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Health IT: The Big Picture Health IT: The Big Picture Nawanan Theera-Ampornpunt, MD, MS Except where citing 1 Healthcare CIO Program, Ramathibodi Hospital Administration School Dec. 3, 2010 SlideShare.net/Nawanan where citing other works

Health IT: The Big Picture

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A presentation on Dec. 3, 2010 for Hospital Administration School, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand.

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Page 1: Health IT: The Big Picture

Health IT: The Big PictureHealth IT: The Big PictureNawanan Theera-Ampornpunt, MD, MS Except 

where citing

1

Healthcare CIO Program, Ramathibodi Hospital Administration SchoolDec. 3, 2010 SlideShare.net/Nawanan

where citing other works

Page 2: Health IT: The Big Picture

The Anatomy of Health IT

Health GoalHealth f

Goal

Information Value‐Add

Technology MeansTechnology Means

2

Page 3: Health IT: The Big Picture

Various Forms of Health IT

Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)

Electronic Health

Records Picture Archiving and

3

Records (EHRs)

gCommunication System

(PACS)

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Still Many Other Forms of Health IT

Health Information Exchange (HIE)Exchange (HIE)

m-Health

Biosurveillance

Personal Health Records (PHRs)

Telemedicine &

( )

4

Information RetrievalTelemedicine &

Telehealth

Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, Inc.

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Information is Everywhere in Medicine

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Page 6: Health IT: The Big Picture

Why Healthcare Isn’t Like Banking

• We are in a life‐or‐death business– One small mistake can lead to M&M

d l di d• Fragmented, poorly‐coordinated systems• High volume low resources little time• High volume, low resources, little time• Large, ever‐growing & changing knowledge body

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Why Healthcare Isn’t Like Banking

• Evolving standards of care & expectationsg p• Complex, diverse nature of information• Difficult (and dangerous) to automate clinical decision making Medico legalclinical decision making. Medico‐legal liabilities?

• Professional cultures & values

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Page 8: Health IT: The Big Picture

Is There A Role for Health IT?

8(IOM, 2000)

Page 9: Health IT: The Big Picture

Landmark IOM Reports

9

(IOM, 2001)(IOM, 2000)

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Landmark IOM Reports: Summary

• Humans are not perfect and are bound to• Humans are not perfect and are bound to make errors

• High‐light problems in the U.S. health care system that systematically contributes tosystem that systematically contributes to medical errors and poor qualityR d f th t ld h• Recommends reform that would change how health care works and how technology innovations can help improve quality/safety

10

q y/ y

Page 11: Health IT: The Big Picture

Why We Need Health IT

• Health care is very complex (and inefficient)• Health care is very complex (and inefficient)• Health care is information‐rich• Quality of care depends on timely availability & quality of informationavailability & quality of information

• Clinical knowledge body is too large to be in any clinician’s brain, and the short time during a visit makes it worseg

• “To err is human”i id li “ h h lf”

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• Practice guidelines are put “on‐the‐shelf”

Page 12: Health IT: The Big Picture

We need “Change”

“...we need to upgrade our medical records by switching from a paper torecords by switching from a paper to an electronic system of record keeping...”

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keeping...President Barack Obama

June 15, 2009

Page 13: Health IT: The Big Picture

The Anatomy of Health IT Revisited

Health GoalHealth f

Goal

Information Value‐Add

Technology MeansTechnology Means

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Page 14: Health IT: The Big Picture

Ultimate Goals of Health IT

I di id l’ H lth• Individual’s Health

•Population’s Healthp

•Organization’s Health

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Page 15: Health IT: The Big Picture

Dimensions of Quality Health Care

• Safety• Safety• Timeliness• EffectivenessEffi i• Efficiency

• Equityq y• Patient‐centeredness

15(IOM, 2001)

Page 16: Health IT: The Big Picture

CLASS EXERCISE #2

For each of Institute of Medicine’s 6 dimensions of quality health care, suggest ways health IT can help.suggest ways health IT can help.

Safety Timeliness EffectivenessSafety Timeliness EffectivenessEfficiency Equity Patient‐centeredness

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Page 17: Health IT: The Big Picture

Safety?

