Health Informatics: The Next Stethoscope in Healthcare

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Theera-Ampornpunt N. Health informatics: the next “stethoscope” in healthcare. Presented at: Intelligent logistics for innovation hospitals; 2010 Dec 23; Faculty of Engineering, Mahidol University, Thailand. Invited speaker, in Thai.

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H lth I f ti Health Informatics: The Next “Stethoscope” in Healthcarep

Nawanan Theera-Ampornpunt, MD, MS

Healthcare &

H lth ITHealth IT

Manufacturingg

Source: Guardian.co.uk

Bankingg

Source: Cablephet.com

Healthcare

Source: nj.com

Why Healthcare Isn’t Like Any Others?

• Life-or-Death

• Many & varied stakeholders

• Strong professional values

• Evolving standards of care

• Fragmented poorly-coordinated systemsFragmented, poorly coordinated systems

• Large, ever-growing & changing body of knowledge

• High volume, low resources, little time

Source: nj.com

Why Healthcare Isn’t Like Any Others?

• Large variations & contextual dependenceg p

Input Process OutputInput Process Output

Patient Decision BiologicalPatient Presentation

Decision‐Making

Biological Responses

Source: nj.com

But...Are We That Different?

Banking

Input Process Output

Transfer

Location A Location BValue‐Add

‐ SecurityC i

Location A Location B

‐ Convenience‐ Customer Service

But...Are We That Different?

Manufacturing

Input Process Output

AssemblingRaw FinishedAssemblingRaw Materials

Finished Goods

Value‐Add‐ Innovation‐ Skills‐ QA

But...Are We That Different?

Healthcare

Input Process Output

Patient CareSick Patient Well Patient

Value‐Add‐Medical technology & medications‐ Clinical knowledge & skillsg‐ Quality of care; process improvement‐ Information

Information is Everywherey

Various Forms of Health IT

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

Electronic Health

Records Picture Archiving and Records (EHRs)

gCommunication System

(PACS)

Still Many Other Forms of Health IT

Health Information Exchange (HIE)

m Health

g ( )

m-Health

Biosurveillance

Personal Health Records (PHRs)

Telemedicine & Information Retrieval Telehealth

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

Why Adopting Health IT?

“Computerize”“Go paperless” ComputerizeGo paperless

“Digital Hospital”“Get a HIS”

Digital Hospital

“H EMR ”“Modernize”

“Have EMRs”

“Share data”Share data

Some Quotes

• “Don’t implement technology just for technology’s sake ”• Don t implement technology just for technology s sake.

• “Don’t make use of excellent technology.

Make excellent use of technology.”(Tangwongsan, Supachai. Personal communication, 2005.)

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

• “We worry, however, that [electronic records] are being

touted as a panacea for nearly all the ills of modern touted as a panacea for nearly all the ills of modern

medicine.”(Hartzband & Groopman, 2008)

Health IT: What’s In A Word?

Health GoalHealthf

Goal

Information  Value-Add

Technology ToolsTechnology Tools

Dimensions of Quality Healthcare

• Safety• Safety

• Timeliness

• Effectiveness

• Efficiency

• E it• Equity

• Patient-centerednessat e t ce te ed ess

(IOM, 2001)

Value of Health IT

• G ideline adherence• Guideline adherence

• Better documentationBetter documentation

• Practitioner decision making or process of care

• Medication safety

• Patient surveillance & monitoring

• Patient ed cation/reminder• Patient education/reminder

Fundamental Theorem of Informatics

(Friedman, 2009)

Is There A Role for Health IT?

(IOM, 2000)

Landmark IOM Reports

(IOM, 2001)(IOM, 2000)

Landmark IOM Reports: Summary

• Humans are not perfect and are bound to make errorsp

• High-light problems in the U.S. health care system that

systematically contributes to medical errors and poor

qualityquality

• Recommends reform that would change how health

care works and how technology innovations can help

improve quality/safetyimprove quality/safety

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 information

• Clinical knowledge body is too largeClinical knowledge body is too large

• Short time during a visit

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

• “To err is human”

To Err Is Human

• Perception errorsPerception errors

Source: interaction-dynamics.com

To Err Is Human

• Lack of AttentionLack of Attention

Source: aafp.org

To Err Is Human

• Decoy PricingDecoy Pricing

The Economist Purchase Options# of

People

• Economist.com subscription $59• Print subscription $125• Print & web subscription $125

16084• Print & web subscription $125 84

# ofThe Economist Purchase Options

• Economist com subscription $59 68

# of People

(Ariely, 2008)

• Economist.com subscription $59• Print & web subscription $125

6832

What If This Happens in Healthcare?

