hospital and community. Canberra, Commonwealth Department of

Health and Family services.

Avezum, A., M. Makdisse, et al. (2005). "Impact of age on management and outcome of acute coronary

syndrome: Observations from the global registry of acute coronary events (GRACE)." Am. Heart J.

149(1): 67-73.

Avorn, J., J. Monette, et al. (1998). "Persistence of use of lipid-lowering medications: a cross-national

study." JAMA 279(18): 1458-62.

Ayanian, J. Z., P. J. Hauptman, et al. (1994). "Knowledge And Practices Of Generalist And Specialist

Physicians Regarding Drug Therapy For Acute Myocardial Infarction." N. Engl. J. Med. 331(17):

1136-1142.

Ayanian, J. Z., M. B. Landrum and B. J. McNeil (2002). "Use of cholesterol-lowering therapy by elderly

adults after myocardial infarction." Arch. Intern. Med. 162: 1013-1019.

368

Baber, N. S., D. G. Julian, J. A. Lewis and G. Rose (1984). "Beta blockers after myocardial infarction:

have trials changed practice?" BMJ. 289(6456): 1431-2.

Bairey-Merz, C. N., G. A. Mensah, V. Fuster, P. Greenland and P. D. Thompson (2002). "Task Force #5-

The Role of Cardiovascular Specialists as Leaders in Prevention: From Training to Champion." J. Am.

Coll. Cardiol. 40(4): 579-651.

Balkrishnan, R. (1998). "Predictors of medication adherence in the elderly." Clin. Ther. 20(4): 764-71.

Barron, H. V., A. D. Michaels, C. Maynard and N. R. Every (1998a). "Use of angiotensin-converting

enzyme inhibitors at discharge in patients with acute myocardial infarction in the United States: data from

the National Registry of Myocardial Infarction 2." J. Am. Coll. Cardiol. 32(2): 360-7.

Barron, H. V., S. Viskin, et al. (1998b). "Beta-blocker dosages and mortality after myocardial infarction:

data from a large health maintenance organization." Arch. Intern. Med. 158(5): 449-53.

Barter, P. J. and R. C. O'Brien (2000). "Achievement of target plasma cholesterol levels in

hypercholesteremic patients being treated in general practice." Atherosclerosis 149: 199-205.

Baxter, C., R. Jones and L. Corr (1998). "Time trend analysis and variations in prescribing lipid lowering

drugs in general practice." BMJ 317(7166): 1134-5.

Beck, C. A., C. Lauzon, et al. (2001). "Discharge prescriptions following admission for acute myocardial

infarction at tertiary care and community hospitals in Quebec." Can. J. Cardiol. 17(1): 33-40.

Becker, M. H. (1985). "Patient adherence to prescribed therapies." Med. Care 23(5): 539-55.

Bedell, S. E., S. Jabbour, et al. (2000). "Discrepancies in the use of medications: their extent and

predictors in an outpatient practice." Arch. Intern. Med. 160(14): 2129-34.

Benner, J. S., R. J. Glynn, et al. (2002). "Long-term persistence in use of statin therapy in elderly

patients." JAMA. 288(4): 455-61.

Benner, J. S., M. F. Pollack, et al. (2005). "Association between short-term effectiveness of statins and

long-term adherence to lipid-lowering therapy." American Journal of Health-System Pharmacy July 15

62(14): 1468-1475.

Benner, J. S., J. C. Tierce, et al. (2004). "Follow-up Lipid Tests and Physician Visits are Associated with

Improved Adherence to Statin Therapy." Pharmacoeconomics 22 (Supplement 3): 13-23.

Bennett, K. E., D. Williams and J. Feely (2002). "Inequalities in prescribing of secondary preventative

therapies for ischaemic heart disease in Ireland." Ir. Med. J. 95(6): 169-72.

Beta-Blocker Heart Attack Trial Research Group (1982). "A randomized trial of propranolol in patients

with acute myocardial infarction. I. Mortality results." JAMA 247(12): 1707-14.

Beta-Blocker Heart Attack Trial Research Group (1983). "A randomized trial of propranolol in patients

with acute myocardial infarction. II. Morbidity results." JAMA 250(20): 2814-9.

Bodenheimer, T. (1999). "The American health care system--the movement for improved quality in

health care." N. Engl. J. Med. 340(6): 488-92.

369

Bolton, P., M. Mira, P. Kennedy and M. M. Lahra (1998). "The quality of communication between

hospitals and general practitioners: an assessment." J. Qual. Clin. Pract. 18(4): 241-7.

Borrello, F., M. Beahan, L. Klein and M. Gheorghiade (2003). "Reappraisal of beta-blocker therapy in the

acute and chronic post-myocardial infarction period." Reviews in Cardiovascular Medicine 4 (suppl 3):

S13-S24.

Bourquin, M. G., V. Wietlisbach, M. Rickenbach, F. Perret and F. Paccaud (1998). "Time trends in the

treatment of acute myocardial infarction in Switzerland from 1986 to 1993: do they reflect the advances

in scientific evidence from clinical trials?" J. Clin. Epidemiol. 51(9): 723-32.

Bradley, C. P. (1991). "Decision making and prescribing patterns--a literature review." Fam. Pract. 8(3):

276-87.

Bradley, F., S. Morgan, H. Smith and D. Mant (1997). "Preventive care for patients following myocardial

infarction. The Wessex Research Network (WReN)." Fam. Pract. 14(3): 220-6.

Bradshaw, P. J., K. Jamrozik, I. Gilfillan and P. L. Thompson (2004). "Preventing recurrent events long

term after coronary artery bypass graft: suboptimal use of medications in a population study." Am. Heart

J. 147(6): 1047-53.

Brady, A. J. B., M. A. Oliver and J. B. Pittard (2001). "Secondary prevention in 24 431 patients with

coronary heart disease: survey in primary care." BMJ 322: 1463.

Brand, D. A., L. N. Newcomer, A. Freiburger and H. Tian (1995). "Cardiologists' practices compared

with practice guidelines: use of beta-blockade after acute myocardial infarction." J. Am. Coll. Cardiol.

26(6): 1432-6.

Braunwald, E. (2001). "Changing the practice of cardiovascular medicine." Atherosclerosis Supplements

2(1): 27-30.

Braunwald, E., E. M. Antman, et al. (2002). "ACC/AHA Guideline Update for the Management of

Patients With Unstable Angina and Non-ST-Segment Elevation Myocardial Infarction--2002: Summary

Article: A Report of the American College of Cardiology/American Heart Association Task Force on

Practice Guidelines (Committee on the Management of Patients With Unstable Angina)." Circulation

106(14): 1893-1900.

Braunwald, E., M. J. Domanski, et al. (2004). "Angiotensin-converting-enzyme inhibition in stable

coronary artery disease." N. Engl. J. Med. 351(20): 2058-68.

Brawley, L. R. and S. N. Culos-Reed (2000). "Studying adherence to therapeutic regimens: overview,

theories, recommendations." Control. Clin. Trials 21(5 Suppl).

British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society and British

Diabetic Association (2000). "Joint British recommendations on prevention of coronary heart disease in

clinical practice: summary." BMJ 320: 705-708.

Brotons, C., F. Calvo, et al. (1998). "Is prophylactic treatment after myocardial infarction evidence-

based?" Fam. Pract. 15(5): 457-61.

370

Brown, A. S., R. G. Bakker-Arkema, et al. (1998). "Treating patients with documented atherosclerosis to

National Cholesterol Education Program-recommended low-density-lipoprotein cholesterol goals with

atorvastatin, fluvastatin, lovastatin and simvastatin." J Am Coll Cardiol. 32(3): 665-72.

Bultman, D. C. and B. L. Svarstad (2000). "Effects of physician communication style on client

medication beliefs and adherence with antidepressant treatment." Patient Educ. Couns. 40(2): 173-85.

Burke, L. E., J. M. Dunbar-Jacob and M. N. Hill (1997). "Compliance with cardiovascular disease

prevention strategies: a review of the research." Ann. Behav. Med. 19(3): 239-63.

Burwen, D. R., D. Galusha, et al. (2003). "National and state trends in quality of care for acute

myocardial infarction between 1994-1995 and 1998-1999: The Medicare health care quality improvement

program." Arch. Intern. Med. 163(12): 1430-1439.

Butler, J., P. G. Arbogast, et al. (2002). "Outpatient adherence to beta-blocker therapy after acute

myocardial infarction." J. Am. Coll. Cardiol. 40(9): 1589-1595.

Campbell, N. C., L. D. Ritchie, et al. (1998a). "Secondary prevention in coronary heart disease: a

randomised trial of nurse led clinics in primary care." Heart 80(5): 447-52.

Campbell, N. C., J. Thain, H. G. Deans, L. D. Ritchie and J. M. Rawles (1998b). "Secondary prevention

in coronary heart disease: baseline survey of provision in general practice." BMJ 316(7142): 1430-4.

Cannon, C. P., E. Braunwald, et al. (2004). "Intensive versus moderate lipid lowering with statins after

acute coronary syndromes." N. Engl. J. Med. 350(15): 1495-504.

CAPRIE Steering Committee (1996). "A randomised, blinded, trial of clopidogrel versus aspirin in

patients at risk of ischaemic events (CAPRIE)." Lancet 348(9038): 1329-39.

Caro, J. J., M. Salas, J. L. Speckman, G. Raggio and J. D. Jackson (1999a). "Persistence with treatment

for hypertension in actual practice." CMAJ 160(1): 31-7.

Caro, J. J., J. L. Speckman, M. Salas, G. Raggio and J. D. Jackson (1999b). "Effect of initial drug choice

on persistence with antihypertensive therapy: the importance of actual practice data." CMAJ 160(1): 41-6.

Chandra, N. C., R. C. Ziegelstein, et al. (1998). "Observations of the treatment of women in the United

States with myocardial infarction: a report from the National Registry of Myocardial Infarction-I." Arch.

Intern. Med. 158(9): 981-8.

Charlson, M. E., P. Pompei, K. L. Ales and C. R. MacKenzie (1987). "A New Method Of Classifying

Prognostic Comorbidity in Longitudinal Studies: Development and Validation." J. Chronic Dis. 40: 373-

383.

Chassin, M. R. and R. W. Galvin (1998). "The urgent need to improve health care quality. Institute of

Medicine National Roundtable on Health Care Quality." JAMA 280(11): 1000-5.

Chavey II, W. E. (2000). "The importance of beta blockers in the treatment of heart failure." Am. Fam.

Physician 62: 2453-62.

Chen, J., T. A. Marciniak, J. M. Radford, Y. Wang and H. M. Krumholz (1999a). "Beta-blocker therapy

for secondary prevention of myocardial infarction in elderly diabetic patients." JACC 34: 1388-94.

371

Chen, J., M. J. Radford, Y. Wang, T. A. Marciniak and H. M. Krumholz (1999b). "Do "America's Best

Hospitals" perform better for acute myocardial infarction?" N. Engl. J. Med. 340(4): 286-92.

Chen, J., M. J. Radford, Y. Wang, T. A. Marciniak and H. M. Krumholz (2001). "Effectiveness of beta-

blocker therapy after acute myocardial infarction in elderly patients with chronic obstructive pulmonary

disease or asthma." J. Am. Coll. Cardiol. 37(7): 1950-6.

Chin, M. H., P. D. Friedmann, C. K. Cassel and R. M. Lang (1997). "Differences in Generalist and

Specialist Physicians' Knowledge and Use of Angiotensin-Converting Enzyme Inhibitors for Congestive

Heart Failure." J. Gen. Intern. Med. 12: 523-530.

Choo, P. W., C. S. Rand, et al. (1999). "Validation of patient reports, automated pharmacy records, and

pill counts with electronic monitoring of adherence to antihypertensive therapy." Med. Care 37(9): 846-

57.

Chowdhury, T. A., S. S. Lasker and P. H. Dyer (1999). "Comparison of secondary prevention measures

after myocardial infarction in subjects with and without diabetes mellitus." J. Intern. Med. 245(6): 565-

70.

Cilla, D. C., D. M. Gibson, L. R. Whitfield and A. J. Sedman (1996). "Pharmacokinetic Effects and

Pharmacokinetics of Atorvastatin after the Administration to Normocholesterolemic Subjects in the

Morning and Evening." J. Clin. Pharmacol. 36: 604-609.

Clark, L. T. (2003). "Treating dyslipidemia with statins: the risk-benefit profile." Am. Heart J. 145(3):

387-96.

Claxton, A. J., J. Cramer and C. Pierce (2001). "A Systematic Review of the Association Between Dose

Regimens and Medication Compliance." Clin. Ther. 23(8): 1296-1310.

Cleary, P. D., S. Edgman-Levitan, et al. (1991). "Patients evaluate their hospital care: a national survey."

Health Aff. (Millwood). 10(4): 254-67.

Col, N. F., T. J. McLaughlin, et al. (1996). "The impact of clinical trials on the use of medications for

acute myocardial infarction. Results of a community-based study." Arch. Intern. Med. 156(1): 54-60.

Commonwealth Department of Health and Aged Care (1999). National Medicines Policy. Canberra,

Commonwealth of Australia.

Commonwealth Department of Health Housing and Community Services (1995). Manual of indicators to

measure the effect of initiatives under the quality use of medicine arm of the national medicinal drug

policy. Canberra, Australian Publishing Services.

Compliance Action Program American Heart Association.

http://www.americanheart.org/presenter.jhtml?identifier=1657.

Coronary Drug Project Research Group (1980). "Influence of adherence to treatment and response of

cholesterol on mortality in the coronary drug project." N. Engl. J. Med. 303(18): 1038-41.

Cramer, J. A. (2002). "Effect of partial compliance on cardiovascular medication effectiveness." Heart.

88(2): 203-6.

372

Cramer, J. A., R. H. Mattson, M. L. Prevey, R. D. Scheyer and V. L. Ouellette (1989). "How often is

medication taken as prescribed? A novel assessment technique." JAMA. 261(22): 3273-7.

Cramer, J. A., R. D. Scheyer and R. H. Mattson (1990). "Compliance declines between clinic visits."

Arch. Intern. Med. 150(7): 1509-10.

Culos-Reed, S. N., W. J. Rejeski, E. McAuley, J. K. Ockene and D. L. Roter (2000). "Predictors of

adherence to behavior change interventions in the elderly." Control. Clin. Trials 21(5 Suppl): 200S-5S.

Czarn, A. O., K. Jamrozik, M. S. Hobbs and P. L. Thompson (1992). "Follow-up care after acute

myocardial infarction." Med. J. Aust. 157(5): 302-5.

Dailey, G., M. S. Kim and J. F. Lian (2001). "Patient compliance and persistence with antihyperglycemic

drug regimens: evaluation of medicaid patient population with type 2 diabetes mellitus." Clin. Ther. 23:

1311-1320.

Dalal, H., P. H. Evans and J. L. Campbell (2004). "Recent developments in secondary prevention and

cardiac rehabilitation after acute myocardial infarction." BMJ 328: 693-7.

Dalal, H. M. and P. H. Evans (2003). "Achieving national service framework standards for cardiac

rehabilitation and secondary prevention." BMJ 326(7387): 481-484.

Danchin, N., O. Grenier, J. Ferrieres, C. Cantet and J. Cambou (2002). "Use of secondary preventive

drugs in patients with acute coronary syndromes treated medically or with coronary angioplasty: results

from the nationwide French PREVINIR survey." Heart 88: 159-162.

de Looper, M. and K. Bhatia (2001). Australian health trends 2001. Canberra, Australian Institute of

Health and Welfare.

de Oya, M., J. L. Lopez Sendon, et al. (2000). "The impact of landmark clinical trials on secondary

prevention of acute myocardial infarction (AMI) in Spain. Prevese 98 study." Atherosclerosis.

Department of Health and Aging (2003). Medicare Statistics. http://www.health.gov.au/haf/medstats/,

Commonwealth of Australia.

DeWilde, S., I. M. Carey, et al. (2003). "Evolution of statin prescribing 1994-2001: a case of agism but

not of sexism?" Heart 89(4): 417-421.

Dickstein, K., J. Kjekshus and O. S. G. for the OPTIMAAL Steering Committee (2002). "Effects of

losartan and captopril on mortality and morbidity in high-risk patients after acute myocardial infarction:

the OPTIMAAL randomised trial." Lancet 360: 752-60.

DiMatteo, M. R. (1994). "Enhancing patient adherence to medical recommendations." JAMA 271(1): 5.

Donovan, J. L. and D. R. Blake (1992). "Patient non-compliance: deviance or reasoned decision-

making?" Social Science & Medicine 34(5): 507-13.

Dudas, V., T. Bookwalter, K. M. Kerr and S. Z. Pantilat (2001). "The impact of follow-up telephone calls

to patients after hospitalization." Am. J. Med. 111(9B): 26S-30S.

373

Dunbar-Jacob, J., J. A. Erlen, et al. (2000). "Adherence in chronic disease." Annu. Rev. Nurs. Res. 18:

48-90.

Dunbar-Jacob, J. M., E. A. Schlenk, L. E. Burke and J. T. Matthews (1998). Predictors of Patient

Adherence: Patient Characteristics. The Handbook of Health Behaviour Change. S. A. Shumaker, S. E.

B., J. O. Ockene and M. W. L. New York, Springer Pub. Co.: 491-511.

Dunbar-Jacob, L., L. Burke and S. Pyczynski (1995). Clinical Assessment and Management of Adherence

to Medical Regimes. Managing Chronic Illness: A Biopsychosocial Perspective. S. T. Nicassio PM.

Washington, American Psychological Association.

Dwamena, F. C., H. El-Tamimi, et al. (2000). "The use of angiotensin-converting enzyme inhibitors in

patients with acute myocardial infarction in community hospitals. Michigan State University Inter-

Institutional Collaborative Heart (MICH) Study Group." Clin. Cardiol. 23(5): 341-6.

Eagle, K. A. (2003). ACC AMI GAP: American College of Cardiology Acute Myocardial Infarction

Guidelines Applied in Practice. American College of Cardiology 52nd Annual Scientific Meeting,

Chicago, Illinois.

Eagle, K. A., E. Kline-Rogers, et al. (2004). "Adherence to evidence-based therapies after discharge for

acute coronary syndromes: an ongoing prospective, observational study." Am. J. Med. 117(2): 73-81.

Ebrahim, S., L. Wei, P. D. Davey, T. M. MacDonald and F. M. Sullivan (2005). "Secondary prevention of

heart disease with statins." BMJ 330: 1208-09.

Eccles, M. and C. Bradshaw (1991). "Use of secondary prophylaxis against myocardial infarction in the

north of England." BMJ 302(6768): 91-2.

Eisen, S. A., D. K. Miller, R. S. Woodward, E. Spitznagel and T. R. Przybeck (1990). "The effect of

prescribed daily dose frequency on patient medication compliance." Arch. Intern. Med. 150(9): 1881-4.

Ellerbeck, E. F., S. F. Jencks, et al. (1995). "Quality of care for Medicare patients with acute myocardial

infarction. A four-state pilot study from the Cooperative Cardiovascular Project." JAMA 273(19): 1509-

14.

Eraker, S. A., J. P. Kirscht and M. H. Becker (1984). "Understanding and improving patient compliance."

Ann. Intern. Med. 100(2): 258-68.

Eriksson, M., K. Hadell, I. Holme, G. Walldius and T. Kjellstrom (1998). "Compliance with and efficacy

of treatment with pravastatin and cholestyramine: a randomized study on lipid-lowering in primary care."

