The Art of the Possible Using CPCSSN Data for Primary Care Research

Family Medicine ForumNov 16, 2012

Karim Keshavjee - EMR Consultant & Research Data ArchitectKen Martin - Information and Technology Manager

Outline• Introduction to CPCSSN• CPCSSN Data Holdings• A Tour of CPCSSN Data Tables• Current Research Projects at CPCSSN• The Art of the Possible• How to use CPCSSN data for your research• Goodies for Today

329 physicians in 8 provinces using 10 EMRs

10 PC-PBRNs• British Columbia - BCPCReN (Wolf ) • Alberta - SaPCReN, Calgary (Med Access, Wolf) - AFRPN, Edmonton (Med Access)

• Manitoba - MaPCReN, Winnipeg (Jonoke)

• Ontario - DELPHI, London (Healthscreen, Optimed, OSCAR - NorTReN, Toronto (Nightingale, xwave, Practice Solutions) - CSPC, Kingston (P&P, OSCAR, xwave)

• Quebec - Q-Net, Montréal (Da Vinci, Purkinje)

• Nova Scotia / New Brunswick - MarNet, Halifax (Nightingale, Purkinje)

• Newfoundland - APBRN, St. John’s (Wolf , Nightingale)

CPCSSN population

CPCSSN PopulationData Extracted on all patients in the practice, including children Studying patients with the following chronic diseases

• Chronic Obstructive Lung Disease • Depression• Diabetes• Hypertension• Osteoarthritis

Chronic Neurological Disease• Dementia• Epilepsy• Parkinson's Disease

Data Holdings Q2 2012

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6Database Schema - ERD

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Data Cleaning/Recoding• We clean and recode the following fields

• Billing, Encounter and Problem List Diagnoses (ICD9)• Medications (ATC)• Lab results (LOINC)• Referrals (SNOMED CT)• Physical signs (Wt, Ht, BP, unit conversion, calculate

BMI)• Vaccines (ATC)• Risk factors (smoking, alcohol, diet --Text)

8Patient Demographics

} < 5%

} < 5%

368,000 Records368,000 Records

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Provider Information

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Billing

6.8 Million Records6.8 Million Records

Dates of EncounterDates of Encounter

Original diagnosis sent for billing

Original diagnosis sent for billing

Text from Code Recoded by CPCSSN

Text from Code Recoded by CPCSSN

Original Diagnosis Code sent for billing

Original Diagnosis Code sent for billing

Recoded by CPCSSNRecoded by CPCSSN

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Research Discussion• Useful for case finding• Useful for understanding deficiencies of using

billing information for clinical research

• There is some inconsistency in use of billing codes across the country

• CPCSSN recodes all billing diagnosis codes to a standard version

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Encounters

5.1 Million Records5.1 Million Records

Dates of EncounterDates of Encounter

Data inconsistent across the Country

Data inconsistent across the Country

CPCSSN Cleaning Not StartedCPCSSN Cleaning Not Started

Active area of CleaningE.g., Office Visit, Phone, E-mail etc

Active area of CleaningE.g., Office Visit, Phone, E-mail etc

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Research Discussion• Can we segment patients by pattern of visits?• Does pattern of visits predict other things?

– Control of disease– Frequency of prescriptions– Multiple comorbidities

• Does visit type affect quality of care?

• Reason for Encounter is poorly captured in most EMRs

Problem List Diagnoses

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Original Diagnosis Written by UserE.g. DMT2

Original Diagnosis Written by UserE.g. DMT2

Recoded by CPCSSNE.g., Diabetes Mellitus, Type 2

Recoded by CPCSSNE.g., Diabetes Mellitus, Type 2

} Not well populated

1.8 Million Records1.8 Million Records

Active = Problem ListInactive = Past Medical History

Active = Problem ListInactive = Past Medical History

Problem List Diagnoses

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List of cleaned up diagnoses

Chronic airway obstruction, not elsewhere classified (496)Bronchitis, not specified as acute or chronic (490)Chronic bronchitis (491)Emphysema (492)Diabetes mellitus (250)Depressive disorder, not elsewhere classified (311)Suicide and self-inflicted poisoning by solid or liquid substances (E590)Suicidal ideation (V62.84) Adjustment reaction (309)Post traumatic stress disorder (309.81)Major depressive disorder, recurrent episode (296.3)Bipolar I disorder, most recent episode (or current) (296.7)Mental disorders complicating pregnancy, childbirth, or the puerperium (648.4)Essential hypertension (401)Osteoarthrosis and allied disorders (715)Spondylosis and allied disorders (721)Total knee replacement (81.54)Total hip replacement (81.51)Polycystic ovarian syndrome (256.4)Abnormal glucose tolerance of mother complicating pregnancy childbirth or the puerperium (648.8)Secondary diabetes mellitus (249)