• It l d h• It already happens....(Mamede et al., 2010; Croskerry, 2003; Klein, 2005)

• What if health IT can help?

U.S.’s Efforts on Health IT Adoption

??

“ We will make wider use of electronic records and ...We will make wider use of electronic records and

other health information technology, to help control

costs and reduce dangerous medical errors.”President George W. Bush

Source: Wikisource.org Image Source: Wikipedia.org

Sixth State of the Union Address, January 31, 2006

Public Policy in Informatics: A US’s Case

1991: IOM’s CPR Report published1991: IOM s CPR Report published

1996: HIPAA enacted

2000‐2001: IOM’s To Err Is Human & Crossing the Quality Chasm published

2004: George W. Bush’s Executive Order establishing ONCHIT (ONC)

2009‐2010: ARRA/HITECH Act & “Meaningful use” regulationsMeaningful use  regulations

U.S. Adoption of Health IT

Ambulatory (Hsiao et al, 2009) Hospitals (Jha et al, 2009)

Basic EHRs w/ notes 7.6%Comprehensive EHRs 1.5%pCPOE 17%

• U.S. lags behind other Western countries (Schoen et al, 2006;Jha et al, 2008)

• Money and misalignment of benefits is the biggest

reason

We Need “Change”

“...we need to upgrade our medical records by switching from a paper to y g p pan electronic system of record keeping...”

P id t B k ObPresident Barack ObamaJune 15, 2009

The Birth of “Meaningful Use”

“...Our recovery plan will invest in y pelectronic health records and new technology that will reduce errors, bring down costs, 

ensure privacy and save lives ”ensure privacy, and save lives.

President Barack ObamaAddress to Joint Session of CongressAddress to Joint Session of Congress

February 24, 2009

Source: WhiteHouse.gov

American Recovery & Reinvestment Act

• Contains HITECH Act

(Health Information Technology for Economic and ( gy

Clinical Health Act)

• ~ 20 billion dollars for Health IT investments 20 billion dollars for Health IT investments

• Incentives & penalties for providers

National Leadership

Offi f th N ti l C di t f H lth I f ti Office of the National Coordinator for Health Information

Technology (ONC -- formerly ONCHIT)

David Blumenthal, MD, MPPNational Coordinator for Health Information TechnologyHealth Information Technology (2009 - Present)

Photo courtesy of U.S. Department of Health & Human Services

What is in the HITECH Act?

(Blumenthal, 2010)

“Meaningful Use”g

“Meaningful Use”

of a PumpkinPumpkin

of a Pumpkin

Image Source & Idea Courtesy of Pat Wise at HIMSS, Oct. 2009

“Meaningful Use” of Health ITg

Stage 1Stage 1‐ Electronic capture of health information‐ Information sharing

St 3

Better Health

‐ Data reportingStage 2

Stage 3

Use of EHRs to

Use of EHRsto improve processes of 

EHRs to improve outcomes

care

(Blumenthal, 2010)

Health IT

A li tiApplications

Enterprise-wide Hospital IT

• Master Patient Index (MPI)

• Admit-Discharge-Transfer (ADT)

• Electronic Health Records (EHRs)

• C t i d Ph i i O d E t (CPOE)• Computerized Physician Order Entry (CPOE)

• Clinical Decision Support Systems (CDSSs)pp y

• Picture Archiving and Communication System (PACS)

• Nursing applications

l ( )• Enterprise Resource Planning (ERP)

Departmental IT

• Pharmacy applicationsy pp

• Laboratory Information System (LIS)

• Specialized applications (ER, OR, LR, Anesthesia,

Critical Care, Dietary Services, Blood Bank)Critical Care, Dietary Services, Blood Bank)

• Incident management & reporting system

EHRs & HISThe Challenge ‐ Knowing What It Means

Electronic Health Records (EHRs)

Hospital Information

Electronic Medical Records (EMRs)

Hospital Information System (HIS)

Records (EMRs)

Electronic Patient 

C B d

Records (EPRs)

Personal Health 

Clinical Information System (CIS)

Computer‐Based Patient Records 

(CPRs)

Records (PHRs)

EHR Systems

Just electronic documentation?