J. Intern. Med. 243(5): 373-80.

Euroaspire I and II Group (2001). "Clinical reality of coronary prevention guidelines: a comparison of

EUROASPIRE I and II in nine countries. EUROASPIRE I and II Group. European Action on Secondary

Prevention by Intervention to Reduce Events." Lancet 357(9261): 995-1001.

Euroaspire II Study Group (2001). "Lifestyle and risk factor management and use of drug therapies in

coronary patients from 15 countries; principal results from EUROASPIRE II Euro Heart Survey

Programme." Eur. Heart J. 22(7): 554-72.

374

EUROASPIRE Study Group (1997). "EUROASPIRE. A European Society of Cardiology survey of

secondary prevention of coronary heart disease: principal results. EUROASPIRE Study Group. European

Action on Secondary Prevention through Intervention to Reduce Events." Eur. Heart J. 18(10): 1569-82.

Faergeman, O., J. Kjekshus, et al. (1998). "Differences in the treatment of coronary heart disease between

countries as revealed in the Scandinavian Simvastatin Survival Study (4S)" Eur. Heart J. 19(10): 1531-7.

Fairhurst, K. and G. Huby (1998). "From trial data to practical knowledge: qualitative study of how

general practitioners have accessed and used evidence about statin drugs in their management of

hypercholesterolaemia." BMJ 317(7166): 1130-1134.

Farrell, M. H., J. M. Foody and H. M. Krumholz (2002). "Beta-blockers in heart failure: Clinical

applications." JAMA 287(7): 890.

Feder, G., C. Griffiths, S. Eldridge and M. Spence (1999). "Effect of postal prompts to patients and

general practitioners on the quality of primary care after a coronary event (POST): randomised controlled

trial." BMJ 318(7197): 1522-6.

Federman, A. D., A. S. Adams, D. Ross-Degnan, S. B. Soumerai and J. Z. Ayanian (2001).

"Supplemental insurance and use of effective cardiovascular drugs among elderly Medicare beneficiaries

with coronary heart disease." JAMA 286(14): 1732-9.

Feely, J. (1999). "The therapeutic gap--compliance with medication and guidelines." Atherosclerosis

147(Suppl 1): S31-7.

Feely, J., R. Chan, J. McManus and B. O'Shea (1999). "The influence of hospital-based prescribers on

prescribing in general practice." Pharmacoeconomics. 16(2): 175-81.

Ferlie, E. B. and S. M. Shortell (2001). "Improving the quality of health care in the United Kingdom and

the United Sates: A framework for change." Milbank Q. 79(2): 281-315.

Flanagan, D. E., P. Cox, D. Paine, J. Davies and M. Armitage (1999). "Secondary prevention of coronary

heart disease in primary care: a healthy heart initiative." QJM 92(5): 245-50.

Flather, M. D., S. Yusuf, et al. (2000). "Long-term ACE-inhibitor therapy in patients with heart failure or

left-ventricular dysfunction: a systematic overview of data from individual patients. ACE-Inhibitor

Myocardial Infarction Collaborative Group." Lancet. 355(9215): 1575-81.

Fonarow, G. C., W. J. French, L. S. Parsons, H. Sun and J. A. Malmgren (2001a). "Use of lipid-lowering

medications at discharge in patients with acute myocardial infarction: data from the National Registry of

Myocardial Infarction 3." Circulation 103(1): 38-44.

Fonarow, G. C. and A. Gawlinski (2000). "Rationale and design of the Cardiac Hospitalization

Atherosclerosis Management Program at the University of California Los Angeles." Am. J. Cardiol.

85(3A): 10A-17A.

Fonarow, G. C., A. Gawlinski, S. Moughrabi, M. N. Samira and J. H. Tillisch (2001b). "Improved

Treatment of Coronary Heart Disease by Implementation of a Cardiac Hospitalization Atherosclerosis

Management Program (CHAMP)." Am. J. Cardiol. 87(7): 819-822.

375

Foody, J. M., M. H. Farrell and H. M. Krumholz (2002). "Beta-blocker therapy in heart failure: Scientific

review." JAMA 287(7): 883.

Fortess, E. E., S. B. Soumerai, T. J. McLaughlin and D. Ross-Degnan (2001). "Utilization of essential

medications by vulnerable older people after a drug benefit cap: importance of mental disorders, chronic

pain and practice setting." J. Am. Geriatr. Soc. 49: 793-797.

Frances, C. D., A. S. Go, et al. (1999). "Outcome following acute myocardial infarction: are differences

among physician specialties the result of quality of care or case mix?" Arch. Intern. Med. 159(13): 1429-

36.

Frances, C. D., M. G. Shlipak, H. Noguchi, P. A. Heidenreich and M. McClellan (2000). "Does physician

specialty affect the survival of elderly patients with myocardial infarction?" Health Serv. Res. 35(5 Pt 2):

1093-116.

Freeman, A. C. and K. Sweeney (2001). "Why general practitioners do not implement evidence:

qualitative study." BMJ 323(7321): 1100-2.

Freemantle, N., J. Cleland, P. Young, J. Mason and J. Harrison (1999). "Beta Blockade after myocardial

infarction: systematic review and meta regression analysis." BMJ 318(7200): 1730-7.

Fremont, A. M., P. D. Cleary, et al. (2001). "Patient-centred Processes of Care and Long-term Outcomes

of Myocardial Infarction." J Gen Intern Med 16: 800-808.

Friedman, L., N. K. Wenger and G. L. Knatterud (1983). "Impact of the Coronary Drug Project findings

on clinical practice." Control. Clin. Trials 4(4): 513-22.

Frishman, W. H. and A. Cheng (1999). "Secondary prevention of myocardial infarction: role of beta-

adrenergic blockers and angiotensin-converting enzyme inhibitors." Am. Heart J. 137(4 Pt 2): S25-S34.

Frolkis, J. P., G. L. Pearce, V. Nambi, S. Minor and D. L. Sprecher (2002). "Statins do not meet

expectations for lowering low-density lipoprotein cholesterol levels when used in clinical practice." Am.

J. Med. 113(8): 625-9.

Fuster, V., M. L. Dyken, P. S. Vokonas and C. Hennekens (1993). "Aspirin as a therapeutic agent in

cardiovascular disease. Special Writing Group." Circulation 87(2): 659-75.

Ganz, D. A., G. A. Lamas, et al. (1999). "Age-related differences in management of heart disease: a study

of cardiac medication use in an older cohort. Pacemaker Selection in the Elderly (PASE) Investigators." J.

Am. Geriatr. Soc. 47(2): 145-50.

Garg, A. X., N. K. J. Adhikari, et al. (2005). "Effects of Computerized Clinical Decision Support Systems

on Practitioner Performance and Patient Outcomes: A Systematic Review." JAMA 293(10): 1223-1238.

Gaspoz, J.-M., P. G. Coxson, et al. (2002). "Cost Effectiveness of Aspirin, Clopidogrel, or Both for

Secondary Prevention of Coronary Heart Disease." N Engl J Med 346(23): 1800-1806.

Get with the guidelines American Heart Association.

http://www.americanheart.org/presenter.jhtml?identifier=1165.

376

Gheorghiade, M., W. S. Colucci and K. Swedberg (2003). "Beta-Blockers in Chronic Heart Failure."

Circulation 107(12): 1570-1575.

Gheorghiade, M. and S. Goldstein (2002). "Beta-blockers in the post-myocardial infarction patient."

Circulation 106: 394-398.

Giesler, G., D. J. Lenihan and J. B. Durand (2004). "The update on the rationale, use and selection of

beta-blockers in heart failure." Curr. Opin. Cardiol. 19(3): 250-3.

GISEN Group (Gruppo Italiano di Studi Epidemiologici in Nefrologia), T. (1996). "Randomised placebo-

controlled trial of effect of ramipril on decline in glomerular filtration rate and risk of terminal renal

failure in proteinuric, non-diabetic nephropathy." The Lancet 349(9069): 1857-1863.

Giugliano, R. P., C. A. Camargo, Jr., et al. (1998). "Elderly patients receive less aggressive medical and

invasive management of unstable angina: potential impact of practice guidelines." Arch. Intern. Med.

158(10): 1113-20.

Go, A. S., R. K. Rao, K. W. Dauterman and B. M. Massie (2000). "A systematic review of the effects of

physician specialty on the treatment of coronary disease and heart failure in the United States." Am. J.

Med. 108(3): 216-26.

Gobble, A. J. and M. U. C. Worcester (1999). Best Practice Guidelines for Cardiac Rehabilitation and

Secondary Prevention, Department of Human Services Victoria.

Goldberg, R. B. (1999). "The benefits of lowering cholesterol in subjects with mild hyperglycemia."

Arch. Intern. Med. 159: 2627-28.

Goldberg, R. J., I. S. Ockene, J. Yarzebski, J. Savageau and J. M. Gore (1997). "Use of lipid-lowering

medication in patients with acute myocardial infarction (Worcester Heart Attack Study)." Am. J. Cardiol.

79(8): 1095-7.

Goldstein, M. G. (2002). "Benefits of beta-blocker Therapy for Heart Failure." Arch. Intern. Med. 162:

641-648.

Gomma, A., J. Henderson, H. Purcell and K. A. Fox (2002). "The clinical application of ACE inhibitors

in coronary heart disease." Br. J. Pharmacol. 9(3): 158-162.

Gordis, L. (1979). Conceptual and Methodological Problems in Measuring Patient Compliance.

Compliance in Health Care. R. B. Haynes, D. W. Taylor and D. L. Sackett. Baltimore, John Hopkins

University Press: 23-45.

Gorelick, P. B., G. V. Born, et al. (1999). "Therapeutic benefit. Aspirin revisited in light of the

introduction of clopidogrel." Stroke 30(8): 1716-21.

Gottlieb, S. S., R. J. McCarter and R. A. Vogel (1998). "Effect of beta-blockade on mortality among high-

risk and low-risk patients after myocardial infarction." N. Engl. J. Med. 339(8): 489-97.

Gotto, A. M., Jr. (1997). "Cholesterol management in theory and practice." Circulation 96(12): 4424-30.

Grimshaw, J. M. and I. T. Russell (1993). "Effect of clinical guidelines on medical practice: a systematic

review of rigorous evaluations." Lancet 342(8883): 1317-1322.

377

Grundy, S. M., G. J. Balady, et al. (1997). "When to start cholesterol-lowering therapy in patients with

coronary heart disease. A statement for healthcare professionals from the American Heart Association

Task Force on Risk Reduction." Circulation 95(6): 1683-5.

Grundy, S. M., J. I. Cleeman, et al. (2004). "Implications of recent clinical trials for the National

Cholesterol Education Program Adult Treatment Panel III Guidelines." J. Am. Coll. Cardiol. 44(3): 720-

32.

Gurwitz, J. H., R. J. Goldberg, Z. Chen, J. M. Gore and J. S. Alpert (1992). "Beta-blocker therapy in

acute myocardial infarction: evidence for underutilization in the elderly." Am. J. Med. 93(6): 605-10.

Haffner, S. M., C. M. Alexander, et al. (1999). "Reduced coronary events in simvastatin-treated patients

with coronary heart disease and diabetes or impaired fasting glucose levels: subgroup analyses in the

Scandinavian Simvastatin Survival Study." Arch. Intern. Med. 159(22): 2661-7.

Hansson, L., L. H. Lindholm, et al. (1999). "Effect of angiotensin-converting-enzyme inhibition

compared with conventional therapy on cardiovascular morbidity and mortality in hypertension: the

Captopril Prevention Project (CAPPP) randomised trial." The Lancet 353(9153): 611-616.

Harris, D. E., N. B. Record, G. W. Gipson and T. A. Pearson (1998). "Lipid lowering in a

multidisciplinary clinic compared with primary physician management." Am. J. Cardiol. 81(7): 929-33.

Haynes, R. B., H. McDonald, A. X. Carg and P. Montague (2002). "Interventions for helping patients to

follow prescriptions for medications." Cochrane Database of Systematic Reviews, Issue 2: Art. No.:

CD000011. DOI: 10.1002/14651858.CD000011.

Haynes, R. B., D. W. Taylor and D. L. Sackett (1979). Compliance in Health Care. Baltimore, John

Hopkins University Press.

Heart Outcomes Prevention Evaluation Study Investigators (2000). "Effects of ramipril on cardiovascular

and microvascular outcomes in people with diabetes mellitus: results of the HOPE study and MICRO-

HOPE substudy. Heart Outcomes Prevention Evaluation Study Investigators." Lancet 355(9200): 253-9.

Heart Protection Study Collaborative Group (2002). "MRC/BHF Heart Protection Study of cholesterol

lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial." Lancet.

360(9326): 7-22.

Hedblad, B., J. Wikstrand, L. Janzon, H. Wedel and G. Berglund (2001). "Low-dose metoprolol CR/XL

and fluvastatin slow progression of carotid intima-thickness: main results from the beta-blocker

cholesterol lowering asymptomatic plaque study (BCAPS)." Circulation 103: 1721-1726.

Heeschen, C. and C. W. Hamm (2000). "Difficulties with oral platelet glycoprotein IIb/IIIa receptor

antagonists." Lancet 355: 330-331.

Heller, D. A., F. M. Ahern and M. Kozak (2000). "Changes in rates of beta-blocker use between 1994 and

1997 among elderly survivors of acute myocardial infarction." Am. Heart J. 140(4): 663-71.

378

Heller, R. F., A. J. Dobson, H. M. Alexander, P. L. Steele and J. A. Malcolm (1992). "Changes in drug

treatment and case fatality of patients with acute myocardial infarction. Observations from the Newcastle

MONICA Project, 1984/1985 to 1988/1990." Med. J. Aust. 157(2): 83-6.

Hemels, M. E., H. A. Bennett, et al. (2003). "HOPE study impact on ACE inhibitors use." Ann.

Pharmacother. 37(5): 640-5.

Hennekens, C. H., M. L. Dyken and V. Fuster (1997). "Aspirin as a therapeutic agent in cardiovascular

disease: a statement for healthcare professionals from the American Heart Association." Circulation

96(8): 2751-3.

Hennessy, S. and S. E. Kimmel (2004). "Is Improved Survival a Class Effect of Angiotensin-Converting

Enzyme Inhibitors?" Ann Intern Med 141(2): 157-158.

Herholz, H., D. C. Goff, et al. (1996). "Women and Mexican Americans receive fewer cardiovascular

drugs following myocardial infarction than men and non-Hispanic whites: the Corpus Christi Heart

Project, 1988-1990." J. Clin. Epidemiol. 49(3): 279-87.

Hermann, D. D. (2002). "Beta-Adrenergic Blockade 2002: A Pharmacologic Odyssey in Chronic Heart

Failure." CHF 8(5): 262-269.

Hillis, G. S., R. J. Trent, P. Winton, A. M. MacLeod and K. P. Jennings (1996). "Angiotensin-converting-

enzyme inhibitors in the management of cardiac failure: are we ignoring the evidence?" QJM 89(2): 145-

50.

Hippisley-Cox, J., R. Carter, M. Pringle and C. Coupland (2003). "Cross sectional survey of effectiveness

of lipid lowering drugs in reducing serum cholesterol concentration in patients in 17 general practices."

BMJ 326: 689-93.

Hippisley-Cox, J. and C. Coupland (2005). "Effect of combinations of drugs on all cause mortality in

patients with ischaemic heart disease: nested case-control analysis." BMJ 330(7499): 1059-1063.

Hippisley-Cox, J., M. Pringle, N. Crown, A. Meal and A. Wynn (2001). "Sex inequalities in ischaemic

heart disease in general practice: cross sectional survey." BMJ 322(7290): 832.

Hjalmarson, A., D. Elmfeldt, et al. (1981). "Effect on mortality of metoprolol in acute myocardial

infarction. A double-blind randomised trial." Lancet. 2(8251): 823-7.

Hlatky, M. A., H. E. Cotugno, et al. (1988). "Trends in physician management of uncomplicated acute

myocardial infarction, 1970 to 1987." Am. J. Cardiol. 61(8): 515-8.

Hobbs, F. R. and L. Erhardt (2002). "Acceptance of guideline recommendations and perceived

implementation of coronary heart disease prevention among primary care physicians in five European

countries: the Reassessing European Attitudes about Cardiovascular Treatment (REACT) survey." Fam.

Pract. 19(6): 596-604.

Holt, N. D., A. Johnson and M. De Belder (2000). "Patient empowerment in secondary prevention of

coronary heart disease." BMJ 356: 314.

379

Horwitz, R. I., C. M. Viscoli, et al. (1990). "Treatment adherence and risk of death after a myocardial

infarction." Lancet 336(8714): 542-5.

Houghton, T., N. Freemantle and J. Cleland (2000). "Are beta-blockers effective in patients who develop

heart failure soon after myocardial infarction? A meta-regression analysis of randomised trials." European

Journal of Heart Failure 2: 333-340.

Howard, P. A. and E. F. Ellerbeck (2000). "Optimizing beta-blocker use after myocardial infarction."

Am. Fam. Physician 62(8): 1853-60, 1865-6.

Hudson, M., H. Richard and L. Pilote (2005). "Differences in outcomes of patients with congestive heart

failure prescribed celecoxib, rofecoxib, or non-steroidal anti-inflammatory drugs: population based

study." BMJ June 11 330(7504): 1370.

Hung, J. and Medical Issues Committee of the National Heart Foundation of Australia (2003). "Aspirin

for cardiovascular disease prevention." Med. J. Aust. 179(3): 147-52.

Hunink, M. G., L. Goldman, et al. (1997). "The recent decline in mortality from coronary heart disease,

1980-1990. The effect of secular trends in risk factors and treatment." JAMA. 277(7): 535-42.

Hunninghake, D. M. D., R. G. M. S. Bakker-Arkema, et al. (1998). "Treating to Meet NCEP-

Recommended LDL Cholesterol Concentrations with Atorvastatin, Fluvastatin, Lovastatin, or

Simvastatin in Patients with Risk Factors for Coronary Heart Disease." J. Fam. Pract. 47(5): 349-356.

Hunt, D., P. Young, et al. (2001). "Benefits of pravastatin on cardiovascular events and mortality in older

patients with coronary heart disease are equal to or exceed those seen in younger patients: Results from

the LIPID trial." Ann. Intern. Med. 134(10): 931-40.

Hurlen, M., M. Abdelnoor, P. Smith, J. Erikssen and H. Arnesen (2002). "Warfarin, aspirin or both after

myocardial infarction." N. Engl. J. Med. 347: 969-974.

Hutchison, S. J. and S. M. Cobbe (1987). "Management of myocardial infarction in Scotland: have

clinical trials changed practice?" British Medical Journal 294(6582): 1261.

Iliff, R. D. (2002). "Weekly versus daily dosing of atorvastatin." J. Fam. Pract. 51(4): 365-6.

Insull, W. (1997). "The problem of compliance to cholesterol altering therapy." J. Intern. Med. 241(4):

317-25.

Jabbour, S., Y. Young-Xu, et al. (2004). "Long-term outcomes of optimized medical management of

outpatients with stable coronary artery disease." The American Journal of Cardiology 93(3): 294-299.

Jackevicius, C. A., G. M. Anderson, L. Leiter and J. V. Tu (2001). "Use of the statins in patients after

acute myocardial infarction: does evidence change practice?" Arch. Intern. Med. 161(2): 183-8.

Jackevicius, C. A., M. Mamdani and J. V. Tu (2002). "Adherence with statin therapy in elderly patients

with and without acute coronary syndromes." JAMA. 288(4): 462-7.