MORE BEING ADDED SOON

Other abnormal glucose (790.29)Migraine (346)Heart failure (428)Acute myocardial infarction (410)Old myocardial infarction (412)Other forms of chronic ischemic heart disease (414)Cardiac dysrhythmias (427)Essential and other specified forms of tremor (333.1)Esophageal varices with bleeding (456.0)Esophageal varices without bleeding (456.1)Angina pectoris (413)Other acute and subacute forms of ischemic heart disease (411)Calculus of kidney and ureter (592)Portal hypertension (572.3)Asthma (493)Dementias (290)Alzheimer's disease (331.0)Dementia with lewy bodies (331.82)Parkinson's disease (332)Epilepsy and recurrent seizures (345)Epileptic convulsions, fits, or seizures nos (345.9)

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Research Discussion• Sensitivity and specificity of problem list

diagnoses not currently known, so cannot determine incidence and prevalence of disease from problem list alone

• Need to develop case finding criteria for diseases (includes diagnosis, meds, labs, etc)

• Need to identify sensitivity and specificity of having a diagnosis in the problem list

• Currently in the process of validating 8 case finding criteria across the country

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Vital Signs

Name of exam (e.g., sBP)Name of exam (e.g., sBP)

Cleaned up result(e.g, lbs -> kg, inch -> cm)

Cleaned up result(e.g, lbs -> kg, inch -> cm)

5 Million Records5 Million Records

Cleaned up unit of measure(e.g., unit is kg, but result was lb)

Cleaned up unit of measure(e.g., unit is kg, but result was lb)

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Research Discussion• Currently have access to

– sBP/dBP– Ht– Wt– BMI– Waist circum

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Allergies

Name of allergenName of allergen

Cleaned up nameCleaned up name

155K Records155K Records

Data will be coded as ATCData will be coded as ATC

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Research Discussion• Not yet cleaned, but will soon clean it• Focus of cleaning will be on medication

allergies– All other allergies will be retained as original text

• Useful when assessing why patients are not receiving medications for a particular disease

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Risk Factors

Name of Risk Factor (e.g., smoking)Name of Risk Factor (e.g., smoking)

Cleaned up version of Risk Factors.Cleaned up version of Risk Factors.

588K Records588K Records

Working on cleaning up Current Exposures & Cumulative Exposures

Working on cleaning up Current Exposures & Cumulative Exposures

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Research Discussion• Risk factors are actively being cleaned

• Getting the status of the risk factor (i.e., smoker/non-smoker) is difficult, but easier than

• Current levels of exposure (e.g., # of cig/day)• Cumulative exposure (e.g., pack years)• Alcohol use is also being cleaned up

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Laboratory Results

Original Lab Result Name(e.g., Hb A1c, HGbA1c, etc)Original Lab Result Name

(e.g., Hb A1c, HGbA1c, etc)

Recoded by CPCSSN 100% LOINC(e.g., HBA1C)

Recoded by CPCSSN 100% LOINC(e.g., HBA1C)

3 Million Records3 Million Records

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Research Discussion• Currently only capturing the following

• One site does not capture labs yet

HDLTRIGLYCERIDESLDLTOTAL CHOLESTEROLFASTING GLUCOSEHBA1CURINE ALBUMIN CREATININE RATIOMICROALBUMINGLUCOSE TOLERANCE

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Encounter Diagnoses

Original Diagnosis Recorded in Encounter(e.g., axniety)

Original Diagnosis Recorded in Encounter(e.g., axniety)

83% Recoded by CPCSSN(Anxiety ICD-9 300)

83% Recoded by CPCSSN(Anxiety ICD-9 300)

6.3 Million Records6.3 Million Records

63% Originally coded by Doctor63% Originally coded by Doctor

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Research Discussion• Not all EMRs capture Encounter Diagnoses in a

structured manner

• This table is not ready for prime time across all sites, but may be useful for projects where data from just a few sites is acceptable

Medications

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What the doctor orderedE.g., HCTZ 25 mg bid

What the doctor orderedE.g., HCTZ 25 mg bid

91% Recoded by CPCSSNE.g., Hydrochlorthiazide

91% Recoded by CPCSSNE.g., Hydrochlorthiazide

56% Coded as DIN56% Coded as DIN

Strength 56%Dose 70%

Unit of Measure 84%Frequency 95%Duration 52%

Dispensed 86%

Strength 56%Dose 70%

Unit of Measure 84%Frequency 95%Duration 52%

Dispensed 86%

72% Coded by doctor (DIN + other)72% Coded by doctor (DIN + other)