Diag‐nosis

History & PE

Treat‐ments ...

O d th h th l ?Or do they have other values?

Functions that Should Be Part of EHR Systems

• Computerized Medication Order Entry

• Computerized Laboratory Order Entry

• Computerized Laboratory Resultsp y

• Physician Notes

• P ti t D hi• Patient Demographics

• Problem Lists

• Medication Lists

• Discharge SummariesDischarge Summaries

• Diagnostic Test Results

• Radiologic Reports

(IOM, 2003; Blumenthal et al, 2006)

Computerized Physician Order Entry

ValuesValues

• No handwriting!!!• No handwriting!!!• Structured data entry: Completeness clarity Structured data entry: Completeness, clarity,

fewer mistakes (?)

• No transcription errors!

E i f CDSS• Entry point for CDSSs

• Streamlines workflow, increases efficiencyStreamlines workflow, increases efficiency

Clinical Decision Support Systems (CDSSs)

• The real place where most of the values of health IT can be achieved

– Expert systems

• Based on artificial intelligence, machine learning, rules, or statistics

• Examples: differential diagnoses, treatment options

– Alerts & reminders– Alerts & reminders

• Based on specified logical conditions

• Examples: drug-allergy checks, drug-drug interaction checks,

reminders for preventive services or certain actions (e.g. smoking

cessation), clinical practice guideline integration

– Evidence-based knowledge sources e.g. drug database, literature

– Simple UI designed to help clinical decision making

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

Attention

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference

DECISIONFrom a teaching slide by Don Connelly, 2006

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

AttentionAbnormal lab

highlights

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference

DECISION

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

AttentionDrug-Allergy

Checks

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference

DECISION

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

Drug-Drug Interaction

ChecksAttention

Checks

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference

DECISION

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

Clinical Practice

Attention Guideline Reminders

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference

DECISION

Clinical Decision Support Systems (CDSSs)

PATIENT

PerceptionCLINICIAN

Attention

External MemoryLong Term Memory WorkingMemory

Knowledge DataKnowledge DataMemory

Inference Diagnostic/Treatment Expert Systems

DECISION

Clinical Decision Support Systems (CDSSs)

• CDSS as a supplement or replacement of clinicians?

– The demise of the “Greek Oracle” model (Miller & Masarie, 1990)

The “Greek Oracle” Model

The “Fundamental Theorem”

(Friedman, 2009)

Clinical Decision Support Systems (CDSSs)

Some risks• Alert fatigue

Workarounds

Health IT for Medication Safety

Ordering Transcription Dispensing Administrationg p p g

C OAutomatic Electronic

CPOEAutomatic Medication Dispensing

Electronic Medication

Administration Records (e-MAR)

BarcodedBarcodedMedication Di i Medication

AdministrationDispensing

Health Information Exchange (HIE)

Government

Hospital A Hospital B

Government

Clinic CL b P ti t t HLab Patient at Home

4 Quadrants of Health IT

Strategic

HIEBusiness

Intelligence

CPOE

CDSS

g

ClinicalAdministrative

CPOE

EHRsVMILIS

EHRsERP

VMI

ADT

Operational (Theera-Ampornpunt [unpublished], 2010)

Health Informatics

As A FieldAs A Field

Biomedical/Health Informatics

• “[T]he field that is concerned with the optimal use of

information, often aided by the use of technology, to

improve individual health health care public health improve individual health, health care, public health,

and biomedical research” (Hersh, 2009)

• “[T]he application of the science of information as

d t l i t bl f bi di l data plus meaning to problems of biomedical

interest” (Bernstam et al, 2010)

Data-Information-Knowledge-Wisdom Pyramid

WisdomWisdom

KnowledgeKnowledge

Information

Data

Task-Oriented View

Collection Processing UtilizationCollection Processing Utilization

StorageCommunication/Dissemination/Presentation

M/B/H Informatics As A Field

(Shortliffe, 2002)

M/B/H Informatics and Other Fields

Social Sciences (Psychology Statistics &

Cognitive & Decision

(Psychology, Sociology, 

Linguistics, Law & Ethics)

Statistics & Research Methods

Medical Sciences &Decision 

ScienceSciences & Public Health

Engineering Management

Biomedical/Computer & Library Science,Biomedical/Health 

Informatics

Computer & Information Science

Library Science, Information Retrieval, KM

And More!