Jamrozik, K. and R. Hockey (1989). "Trends in risk factors for vascular disease in Australia." Med. J.

Aust. 150(1): 14-8.

380

Jencks, S. F., E. D. Huff and T. Cuerdon (2003). "Change in the quality of care delivered to Medicare

beneficiaries, 1998-1999 to 2000-2001." JAMA 289(3): 305.

Johnson, R. E., M. J. Goodman, M. C. Hornbrook and M. B. Eldredge (1997a). "The effect of increased

prescription drug cost-sharing on medical care utilization and expenses of elderly health maintenance

organization members." Med. Care 35(11): 1119-31.

Johnson, R. E., M. J. Goodman, M. C. Hornbrook and M. B. Eldredge (1997b). "The impact of increasing

patient prescription cost sharing on therapeutic classes of drugs received and on the health status of

elderly HMO members." Health Serv. Res. 32(1): 103-122.

Joint Commission on Accreditation of Healthcare Organisations (2005). Speak Up.

http://www.jcaho.org/general+public/patient+safety/index.htm.

Jollis, J. G., E. R. DeLong, et al. (1996). "Outcome of acute myocardial infarction according to the

specialty of the admitting physician." N. Engl. J. Med. 335(25): 1880-7.

Jones, P., S. Kafonek, I. Laurora and D. Hunninghake (1998). "Comparative dose efficacy study of

atorvastatin versus simvastatin, pravastatin, lovastatin, and fluvastatin in patients with

hypercholesterolemia (the CURVES study)." Am. J. Cardiol. 81(5): 582-7.

Kawamoto, K., C. A. Houlihan, E. A. Balas and D. F. Lobach (2005). "Improving clinical practice using

clinical decision support systems: a systematic review of trials to identify features critical to success."

BMJ 330(7494): 765-.

Keech, A., D. Colquhoun, et al. (2003). "Secondary prevention of cardiovascular events with long-term

pravastatin in patients with diabetes or impaired fasting glucose." Diabetes Care 26: 2713-21.

Kehoe, W. A. and R. C. Katz (1998). "Health behaviors and pharmacotherapy." Ann. Pharmacother.

32(10): 1076-86.

Kizer, J. R., C. P. Cannon, et al. (1999). "Trends in the use of pharmacotherapies for acute myocardial

infarction among physicians who design and/or implement randomized trials versus physicians in routine

clinical practice: the MILIS-TIMI experience. Multicenter Investigation on Limitation of Infarct Size.

Thrombolysis in Myocardial Infarction." Am. Heart J. 137(1): 79-92.

Kizer, J. R. and S. E. Kimmel (2001). "Epidemiologic review of the calcium channel blocker drugs. An

up-to-date perspective on the proposed hazards." Arch. Intern. Med. 161(9): 1145-58.

Kloner, R. A. and S. H. Rezkalla (2004). "Cardiac protection during acute myocardial infarction: Where

do we stand in 2004?" J. Am. Coll. Cardiol. 44(2): 276-286.

Knopp, R. H. (1999). "Drug Therapy: Drug Treatment of Lipid Disorders." N. Engl. J. Med. 341(7): 498-

511.

Ko, D. T., P. R. Herbert, et al. (2002). "Beta-blocker therapy and symptoms of depression, fatigue and

sexual dysfunction." JAMA 288: 351-357.

381

Kober, L., C. Torp-Pedersen, et al. (1995). "A Clinical Trial of the Angiotensin-Converting-Enzyme

Inhibitor Trandolapril in Patients with Left Ventricular Dysfunction after Myocardial Infarction." N Engl

J Med 333(25): 1670-1676.

Kravitz, R. L., R. D. Hays, et al. (1993). "Recall of recommendations and adherence to advice among

patients with chronic medical conditions." Arch. Intern. Med. 153(16): 1869-78.

Krumholz, H. M., Y. T. Chen, Y. Wang and M. J. Radford (2001). "Aspirin and angiotensin-converting

enzyme inhibitors among elderly survivors of hospitalization for an acute myocardial infarction." Arch.

Intern. Med. 161(4): 538-44.

Krumholz, H. M., M. J. Radford, et al. (1996). "Aspirin for secondary prevention after acute myocardial

infarction in the elderly: prescribed use and outcomes." Ann. Intern. Med. 124(3): 292-8.

Krumholz, H. M., M. J. Radford, et al. (1998). "National use and effectiveness of beta-blockers for the

treatment of elderly patients after acute myocardial infarction: National Cooperative Cardiovascular

Project." JAMA 280(7): 623-9.

Krumholz, H. M., M. J. Radford, Y. Wang, J. Chen and T. A. Marciniak (1999). "Early beta-blocker

therapy for acute myocardial infarction in elderly patients." Ann. Intern. Med. 131(9): 648-54.

Krumholz, H. M., V. Vaccarino, et al. (1997). "Determinants of appropriate use of angiotensin-converting

enzyme inhibitors after acute myocardial infarction in persons > or = 65 years of age." Am. J. Cardiol.

79(5): 581-6.

Kubler, P. A., P. I. Pillans, M. C. Marrinan and M. Frogley (2004). "Concordance between clopidogrel

use and prescribing guidelines." Intern Med J 34(12): 663-667.

LaBresh, K. A., P. Owen, et al. (2000). "Secondary prevention in a cardiology group practice and hospital

setting after a heart-care initiative." Am. J. Cardiol. 85(3A): 23A-29A.

Lacy, C. R., D. C. Suh, et al. (2002). "Impact of a targeted intervention on lipid-lowering therapy in

patients with coronary artery disease in the hospital setting." Arch. Intern. Med. 162(4): 468-73.

Lamas, G. A., M. A. Pfeffer, et al. (1992). "Do the results of randomized clinical trials of cardiovascular

drugs influence medical practice? The SAVE Investigators." N. Engl. J. Med. 327(4): 241-7.

Lappe, J. M., J. B. Muhlestein, et al. (2004). "Improvements in 1-Year Cardiovascular Clinical Outcomes

Associated with a Hospital-Based Discharge Medication Program." Ann Intern Med 141(6): 446-453.

LaRosa, J. C. (2000). "Poor compliance: the hidden risk factor." Current Atherosclerosis Reports. 2(1): 1-

4.

LaRosa, J. C., J. He and S. Vupputuri (1999). "Effect of statins on risk of coronary disease: a meta-

analysis of randomized controlled trials." JAMA 282(24): 2340-6.

LaRosa, J. H. and J. C. LaRosa (2000). "Enhancing drug compliance in lipid-lowering treatment." Arch.

Fam. Med. 9(10): 1169-75.

382

Larsen, J., A. Vaccheri, M. Andersen, N. Montanaro and U. Bergman (2000). "Lack of adherence to lipid

lowering drug treatment. A comparison of utilization patterns in defined populations in Funen, Denmark

and Bologna, Italy." Br J Clin Pharmacol 49(5): 463-471.

Latini, R., A. P. Maggioni, M. Flather, P. Sleight and G. Tognoni (1995). "ACE inhibitor use in patients

with myocardial infarction. Summary of evidence from clinical trials." Circulation 92(10): 3132-7.

Lau, C. P., H. F. Tse, et al. (2002). "Comparison of perindopril versus captopril for treatment of acute

myocardial infarction." Am. J. Cardiol. 89(2): 150-4.

Le Grand, A., H. V. Hogerzeil and F. M. Haaijer-Ruskamp (1999). "Intervention research in rational use

of drugs: a review." Health Policy Plan. 14(2): 89-102.

Levesque, L. E. B. M., J. M. M. D. P. Brophy and B. M. Zhang (2005). "The Risk for Myocardial

Infarction with Cyclooxygenase-2 Inhibitors: A Population Study of Elderly Adults." Ann. Intern. Med.

142(7): 481-489.

Lewis, E. J., L. G. Hunsicker, R. P. Bain, R. D. Rohde and The Collaborative Study Group (1993). "The

Effect of Angiotensin-Converting-Enzyme Inhibition on Diabetic Nephropathy." N Engl J Med 329(20):

1456-1462.

Lim, L. L., R. F. Heller, R. L. O'Connell and K. D'Este (2000). "Stated and actual management of acute

myocardial infarction among different specialties." Med. J. Aust. 172(5): 208-12.

Lim, L. L., R. L. O'Connell and R. F. Heller (1999). "Differences in management of heart attack patients

between metropolitan and regional hospitals in the Hunter Region of Australia." Aust. N. Z. J. Public

Health 23(1): 61-6.

Lim, L. L., G. M. Tesfay and R. F. Heller (1998). "Management of patients with diabetes after heart

attack: a population-based study of 1982 patients from a heart disease register." Aust. N. Z. J. Med. 28(3):

334-42.

Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Group (1998). "Prevention

of cardiovascular events and death with pravastatin in patients with coronary heart disease and a broad

range of initial cholesterol levels. The Long-Term Intervention with Pravastatin in Ischaemic Disease

(LIPID) Study Group." N. Engl. J. Med. 339(19): 1349-57.

Lonn, E. M., S. Yusuf, et al. (2001). "Effects of Ramipril and Vitamin E on Atherosclerosis : The Study

to Evaluate Carotid Ultrasound Changes in Patients Treated With Ramipril and Vitamin E (SECURE)."

Circulation 103(7): 919-925.

Lonn, E. M., S. Yusuf, et al. (1994). "Emerging role of angiotensin-converting enzyme inhibitors in

cardiac and vascular protection." Circulation 90(4): 2056-2069.

Lutfey, K. E. and W. J. Wishner (1999). "Beyond "compliance" is "adherence". Improving the prospect of

diabetes care." Diabetes Care 22(4): 635-9.

Luzier, A. B., A. Navsarikar, M. F. Wilson, K. Ashai and A. Forrest (1999). "Patterns of prescribing ACE

inhibitors after myocardial infarction." Pharmacotherapy 19(5): 655-60.

383

Majumdar, S. R., J. H. Gurwitz and S. B. Soumerai (1999). "Undertreatment of hyperlipidemia in the

secondary prevention of coronary artery disease." J. Gen. Intern. Med. 14(12): 711-7.

Majumdar, S. R., T. S. Inui, et al. (2001). "Influence of physician specialty on adoption and

relinquishment of calcium channel blockers and other treatments for myocardial infarction." J. Gen.

Intern. Med. 16(6): 351-9.

Malhotra, H. S. and K. L. Goa (2001). "Atorvastatin: an updated review of its pharmacological properties

and use in dyslipidaemia." Drugs. 61(12): 1835-81.

Mann, D. L. and A. Deswal (2003). "Angiotensin-Receptor Blockade in Acute Myocardial Infarction -- A

Matter of Dose." N Engl J Med 349(20): 1963-1965.

Mant, A., L. Kehoe, N. L. Cockayne, K. I. Kaye and W. C. Rotem (2002). "A Quality Use of Medicines

program for continuity of care in therapeutics from hospital to community." Med. J. Aust. 177: 32-34.

Mant, A., W. C. Rotem, L. Kehoe and K. I. Kaye (2001). "Compliance with guidelines for continuity of

care in therapeutics from hospital to community." Med. J. Aust. 174(6): 277-80.

Marcelino, J. J. and K. R. Feingold (1996). "Inadequate treatment with HMG-CoA reductase inhibitors by

health care providers." Am. J. Med. 100(6): 605-10.

Marciniak, T. A., E. F. Ellerbeck, et al. (1998). "Improving the quality of care for Medicare patients with

acute myocardial infarction: results from the Cooperative Cardiovascular Project." JAMA 279(17): 1351-

7.

Marinker, M. (1997). "Personal paper: writing prescriptions is easy." BMJ 314(7082): 747-8.

Marre, M., M. Lievre, et al. (2004). "Effects of low dose ramipril on cardiovascular and renal outcomes in

patients with type 2 diabetes and raised excretion of urinary albumin: randomised, double blind, placebo

controlled trial (the DIABHYCAR study)." BMJ 328(7438): 495-0.

Marshall, T. (2003). "Coronary heart disease prevention: insights from modelling incremental cost

effectiveness." BMJ 327(7426): 1264-0.

Martin, P. D., P. D. Mitchell and D. W. Schneck (2002). "Pharmacodynamic effects and

pharmacokinetics of a new HMG-CoA reductase inhibitor, rosuvastatin, after morning or evening

administration in healthy volunteers." Br. J. Clin. Pharmacol. 54(5): 472-7.

Martinez, M., A. Agusti, J. M. Arnau, X. Vidal and J. R. Laporte (1998). "Trends of prescribing patterns

for the secondary prevention of myocardial infarction over a 13-year period." Eur. J. Clin. Pharmacol.

54(3): 203-8.

Massachusetts Health Quality Partnerships (1998). Massachusetts Acute Care Hospital, Statewide Patient

Survey Project. http://www.mhqp.org.

McAlister, F. A., L. Taylor, et al. (1999). "The treatment and prevention of coronary heart disease in

Canada: do older patients receive efficacious therapies? The Clinical Quality Improvement Network

(CQIN) Investigators." J. Am. Geriatr. Soc. 47(7): 811-8.

384

McBride, P., H. G. Schrott, M. B. Plane, G. Underbakke and R. L. Brown (1998). "Primary care practice

adherence to National Cholesterol Education Program guidelines for patients with coronary heart

disease." Arch. Intern. Med. 158(11): 1238-44.

McColl, A., H. Smith, P. White and J. Field (1998). "General practitioner's perceptions of the route to

evidence based medicine: a questionnaire survey." BMJ 316(7128): 361-5.

McCormick, D., J. H. Gurwitz, et al. (1999a). "Use of aspirin, beta-blockers, and lipid-lowering

medications before recurrent acute myocardial infarction: missed opportunities for prevention?" Arch.

Intern. Med. 159(6): 561-7.

McCormick, D., J. H. Gurwitz, et al. (1999b). "Differences in discharge medication after acute

myocardial infarction in patients with HMO and fee-for-service medical insurance." J. Gen. Intern. Med.

14(2): 73-81.

McDermott, M. M., J. M. Guralnik, et al. (2003). "Statin use and leg functioning in patients with and

without lower-extremity peripheral arterial disease." Circulation. 107(5): 757-61.

McElduff, P., A. J. Dobson, K. Jamrozik and M. S. Hobbs (2001). "Opportunities for control of coronary

heart disease in Australia." Aust. N. Z. J. Public Health 25(1): 24-30.

Mehta, R. H., S. Das, et al. (2000a). "Quality improvement initiative and its impact on the management of

patients with acute myocardial infarction." Arch. Intern. Med. 160(20): 3057-62.

Mehta, R. H. and K. A. Eagle (1998). "Secondary prevention in acute myocardial infarction." BMJ

316(7134): 838-42.

Mehta, R. H., C. K. Montoye, et al. (2002). "Improving quality of care for acute myocardial infarction:

The Guidelines Applied in Practice (GAP) Initiative." JAMA. 287(10): 1269-76.

Mehta, R. H., T. J. Ruane, P. A. McCargar, K. A. Eagle and E. J. Stalhandske (2000b). "The treatment of

elderly diabetic patients with acute myocardial infarction: insight from Michigan's Cooperative

Cardiovascular Project." Arch. Intern. Med. 160(9): 1301-6.

Mendelson, G. and W. S. Aronow (1997). "Underutilization of beta-blockers in older patients with prior

myocardial infarction or coronary artery disease in an academic, hospital-based geriatrics practice." J.

Am. Geriatr. Soc. 45(11): 1360-1.

Mendelson, G. and W. S. Aronow (1998). "Underutilization of angiotensin-converting enzyme inhibitors

in older patients with Q-wave anterior myocardial infarction in an academic hospital-based geriatrics

practice." J. Am. Geriatr. Soc. 46(6): 751-2.

Miettinen, T. A., K. Pyorala, et al. (1997). "Cholesterol-Lowering Therapy in Women and Elderly

Patients With Myocardial Infarction or Angina Pectoris: Findings From the Scandinavian Simvastatin

Survival Study (4S)." Circulation 96(12): 4211-4218.

Miller, M., R. Byington, D. Hunninghake, B. Pitt and C. D. Furberg (2000). "Sex bias and

underutilization of lipid-lowering therapy in patients with coronary artery disease at academic medical

385

centers in the United States and Canada. Prospective Randomized Evaluation of the Vascular Effects of

Norvasc Trial (PREVENT) Investigators." Arch. Intern. Med. 160(3): 343-7.

Miller, N. H., M. Hill, T. Kottke and I. S. Ockene (1997). "The multilevel compliance challenge:

recommendations for a call to action. A statement for healthcare professionals." Circulation 95(4): 1085-

90.

Miller, N. H. B. S. N. (1997). "Compliance With Treatment Regimes In Chronic Asymptomatic

Diseases." Am. J. Med. 102(2A)): 43-49.

Mitra, S., K. Findley, D. Frohnapple and J. L. Mehta (2002). "Trends in long-term management of

survivors of acute myocardial infarction by cardiologists in a government university-affiliated teaching

hospital." Clin. Cardiol. 25(1): 16-8.

Monane, M., R. L. Bohn, et al. (1996). "Compliance with antihypertensive therapy among elderly

Medicaid enrolees: the roles of age, gender, and race." Am. J. Public Health 86(12): 1805-8.

Monane, M., R. L. Bohn, et al. (1997). "The effects of initial drug choice and comorbidity on

antihypertensive therapy compliance: results from a population-based study in the elderly." Am. J.

Hypertens. 10(7 Pt 1): 697-704.

Mooney, G. and R. Scotton, Eds. (1999). Economics and Australian Health Policy, Allen & Unwin.

Moore, C., J. Wisnivesky, S. Williams and T. McGinn (2003). "Medical Errors Related to Discontinuity

of Care from an Inpatient to an Outpatient Setting." J Gen Intern Med 18(8): 646-651.

Morisky, D. E., L. W. Green and D. M. Levine (1986). "Concurrent and predictive validity of a self-

reported measure of medication adherence." Med. Care 24(1): 67-74.

Mudge, A. M., R. Brockett, K. F. Foxcroft and C. P. Denaro (2001). "Lipid-lowering therapy following

major cardiac events: progress and deficits." Med. J. Aust. 175(3): 138-40.

Muhlestein, J. B., B. D. Horne, et al. (2001). "Usefulness of in-hospital prescription of statin agents after

angiographic diagnosis of coronary artery disease in improving continued compliance and reduced

mortality." Am. J. Cardiol. 87(3): 257-61.

Mukherjee, D., J. Fang, et al. (2004). "Impact of combination evidence-based medical therapy on

mortality in patients with acute coronary syndromes." Circulation. 109(6): 745-9.

Muller, C., H. J. Buttner, J. Petersen and H. Roskamm (2000). "A Randomized Comparison of

Clopidogrel and Aspirin Versus Ticlopidine and Aspirin After the Placement of Coronary-Artery Stents."

Circulation 101(6): 590-593.

Murchie, P., N. C. Campbell, L. D. Ritchie, J. A. Simpson and J. Thain (2003). "Secondary prevention

clinics for coronary heart disease: four year follow up of a randomised controlled trial in primary care."

BMJ. 326(7380): 84.

Naoumova, R. P., S. Dunn, et al. (1997). "Prolonged inhibition of cholesterol synthesis explains the

efficacy of atorvastatin." J. Lipid Res. 38(7): 1496-500.

386

Nathan, A., L. Goodyer, A. Lovejoy and A. Rashid (1999). "'Brown bag' medication reviews as a means

of optimizing patients' use of medication and of identifying potential clinical problems." Fam. Pract.

