ICT Applications for Healthcare

ICT Applications for HealthcareMUICT Seminar

Nawanan Theera-Ampornpunt, M.D., Ph.D.Faculty of Medicine Ramathibodi Hospital

February 19, 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 MedicineFaculty of Medicine Ramathibodi HospitalMahidol University

[email protected]://groups.google.com/group/ThaiHealthIT

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Outline

• Healthcare & Information• Why We Need ICT in Healthcare• Health IT & eHealth• Some ICT Applications• A Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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Let’s take a look at these pictures...

5Image Source: Guardian.co.uk

Manufacturing

6Image Source: http://www.oknation.net/blog/phuketpost/2013/10/19/entry-3

Banking

7ER - Image Source: nj.com

Healthcare (on TV)

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Healthcare

(At an undisclosed nearby hospital)

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• Life-or-Death• Difficult to automate human decisions

– Nature of business– Many & varied stakeholders– Evolving standards of care

• Fragmented, poorly-coordinated systems• Large, ever-growing & changing body of

knowledge• High volume, low resources, little time

Why Healthcare Isn’t Like Any Others

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Back to 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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Outline

“Information” in Healthcare• Why We Need ICT in Healthcare• Health IT & eHealth• Some ICT Applications• A Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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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

20Image 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

21Image 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

The Economist Purchase Options

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

Ariely (2008)

16084

The Economist Purchase Options

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

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# of People

# of People

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• It already happens....(Mamede et al., 2010; Croskerry, 2003; Klein, 2005; Croskerry, 2013)

What If This Happens in Healthcare?

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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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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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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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• Medication Errors

– Drug Allergies

– Drug Interactions

• Ineffective or inappropriate treatment

• Redundant orders

• Failure to follow clinical practice guidelines

Common Errors

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#2: Because healthcare is error-prone and technology

can help

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Fragmented Healthcare

http://www.dplindbenchmark.com/wp-content/uploads/2013/02/HHRI-Our-Health-Care-River.pdf

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#3: Because access to high-quality patient

information improves care

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#4: Because healthcare at all levels is fragmented &

in need of process improvement

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Outline

“Information” in HealthcareWhy We Need ICT in Healthcare• Health IT & eHealth• Some ICT Applications• A Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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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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Use of information and communications technology (ICT) for health; Including

• Treating patients• Conducting research• Educating the health workforce• Tracking diseases• Monitoring public health.

Sources: 1) WHO Global Observatory of eHealth (GOe) (www.who.int/goe)2) World Health Assembly, 2005. Resolution WHA58.28

Slide adapted from: Mark Landry, WHO WPRO & Boonchai Kijsanayotin

eHealth

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eHealth Health IT


eHealth & Health IT

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HIS

All information about health

eHealthHMIS

mHealth

Tele-medicine

Slide adapted from: Karl Brown (Rockefeller Foundation), via Boonchai Kijsanayotin

More Terms

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HealthInformationTechnology

Goal

Value-Add

Tools

Health IT: What’s in a Word?

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All components are essential All components should be balanced


eHealth Components (WHO-ITU Model)

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eHealth in Thailand: The current status. Stud Health Technol Inform 2010;160:376–80, Presented at MedInfo2010 South Africa

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Thailand’s eHealth: 2010

40Slide adapted from: Boonchai Kijsanayotin

Thailand: Unbalanced Development

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eHealth Applications

Enabling Policies & Strategies

Foundation Policies & Strategies

• Services• Applications• Software

• Standards & Interoperability

• Capability Building

• Leadership & Governance

• Legislation & Policy• Strategy & Investment • Infrastructure


eHealth Development Model

42Slide adapted from: Boonchai Kijsanayotin

Thailand’s eHealth Development

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Silo-type systems Little integration and interoperability Mostly aim for administration and management 40% of work-hours spent on managing reports and

documents Lack of national leadership and governance body Inadequate HIS foundations development


Thailand’s eHealth Situation

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Outline

“Information” in HealthcareWhy We Need ICT in HealthcareHealth IT & eHealth• Some ICT Applications• A Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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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)

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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• 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

57Image 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

59Image 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

61Image 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

WorkingMemory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

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Abnormal lab highlights


External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIANDrug-Allergy

Checks

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN



Drug-Drug Interaction

Checks

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN



Clinical Practice Guideline

Reminders

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External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN



Diagnostic/Treatment Expert Systems

68Image Source: socialmediab2b.com

IBM’s Watson

69Image Source: englishmoviez.com

Rise of the Machines?

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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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Outline

“Information” in HealthcareWhy We Need ICT in HealthcareHealth IT & eHealthSome ICT Applications• A Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Health Information Exchange (HIE)

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Standards & Interoperability in HIE

Technical Standards (TCP/IP, encryption,

security)

Exchange Standards (HL7 v.2, HL7 v.3 Messaging, HL7 CDA,

DICOM)

Vocabularies, Terminologies, Coding Systems (ICD-10, ICD-9,

CPT, SNOMED CT, LOINC)

Information Models (HL7 v.3 RIM, ASTM CCR, HL7 CCD)

Standard Data Sets

Functional Standards (HL7 EHRFunctional Specifications)

Some may be hybrid: e.g. HL7 v.3, HL7 CCD

Unique ID

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Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Message

Message

Message

MessageMessage

Message Exchange

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• As the second formally-trained M.D., Ph.D. in Health Informatics in Thailand, I am driven and socially obligated...

• To promote personal & population health through establishment of sustainable foundations for eHealth and strengthening of the field of Biomedical and Health Informatics in Thailand before my end of life.

• HIE is at the heart of my life-long dream

My “Mission in Life”

78http://www.ega.or.th/Content.aspx?m_id=94

Cloud: To Go or Not To Go?

79WHO mHealth Report: http://www.who.int/goe/publications/goe_mhealth_web.pdf

Roles of mHealth in Future Healthcare

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Outline

“Information” in HealthcareWhy We Need ICT in HealthcareHealth IT & eHealthSome ICT ApplicationsA Dream for Healthcare• Food for Thought for ICT Folks• Q&A

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• What will the future be for healthcare?• Where’s the roles of ICT professionals in

future healthcare?• How to leverage different perspectives &

strengths to achieve common goals?• How will we shape future healthcare

together?

Some Food for Thought

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Patients Are Counting on Us...

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

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Intelligent & helpful robots

Intelligent humanistic robots in a human world

Machines that replace humans for a “better” world

HAL 9000 Data David NS-5

Dangerous killer machines

What ICT Will It Be?

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

• Thai Health Informatics Academy

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Outline

“Information” in HealthcareWhy We Need ICT in HealthcareHealth IT & eHealthSome ICT ApplicationsA Dream for HealthcareFood for Thought for ICT Folks• Q&A

ICT Applications for Healthcare

Health & Medicine

Transcript of ICT Applications for Healthcare