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Page 18: Health IT: The Big Picture

Safety

• Legible handwriting• Legible handwriting• Proper display of patient information (e.g. abnormal labs)• Alerts• Alerts

– Drug‐Allergy Checks– Drug‐Drug Interaction Checksg g– Drug‐Lab Interaction Checks

• Dose calculator• Prevention of medication errors• Timely information

– Histories– Diagnoses/Problem List

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– Labs– Medication List

Page 19: Health IT: The Big Picture

Timeliness?

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Page 20: Health IT: The Big Picture

Timeliness

• Timely information for emergencies transfers normal visits• Timely information for emergencies, transfers, normal visits– Histories– Diagnoses/Problem List– Labs– Medication List

• Effective communications between providers• Effective triage & patient monitoring

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Page 21: Health IT: The Big Picture

Effectiveness?

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Page 22: Health IT: The Big Picture

Effectiveness

• Reminders/advice for– Guideline adherence– Preventive care

Specialist consults– Specialist consults

• Templates/forms– Order setsOrder sets– Care planning, nursing assessments & interventions, 

nursing documentation

• Availability of patient information• Continuity of care (even in referrals)• Effective display of information (e.g. graphs, user‐friendly 

screens)

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• Assistance in decision‐making (e.g. differential diagnosis)• Access to evidence/references at the point of care

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Efficiency?

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Page 24: Health IT: The Big Picture

Efficiency

• Fast/lean/efficient processes of care– Automation ‐> faster care, fewer workers– Process redesigns/reengineering (e.g. parallel processes/access)

h l d f– Changes in role assignments ‐> productivity gains or more time for patient

• Predictable patterns/“Just‐in‐time” (staffing, resource allocation, inventory bed management)inventory, bed management)

• Flexibility “Organizational slacks” (buffers)

• Drug formulary checks & policy enforcement• Drug‐formulary checks & policy enforcement• Reduction of redundant tests• Efficient management of bed occupancy/hospital capacity• Efficient management of bed occupancy/hospital capacity• Cost‐savings & time‐savings from preventable errors

S i ( di l d PACS)

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• Space‐savings (e.g. medical records, PACS)• Effective communications

Page 25: Health IT: The Big Picture

Equity?

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Page 26: Health IT: The Big Picture

Equity

• Reduction of barriers to care improved access• Reduction of barriers to care, improved access to care– Physical barriers (telemedicine, tele‐consultation)– Structural barriers (information exchange among ( g ghospitals)

– Functional barriers (information access by patientsFunctional barriers (information access by patients, networks of patients)Cultural barriers (tailored information for different– Cultural barriers (tailored information for different patients)

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Page 27: Health IT: The Big Picture

Patient-Centeredness?

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Page 28: Health IT: The Big Picture

Patient-Centeredness

• Patient’s access toPatient s access to– Own clinical informationG l h lth i f ti– General health information

– Tailored health information

• Patient engagement/compliance• Patient empowerment• Patient empowerment

– Patients’ networking & knowledge sharing

• Patient satisfaction with quality & efficient care• Patient’s control of information (privacy)

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• Patient s control of information (privacy)

Page 29: Health IT: The Big Picture

Roles of Health IT

• Information provider• Information provider• Process transformer• Mistake preventer (risk manager)Cli i i ’ h l• Clinician’s helper

• Patient’s educator & supporterpp• Management’s assistantR h ’• Researcher’s gateway

• etc.

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Page 30: Health IT: The Big Picture

Documented Benefits of Health IT

• Literature suggests improvement through• Literature suggests improvement through– Guideline adherence (Shiffman et al, 1999;Chaudhry et al, 2006)

– Better documentation (Shiffman et al, 1999)

– Practitioner decision making or process of care (Balas et al, 1996;Kaushal et al, 2003;Garg et al, 2005)

– Medication safety(Kaushal et al 2003;Chaudhry et al 2006;van Rosse et al 2009)(Kaushal et al, 2003;Chaudhry et al, 2006;van Rosse et al, 2009)

– Patient surveillance & monitoring (Chaudhry et al, 2006)P ti t d ti / i d– Patient education/reminder (Balas et al, 1996)

– Cost  savings and better financial performance (P t & D b 2001 Ch dh t l 2006 A i h t l 2009

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(Parente & Dunbar, 2001;Chaudhry et al, 2006;Amarasingham et al, 2009;Borzekowski, 2009)

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But...But...• “Don’t implement technology just for technology’s• Don t implement technology just for technology s sake.”“D ’t k f ll t t h l• “Don’t make use of excellent technology. Make excellent use of technology.”(Tangwongsan Supachai Personal communication 2005 )(Tangwongsan, Supachai. Personal communication, 2005.)