16(3): 278-82.

National Blood Pressure Advisory Committee (1999). Heart Foundation Guide to Management of

Hypertension for Doctors, National Heart Foundation of Australia.

National Cardiac Rehabilitation Advisory Committee, N. H. F. o. A. (1998). Recommendations for

Cardiac Rehabilitation, National Heart Foundation of Australia.

National Health and Medical Research Council (NHMRC) (1999). A guide to development,

implementation and evaluation of clinical practice guidelines.

http://www.nhmrc.gov.au/publications/synopses/cp30syn.htm.

National Health Priorities and Quality (2002a). Australian Council for Safety and Quality in Health Care.

http://www.health.gov.au/pq/sq/sqcounc.htm, Commonwealth Department of Health and Ageing.

National Health Priorities and Quality (2002b). Clinical Support Systems Program.

http://www.health.gov.au/pq/sq/cssp.htm, Commonwealth Department of Health and Ageing.

National Heart Foundation of Australia (1999). Guide for the use of lipid lowering drugs in adults.

National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand (2003).

Reducing Risk In Heart Disease: Guidelines for preventing cardiovascular events in people with coronary

heart disease, National Heart Foundation.

National Heart Foundation of Australia and T. C. S. o. A. a. N. Zealand (2001). "Lipid management

guidelines--2001." Med. J. Aust. 175(Suppl): S57-S87.

National Institute of Clinical Studies (NICS) (2000). http://www.nicsl.com.au/.

National Prescribing Curriculum (2004). Easy Guide to Good Prescribing.

http://nps.unisa.edu.au/resources/EasyGuide.pdf, National Prescribing Service. 2004.

National Prescribing Service http://www.nps.org.au.

Newby, L. K., R. M. Califf, et al. (2002). "The failure of orally administered glycoprotein IIb/IIa

inhibitors to prevent recurrent cardiac events." Am. J. Med. 112: 647-658.

Nguyen, M., Khang Ngoc, M. Aursnes, PhD, Ivar and M. Kjekshus, PhD, John (1997). "Interaction

Between Enalapril and Aspirin on Mortality After Acute Myocardial Infarction: Subgroup Analysis of the

Cooperative New Scandinavian Enalapril Survival Study II (CONSENSUS II)." Am. J. Cardiol. 79(2):

115-119.

Nicholls, S. J., P. McElduff, et al. (2001). "Underuse of beta-blockers following myocardial infarction: a

tale of two cities." Intern Med J 31(7): 391-6.

Nissen, S. E., E. M. Tuzcu, et al. (2004a). "Effect of antihypertensive agents on cardiovascular events in

patients with coronary disease and normal blood pressure: the CAMELOT study: a randomized controlled

trial." JAMA 292(18): 2217-25.

387

Nissen, S. E., E. M. Tuzcu, et al. (2004b). "Effect of intensive compared with moderate lipid-lowering

therapy on progression of coronary atherosclerosis: a randomized controlled trial." JAMA. 291(9): 1071-

80.

Nissen, S. E., E. M. Tuzcu, et al. (2005). "Statin therapy, LDL cholesterol, C-reactive protein, and

coronary artery disease." N. Engl. J. Med. 352(1): 29-38.

North of England Evidence-based Guidelines Development Project (2001). Prophylaxis for patients who

have experienced a myocardial infarction: drug treatment, cardiac rehabilitation and dietary manipulation,

Centre for Health Services Research, University of Newcastle upon Tyne, Medicines Evaluation Group,

Centre for Health Economics, University of York.

Ockene, I. S., L. L. Hayman, R. C. Pasternak, E. Schron and J. Dunbar-Jacob (2002). "Task force #4 -

Adherence issues and behavior changes: Achieving a long-term solution." J. Am. Coll. Cardiol. 40(4):

630-640.

O'Connor, G. T., H. B. Quinton, et al. (1999). "Geographic variation in the treatment of acute myocardial

infarction: the Cooperative Cardiovascular Project." JAMA 281(7): 627-33.

Oliveria, S. A., P. Lapuerta, et al. (2002). "Physician-related barriers to the effective management of

uncontrolled hypertension." Arch. Intern. Med. 162(4): 413-20.

Packer, M., A. J. Coats, et al. (2001). "Effect of carvedilol on survival in severe chronic heart failure." N.

Engl. J. Med. 344(22): 1651-8.

Packham, C., J. Pearson, J. Robinson and D. Gray (2000). "Use of statins in general practices, 1996-8:

cross sectional study." BMJ 320(7249): 1583-4.

Pantilat, S. Z., P. K. Lindenauer, P. P. Katz and R. M. Wachter (2001). "Primary care physician attitudes

regarding communication with hospitalists." Am. J. Med. 111(9B): 15S-20S.

Pearson, T. A. and W. Feinberg (1997a). "Behavioral issues in the efficacy versus effectiveness of

pharmacologic agents in the prevention of cardiovascular disease." Ann. Behav. Med. 19(3): 230-8.

Pearson, T. A., I. Laurora, H. Chu and S. Kafonek (2000). "The lipid treatment assessment project (L-

TAP): a multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering

therapy and achieving low-density lipoprotein cholesterol goals." Arch. Intern. Med. 160(4): 459-67.

Pearson, T. A., P. E. McBride, N. H. Miller and S. C. Smith (1996). " Organization of preventive

cardiology service. Task Force 8. 27th Bethesda Conference: matching the intensity of risk factor

management with the hazard for coronary disease events." J. Am. Coll. Cardiol. 27(5): 1039-47.

Pearson, T. A. and T. D. Peters (1997b). "The treatment gap in coronary artery disease and heart failure:

community standards and the post-discharge patient." Am. J. Cardiol. 80(8B): 45H-52H.

Pearson, T. A., T. D. Peters and D. Feury (1997c). "Comprehensive Risk Reduction in Coronary Patients:

Attainment of Goals of the AHA Guidelines in U.S. Patients." Circulation 96(8S (Supplement)): 733-I.

Pepine, C. J. (2003). "Optimizing lipid management in patients with acute coronary syndromes." Am. J.

Cardiol. 91: 30B-35B.

388

Pepine, C. J., E. M. Handberg, et al. (2003). "A Calcium Antagonist vs a Non-Calcium Antagonist

Hypertension Treatment Strategy for Patients With Coronary Artery Disease: The International

Verapamil-Trandolapril Study (INVEST): A Randomized Controlled Trial." JAMA 290(21): 2805-2816.

Peters, R. J. G., S. R. Mehta, et al. (2003). "Effects of Aspirin Dose When Used Alone or in Combination

With Clopidogrel in Patients With Acute Coronary Syndromes: Observations From the Clopidogrel in

Unstable angina to prevent Recurrent Events (CURE) Study." Circulation 108(14): 1682-1687.

Peterson, G. M., K. D. Fitzmaurice, et al. (2004). "Impact of pharmacist-conducted home visits on the

outcomes of lipid-lowering drug therapy." J Clin Pharm Ther 29(1): 23-30.

Pettinger, M. B., M. A. Waclawiw, et al. (1999). "Compliance to multiple interventions in a high risk

population." Ann. Epidemiol. 9(7): 408-18.

Pfeffer, M. A. (1998). "ACE inhibitors in acute myocardial infarction: patient selection and timing."

Circulation. 97(22): 2192-4.

Pfeffer, M. A., E. Braunwald, et al. (1992). "Effect of captopril on mortality and morbidity in patients

with left ventricular dysfunction after myocardial infarction. Results of the survival and ventricular

enlargement trial. The SAVE Investigators." N. Engl. J. Med. 327(10): 669-77.

Pfeffer, M. A., J. J. V. McMurray, et al. (2003). "Valsartan, Captopril, or Both in Myocardial Infarction

Complicated by Heart Failure, Left Ventricular Dysfunction, or Both." N. Engl. J. Med. 349(20): 1893-

1906.

Pharmaceutical Benefits Scheme (2004). Schedule of Pharmaceutical Benefits.

http://www1.health.gov.au/pbs/, Australian Government, Department of Health and Aging.

Pharmaceutical Benefits Scheme (2005). Schedule of Pharmaceutical Benefits.

http://www1.health.gov.au/pbs/index.htm, Australian Government, Department of Health and Aging.

Pharmaceutical Health and Rational Use of Medicines Committee (PHARM) and Australian

Pharmaceutical Advisory Council (APAC) (2001). Quality Use of Medicines: A decade of research,

development and service activity. Adelaide, Quality Use of Medicines and Pharmacy Research Centre,

University of South Australia.

Phillips, B. G., J. M. Yim, et al. (1996). "Pharmacologic profile of survivors of acute myocardial

infarction at United States academic hospitals." Am. Heart J. 131(5): 872-8.

Phillips, K. A., M. G. Shlipak, et al. (2000). "Health and economic benefits of increased beta-blocker use

following myocardial infarction." JAMA 284(21): 2748-54.

Pilote, L., M. Abrahamowicz, E. Rodrigues, M. J. Eisenberg and E. Rahme (2004). "Mortality Rates in

Elderly Patients Who Take Different Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial

Infarction: A Class Effect?" Ann Intern Med 141(2): 102-112.

Pilote, L., C. Beck, H. Richard and M. J. Eisenberg (2002). "The effects of cost-sharing on essential drug

prescriptions, utilization of medical care and outcomes after acute myocardial infarction in elderly

patients." CMAJ 167(3): 246-252.

389

Pilote, L., F. Lavoie, V. Ho and M. J. Eisenberg (2000). "Changes in the treatment and outcomes of acute

myocardial infarction in Quebec, 1988-1995." CMAJ 163(1): 31-6.

Poole-Wilson, P. A., K. Swedberg, et al. (2003). "Comparison of carvedilol and metoprolol on clinical

outcomes in patients with chronic heart failure in the Carvedilol or Metoprolol European Trial (COMET)

randomised controlled trial." Lancet 362: 7-13.

Pronovost, P., B. Weast, et al. (2003). "Medication reconciliation: a practical tool to reduce the risk of

medication errors." J. Crit. Care 18(4): 201-5.

Pryce, A. J., H. F. Heatlie and S. R. Chapman (1996). "Buccaling under the pressure: influence of

secondary care establishments on the prescribing of glyceryl trinitrate buccal tablets in primary care."

BMJ 313(7072): 1621-1624.

Putnam, W., F. I. Burge, et al. (2004). "Evidence-based cardiovascular care in the community: a

population-based cross-sectional study." BMC Family Practice. 5(1): 6.

Quality Metric Incorporated and Medical Outcomes Trust (1998). SF-36 Health Survey, Version 2.

Raftery, J. P., G. L. Yao, P. Murchie, N. C. Campbell and L. D. Ritchie (2005). "Cost effectiveness of

nurse led secondary prevention clinics for coronary heart disease in primary care: follow up of a

randomised controlled trial." BMJ 330(7493): 707-711.

Rathore, S. S., R. H. Mehta, Y. Wang, M. J. Radford and H. M. Krumholz (2003). "Effects of age on the

quality of care provided to older patients with acute myocardial infarction." Am. J. Med. 114(4): 307-15.

Raynor, D. K., T. G. Booth and A. Blenkinsopp (1993). "Effects of computer generated reminder charts

on patients' compliance with drug regimens." BMJ 306(6886): 1158-61.

Ridker, P. M., C. P. Cannon, et al. (2005). "C-reactive protein levels and outcomes after statin therapy."

N. Engl. J. Med. 352(1): 20-8.

Rochon, P. A., G. M. Anderson, et al. (1999a). "Use of beta-blocker therapy in older patients after acute

myocardial infarction in Ontario." CMAJ 161(11): 1403-8.

Rochon, P. A. and J. H. Gurwitz (1999b). "Prescribing for seniors. Neither too much nor too little."

JAMA 282(2): 113-5.

Rochon, P. A., K. Sykora, et al. (2004). "Use of Angiotensin-converting Enzyme Inhibitor Therapy and

Dose-related Outcomes in Older Adults with New Heart Failure in the Community." J. Gen. Intern. Med.

19(6): 676-683.

Roe, C. M., B. R. Motheral, F. Teitelbaum and M. W. Rich (1999). "Angiotensin-converting enzyme

inhibitor compliance and dosing among patients with heart failure." Am. Heart J. 138(5 Pt 1): 818-25.

Rogers, W. J., J. G. Canto, et al. (2000). "Temporal trends in the treatment of over 1.5 million patients

with myocardial infarction in the U.S. from 1990 through 1999: The National Registry of Myocardial

Infarction 1, 2 and 3." J. Am. Coll. Cardiol. 36(7): 2056-2063.

390

Roughead, E. E., A. L. Gilbert, J. G. Primrose, K. J. Harvey and L. N. Samson (1999). Report of the

national indicators: Evaluating the Quality Use of Medicines component of Australia's National Medicine

Policy. Canberra, Commonwealth Department of Health and Aged Care.

Rouleau, J. L., L. A. Moye, et al. (1993). "A comparison of management patterns after acute myocardial

infarction in Canada and the United States. The SAVE investigators." N. Engl. J. Med. 328(11): 779-84.

Rozich, J. D., R. J. Howard, et al. (2004). "Standardization as a mechanism to improve safety in health

care." Joint Commission Journal on Quality & Safety 30(1): 5-14.

Rudd, P. (1995). "Clinicians and patients with hypertension: unsettled issues about compliance." Am.

Heart J. 130(3 Pt 1): 572-9.

Rudd, P., S. Ahmed, V. Zachary, C. Barton and D. Bonduelle (1990). "Improved compliance measures:

applications in an ambulatory hypertensive drug trial." Clin. Pharmacol. Ther. 48(6): 676-85.

Rudd, P., J. Ramesh, C. Bryant-Kosling and D. Guerrero (1993). "Gaps in cardiovascular medication

taking: the tip of the iceberg." J. Gen. Intern. Med. 8(12): 659-66.

Rumboldt, Z., I. Bozic and S. Sardelic (1995). "Secondary prevention of myocardial infarction: impact of

clinical trials on clinical practice." Eur. J. Clin. Pharmacol. 48(3-4): 311-2.

Ryan, T. J., E. M. Antman, et al. (1999). "1999 update: ACC/AHA guidelines for the management of

patients with acute myocardial infarction. A report of the American College of Cardiology/American

Heart Association Task Force on Practice Guidelines (Committee on Management of Acute Myocardial

Infarction)." J. Am. Coll. Cardiol. 34(3): 890-911.

Sackett, D. L. and J. C. Snow (1979). The Magnitude of Compliance and Noncompliance. Compliance in

Health Care. R. B. Haynes, D. W. Taylor and D. L. Sackett. Baltimore, John Hopkins University Press:

11-22.

Sackner-Bernstein, J. D. (2003). "New evidence from the CAPRICORN Trial: The role of carvedilol in

high-risk, post-myocardial infarction patients." Reviews in Cardiovascular Medicine 4(suppl 3): S25-S29.

Sacks, F. M., L. A. Moye, et al. (1998). "Relationship between plasma LDL concentrations during

treatment with pravastatin and recurrent coronary events in the Cholesterol and Recurrent Events trial."

Circulation. 97(15): 1446-52.

Sacks, F. M., M. A. Pfeffer, et al. (1996). "The effect of pravastatin on coronary events after myocardial

infarction in patients with average cholesterol levels. Cholesterol and Recurrent Events Trial

investigators." N. Engl. J. Med. 335(14): 1001-9.

Sacks, F. M. M. D., A. M. M. D. Tonkin, et al. (2000). "Effect of Pravastatin on Coronary Disease Events

in Subgroups Defined by Coronary Risk Factors: The Prospective Pravastatin Pooling Project."

Circulation 102(16): 1893-1900.

Salpeter, S., T. Ormiston, E. Salpeter and R. Wood-Baker (2004). Cardioselective beta-blockers for

reversible airway disease. The Cochrane Database of Systematic Reviews 2002. Issue 4. Art. No.:

CD002992. DOI: 10.1002/14651858.CD002992, The Cochrane Library.

391

Sarasin, F. P., M. L. Maschiangelo, et al. (1999). "Successful implementation of guidelines for

encouraging the use of beta blockers in patients after acute myocardial infarction." Am. J. Med. 106(5):

499-505.

Scandinavian Simvastatin Survival Study Group (1994). "Randomised trial of cholesterol lowering in

4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S)." Lancet

344(8934): 1383-9.

Schneeweiss, S., S. B. Soumerai, et al. (2002a). "Impact of reference based pricing for angiotensin-

converting enzyme inhibitors on drug utilization." Can. Med. Assoc. J. 166(6): 737-745.

Schneeweiss, S., A. M. Walker, et al. (2002b). "Outcomes of reference pricing for angiotensin-

converting-enzyme inhibitors." N. Engl. J. Med. 346(11): 822-9.

Schreiber, T. L., A. Elkhatib, C. L. Grines and W. W. O'Neill (1995). "Cardiologist versus internist

management of patients with unstable angina: treatment patterns and outcomes." J. Am. Coll. Cardiol.

26(3): 577-82.

Schrott, H. G., V. Bittner, E. Vittinghoff, D. M. Herrington and S. Hulley (1997). "Adherence to National

Cholesterol Education Program Treatment goals in postmenopausal women with heart disease. The Heart

and Estrogen/Progestin Replacement Study (HERS). The HERS Research Group." JAMA 277(16): 1281-

6.

Schuster, M. A., E. A. McGlynn and R. H. Brook (1998). "How good is the quality of health care in the

United States." Milbank Q. 76(4): 517-563.

Schwartz, G. G., A. G. Olsson, et al. (2001). "Effects of atorvastatin on early recurrent ischemic events in

acute coronary syndromes: the MIRACL study: a randomized controlled trial." Jama. 285(13): 1711-8.

Scott, I. (2002). "Time for a collective approach from medical specialists to clinical governance." Intern

Med J 32: 499-501.

Scott, I., C. Harper, A. Clough and M. West (2000a). "WESTCOP: a disease management approach to

coronary artery disease." Aust. Health Rev. 23(2): 96-112.

Scott, I. A., I. C. Darwin, et al. (2004). "Multisite, quality-improvement collaboration to optimise cardiac

care in Queensland public hospitals." Med. J. Aust. 180: 392-397.

Scott, I. A., C. P. Denaro, et al. (2002). "Quality of care of patients hospitalized with acute coronary

syndromes." Intern Med J 32(11): 502-11.

Scott, I. A., M. L. Eyeson-Annan, S. L. Huxley and M. J. West (2000b). "Optimising care of acute

myocardial infarction: results of a regional quality improvement project." J. Qual. Clin. Pract. 20(1): 12-9.

Scottish Intercollegiate Guidelines Network (2000). Secondary prevention of coronary heart disease

following myocardial infarction. SIGN Publication Number 41.

http://www.sign.ac.uk/guidelines/fulltext/41/index.html.

392

Second International Study of Infarct Survival Collaborative Group (1988). "Randomised trial of

intravenous streptokinase, oral aspirin, both, or neither among 17,187 cases of suspected acute myocardial

infarction: ISIS-2." Lancet 2(8607): 349-60.

Second Joint Task Force of European and other Societies on coronary prevention (1998). "Prevention of

coronary heart disease in clinical practice. Recommendations of the Second Joint Task Force of European

and other Societies on coronary prevention." Eur. Heart J. 19(10): 1434-503.

Seddon, M. E., J. Z. Ayanian, et al. (2001). "Quality of ambulatory care after myocardial infarction

among Medicare patients by type of insurance and region." Am. J. Med. 111(1): 24-32.