Balanced Focus of Informatics

People

Techno‐logyProcess

Informatics & Engineering

Process focusProcess-focus

• Industrial Engineering / Operations Research g g p

& Management / Business Process Reengineering

Technology-focus

• Computer & Software EngineeringComputer & Software Engineering

• Biomedical Engineering

• Electrical Engineering

Summary

• Healthcare will benefit from health IT through• Healthcare will benefit from health IT through

– Information deliveryy

– Process improvement

• The world is moving toward health IT

• H lth i f ti d ti f i i & • Health informatics needs expertise from engineering &

other fields

• Health informatics will be crucial to future’s healthcare

Let’s Build The Let s Build The

Next Generation’s

H lth !Healthcare!

References

• Bernstam EV, Smith JW, Johnson TR. What is biomedical informatics? J Biomed Inform. 2010 Feb;43(1):104‐10.

• Blumenthal D. Launching HITECH. N Engl J Med. 2010 Feb 4;362(5):382‐5.• Blumenthal D, DesRoches C, Donelan K, Ferris T, Jha A, Kaushal R, Rao S, Rosenbaum S. 

Health information technology in the United States: the information base for progress [Internet]. Princeton (NJ): Robert Wood Johnson Foundation; 2006

• Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. A d M d 2003 A 78(8) 775 80 81 A il bl fAcad Med. 2003 Aug;78(8):775‐80. 81 p. Available from: http://www.rwjf.org/files/publications/other/EHRReport0609.pdf

• Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc. 2009 Apr;16(2):169‐702009 Apr;16(2):169 70.

• Hersh W. A stimulus to define informatics and health information technology. BMC Med Inform Decis Mak. 2009;9:24.

• Hsiao C, Beatty PC, Hing ES, Woodwell DA. Electronic medical record/electronic health recordHsiao C, Beatty PC, Hing ES, Woodwell DA. Electronic medical record/electronic health record use by office‐based physicians: United States, 2008 and preliminary 2009 [Internet]. 2009 [cited 2010 Apr 12]; Available from: http://www.cdc.gov/nchs/data/hestat/emr_ehr/emr_ehr.pdf

References

• Institute of Medicine, Board on Health Care Services, Committee on Data Standards for f b l f l h l h d l [ ]Patient Safety. Key Capabilities of an electronic health record system: letter report [Internet]. 

Washington, DC: National Academy of Sciences; 2003. 31 p. Available from: http://www.nap.edu/catalog/10781.html

• Jha AK DesRoches CM Campbell EG Donelan K Rao SR Ferris TG Shields A Rosenbaum S• Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG, Shields A, Rosenbaum S, Blumenthal D. Use of electronic health records in U.S. hospitals. N Engl J Med. 2009;360(16):1628‐38.

• Jha AK, Doolan D, Grandt D, Scott T, Bates DW. The use of health information technology in , , , , gyseven nations. Int J Med Inform. 2008;77(12):848‐54.

• Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ. 2005 Apr 2;330(7494):781‐3.

• Mamede S, van Gog T, van den Berge K, Rikers RM, van Saase JL, van Guldener C, Schmidt HG. Effect of availability bias and reflective reasoning on diagnostic accuracy among internal medicine residents. JAMA. 2010 Sep 15:304(11):1198‐203.Mill RA M i FE Th d i f h "G k O l " d l f di l di i• Miller RA, Masarie FE. The demise of the "Greek Oracle" model for medical diagnostic systems. Methods Inf Med. 1990 Jan;29(1):1‐2. 

• Schoen C, Osborn R, Huynh PT, Doty M, Puegh J, Zapert K. On the front lines of care: primary care doctors’ office systems experiences and views in seven countries Health Affcare doctors  office systems, experiences, and views in seven countries. Health Aff(Millwood). 2006;25(6):w555‐71.

• Shortliffe EH. JBI status report. Journal of Biomedical Informatics. 2002 Oct;35(5‐6):279‐80.