• “Health care IT is not a panacea for all that ails medicine ” (H h 2004)medicine.  (Hersh, 2004)

• “We worry, however, that [electronic records] are b d f l ll h ll fbeing touted as a panacea for nearly all the ills of modern medicine.”(H t b d & G 2008)

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(Hartzband & Groopman, 2008)

Page 32: Health IT: The Big Picture

Common “Goals” for Adopting HIT

“Computerize”“Go paperless” ComputerizeGo paperless

“Digital Hospital”“Get a HIS”

Digital Hospital

“H EMR ”“Modernize”

“Have EMRs”

“Share data”

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Share data

Page 33: Health IT: The Big Picture

The Common Denominator

H lth I f ti T h l•Health Information Technology

•Electronic Health Records

•Health Information Exchange

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Page 34: Health IT: The Big Picture

Some Misconceptions about HIT

Ifd

IfCurrent 

EnvironmentNew, Modern, Electronic 

EnvironmentEnvironment

ThenAlways

Bad GoodAlways

34

ad

Page 35: Health IT: The Big Picture

Fundamental Theorem of Informatics

35(Friedman, 2009)

Page 36: Health IT: The Big Picture

Take-Home Messages

• Health IT has documented benefits to• Health IT has documented benefits to quality & efficiency of care

• Implementing health IT will not a tomaticall fi all problemsautomatically fix all problems

• Health IT is not without risks• Find the ways health IT can help• Focus on the ultimate goals• Benefits of health IT may vary by

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• Benefits of health IT may vary by context

Page 37: Health IT: The Big Picture

NEXTHealth IT inHealth IT in Hospital SettingsHospital Settings

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References

• Amarasingham R, Plantinga L, Diener‐West M, Gaskin DJ, Powe NR. Clinical information g gtechnologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108‐14.

• Balas EA, Austin SM, Mitchell JA, Ewigman BG, Bopp KD, Brown GD. The clinical value of d f f d d l l l hcomputerized information services. A review of 98 randomized clinical trials. Arch Fam

Med. 1996;5(5):271‐8.• Borzekowski R. Measuring the cost impact of hospital information systems: 1987‐1994. J 

Health Econ 2009;28(5):939 49Health Econ. 2009;28(5):939‐49.• Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG. 

Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742‐52.; ( )

• DeLone WH, McLean ER. Information systems success: the quest for the dependent variable. Inform Syst Res. 1992 Mar;3(1):60‐95. 

• Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc. 2009 Apr;16(2):169‐70.

• Garg AX, Adhikari NKJ, McDonald H, Rosas‐Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance d i i i JAMA 2005 293(10) 1223 38

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and patient outcomes: a systematic review. JAMA. 2005;293(10):1223‐38.• Hartzband P, Groopman J. Off the record‐‐avoiding the pitfalls of going electronic. N Engl

J Med. 2008 Apr 17;358(16):1656‐1658. 

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References

• Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov 10:292(18):2273 410:292(18):2273‐4.

• Institute of Medicine, Committee on Quality of Health Care in America. To err is human: building a safer health system. Kohn LT, Corrigan JM, Donaldson MS, editors. Washington, DC: National Academy Press; 2000. 287 p.g , y ; p

• Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001. 337 p.

• Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch. Intern. Med. 2003;163(12):1409‐16.P ST D b JL I h l h i f i h l i l d h• Parente ST, Dunbar JL. Is health information technology investment related to the financial performance of US hospitals? An exploratory analysis. Int J Healthc TechnolManag. 2001;3(1):48‐58.

• Shiffman RN Liaw Y Brandt CA Corb GJ Computer‐based guideline implementation• Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer‐based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc. 1999;6(2):104‐14.

• Van Rosse F, Maat B, Rademaker CMA, van Vught AJ, Egberts ACG, Bollen CW. The effect 

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g gof computerized physician order entry on medication prescription errors and clinical outcome in pediatric and intensive care: a systematic review. Pediatrics. 2009;123(4):1184‐90.

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Various Ways to Measure Success

• DeLone & McLean (1992;2003)• DeLone & McLean (1992;2003)

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