Sever, P. S., B. Dahlöf, et al. (2003). "Prevention of coronary and stroke events with atorvastatin in

hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-

Scandinavian Cardiac Outcomes Trial--Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised

controlled trial." Lancet 361: 1149-58.

Shekelle, P. G., M. Eccles, J. M. Grimshaw and S. H. Woolf (2001). "When should clinical guidelines be

updated?" BMJ 323: 155-157.

Sheldon, T. A., G. H. Guyatt and A. Haines (1998). "Getting research findings into practice. When to act

on the evidence." BMJ 317(7151): 139-42.

Shepherd, J., G. J. Blauw, et al. (2002). "Pravastatin in elderly individuals at risk of vascular disease

(PROSPER): a randomised control trial." Lancet 360: 1623-1630.

Shepherd, J., D. Hunninghake, P. Barter, J. M. Mckenney and H. G. Hutchinson (2003). "Guidelines for

lowering lipids to reduce coronary artery disease risk: A comparison of rosuvastatin with atorvastatin,

pravastatin and simvastatin for achieving lipid lowering goals." Am. J. Cardiol. 91(5A): 11C-19C.

Sherbourne, C. D., R. D. Hays, L. Ordway, M. R. DiMatteo and R. L. Kravitz (1992). "Antecedents of

adherence to medical recommendations: results from the Medical Outcomes Study." J. Behav. Med.

15(5): 447-68.

Shlipak, M. G., W. S. Browner, et al. (2001). "Comparison of the effects of angiotensin converting-

enzyme inhibitors and beta blockers on survival in elderly patients with reduced left ventricular function

after myocardial infarction." Am. J. Med. 110(6): 425-33.

Silagy, C. A. (1996). Quality Care In Cardiovascular Disease Prevention At The Primary/Secondary

Interface, Quality Use of Medicine Mapping Project, Department of Health and Aged Care

http://www.qummap.health.gov.au/plist.asp?project=859.

Silagy, C. A., J. J. McNeil, et al. (1994). "The PACE pilot study: 12-month results and implications for

future primary prevention trials in the elderly. (Prevention with low-dose Aspirin of Cardiovascular

disease in the Elderly)." J. Am. Geriatr. Soc. 42(6): 643-7.

Simons, L. A., G. Levis and J. Simons (1996). "Apparent discontinuation rates in patients prescribed

lipid-lowering drugs." Med. J. Aust. 164(4): 208-11.

393

Simons, L. A., J. Simons, P. McManus and J. Dudley (2000). "Discontinuation rates for use of stains are

high." BMJ 321(7268): 1084.

Simpson, E., C. Beck, H. Richard, M. J. Eisenberg and L. Pilote (2003). "Drug prescriptions after acute

myocardial infarction: dosage, compliance, and persistence." Am. Heart J. 145(3): 438-44.

Simpson, R. J., Jr., R. R. Weiser, S. Naylor, C. A. Sueta and A. K. Metts (1997). "Improving care for

unstable angina patients in a multiple hospital project sponsored by a federally designated quality

improvement organization." Am. J. Cardiol. 80(8B): 80H-84H.

Sjahid, S. I., P. D. van der Linden and B. H. Stricker (1998). "Agreement between the pharmacy

medication history and patient interview for cardiovascular drugs: the Rotterdam elderly study." Br. J.

Clin. Pharmacol. 45(6): 591-5.

Skaer, T. L., D. A. Sclar and L. M. Robison (1996). "Noncompliance with antihypertensive therapy.

Economic consequences." Pharmacoeconomics 9(1): 1-4.

Smith, N. L., B. M. Psaty, S. R. Heckbert, R. P. Tracy and E. S. Cornell (1999a). "The reliability of

medication inventory methods compared to serum levels of cardiovascular drugs in the elderly." J. Clin.

Epidemiol. 52(2): 143-6.

Smith, N. L., G. E. Reiber, et al. (1999b). "Trends in the post-hospitalization medical treatment of

unstable angina pectoris: 1990 to 1995." Am. J. Cardiol. 84(6): 632-8.

Smith, S. C., Jr, S. N. Blair, et al. (2001a). "AHA/ACC Guidelines for Preventing Heart Attack and Death

in Patients With Atherosclerotic Cardiovascular Disease: 2001 Update: A Statement for Healthcare

Professionals From the American Heart Association and the American College of Cardiology."

Circulation 104(13): 1577-1579.

Smith, S. C., Jr. (1996). "Risk-reduction therapy: the challenge to change. Presented at the 68th scientific

sessions of the American Heart Association November 13, 1995 Anaheim, California." Circulation

93(12): 2205-11.

Smith, S. C., Jr., J. T. Dove, et al. (2001b). "ACC/AHA guidelines of percutaneous coronary

interventions (revision of the 1993 PTCA guidelines)--executive summary. A report of the American

College of Cardiology/American Heart Association Task Force on Practice Guidelines (committee to

revise the 1993 guidelines for percutaneous transluminal coronary angioplasty)." J. Am. Coll. Cardiol.

37(8): 2215-39.

Soumerai, S., D. Ross-Degnan, J. Avorn, T. McLaughlin and I. Choodnovskiy (1991). "Effects of

Medicaid drug-payment limits on admission to hospitals and nursing homes." N Engl J Med 325(15):

1072-1077.

Soumerai, S. B., T. J. McLaughlin, et al. (1998). "Effect of local medical opinion leaders on quality of

care for acute myocardial infarction: a randomized controlled trial." JAMA 279(17): 1358-63.

Soumerai, S. B., T. J. McLaughlin, D. Ross-Degnan, C. S. Casteris and P. Bollini (1994). "Effects of

Limiting Medicaid Drug-Reimbursement Benefits on the Use of Psychotropic Agents and Acute Mental

Health Services by Patients with Schizophrenia." N Engl J Med 331(10): 650-655.

394

Soumerai, S. B., T. J. McLaughlin, et al. (1997). "Adverse outcomes of underuse of beta-blockers in

elderly survivors of acute myocardial infarction." JAMA 277(2): 115-21.

Spencer, F., G. Scleparis, et al. (2001). "Decade-long trends (1986 to 1997) in the medical treatment of

patients with acute myocardial infarction: A community-wide perspective." Am. Heart J. 142(4): 594-

603.

Spencer, F. A., S. Jabbour, et al. (2003). "Two-decade-long trends (1975-1997) in the incidence,

hospitalization, and long-term death rates associated with complete heart block complicating acute

myocardial infarction: a community-wide perspective." Am. Heart J. 145(3): 500-7.

Spertus, J. A. (1993). Scoring the Seattle Angina Questionnaire. Medical Outcomes Trust. Massachusetts.

Spertus, J. A., J. A. Winder, et al. (1995). "Development and evaluation of the Seattle Angina

Questionnaire: A new functional status Measure for Coronary Heart Disease." J. Am. Coll. Cardiol.

25(2): 333-41.

Stafford, R. S. (2000). "Aspirin use is low among United States outpatients with coronary artery disease."

Circulation 101(10): 1097-101.

Stamler, J., D. Wentworth and J. D. Neaton (1986). "Is relationship between serum cholesterol and risk of

premature death from coronary heart disease continuous and graded? Findings in 356,222 primary

screenees of the Multiple Risk Factor Intervention Trial (MRFIT)." JAMA. 256(20): 2823-8.

Steele, D. J., T. C. Jackson and M. C. Gutmann (1990). "Have you been taking your pills? The adherence-

monitoring sequence in the medical interview." Journal of Family Practice. 30(3): 294-9.

Steg, P. G., R. J. Goldberg, et al. (2002a). "Baseline characteristics, management practices, and in-

hospital outcomes of patients hospitalized with acute coronary syndromes in the Global Registry of Acute

Coronary Events (GRACE)." Am. J. Cardiol. 90(4): 358-363.

Steg, P. G., B. Iung, et al. (2002b). "Impact of availability and use of coronary interventions on the

prescription of aspirin and lipid lowering treatment after acute coronary syndromes." Heart 88(1): 20-24.

Steiner, J. F. and M. A. Earnest (2000). "The language of medication-taking." Ann. Intern. Med. 132(11):

926-30.

Steinhubl, S. R., P. B. Berger, et al. (2002). "Early and sustained dual oral antiplatelet therapy following

percutaneous coronary intervention: a randomized controlled trial." JAMA. 288(19): 2411-20.

Stenestrand, U. and L. Wallentin (2001). "Early statin treatment following myocardial infarction and 1-

year survival." JAMA 285(4): 430-436.

Stephenson, B. J., B. H. Rowe, R. B. Haynes, W. M. Macharia and G. Leon (1993). "Is this patient taking

the treatment as prescribed?" JAMA 269(21): 2779-81.

Stewart, S., A. J. Vandenbroek, S. Pearson and J. D. Horowitz (1999). "Prolonged beneficial effects of a

home-based intervention on unplanned readmissions and mortality among patients with congestive heart

failure." Arch. Intern. Med. 159(3): 257-61.

395

Straka, R. J., J. T. Fish, S. R. Benson and J. T. Suh (1996). "Magnitude and nature of noncompliance with

treatment using isosorbide dinitrate in patients with ischemic heart disease." J. Clin. Pharmacol. 36(7):

587-94.

Straka, R. J., J. T. Fish, S. R. Benson and J. T. Suh (1997). "Patient self-reporting of compliance does not

correspond with electronic monitoring: an evaluation using isosorbide dinitrate as a model drug."

Pharmacotherapy 17(1): 126-32.

Strandberg, T. E., H. Vanhanen and M. J. Tikkanen (1999). "Frequency of lipid-lowering therapy after a

coronary event in Helsinki, Finland." Am. J. Cardiol. 84(1): 95, A8.

Stuart, B. and C. Zacker (1999). "Who bears the burden of Medicaid drug copayment policies?" Health

Aff. (Millwood). 18(2): 201-212.

Sueta, C. A., M. Chowdhury, et al. (1999). "Analysis of the degree of undertreatment of hyperlipidemia

and congestive heart failure secondary to coronary artery disease." Am. J. Cardiol. 83(9): 1303-7.

Sung, J. C., M. B. Nichol, et al. (1998). "Factors affecting patient compliance with antihyperlipidemic

medications in an HMO population." Am. J. Manag. Care 4(10): 1421-30.

Svarstad, B. L., B. A. Chewning, B. L. Sleath and C. Claesson (1999). "The brief medication

questionnaire: A tool for screening patient adherence and barriers to adherence." Patient Educ. Couns.

37(2): 113-124.

Tamblyn, R., R. Laprise, et al. (2001). "Adverse events associated with prescription drug cost-sharing

among poor and elderly persons." JAMA 285(4): 421-9.

Teo, K. K., S. Yusuf, et al. (2002). "Effects of long-term treatment with angiotensin-converting-enzyme

inhibitors in the presence or absence of aspirin: a systematic review." Lancet. 360(9339): 1037-43.

The CAPRICORN Investigators (2001). "Effect of carvedilol on outcome after myocardial infarction in

patients with left-ventricular dysfunction: the CAPRICORN randomised trial." Lancet 357: 1385-90.

The Clopidogrel in Unstable Angina to Prevent Recurrent Events (CURE) Trial Investigators (2001).

"Effects of Clopidogrel in Addition to Aspirin in Patients with Acute Coronary Syndromes without ST-

Segment Elevation." N Engl J Med 345(7): 494-502.

The EURopean trial On reduction of cardiac events with Perindopril in stable coronary Artery disease

Investigators (2003). "Efficacy of perindopril in reduction of cardiovascular events among patients with

stable coronary artery disease: randomised, double-blind, placebo-controlled, multicentre trial (the

EUROPA study)." Lancet 362: 782-788.

The Heart Outcomes Prevention Evaluation Study Investigators (2000). "Effects of an angiotensin-

converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients." N. Engl. J. Med.

342(3): 145-53.

The National Registry of Myocardial Infarction (2004). http://www.nrmi.org.

The Norwegian Multicentre Study Group (1981). "Timolol-induced reduction in mortality and

reinfarction in patients surviving acute myocardial infarction." N. Engl. J. Med. 304: 801-7.

396

The SOLVD Investigators (1991). "Effect of enalapril on survival in patients with reduced left ventricular

ejection fraction and congestive heart failure." N. Engl. J. Med. 325: 293-302.

The West of Scotland Coronary Prevention Study (1997). "Compliance and adverse event withdrawal:

their impact on the West of Scotland Coronary Prevention Study." Eur. Heart J. 18(11): 1718-24.

Thompson, P. L. (2001a). "Clinical relevance of statins: instituting treatment early in acute coronary

syndrome patients." Atherosclerosis Supplements. 2(1): 15-9.

Thompson, P. L. (2001b). "Time to move beyond clinical practice guidelines?" Med. J. Aust. 174: 211-

212.

Thompson, P. L., I. Meredith, et al. (2004). "Effect of pravastatin compared with placebo initiated within

24 hours of onset of acute myocardial infarction or unstable angina: the Pravastatin in Acute Coronary

Treatment (PACT) trial." Am. Heart J. 148(1).

Thompson, P. L., R. W. Parsons, et al. (1992). "Changing patterns of medical treatment in acute

myocardial infarction. Observations from the Perth MONICA Project 1984-1990." Med. J. Aust. 157(2):

87-92.

Tomlin, Z., C. Humphrey and S. Rogers (1999). "General practitioners' perceptions of effective health

care." BMJ 318(7197): 1532-1535.

Toop, L. and D. Richards (2001). "Preventing cardiovascular disease in primary care." BMJ 323(7307):

246-7.

Topol, E. J., Ed. (2001). Acute Coronary Syndromes. New York, Marcel Dekker Inc.

Topol, E. J. (2004). "Intensive statin therapy--a sea change in cardiovascular prevention." N. Engl. J.

Med. 350(15): 1562-4.

Tran, C. T., A. Laupacis, M. M. Mamdani and J. V. Tu (2004a). "Effect of age on the use of evidence-

based therapies for acute myocardial infarction." Am. Heart J. 148(5): 834-41.

Tran, H. and S. S. Anand (2004b). "Oral Antiplatelet Therapy in Cerebrovascular Disease, Coronary

Artery Disease and Peripheral Vascular Disease." JAMA 292(15): 1867-74.

Tsuyuki, R. T., J. A. Johnson, et al. (2002). "A randomized trial of the effect of community pharmacist

intervention on cholesterol risk management: the Study of Cardiovascular Risk Intervention by

Pharmacists (SCRIP)." Archives of Internal Medicine. 162(10): 1149-55.

Tu, K., M. M. Mamdani, et al. (2003). "The striking effect of the Heart Outcomes Prevention Evaluation

(HOPE) on ramipril prescribing in Ontario." CMAJ 168(5): 553-557.

Tunstall-Pedoe, H., K. Kuulasmaa, et al. (1999). "Contribution of trends in survival and coronary-event

rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project

populations. Monitoring trends and determinants in cardiovascular disease." Lancet. 353(9164): 1547-57.

U.S.Food and Drug Administration (2001). Bayer voluntarily withdraws Baycol.

http://www.fda.gov/bbs/topics/ANSWERS/2001/ANS01095.html.

397

Ubbink, D. T., E. E. Verhaar, H. K. Lie and D. A. Legemate (2003). "Effect of beta-blockers on

peripheral skin microcirculation in hypertension and peripheral vascular disease." J. Vasc. Surg. 38(3):

535-40.

Underwood, P. and P. Beck (2002). "Secondary prevention following myocardial infarction: evidence

from an audit in South Wales that the National Service Framework for coronary heart disease does not

address all the issues." Qual Saf Health Care 11(3): 230-232.

Vale, M. J., M. V. Jelinek, J. D. Best and C. s. g. C. p. o. A. C. Health (2002a). "How many patients with

coronary heart disease are not achieving their risk-factor targets? Experience in Victoria 1996-1998

versus 1999-2000." Med. J. Aust. 176(5): 211-5.

Vale, M. J., M. V. Jelinek, J. D. Best and J. D. Santamaria (2002b). "Coaching patients with coronary

heart disease to achieve the target cholesterol: a method to bridge the gap between evidence-based

medicine and the "real world"--randomized controlled trial." J. Clin. Epidemiol. 55(3): 245-52.

Van de Werf, F., D. Ardissino, et al. (2003). "Management of acute myocardial infarction in patients

presenting with ST-segment elevation. The Task Force on the Management of Acute Myocardial

Infarction of the European Society of Cardiology." Eur. Heart J. 24(1): 28-66.

van Es, R. F., J. J. C. Jonker, et al. (2002). "Aspirin and coumadin after acute coronary syndromes (the

ASPECT-2 study): a randomised controlled trial." Lancet 360: 109-113.

van Walraven, C., R. Seth, P. C. Austin and A. Laupacis (2002). "Effect of discharge summary

availability during post-discharge visits on hospital readmission." J. Gen. Intern. Med. 17(3): 186-92.

Vaughan, C. J., A. M. Gotto and C. T. Basson (2000). "The evolving role of statins in the management of

atherosclerosis." J. Am. Coll. Cardiol. 35(1): 1-10.

Veninga, C. C., C. S. Lundborg, et al. (2000). "Treatment of uncomplicated urinary tract infections:

exploring differences in adherence to guidelines between three European countries. Drug Education

Project Group." Ann. Pharmacother. 34(1): 19-26.

Venturini, F., M. Romero and G. Tognoni (1999). Patterns of practice for acute myocardial infarction in a

population from ten countries. Eur. J. Clin. Pharmacol. 54: 877-86.

Viskin, S., I. Kitzis, et al. (1995). "Treatment with beta-adrenergic blocking agents after myocardial

infarction: from randomized trials to clinical practice." J. Am. Coll. Cardiol. 25(6): 1327-32.

Wallace, A., D. Chinn and G. Rubin (2003). "Taking Simvastatin in the morning compared with the

evening: randomised control trial." BMJ 327: 788.

Wallentin, L., R. G. Wilcox, et al. (2003). "Oral ximelagatran for secondary prophylaxis after myocardial

infarction: the ESTEEM randomised controlled trial." Lancet 362: 789-97.

Wang, T. J. and R. S. Stafford (1998). "National patterns and predictors of beta-blocker use in patients

with coronary artery disease." Arch. Intern. Med. 158(17): 1901-6.

Wang, T. J., R. S. Stafford, J. C. Ausiello and C. E. Chaisson (2001). "Randomized clinical trials and

recent patterns in the use of statins." Am. Heart J. 141(6): 957-63.

398

Waters, A. -M., T. Armstrong and S. Senses-Ferrari (1998). Medical care of cardiovascular disease in

Australia. (Cardiovascular Disease Series no. 7). Canberra, Australian Institute of Health and Welfare.

Wattanasuwan, N., I. A. Khan, R. M. Gowda, B. C. Vasavada and T. J. Sacchi (2001). "Effect of acute

myocardial infarction on cholesterol ratios." Chest 120: 1196-1199.

West of Scotland Coronary Prevention Study Group (1997). "Compliance and adverse event withdrawal:

their impact on the West of Scotland Coronary Prevention Study." Eur. Heart J. 18(11): 1718-24.

Whincup, P. H., J. R. Emberson, et al. (2002). "Low prevalence of lipid lowering drug use in older men

with established coronary heart disease." Heart. 88(1): 25-9.

White, H. D. (2003). "Should all patients with coronary disease receive angiotensin-converting-enzyme

inhibitors?” Lancet 362: 755-756.

White, H. D. and J. T. Willerson (2004). "We Must Use the Knowledge That We Have to Treat Patients

With Acute Coronary Syndromes." Circulation 109(6): 698-700.