91% Coded by CPCSSN (ATC)91% Coded by CPCSSN (ATC)

4.9 Million Records4.9 Million Records

}

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Research Discussion• Medication name data is relatively clean• Medications coded as ATC

– Allows easy grouping by class

• Don’t have daily dose and months supply for many records –working on clean up

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Referrals

Original Text of ReferralOriginal Text of Referral

80% Recoded by CPCSSNSNOMED-CT

80% Recoded by CPCSSNSNOMED-CT

600 K Records600 K Records

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Procedures

Original Text of ProcedureOriginal Text of Procedure

Not Currently Coded by CPCSSNNot Currently Coded by CPCSSN

1.3 Million Records1.3 Million Records

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Vaccines

What the doctor typedWhat the doctor typed

93% Recoded by CPCSSN (ATC)93% Recoded by CPCSSN (ATC)

960 K Records960 K Records

46% Coded by Doctor (DIN)46% Coded by Doctor (DIN)

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Disease Cases

173,000 Records173,000 Records

Case Definitions are developed by CPCSSN and are in the process ofbeing validated through chart reviews

How a Case is identified is recorded in this table

Allows full traceability for each case

Current Research Projects at CPCSSN

N=46

Association Study 9%Attitudes 2%Audit and feedback 2%Case control study 7%Case Finding 9%Clinical Quality Improvement 2%Continuity of Care 2%Data Quality 20%De-identification 2%Denominator 2%Descriptive Study 2%EMR Adoption 2%Feasibility 2%Intervention Assessment 2%Medication 2%Practice Profile 4%Prevalence 7%Prevalence, Case finding 2%Resource Use 7%SES Study 4%Treatment pattern 4%Validation 4%

Research Opportunities• Population Health and Epidemiological Studies

– Incidence/Prevalence of disease– Impact of SES on health– Rates of treatment for diseases– Rates of disease control– Burden of illness and multi-morbidity

• Clinical –database studies– Comparative effectiveness– Case-Control– Exposure-Outcome– Quality Improvement– Associations– Intervention-Outcome– Guideline effectiveness

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Research Opportunities• Clinical –prospective, interventional studies

– Conduct pragmatic RCTs –data is already collected– Conduct in-clinic interventions– Not ready for these yet

• Health Services– EMR adoption– Resource Utilization (consults, labs, procedures)– Policy Intervention (cross-province comparisons)– Patient behaviors –frequency of visits– Medical errors and patient safety

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Research Opportunities• Health informatics

– Natural language processing– Machine learning– De-identification algorithms– Predictive Analytics

• eHealth and mHealth– Develop and test apps using CPCSSN data– Patient education apps with their own data– Apps for healthcare providers to educate patients

about their disease with nice visualizations

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Research Using CPCSSN Data

ResearcherLetter of

Intent

CPCSSN Research

Committee

Writes

Letter of Intent

Reviews

1 page, includes: Researchers, Organization, Research Title,

Objective, Methodology, Data Required

Approved

1. Resubmit2. Not Feasible

3. Outside Mandate

No

Researcher

1. Protocol2. Data Access Request Form

3. Data Sharing Agreement

Letter of Acceptance Yes

Writes

CPCSSN Research

Committee

CPCSSN Data

ResearcherInvoice

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Goodies For Today• Copy of the presentation: The Art of the Possible: Using CPCSSN

Data for Primary Care Research• Sample of CPCSSN data for 200 patients

– Anonymized and scrambled to protect patient privacy– (MS Access file format)

• CPCSSN database entity relationship diagram (ERD)• CPCSSN database data dictionary• CPCSSN central repository data holdings summary• CPCSSN Data Access Request Form Central Repository• Process for Requesting Access to CPCSSN Data

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Next Steps• Sign a License Agreement today to get your copy of

the CPCSSN Data Product

• Evaluate the data CPCSSN has

• Plan your next grant application around CPCSSN data

• Add CPCSSN Data as a budget item into your next grant application– You can contact us to get a quote

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Contact

Tyler Williamson, Senior Epidemiologist Canadian Primary Care Sentinel Surveillance Network

Centre for Studies in Primary CareQueen’s UniversityKingston ON K7L 5E9

Tel: (613) 533-9300, Ext. 73838Fax: (613) 533-9302e-mail: tylerw@cpcssn.org

Thanks to all Funders, Stakeholders, Partners, AND sentinel Physicians

Cette publication a été réalisée grâce au financement de l'Agence de la santé publique du Canada. Les opinions exprimées ici ne reflètent pas nécessairement celles de l'Agence de la santé publique du Canada.

Funding for this publication was provided by the Public Health Agency of Canada The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada.