Overview of

Hospital Information Systems

Nawanan Theera-Ampornpunt, M.D., Ph.D.

Department of Community Medicine

Faculty of Medicine Ramathibodi Hospital

March 3, 2014

SlideShare.net/Nawanan

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A Bit About Myself...

2003 M.D. (First-Class Honors) (Ramathibodi)

2009 M.S. in Health Informatics (U of MN)

2011 Ph.D. in Health Informatics (U of MN)

2012 Certified HL7 CDA Specialist

• Deputy Executive Director for Informatics (CIO/CMIO)

Chakri Naruebodindra Medical Institute

• Lecturer, Department of Community Medicine

Faculty of Medicine Ramathibodi Hospital

Mahidol University

nawanan.the@mahidol.ac.th

http://groups.google.com/group/ThaiHealthIT

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Outline

• Healthcare & Information

• Why We Need ICT in Healthcare

• Health IT

• Hospital Information Systems

• Health Information Exchange

• Q&A

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Let’s start with

something simple...

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What Clinicians Want?

To treat & to care for their patients to their best abilities, given limited time & resources

Image Source: http://en.wikipedia.org/wiki/File:Newborn_Examination_1967.jpg (Nevit Dilmen)

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High Quality Care

• Safe

• Timely

• Effective

• Patient-Centered

• Efficient

• Equitable

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.

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Information is Everywhere in Healthcare

Shortliffe EH. Biomedical informatics in the education of

physicians. JAMA. 2010 Sep 15;304(11):1227-8.

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“Information” in Medicine

Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.

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Why We Need ICT

in Healthcare?

#1: Because information is

everywhere in healthcare

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(IOM, 2001)(IOM, 2000) (IOM, 2011)

Landmark IOM Reports

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Patient Safety

• To Err is Human (IOM, 2000) reported

that:

– 44,000 to 98,000 people die in U.S.

hospitals each year as a result of

preventable medical mistakes

– Mistakes cost U.S. hospitals $17 billion to

$29 billion yearly

– Individual errors are not the main problem

– Faulty systems, processes, and other

conditions lead to preventable errorsHealth IT Workforce Curriculum Version

3.0/Spring 2012 Introduction to Healthcare and Public Health in the US: Regulating Healthcare - Lecture d

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IOM Reports Summary

• Humans are not perfect and are bound to

make errors

• Highlight problems in U.S. health care

system that systematically contributes to

medical errors and poor quality

• Recommends reform

• Health IT plays a role in improving patient

safety

13Image Source: (Left) http://docwhisperer.wordpress.com/2007/05/31/sleepy-heads/

(Right) http://graphics8.nytimes.com/images/2008/12/05/health/chen_600.jpg

To Err is Human 1: Attention

14Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University

To Err is Human 2: Memory

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To Err is Human 3: Cognition

• Cognitive Errors - Example: Decoy Pricing

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Ariely (2008)

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0

84

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68

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# of

People

# of

People

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Cognitive Biases in Healthcare

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

“Everyone makes mistakes. But our

reliance on cognitive processes prone to

bias makes treatment errors more likely

than we think”

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Cognitive Biases in Healthcare

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.

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Cognitive Biases in Healthcare

Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them.

Acad Med. 2003 Aug;78(8):775-80.

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• Medication Errors

– Drug Allergies

– Drug Interactions

• Ineffective or inappropriate treatment

• Redundant orders

• Failure to follow clinical practice guidelines

Common Errors

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Why We Need ICT

in Healthcare?

#2: Because healthcare is

error-prone and technology

can help

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Why We Need ICT

in Healthcare?

#3: Because access to

high-quality patient

information improves care

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Use of information and communications

technology (ICT) in health & healthcare

settings

Source: The Health Resources and Services Administration, Department of

Health and Human Service, USA

Slide adapted from: Boonchai Kijsanayotin

Health IT

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Health

Information

Technology

Goal

Value-Add

Tools

Health IT: What’s in a Word?

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• Patient’s Health

• Population’s Health

• Organization’s Health (Quality, Reputation & Finance)

“Health” in “Health IT”

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

Electronic

Health

Records

(EHRs)

Picture Archiving and

Communication System

(PACS)

Various Forms of Health IT

Screenshot Images from Faculty of Medicine Ramathibodi Hospital, Mahidol University

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mHealth

Biosurveillance

Telemedicine &

Telehealth

Images from Apple Inc., Geekzone.co.nz, Google, HealthVault.com and American Telecare, Inc.

Personal Health Records

(PHRs) and Patient Portals

Still Many Other Forms of Health IT

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• Guideline adherence

• Better documentation

• Practitioner decision making or

process of care

• Medication safety

• Patient surveillance & monitoring

• Patient education/reminder

Values of Health IT

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• Master Patient Index (MPI)

• Admit-Discharge-Transfer (ADT)

• Electronic Health Records (EHRs)

• Computerized Physician Order Entry (CPOE)

• Clinical Decision Support Systems (CDS)

• Picture Archiving and Communication System (PACS)

• Nursing applications

• Enterprise Resource Planning (ERP) - Finance, Materials Management, Human Resources

Enterprise-wide Hospital IT

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• Pharmacy applications

• Laboratory Information System (LIS)

• Radiology Information System (RIS)

• Specialized applications (ER, OR, LR,

Anesthesia, Critical Care, Dietary

Services, Blood Bank)

• Incident management & reporting system

Departmental IT in Hospitals

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The Challenge - Knowing What It Means

Electronic Medical

Records (EMRs)

Computer-Based

Patient Records

(CPRs)

Electronic Patient

Records (EPRs)

Electronic Health

Records (EHRs)

Personal Health

Records (PHRs)

Hospital

Information System

(HIS)

Clinical Information

System (CIS)

EHRs & HIS

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Computerized Provider Order Entry (CPOE)

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Values

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

fewer mistakes (?)

• No transcription errors!

• Streamlines workflow, increases efficiency

Computerized Provider Order Entry (CPOE)

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Ordering Transcription Dispensing Administration

CPOEAutomatic

Medication

Dispensing

Electronic

Medication

Administration

Records

(e-MAR)

Barcoded

Medication

Administration

Barcoded

Medication

Dispensing

Stages of Medication Process

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• 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(Shortliffe, 1976)

Clinical Decision Support Systems (CDS)

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– Alerts & reminders

• Based on specified logical conditions

• Examples:

– Drug-allergy checks

– Drug-drug interaction checks

– Reminders for preventive services

– Clinical practice guideline integration

Clinical Decision Support Systems (CDS)

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Example of “Reminders”

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• Reference information or evidence-

based knowledge sources

– Drug reference databases

– Textbooks & journals

– Online literature (e.g. PubMed)

– Tools that help users easily access

references (e.g. Infobuttons)

More CDS Examples

38Image Source: https://webcis.nyp.org/webcisdocs/what-are-infobuttons.html

Infobuttons

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• Pre-defined documents

– Order sets, personalized “favorites”

– Templates for clinical notes

– Checklists

– Forms

• Can be either computer-based or

paper-based

Other CDS Examples

40Image Source: http://www.hospitalmedicine.org/ResourceRoomRedesign/CSSSIS/html/06Reliable/SSI/Order.cfm

Order Sets

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• Simple UI designed to help clinical

decision making

– Abnormal lab highlights

– Graphs/visualizations for lab results

– Filters & sorting functions

Other CDS Examples

42Image Source: http://geekdoctor.blogspot.com/2008/04/designing-ideal-electronic-health.html

Abnormal Lab Highlights

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

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Abnormal lab

highlights

Clinical Decision Making

External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIAN

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Clinical Decision Making

External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIANDrug-Allergy

Checks

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

Drug-Drug

Interaction

Checks

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

Clinical Practice

Guideline

Reminders

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

Working

Memory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

Diagnostic/Treatment

Expert Systems

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• CDSS as a replacement or supplement of

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

The “Greek Oracle” Model

The “Fundamental Theorem” Model

Friedman (2009)

Wrong Assumption

Correct Assumption

Proper Roles of CDS

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Some risks

• Alert fatigue

Unintended Consequences of Health IT

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Workarounds

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Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Health Information Exchange (HIE)

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Outline

Healthcare & Information

Why We Need ICT in Healthcare

Health IT

Hospital Information Systems

Health Information Exchange

• Q&A

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Patients Are Counting on Us...

Image Source: http://www.flickr.com/photos/childrensalliance/3191862260/

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More Resources

• American Medical Informatics Association (AMIA)

www.amia.org

• International Medical Informatics Association (IMIA)

www.imia.org

• Thai Medical Informatics Association (TMI)

www.tmi.or.th

• Asia eHealth Information Network (AeHIN)

www.aehin.org

• ThaiHealthIT Google Groups Mailing List

http://groups.google.com/group/ThaiHealthIT

• Thai Health Informatics Academy