Whitford, D. L. and A. J. Southern (1994). "Audit of secondary prophylaxis after myocardial infarction."

BMJ 309(6964): 1268-9.

Wiklund, O., J. Hulthe, et al. (2002). "Effect of Controlled Release/Extended Release Metoprolol on

Carotid Intima-Media Thickness in Patients With Hypercholesterolemia: A 3-Year Randomized Study."

Stroke 33(2): 572-577.

Wilcox, R. G., J. M. Roland, D. C. Banks, J. R. Hampton and J. R. Mitchell (1980). "Randomised trial

comparing propranolol with atenolol in immediate treatment of suspected myocardial infarction." BMJ

280: 885-8.

Williamson, D. J., P. Whipple, et al. (2004). Medication management of patients in an Acute Assessment

Unit. National Medicines Symposium, Brisbane.

Willich, S. N., J. Muller-Nordhorn, et al. (2001). "Cardiac risk factors, medication, and recurrent clinical

events after acute coronary disease; a prospective cohort study." Eur. Heart J. 22(4): 307-13.

Willison, D. J., S. B. Soumerai and R. H. Palmer (2000). "Association of physician and hospital volume

with use of aspirin and reperfusion therapy in acute myocardial infarction." Med. Care 38(11): 1092-102.

Wilson, S., W. Ruscoe, M. Chapman and R. Miller (2001). "General practitioner-hospital

communications: a review of discharge summaries." J. Qual. Clin. Pract. 21(4): 104-8.

Woolf, S. H., R. P. Grol, A. Hutchinson, M. Eccles and J. M. Grimshaw (1999). "Potential benefits,

limitations, and harms of clinical guidelines." BMJ 318: 527-530.

Wright, E. C. (1993). "Non-compliance--or how many aunts has Matilda?" Lancet 342(8876): 909-13.

Yancy, C. W. (2001). "Clinical trials of beta-blockers in heart failure: a class review." Am. J. Med.

110(Suppl 5A): 7S-10S.

399

Yarzebski, J., C. F. Bujor, et al. (2002). "A community-wide survey of physician practices and attitudes

toward cholesterol management in patients with recent acute myocardial infarction." Arch. Intern. Med.

162(7): 797-804.

Yarzebski, J., F. Spencer, R. J. Goldberg, D. Lessard and J. M. Gore (2001). "Temporal trends (1986-

1997) in cholesterol level assessment and management practices in patients with acute myocardial

infarction: a population-based perspective." Arch. Intern. Med. 161(12): 1521-8.

Yim, J. M., T. J. Hoon, et al. (1995). "Angiotensin-converting enzyme inhibitor use in survivors of acute

myocardial infarction." Am. J. Cardiol. 75(16): 1184-6.

Young, J. M., P. Glasziou and J. E. Ward (2002). "General practitioners' self ratings of skills in evidence

based medicine: validation study." BMJ 324(7343): 950-951.

Yusuf, S. (2002). "Two decades progress in preventing vascular disease." Lancet 360: 2-3.

Yusuf, S., R. Lopez and P. Sleight (1979). "Effect of atenolol on recovery of the electrocardiographic

signs of myocardial infarction." Lancet. 2(8148): 868-9.

Yusuf, S., S. R. Mehta, et al. (2003). "Early and late effects of clopidogrel in patients with acute coronary

syndromes." Circulation. 107(7): 966-72.

Yusuf, S., R. Peto, J. Lewis, R. Collins and P. Sleight (1985). "Beta blockade during and after myocardial

infarction: an overview of the randomized trials." Prog. Cardiovasc. Dis. 27(5): 335-71.

Yusuf, S., P. Sleight, et al. (2000). "Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on

cardiovascular events in high-risk patients. The Heart Outcomes Prevention Evaluation Study

Investigators." N. Engl. J. Med. 342(3): 145-53.

Zuanetti, G., R. Latini, et al. (1996). "Trends and determinants of calcium antagonist usage after acute

myocardial infarction (the GISSI experience)." Am. J. Cardiol. 78(2): 153-7.

Zuanetti, G., R. Latini, A. P. Maggioni, L. Santoro and M. G. Franzosi (1993). "Influence of diabetes on

mortality in acute myocardial infarction: data from the GISSI-2 study." J. Am. Coll. Cardiol. 22(7): 1788-

94.

Zuckerman, I. H., S. R. Weiss, et al. (2004). "Impact of an Educational Intervention for Secondary

Prevention of Myocardial Infarction on Medicaid Drug Use and Cost." Am. J. Manag. Care 10(7): 593-

500.

Appendices

Appendix A Medical record review data set

Appendix B Documentation for 3 month (early) follow-up

Appendix C Documentation for 12 month (late) follow-up

Appendix D Patient interview

Appendix E Cardiology staff interviews

Appendix A

Medical record review data set

Patient data at the time of admission

Demographic data Gender

Date of Birth

Date of admission

Insurance

Public patient

Private patient (including Veterans affairs)

Medical History

Cardiac history Angina

Myocardial infarction (MI)

Congestive heart failure (CHF)

Percutaneous coronary intervention (PCI)

Coronary artery bypass graft (CABG)

Catheterisation

Stroke or Transient ischaemic attack

Diabetes: insulin or non insulin dependent

Hypertension

Hyperlipidemia

Smoking: current or ex-smoker

Family history of coronary heart disease (CHD)

Peripheral vascular disease

Drugs prior to admission All drugs recorded at the time of admission

Hospital episode

Clinical presentation Date

Chest pain

Hours since onset of chest pain

Heart rate (HR), first and last recorded

Systolic blood pressure (SBP),first and last recorded

Diastolic blood pressure (DBP), first and last recorded

ECG changes

Type

Changes recorded by doctors in medical notes

ST segment elevation

ST segment depression

T wave inversion

Q wave

Left Bundle Branch Block

Location of ECG changes Inferior

Anterior

Lateral

Posterior

Type of MI Q-wave/Non-Q-wave (early)

ST-elevation (STEMI)/Non-ST-elevation MI (NSTEMI)

Emergency reperfusion Thrombolytic therapy

Primary PCI

Complications

Reinfarction

Recurrent chest pain

Stroke

TIA

CHF

Pulmonary oedema

Cardiogenic shock

Sinus bradycardia

PR interval >0.2

2nd degree heart block

Complete Atrioventricular block

Atrial Arrhythmia

Ventricular arrhythmia

Hypotension

Laboratory tests

Peak Creatine Kinase (CK) (U/L)

Troponin T or Troponin I (µg/L)

Total cholesterol (mmol/L)

LDL-cholesterol (mmol/L)

HDL-cholesterol (mmol/L)

Triglycerides (mmol/L)

Serum glucose (mmol/L)

Haemoglobin A1c (HbA1c) (%)

Glucose Tolerance Test (mmol/L)

Serum creatinine (µmol/L)

Urea (mmol/L)

Haemoglobin (g/L)/ Hematocrit (%)

Platelets ( 109/L)

Cardiac tests and procedures Exercise Stress test

Radionuclide scans

Echocardiography

Left Ventricular Ejection Fraction

Catheterisation/Angiography

PCI

Stent insertion

CABG

Pacemaker temporary or permanent

Risk factors recorded Hypertension

Hyperlipidemia

Diabetes

Smoking

Body weight

Physical inactivity

Hospital discharge Date

Discharging ward

Discharging consultant

Appendix B

Documentation for 3 month (early) follow-up

Documentation for patients

Letter

Information Sheet with copy of Consent Form

Consent Form

Questionnaire

Documentation for doctors

Letter

Questionnaire

Reminder letter

LETTERHEAD

Department of Public Health, University of Western Australia, 35 Stirling Hwy, Crawley 6009

Ref Number: <RefID> <Title> <Fname> <Sname> <Street> <Suburb> WA <PCODE>

Dear <Title> <Sname>

People who have had a heart attack can sometimes develop further heart problems. In addition to lifestyle factors, a number of medications have been shown to reduce the risk of further problems in people with heart disease.

As well as providing the best possible medical care immediately after a heart attack, the hospital also has a role in helping patients to understand, and make, the changes that will help keep them as healthy as possible. These changes include taking medications as well as changes in lifestyle.

< Hospital> and the Department of Public Health at The University of Western Australia are conducting a study to find out what medications are being prescribed and taken to help reduce the chances of further heart problems.

I am writing to ask you to be a part of this important study and to help us improve the treatment available to patients with heart disease like yourself.

We would like to find out about the medications you are using, any problems that you have with the medications and the reasons why you might have stopped taking some medications. We would also like to get some details about the treatment you received while you were in hospital, any changes to your lifestyle and how your health is now.

The study is funded by the Quality Use of Medicines Program provided by the Commonwealth Department of Health and Aged Care and has the approval of the Ethics Committee at Sir Charles Gairdner Hospital.

Enclosed is an Information Sheet giving more details about the study and a Questionnaire for you to complete. I will call you in about a week to answer any of your questions about the study, or if you prefer, you can call me on 9380 1221.

Your sincerely

Margherita Veroni Study Coordinator <Date>

The < Hospital >Human Research Ethics Committee has given approval for the conduct of the project. If you have any concerns regarding the ethical issues you can contact the Secretary of the <Hospital> Ethics Committee (telephone number <ethics phone>). All study participants will be provided with a copy of the Information Sheet and Consent Form for their personal records. 8 March 2000

Information Sheet

The Use Of Medications In The Continuing Care of Coronary Heart Disease

Investigators Clinical Professor Peter Thompson. Department of Cardiovascular Medicine and University Department of Medicine, Sir Charles Gairdner Hospital Professor D’Arcy Holman. Department of Public Health, The University of Western Australia

What the study is about The purpose of this study is to find out if all patients who have had a heart attack receive the best treatment to help them reduce the risk of further heart problems. We would also like to find out about any problems patients have in taking these medications.

The study will collect information from hospital medical records, questionnaires completed by patients, a home visit and, a questionnaire sent to the doctor with the patient’s consent.

What the study involves for you There are three things that we would like you to do.

First we would like you to complete the enclosed questionnaire. It will take about 40 minutes.

Second we would be grateful if you would receive a home visit from a member of the research team. You will receive a phone call in about a week’s time to see if you are willing to receive a home visit. Arrangements will then be made to visit you. The purpose of the home visit is to get more information about your medications, to answer any questions you might have about to the questionnaire or the study and to collect the completed questionnaire. This home visit should not take more than 30 minutes.

Finally, we would like your permission to contact your General Practitioner for some additional information about your medications. If you do not want us to contact your doctor you can still participate in the rest of the study.

If you prefer not to receive the home visit then you can still participate by completing the questionnaire (and the consent form if you do not mind us contacting your doctor about medications) and returning it in the reply paid envelope.

If you have any questions or concerns please call the study coordinator Margherita Veroni on 9380 1221.

Confidentiality Your name will not be attached to any information about you. We will identify you only by a code. The data will be stored on password protected computers and forms kept in locked filing cabinets. Data will be stored for no longer than five years. Your name will not appear in any report.

Your participation is voluntary and whether or not you take part will not directly affect your health care. We would be very grateful if your were able to help us improve our health services.

This study will be carried out in a manner conforming to the principles set out by the National Health and Medical Research Council.

THIS IS A COPY FOR YOU TO KEEP

Consent to contact Doctor

The Use Of Medications In The Secondary Prevention Of Coronary Heart Disease

Researchers Clinical Professor Peter Thompson. Department of Cardiovascular Medicine and University Department of Medicine, Sir Charles Gairdner Hospital Professor D’Arcy Holman. Department of Public Health, The University of Western Australia

In addition to the information that we need from you we would like your permission to contact your doctor for some additional information about your treatment. As researchers we must follow strict rules and procedures to ensure and maintain your confidentiality. Your name will not be attached to any information about you. We will identify you only by a code. The data will be stored on password protected computers and forms kept in locked filing cabinets. Your name will not be included in any report. If you have any questions or concerns about these issues please contact the study coordinator Margherita Veroni on 9380 1221. I …………………………………………………………………………………[name]

of……………………………………………………………………………[address]

give permission for the researchers to contact my doctor for further information regarding my treatment. Doctor’s details Name…………………………………………………………………………………

Address………………………………………………………………………………

Phone…………………………………………………………………………………

This questionnaire includes the SF-36 (Q 58– Q 68) and the Seattle Angina Questionnaire Copyright © John Spertus (Q 72– Q 82).

Ref Number:

The use of medications in the continuing care of coronary heart disease

Patient questionnaire

This questionnaire is about your admission to hospital on . It collects information on the care you received in hospital, the medical followup you have had since leaving hospital and how you are feeling now. This questionnaire is voluntary and whether or not you complete the questionnaire will not directly affect your health care. We would be grateful if you are able to help us improve health services by answering these questions. A number of the questions ask you to “Tick all that apply”. Please tick only those answers that you are certain applies to you. Please write today’s date here:

1

SECTION 1 The following questions are about your health before your hospital admission. Q 1. Before this hospital admission had you ever been told you had high blood

pressure? Tick one.

Yes r No r Q 2. Before this hospital admission had you ever been told you had high cholesterol? Tick one.

Yes r No r Q 3. Before this hospital admission had you ever been told you had high blood sugar?

Tick one.

Yes r No r Q 4. Before this hospital admission had you ever been told you had heart problems?

Tick one.

Yes r No r

Q 5. Before this hospital admission had you ever had any of the following? Tick all that apply.

Cardiac catheter, dye injected into the heart to see arteries r Angioplasty (PTCA), a balloon used to unblock arteries in the heart r Coronary artery bypass graft surgery (CABG) r None of these r SECTION 2 This section deals with the care you received during this hospital stay. Q 6. During this hospital stay what heart problem were you treated for?

Tick all that apply.

Heart attack r Angina or chest pain r Other (please explain)_________________________________r Q 7. During this hospital stay did you have any of the following procedures?

Tick all that apply.

Cardiac catheter, dye injected into the heart to see arteries r Angioplasty (PTCA), a balloon used to unblock arteries in the heart r Coronary artery bypass graft surgery (CABG) r None of these r

2

The following questions are about the advice and help you were given to make changes in risk factors for heart disease while you were in hospital.

Q 8. At the time of this hospital admission were you a smoker? Tick one.

Yes r No r áGo to Q 11

Q 9. While you were in hospital did anyone talk to you about the need to stop smoking? Tick all that apply.

No r áGo to Q 11 Doctor r Nurse r

Ward pharmacist r Other health professional r Yes not sure who r

Q 10. While you were in hospital what assistance were you given to stop smoking? Tick all that apply.

None r Outpatient followup support r Nicotine replacement r Reading material r

QUITline phone number r

Other (explain)________________________ r

Q 11. At the time of this hospital admission were you taking any medication to lower your cholesterol? Tick one.

Yes r No r

Q 12. While you were in hospital did any one talk to you about why it is good to have low cholesterol? Tick all that apply.



Q 13. While you were in hospital what assistance were you given to lower your cholesterol? Tick all that apply.

None r

Medication r Diet advice r

Exercise advice r

Written information r

Other (explain)________________________ r

3

Q 14. At the time of this hospital admission were you taking any medication to lower your blood pressure? Tick one.

Yes r

No r

Q 15. While you were in hospital did any one talk to you about why it is a good to lower your blood pressure? Tick all that apply.

No r áGo to Q 17

Doctor r Nurse r


Q 16. While you were in hospital what assistance were you given to lower your blood pressure? Tick all that apply.

None r

Medication r

Diet advice r

Exercise advice r

Stress management r

Blood pressure monitoring r

Other (explain)________________________ r

Q 17 At the time of this hospital admission were you using any medication or insulin to control your blood sugar? Tick one.

Yes r

No r

Q 18. While you were in hospital did anyone talk to you about why it is important to control blood sugar levels? Tick all that apply.

No r áGo to Q 20

Doctor r Nurse r


Q 19. While you were in hospital what assistance were you given to help control your blood sugar levels or diabetes? Tick all that apply.

None r

Told to see my doctor for further tests r

Referred to specialist r

Referred to diabetic educator r Medication r

Diet advice r

Exercise advice r

Advice on monitoring blood sugars r

Other (explain)________________________ r

4

Q 20. At the time of this hospital admission did you think you were overweight? Tick one.

Yes r

No r

Q 21. While you were in hospital did any one talk to you about your weight? Tick all that apply.



Q 22. While you were in hospital what assistance were you given to lower your weight? Tick all that apply.

None r

Outpatient appointment with Dietician r

Diet advice r

Exercise program r

Exercise advice r

Written information r

Other (explain)________________________ r

Q 23. At the time of this hospital admission did you think you were as physically active as you should be? Tick one

Yes r

No r

Q 24. While you were in hospital did any one talk to you about your level of physical activity? Tick all that apply.

No r áGo to Q 26

Doctor r Nurse r


Q 25. While you were in hospital what assistance were you given to help increase your usual level of physical activity level? Tick all that apply

None r

Exercise program r

Advice on exercise r

Written material r

Other (explain)________________________ r

5

These questions are about information that was provided and arrangements that were made at the time you left hospital. Q 26.Did anyone talk to you about the new medicines you would be taking at home? Tick all that apply.

No, I had no new medicines r áGo to Q 28 No, I had new medicines but no one talked to me about them r áGo to Q 28 Doctor r Nurse r

Ward pharmacist r Other health professional r Yes not sure who r Q 27.What were you told about your new medicines? Tick all that apply. The purpose of the medicines r When to take the medicines r

Ways to remember to take the medicines r Possible side effects of the medicines r No information given r Q 28.Please list all tablets and medicines you were taking at the time you left hospital.

6

Q 29. At the time you left hospital were you referred to any special programs? Tick all that apply.

Cardiac Rehabilitation Program r

Exercise Program r

Other (please explain)____________________________________r

None r Q 30. At the time you left hospital were you given any appointments to see any of the

following as an outpatient? Tick all that apply.

Occupational Therapist r

Physiotherapist r

Social Worker r

Dietician r

Cardiac Rehabilitation Nurse r

None r Q 31. At the time you left hospital what arrangements were made for your followup

care? Tick all that apply.

Appointment for further tests or procedures r Appointment to see cardiologist in private rooms r Appointment made for outpatients’ clinic r I was told to see my General Practitioner r

Other (please explain)________________________ r Q 32. What written information were you given while you were in hospital or when you

left hospital? Tick all that apply.

A list of all the medicines I had to take at home r Information about risk factors and changes to make r Information about medications and how they work r Details about a support group r A contact phone number for any problems or queries r

Other (please explain)________________________ r Q 33. Were you given a copy of your discharge letter? Tick one.

Yes r

No, I was told a letter would be sent to my doctor r

No, no letter was mentioned r

7

Q 34. The following questions are about how you felt about the care you received in hospital. Tick one on each line

Yes,

definitely Yes,

somewhat No No

opinion

Did you get enough information about your condition and treatment while you were in hospital?

r r r r

When you had questions about your condition and treatment did you get answers you could understand?

r r r r

Did you get enough encouragement to ask the questions you wanted to ask about your condition and treatment?

r r r r

Were the purpose of tests explained to you in a way that you could understand?

r r r r

Were the results of tests explained to you in a way that you could understand?

r r r r

Was enough effort made to discuss the benefits and risks of your treatment with you?

r r r r

Did anyone explain the purpose and potential side effects of medicines you were to take at home in a way that you could understand?

r r r r

Was enough information about your condition or treatment given to your family or someone close to you?

r r r r

Were you given enough information on how to manage your condition/recovery at home?

r r r r

8

SECTION 3 This section is about the followup care you received after you left the hospital on . Q 35. Did you receive a follow up phone call from the hospital in the first two weeks

after you left hospital? Tick one.

Yes r No r

Q 36. What was the reason for the telephone call? Tick one.

To see if I was having any problems r Followup for a study (clinical trial) r Other (explain)___________________________r Q 37. Which of the following have you seen since you left hospital? Do not include

group educational sessions. Tick all that apply.

Cardiologist r How many times? _____ Doctor in Outpatients r How many times? _____ General Practitioner r How many times? _____ Dietician r Physiotherapist r Social worker r

Occupational Therapist r

Cardiac rehabilitation nurse r

Other (explain)__________________________ r

None r Q 38. Which of the following group sessions did you attend either while you were in

hospital or after you left hospital? Tick all that apply.

Exercise program r Education session about heart disease r Education session about risk factors r Education session about medications r Education session on diet r

Education session on stress management r I did not attend any r

9

Q 39. Since you left the hospital which of the following tests have you had? Tick all that apply.

An echo or ultrasound of the heart r An exercise test r A nuclear scan r An ECG r None of these r Q 40. Since you left the hospital which of the following procedures have you had? Tick all that apply.

Cardiac catheter, dye injected into the heart to see arteries r Angioplasty (PTCA), a balloon used to unblock arteries in the heart r Coronary artery bypass graft surgery (CABG) r Other heart surgery specify__________________ r None of these r Q 41. What is your current smoking status? Tick one.

Never smoked r Quit more than 5 years ago r

Quit more than 12 months ago r Quit less than 12 months ago r Quit smoking since I was in hospital r

Smoker, trying to Quit. _____ cigarettes a day r Smoker. _____ cigarettes a day r Q 42. Have you been back in hospital since ? Tick one.

Yes r No ráGo to Q 44 Q 43. Was the main reason for returning to hospital related your heart problems? Tick one.

Yes r No r

10

Q 44. Which of the following have spoken to you about your smoking since you left hospital? Tick all that apply.

Not a smoker r Cardiologist r Hospital Doctor r

General Practitioner r Other ________________________________ r

None r

Q 45. Which of the following have checked your cholesterol level since you left hospital? Tick all that apply.

Cardiologist r Hospital Doctor r


None r

Q 46. Which of the following have checked your blood pressure since you left hospital? Tick all that apply.



None r

Q 47. Which of the following have talked to you about your weight since you left hospital? Tick all that apply.



None r

Q 48. Which of the following have talked to you about your level of physical activity since you left hospital? Tick all that apply.



None r

Q 49. Which of the following have checked your blood sugar level since you left hospital? Tick all that apply.



None r

11

Q 50. Please list all the medicines you are taking now.

Q 51. Are you confident that you know the purpose of each the medicines you are

taking? Tick one

Yes r

No r Q 52. Which medicines are you not sure about?

Q 53. Are you confident that you know when to take each of the medicines? Tick one

Yes r


12

Q 55. Do you have any comment about the explanations you were given about your medicines?

Q 56. We would like to know about any changes to your medications since you left

hospital. Please list any medicine that you were taking when you left the hospital but are not taking now.

Name of medicine:

Why did you stop taking this medication? Tick all that apply .

The doctor gave me a different medicine r The doctor said I didn’t need to take it anymore r The doctor said to stop taking it because it was causing me problems r I decided I didn’t need to take it anymore r I decided to stop taking it because it was causing me problems r I decided to stop taking it because it wasn’t making any difference r The medicine was too expensive r I just don’t like taking medicine r Other; please explain r

13

Why did you stop taking this medication? Tick all that apply.

The doctor gave me a different medicine r The doctor said I didn’t need to take it anymore r The doctor said to stop taking it because it was causing me problems r I decided I didn’t need to take it anymore r I decided to stop taking it because it was causing me problems r I decided to stop taking it because it wasn’t making any difference r The medicine was too expensive r I just don’t like taking medicine r Other; please specify r

Name of medicine:

Why did you stop taking this medication? Tick all that apply.

The doctor gave me a different medicine r The doctor said I didn’t need to take it anymore r The doctor said to stop taking it because it was causing me problems r I decided I didn’t need to take it anymore r I decided to stop taking it because it was causing me problems r I decided to stop taking it because it wasn’t making any difference r The medicine was too expensive r I just don’t like taking medicine r Other; please specify r

14

Q 57. The following questions are used by the American Board of Internal Medicine to measure patients’ experiences with the health care system.

In your experience how is your general practitioner at….. Tick one on each line

Excellent Very Good

Good Fair Poor Can’t Say

Treating you like you’re on the same level; not “talking down” to you or treating you like a child

r r r r r r

Letting you tell your story; listening carefully; asking thoughtful questions; not interrupting while you’re talking

r r r r r r

Discussing options with you; asking your opinion; offering choices and letting you help decide what to do; asking what you think before telling you what to do

r r r r r r

Encouraging you to ask questions; answering them clearly; not avoiding the questions or lecturing you

r r r r r r

Explaining what you need to know about your problems, how and why they occurred and what to expect next

r r r r r r

Using words you can understand when explaining your problems and treatment; explaining any technical medical terms in plain language

r r r r r r

SECTION 4 This section deals with your general health as well as symptoms of heart disease you may be experiencing. Please answer every question. Some questions may look like others, but each one is different. Please take the time to read and answer each question carefully by marking the box that best represents your response. Q 58. In general would you say your health is: Tick one

Excellent Very good Good Fair Poor

r r r r r Q 59. Compared to one year ago, how is your health in general now? Tick one

Much better

now than one year ago

Somewhat better now than one

year ago

About the same as one

year ago

Somewhat worse now than

one year ago

Much worse now than one

year ago

r r r r r

15

Q 60. The following questions are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much?

Tick one on each line

Yes, Limited A Lot

Yes, Limited A Little

No, Not Limited At All

a. Vigorous activities, such as running, lifting heavy objects, participating in strenuous sports r r r

b. Moderate activities, such as moving a table, pushing a vacuum cleaner, bowling or playing golf r r r

c. Lifting or carrying groceries r r r

d. Climbing several flights of stairs r r r

e. Climbing one flight of stairs r r r

f. Bending, kneeling or stooping r r r

g. Walking more than one kilometre r r r

h. Walking half a kilometre r r r

i. Walking 100 metres r r r

j. Bathing or dressing yourself r r r

Q 61. During the past 4 weeks, how much of the time have you had any of the

following problems with your work or other regular activities as a result of your physical health?


All of the time

Most of the time

Some of the time

A little of the time

None of the time

a. Cut down on the amount of time you spent on work or other activities

r r r r r

b. Accomplished less than you would like r r r r r

c. Were limited in the kind of work or other activity r r r r r

d. Had difficulty performing the work or other activities (for example it took extra effort)

r r r r r

16

Q 62. During the past 4 weeks, how much of the time have you had any of the following problems with your work or other regular activities as a result of your emotional problems (such as feeling depressed or anxious)?


All of the

time Most of the time

Some of the time


None of the time


r r r r r

b. Accomplished less than you would like

r r r r r

c. Did work or other activities less carefully than usual

r r r r r

Q 63. During the past 4 weeks, to what extent has your physical health or emotional

problems interfered with your normal social activities with family, friends, neighbours, or groups? Tick one

Not at all Slightly Moderately Quite a bit Extremely

r r r r r Q 64. How much bodily pain have you had during the past 4 weeks? Tick one

None Very mild Mild Moderate Severe Very severe r r r r r r

Q 65. During the past 4 weeks, how much did pain interfere with your normal work

(including both outside the home and housework)? Tick one

Not at all Slightly Moderately Quite a bit Extremely r r r r r

17

Q 66. These questions are about how you feel and how things have been with you during the past 4 weeks. For each question, please give the one answer that comes closest to the way you have been feeling. How much of the time during the past 4 weeks -


All of the Time

Most of the Time

Some of the Time

A Little of the Time

None of the Time

a. Did you feel full of life? r r r r r

b. Have you been very nervous?

r r r r r

c. Have you felt so down in the dumps that nothing could cheer you up?

r r r r r

d. Have you felt calm and peaceful?

r r r r r

e. Did you have a lot of energy?

r r r r r

f. Have you felt downhearted and depressed?

r r r r r

g. Did you feel worn out? r r r r r

h. Have you been happy? r r r r r

i. Did you feel tired? r r r r r

Q 67. During the past 4 weeks, how much of the time has your physical health or

emotional problems interfered with your social activities (like visiting with friends, relatives etc.) ? Tick one

All of the

time Most of the

time Some of the time A little of the time None of the time

r r r r r

18

Q 68. How TRUE or FALSE is each of the following statements for you?


Definitely True

Mostly True

Don’t Know

Mostly False

Definitely False

a. I seem to get sick a little easier than other people r r r r r

b. I am as healthy as anybody I know r r r r r

c. I expect my health to get worse r r r r r

d. My health is excellent r r r r r

Q 69. Over the past four weeks have you suffered from shortness of breath related to

your heart condition? Tick one

Not at all r Only with strenuous effort r Only with normal exertion r On mild exertion r Even at rest r Q 70. Have you had any chest pain, chest tightness or angina since you left hospital. Tick one

Yes r áGo to the next page Q 72 No r Q 71. What medications to prevent or treat angina (chest pain or chest tightness) have

you used since you left hospital? Tick all that apply. Sublingual (under the tongue) spray r Sublingual (under the tongue) tablets r Patches r Duride, Imdur, Imtrate or Mondur r None r áGo to the last page Q 83

19

Q 72. The following is a list of activities that people often do during the week. Although for some people with several medical problems it is difficult to determine what it is that limits them, please go through the activities listed below and indicate how much you have been limited due to chest pain, chest tightness or angina over the past four weeks. Tick one on each line

Extremely

Limited

Quite a bit Limited

Moderately Limited

Slightly Limited

Not at all Limited

Limited for other reasons or did not do the activity

Dressing yourself r r r r r r

Walking indoors on level ground

r r r r r r

Showering r r r r r r

Climbing a hill or a flight of stairs without stopping

r r r r r r

Gardening, vacuuming or carrying groceries

r r r r r r

Walking more than a block at a brisk pace

r r r r r r

Running or jogging r r r r r r

Lifting or moving heavy objects (eg furniture, children)

r r r r r r

Participating in strenuous sports (eg swimming, tennis)

r r r r r r

20

Q 73. Compared with 4 weeks ago, how often do you have chest pain, chest tightness or angina when doing your most strenuous level of activity?

Tick one

Much more often r Slightly more often r About the same r Slightly less often r Much less often r Q 74. Over the past 4 weeks, on average how many times had you had chest pain,

chest tightness or angina? Tick one

4 or more times per day r 1 to 3 times per day r 3 or more times a week but not every day r 1 to 2 times a week r Less than one a week r None over the past 4 weeks r Q 75. Over the past 4 weeks, on average how many times had you to take

nitroglycerine (GTN spray or anginine tablets) for your chest pain, chest tightness or angina? Tick one

4 or more times per day r 1 to 3 times per day r 3 or more times a week but not every day r 1 to 2 times a week r Less than one a week r None over the past 4 weeks r Q 76.How bothersome is it for you to take the medications prescribed for chest pain,


Extremely bothersome r Quite a bit bothersome r Moderately bothersome r Slightly bothersome r Not bothersome at all r My doctor has not prescribed medication r

21

Q 77.How satisfied are you that everything possible is being done to treat your chest pain, chest tightness or angina?

Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 78.How satisfied are you with the explanations your doctor has given you about your

chest pain, chest tightness or angina? Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 79.Overall, how satisfied are you with the current treatment of your chest pain, chest

tightness or angina? Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 80.Over the past 4 weeks, how much has your chest pain, chest tightness or angina

interfered with your enjoyment of life ? Tick one

It has extremely limited my enjoyment of life r It has limited my enjoyment of life quite a bit r It has moderately limited my enjoyment of life r It has slightly limited my enjoyment of life r It has not limited my enjoyment of life r

22

Q 81.If you had to spend the rest of your life with your chest pain, chest tightness or angina the way it is right now, how would you feel about this?

Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 82.How often do you think or worry that you may have a heart attack or die

suddenly? Tick one

I cannot stop thinking or worrying about it r I often think or worry about it r I occasionally think or worry about it r I rarely think or worry about it r I never think or worry about it r

23

Finally a couple of questions about your current situation. Q 83.Which of the following best describes your living arrangements? Tick one

Live alone r Live with spouse/partner or other family r Live with other people r Other r Q 84.What is your current employment status? Tick one

Full-time r Part-time r Retired r Unemployed r Home duties r Voluntary r Q 85.How does your current employment status compare with your pre-heart attack

employment status? Tick one

Working more r Working less r No change r Do you have any comments or suggestions about this questionnaire?

Thankyou very much for your help





of……………………………………………………………………………[address]

give permission for the researchers to contact my doctor for further information regarding my treatment. Doctor’s details

Name…………………………………………………………………………………

Address………………………………………………………………………………

Phone…………………………………………………………………………………

Signed…………………………………………………..Date……………………….

LETTERHEAD


Dr <Initial> <Surname> <Address1> <Address2> <Address3> WA <PCODE> <DATE> Reference Code:,<RefID>

The use of pharmacotherapies in the continuing care of coronary heart disease. Dear Dr <Surname> Patient Name: <Fname> <Sname> Address: <Street>, <Suburb> Date of Birth: <DOB> The use of medicines in the prevention of recurrent coronary heart events in patients following a recent myocardial infarction is a matter of great importance to general practitioners and their patients. The University of Western Australia and <Hospital> are conducting a study to determine the factors that influence prescription of these medications by doctors as well as the continuing effective use of the medications by patients. The issue is considered an area of priority in Australian health care, with significant clinical and public health implications. The study is funded by the Quality Use of Medicines Program provided by the Commonwealth Department of Health and Aged Care and has the approval of the Ethics Committee at <Hospital>. Your patient, who was admitted to < Hospital>, has agreed to participate in our study and has given consent for us to contact you for further details. A copy of their consent is enclosed. If you would take just a few minutes to complete the following questionnaire and return it in the reply-paid envelope, we would greatly appreciate your assistance. We know that the use of your time is a privilege and have therefore limited the exercise to a single page of essential information. If you have any questions please contact the study coordinator, Margherita Veroni, on 9380 1221. Your cooperation is appreciated. Clinical Professor Peter Thompson Professor D’Arcy Holman Cardiologist, Sir Charles Gairdner Hospital Chair in Public Health Clinical Professor, University of Western Australia University of Western Australia

«Fname» «Sname» «RefID»

Thank you very much for your co-operation Department of Public Health, University of Western Australia, 35 Stirling Hwy, Crawley 6009

We are interested in the patient’s medications since their discharge from < Hospital > following a myocardial infarction on the. <Admission_date>

Today’s date ____________

How many visits has the patient made to your practice for their heart since discharge?____________ The following is a list of medications your patient was taking at the time of discharge <Disch_date>. Please indicate any changes to this regime and the reason for these changes. Indicate all changes including those which were part of the management plan at the time of discharge. No change Change (please explain)

«Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________

Please list any additional medications the patient is currently taking.

Yes No Unsure

Did you receive a discharge letter from the hospital? r r r Did you receive a call from the responsible doctor at the time of discharge? r r r Do you have any comments about the transition of care from the hospital back to you?

LETTERHEAD



The use of pharmacotherapies in the continuing care of coronary heart disease. Dear Dr <Surname> Patient Name: <Fname> <Sname> Address: <Street>, <Suburb> Date of Birth: <DOB> We recently wrote to you about your patient’s participation in this study, and sought your assistance in providing details of the patient’s current medications. To date no reply has been received and because it is possible that our letter has become misplaced, we are enclosing a copy of the letter and associated enclosures for your convenience. We know that your time is very valuable and wish that we could afford to do more to compensate you for supporting this research. However, we have taken lengths to ensure that the one-page form asks for an absolute minimum information and takes just a few minutes to complete. We can also assure you that the project deals with a medical issue that is of major significance to public health in our community and the optimal use of medications in the prevention of recurrent coronary events. If you have any questions, please contact either one of us or the study coordinator, Margherita Veroni, on 9380 1221. Your cooperation is appreciated. Clinical Professor Peter Thompson Professor D’Arcy Holman Cardiologist, Sir Charles Gairdner Hospital Chair in Public Health Clinical Professor, University of Western Australia University of Western Australia

Appendix C

Documentation for 12 month (late) follow-up

Documentation for patients

Letter

Information Sheet with copy of Consent Form

Consent Form

Questionnaire

Documentation for doctors

Letter

Questionnaire

Reminder letter

LETTERHEAD


Ref Number: <RefID> <Title> <Fname> <Sname> <Street> <Suburb> WA <PCODE>

Dear <Title> <Sname>

People who have had a heart attack can sometimes develop further heart problems. In addition to lifestyle factors, a number of medications have been shown to reduce the risk of further problems in people with heart disease.

<Hospital> and the Department of Public Health at The University of Western Australia are conducting a study to find out what medications are being prescribed and taken to help reduce the chances of further heart problems.

I wrote to you some months ago inviting you to be a part of this important study and to help us improve the treatment available to patients with heart disease like yourself. It is now about 12 months since your heart attack, and once again we are asking you to help by telling us about the medications you are now using. We would also like to know how your health is now. You will find this questionnaire shorter than the first one and there is no home visit involved although I may telephone you if there have been any changes in your medications. This is the last time we will ask for your help. The study is funded by the Quality Use of Medicines Program provided by the Commonwealth Department of Health and Aged Care and has the approval of the Ethics Committee at Sir Charles Gairdner Hospital.

Enclosed is an Information Sheet giving more details about the study and a Questionnaire for you to complete. Please complete the questionnaire and return it in the reply paid envelope.

If you have any questions or concerns about the study please call me on 9380 1221.

Your sincerely

Margherita Veroni Study Coordinator <DATE>

The < Hospital >Human Research Ethics Committee has given approval for the conduct of the project. If you have any concerns regarding the ethical issues you can contact the Secretary of the <Hospital> Ethics Committee (telephone number <ethics phone>). All study participants will be provided with a copy of the Information Sheet and Consent Form for their personal records. 8 March 2000

Information Sheet The Use Of Medications In The Continuing Care of Coronary Heart Disease

12 Month Follow Up

Investigators Clinical Professor Peter Thompson. Department of Cardiovascular Medicine and University Department of Medicine, Sir Charles Gairdner Hospital Professor D’Arcy Holman. Department of Public Health, The University of Western Australia

What the study is about The purpose of this study is to find out if all patients who have had a heart attack receive the best treatment to help them reduce the risk of further heart problems. We would also like to find out about any problems patients have in taking these medications.

The study will collect information from questionnaires completed by patients, and, a questionnaire sent to the doctor with the patient’s consent. Where there has been a change in relevant heart medications the patient will receive a follow up telephone call.

What the study involves for you First we would like you to complete the enclosed questionnaire. It should take less than 30 minutes.

We would also like your permission to contact your General Practitioner for some additional information about your medications. If you do not want us to contact your doctor you can still participate in the rest of the study.

Please complete the questionnaire (and the consent form if you do not mind us contacting your doctor about medications) and returning it in the reply paid envelope.

You may receive a follow up telephone call to check on your medications.

If you have any questions or concerns please call the study coordinator Margherita Veroni on 9380 1221.

Confidentiality Your name will not be attached to any information about you. We will identify you only by a code. The data will be stored on password protected computers and forms kept in locked filing cabinets. Data will be stored for no longer than five years. Your name will not appear in any report.

Your participation is voluntary and whether or not you take part will not directly affect your health care. We would be very grateful if your were able to help us improve our health services.

This study will be carried out in a manner conforming to the principles set out by the National Health and Medical Research Council..

THIS IS A COPY FOR YOU TO KEEP





of……………………………………………………………………………[address]

give permission for the researchers to contact my doctor for further information regarding my treatment. Doctor’s details Name…………………………………………………………………………………

Address………………………………………………………………………………

Phone…………………………………………………………………………………

This questionnaire includes the SF-36 (Q 20– Q 30) and the Seattle Angina Questionnaire Copyright © John Spertus (Q 34– Q 44).

Ref Number:

The use of medications in the continuing care of coronary heart disease

12 MONTH FOLLOWUP QUESTIONNAIRE

This questionnaire is voluntary and whether or not you complete the questionnaire will not directly affect your health care. We would be very grateful if you help us improve health services by answering these questions. The questionnaire collects information about

• Your medications • Health care you have received for your heart • Your risk factors • Your general health • Your heart health

Please write today’s date here

This first section is about the medications you are taking now. We would like to know about all the medications you are taking now. We would like to know what you are taking, how much you are taking and when you take it. For example, if you are taking ½ a Solprin every morning

Medication Strength Dose Time

Solprin 300 mg ½ morning

Q 1. Please list all the medications you are now taking.


Q 2. Please list any vitamins or natural therapies that you take regularly.


Q 3. Do you have any question or concern about the purpose of any the medicines you are taking?

Tick one

Yes r


Q 5. Do you have any question or concern about when to take any of the

medicines? Tick one

Yes r


Q 7. Where do you get most of your information about your medications? Tick one

My Doctor r

My Pharmacist r Hospital r

Information inside the packet r Other r

Please explain__________________________________ ________________________________________________________________________________________________________________________________________________________________________

This section is about the health care you have received for your heart in the last 12 months. Q 8. When did you last see a cardiologist or attend a cardiology outpatient

clinic?

________________________________________ Q 9. In the past 12 months which of the following tests have you had? Tick all that apply.

An echo or ultrasound of the heart r An exercise test r A nuclear scan r An ECG r None of these r Q 10. Have you been back in hospital in the last 12 months since your heart attack? Tick one.

Yes r No r Q 11. Was the main reason for returning to hospital related your heart problems? Tick one.

Yes r No r Please explain__________________________________ Q 12. Have you had another heart attack in the last 12 months. Tick one.

Yes r No r Q 13. In the past 12 months, which of the following procedures have you had? Tick all that apply.

Cardiac catheter, dye injected into the heart to see arteries r Angioplasty (PTCA), a balloon used to unblock arteries in the heart r Coronary artery bypass graft surgery (CABG) r Other heart surgery specify__________________ r None of these r

This section asks about some risk factors for heart disease. Q 14. How many months is it since your cholesterol was measured?__________ Q 15. What was your cholesterol level the last time it was measured? Tick one.

less than 4.5 mmol/L r 4.5 - 5.5 mmol/L r more than 5.5 mmol/L r Not sure r Q 16. How many months is it since your blood pressure was measured?_______ Q 17. What was your blood pressure the last time it was measured? Tick one.

Good r A bit high r High r Not sure r Q 18. Do you have diabetes, glucose intolerance, or have you ever been told you

blood sugar was high? Tick one.

Yes r No r If YES. How many months is it since your blood sugar it was measured by a

doctor? __________ What was your blood sugar level at this time? Tick one.

Good r A bit high r High r Not sure r Q 19. What is your current smoking status? Tick one.

Never smoked r Quit more than 5 years ago r

Quit more than 12 months ago r Quit in the last 12 months r Smoker, trying to Quit. _____ cigarettes a day r Smoker. _____ cigarettes a day r

This section deals with your general health as well as symptoms of heart disease you may be experiencing. Answer every question by marking the answer as indicated. If you are unsure about how to answer a question, please give the best answer you can. Q 20. In general would you say your health is: Tick one

Excellent Very good Good Fair Poor

r r r r r Q 21. Compared to one year ago, how is your health in general now? Tick one

Much better

now than one year ago

Somewhat better now than one

year ago

About the same as one

year ago

Somewhat worse now than

one year ago

Much worse now than one

year ago

r r r r r Q 22. The following questions are about activities you might do during a typical day.

Does your health now limit you in these activities. If so, how much?


Yes, Limited A Lot

Yes, Limited A Little

No, Not Limited At All

a. Vigorous activities, such as running, lifting heavy objects, participating in strenuous sports r r r

b. Moderate activities, such as moving a table, pushing a vacuum cleaner, bowling or playing golf r r r

c. Lifting or carrying groceries r r r

d. Climbing several flights of stairs r r r

e. Climbing one flight of stairs r r r

f. Bending, kneeling or stooping r r r

g. Walking more than one kilometre r r r

h. Walking half a kilometre r r r

i. Walking 100 metres r r r

j. Bathing or dressing yourself r r r

Q 23. During the past 4 weeks, how much of the time have you had any of the following problems with your work or other regular activities as a result of your physical health?


All of the time

Most of the time

Some of the time


None of the time


r r r r r

b. Accomplished less than you would like r r r r r

c. Were limited in the kind of work or other activity r r r r r

d. Had difficulty performing the work or other activities (for example it took extra effort)

r r r r r

Q 24. During the past 4 weeks, how much of the time have you had any of the

following problems with your work or other regular activities as a result of your emotional problems (such as feeling depressed or anxious)?


All of the

time Most of the time

Some of the time


None of the time


r r r r r

b. Accomplished less than you would like

r r r r r

c. Didn’t do work or other activities as carefully as usual

r r r r r

Q 25. During the past 4 weeks, to what extent has your physical health or emotional

problems interfered with your normal social activities with family, friends, neighbours, or groups? Tick one

Not at all Slightly Moderately Quite a bit Extremely

r r r r r Q 26. How much bodily pain have you had during the past 4 weeks? Tick one

None Very mild Mild Moderate Severe Very severe r r r r r r

Q 27. During the past 4 weeks, how much did pain interfere with your normal work

(including both outside the home and housework)? Tick one

Not at all Slightly Moderately Quite a bit Extremely r r r r r

Q 28. These questions are about how you feel and how things have been with you during the past 4 weeks. For each question, please give the one answer that comes closest to the way you have been feeling. How much of the time during the past 4 weeks -


All of the Time

Most of the Time

Some of the Time

A Little of the Time

None of the Time

a. Did you feel full of life? r r r r r

b. Have you been very nervous?

r r r r r

c. Have you felt so down in the dumps that nothing could cheer you up?

r r r r r

d. Have you felt calm and peaceful?

r r r r r

e. Did you have a lot of energy?

r r r r r

f. Have you felt downhearted and depressed?

r r r r r

g. Did you feel worn out? r r r r r

h. Have you been happy? r r r r r

i. Did you feel tired? r r r r r

Q 29. During the past 4 weeks, how much of the time has your physical health or

emotional problems interfered with your social activities (like visiting with friends, relatives etc.) ? Tick one

All of the

time Most of the

time Some of the time A little of the time None of the time

r r r r r

Q 30. How TRUE or FALSE is each of the following statements for you?


Definitely True

Mostly True

Don’t Know

Mostly False

Definitely False

a. I seem to get sick a little easier than other people

r r r r r

b. I am as healthy as anybody I know r r r r r

c. I expect my health to get worse r r r r r

d. My health is excellent r r r r r

Q 31. Over the past four weeks have you suffered from shortness of breath related

to your heart condition? Tick one

Not at all r Only with strenuous effort r Only with normal exertion r On mild exertion r Even at rest r Q 32. Have you had any chest pain, chest tightness or angina in the past 4 weeks. Tick one

Yes r No r Q 33. What medications to prevent or treat angina (chest pain or chest tightness)

do you use? Tick all that apply. Sublingual (under the tongue) spray r Sublingual (under the tongue) tablets r Patches r Duride, Imdur, Imtrate or Mondur r Other (explain)_________________________ r None r

This section is about chest pain. Only people who take medication to prevent chest pain (angina) or have had chest pain (angina) in the last 4 weeks need to answer this section, otherwise go to the last page, Q45. Q 34. The following is a list of activities that people often do during the week.

Although for some people with several medical problems it is difficult to determine what it is that limits them, please go through the activities listed below and indicate how much you have been limited due to chest pain, chest tightness or angina over the past four weeks.


Extremely Limited

Quite a bit Limited

Moderately Limited

Slightly Limited

Not at all Limited

Limited for other reasons or did not do the activity

Dressing yourself r r r r r r

Walking indoors on level ground

r r r r r r

Showering r r r r r r

Climbing a hill or a flight of stairs without stopping

r r r r r r

Gardening, vacuuming or carrying groceries

r r r r r r

Walking more than a block at a brisk pace

r r r r r r

Running or jogging r r r r r r

Lifting or moving heavy objects (eg furniture, children)

r r r r r r

Participating in strenuous sports (eg swimming, tennis)

r r r r r r

Q 35. Compared with 4 weeks ago, how often do you have chest pain, chest tightness or angina when doing your most strenuous level of activity?

Tick one

Much more often r Slightly more often r About the same r Slightly less often r Much less often r Q 36. Over the past 4 weeks, on average how many times had you had chest pain,


4 or more times per day r 1 to 3 times per day r 3 or more times a week but not every day r 1 to 2 times a week r Less than one a week r None over the past 4 weeks r Q 37. Over the past 4 weeks, on average how many times had you to take

nitroglycerine (GTN spray or anginine tablets) for your chest pain, chest tightness or angina? Tick one

4 or more times per day r 1 to 3 times per day r 3 or more times a week but not every day r 1 to 2 times a week r Less than one a week r None over the past 4 weeks r Q 38. How bothersome is it for you to take the medications prescribed for chest

pain, chest tightness or angina? Tick one

Extremely bothersome r Quite a bit bothersome r Moderately bothersome r Slightly bothersome r Not bothersome at all r My doctor has not prescribed medication r Q 39. How satisfied are you that everything possible is being done to treat your

chest pain, chest tightness or angina? Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r

Q 40. How satisfied are you with the explanations your doctor has given you about

your chest pain, chest tightness or angina? Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 41. Overall, how satisfied are you with the current treatment of your chest pain,


Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 42. Over the past 4 weeks, how much has your chest pain, chest tightness or

angina interfered with your enjoyment of life ? Tick one

It has extremely limited my enjoyment of life r It has limited my enjoyment of life quite a bit r It has moderately limited my enjoyment of life r It has slightly limited my enjoyment of life r It has not limited my enjoyment of life r Q 43. If you had to spend the rest of your life with your chest pain, chest tightness or

angina the way it is right now, how would you feel about this? Tick one

Not satisfied at all r Mostly not satisfied r Somewhat satisfied r Mostly satisfied r Completely satisfied r Q 44. How often do you think or worry that you may have a heart attack or die

suddenly? Tick one

I cannot stop thinking or worrying about it r I often think or worry about it r I occasionally think or worry about it r I rarely think or worry about it r I never think or worry about it r

Finally a couple of questions about your current situation. Q 45. Which of the following best describes your living arrangements? Tick one

Live alone r Live with spouse/partner or other family r Live with other people r Other r Q 46. Compared to one year ago are you Tick one

Working more r Working less r No change r Do you have any comments or suggestions about this questionnaire?

Thankyou very much for your help





of……………………………………………………………………………[address]

give permission for the researchers to contact my doctor for further information regarding my treatment. Doctor’s details

Name…………………………………………………………………………………

Address………………………………………………………………………………

Phone…………………………………………………………………………………

Signed…………………………………………………..Date……………………….

LETTERHEAD



The use of pharmacotherapies in the continuing care of coronary heart disease Final follow up

Dear Dr <Surname> Patient Name: <Fname> <Sname> Address: <Street>, <Suburb> Date of Birth: <DOB> The use of medicines in the prevention of recurrent coronary heart events in patients following a recent myocardial infarction is a matter of great importance to general practitioners and their patients. The University of Western Australia and < Hospital > are conducting a study to determine the factors that influence prescription of these medications by doctors as well as the continuing effective use of the medications by patients. The issue is considered an area of priority in Australian health care, with significant clinical and public health implications. The study, involving a follow up at three and 12 month, is funded by the Quality Use of Medicines Program provided by the Commonwealth Department of Health and Aged Care and has the approval of the Ethics Committee at < Hospital >. Your patient, has agreed to participate in the 12 month follow up and has given consent for us to contact you for further details. A copy of their consent is enclosed. If you would take just a few minutes to complete the following questionnaire and return it in the reply-paid envelope, we would greatly appreciate your assistance. We know that the use of your time is a privilege and have therefore limited the exercise to a single page of essential information. If you have any questions please contact the study coordinator, Margherita Veroni, on 9380 1221. Your cooperation is appreciated. Clinical Professor Peter Thompson Professor D’Arcy Holman Cardiologist, Sir Charles Gairdner Hospital Chair in Public Health Clinical Professor, University of Western Australia University of Western Australia

«Fname» «Sname» «RefID»

Thank you very much for your co-operation Department of Public Health, University of Western Australia, 35 Stirling Hwy, Crawley 6009

Today’s date ____________

How many visits has the patient made to your practice over the past 12 months?________________ The following is a list of medications your patient was using at the time of their 3 month follow up. Please indicate any changes (cessation or alterations in dosage) to this regime and the reason for these changes. No change Change (please explain)

«Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________ «Drug» «Dose» «Frequency» o o___________________________

Please list any additional medications the patient is currently taking.

Yes No Unsure

Is the patient currently smoking? r r r What is their most recent BP and date taken? Date _________mmHg_________

What is their most recent Lipid profile and date taken? Date_________________ Total cholesterol _________ HDL cholesterol _________ LDL cholesterol _________

Yes No Unsure

Is the patient diabetic or glucose intolerant? r r r

If YES, what is their most glucose profile and date taken? Date_________________ BSL _________ Glycated haemoglobin _________

LETTERHEAD



The use of pharmacotherapies in the continuing care of coronary heart disease. Final follow up

Dear Dr <Surname> Patient Name: <Fname> <Sname> Address: <Street>, <Suburb> Date of Birth: <DOB> We recently wrote to you about your patient’s participation in this study, and sought your assistance in providing details of the patient’s current medications. To date no reply has been received and because it is possible that our letter has become misplaced, we are enclosing a copy of the letter and associated enclosures for your convenience. We know that your time is very valuable and wish that we could afford to do more to compensate you for supporting this research. However, we have taken lengths to ensure that the one-page form asks for an absolute minimum information and takes just a few minutes to complete. We can also assure you that the project deals with a medical issue that is of major significance to public health in our community and the optimal use of medications in the prevention of recurrent coronary events. If you have any questions, please contact either one of us or the study coordinator, Margherita Veroni, on 9380 1221. Your cooperation is appreciated. Clinical Professor Peter Thompson Professor D’Arcy Holman Cardiologist, Sir Charles Gairdner Hospital Chair in Public Health Clinical Professor, University of Western Australia University of Western Australia

Appendix D

Patient interview

Home visit interview

People often have difficulty taking their pills for various reasons. I would like to talk about problems you may have with taking medications. 1. Do you ever forget to take any of your pills? What sort of things make you forget? Do you

have any ways of helping you to remember?

2. Do you always take your medications at the same time every day?

3. Sometimes when people feel better they stop taking their medications? Do you ever stop

taking your medications?

4. Sometimes if you feel worse when you are taking your medicine do you stop taking it?

5. Other problems

Now I would like to go through the medications you are taking now.

Medication Strength Dose Frequency Purpose

Appendix E

Cardiology staff interviews

Focus Group

Interviews with Key Informants

Interview with Resident Medical Officers

Focus Group My name is Margherita and I’m in the Department of Public Health at UWA. I am currently doing a study looking at the medications that patients take following an MI – so I’m interested both in the prescribing by doctors and then patient adherence. What I would like to do today is talk with you about The middle bit - what happens at around the time of discharge with regard to education and follow up. I’m particularly interested in patient’s medications but if you think there are important issues with other aspects of the discharge process perhaps relating to follow up care or rehabilitation then please speak about those as well.

• Just a few comments before we start. • Taping. So please only one person speak at a time, and

please speak up. • Alison is going to take notes. • Everything you say is confidential and no names will be

used in the reporting of this discussion. Reporting will be in general terms only.

• In the same vein if you give a specific example please don’t use any names.

Perhaps we could start first with the information that is provided to patients either at discharge or prior to discharge. Who is responsible for telling patients about their medications? Is this what happens? What written information about their medications is given is to the patients? Who is responsible for giving them this information? Who actually does it? Is the information handed over or is medication individually explained to the patient? What happens if you think the patient is unclear about their medications? Is there one person responsible for making sure a patient has been given all the written information about their medications prior to discharge? What about scripts and discharge summaries? Are you generally happy that patients go home with a good understanding of their medications and when to take them? Are there any circumstances when a patient might go home with less than optimal information about their medications? What about scripts or discharge summary? How could the system be changed to ensure that all patients go home with the appropriate medications or scripts and with a clear understanding of how and when to take the medications and why they are taking each one.

Key Informants As you may know I have been conducting a study looking at the medication that patients take following an MI. I have looked at the medications at the time of discharge and then followed the patients up at 3 and 12 months. What I would like to do today is talk with you what happens at around the time of discharge relating to a patient’s medications. Is it OK if I tape this?

Perhaps we could start first with the information that is provided to the patients either at discharge or prior to discharge.

Whose responsibility is it to explain to the patient about their medications?

Can you tell me what written information about their medications is provided to the patient?

Who is responsible for giving them this information? Who actually does it?

What do you see as your role in preparing the patient for discharge, particularly with regard to their medications?

What happens if you think the patient is unclear about their medications?

Is there one person responsible for making sure a patient has been given all the written information about their medications prior to discharge?

What about discharge summaries and scripts?

Are you generally happy that patients go home with a good understanding of their medications and when to take them?

Are there any circumstances when a patient might go home with less than optimal information about their medications?

What about scripts and discharge summary?

How could the system be changed to ensure that all patients go home with the appropriate medications or scripts and with a clear understanding of how and when to take the medications and why they are taking each one.

RMOs interview As you may know I have been conducting a study looking at the medication that patients take following an MI. I have looked at the medications at the time of discharge and then followed the patients up at 3 and 12 months. What I would like to do today is talk with you what happens at around the time of discharge relating to a patient’s medications. Is it OK if I tape this? First can I ask you where you get your information about what drugs to give patients. Are guidelines currently in place? Whose responsibility is it to explain to the patient about their medications? Can you tell me what written information about their medications is provided to the patient? Who is responsible for giving them this information? Who actually does it? What do you see as your role in preparing the patient for discharge, particularly with regard to their medications? What happens if you think the patient is unclear about their medications? Is there one person responsible for making sure a patient has been given all the written information about their medications prior to discharge? What about discharge summaries and scripts? Do you routinely contact the patients GP?

• What type of contact? • When? • What is the purpose of the contact? • Is there a system in place to make sure contact is made? • If not routine under what circumstances would you telephone a

patient’s GP. Are you generally happy that patients go home with a good understanding of their medications and when to take them? Are there any circumstances when a patient might go home with less than optimal information about their medications? What about scripts and discharge summary? How could the system be changed to ensure that all patients go home with the appropriate medications or scripts and with a clear understanding of how and when to take the medications and why they are taking each one.

Documents

The Use of Pharmacotherapies in the Secondary Prevention