Presented at the Faculty of Medicine, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand on April 1, 2019

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Electronic Health Records (EHRs) &
Clinical Decision Support Systems (CDS)
Nawanan Theera-Ampornpunt, M.D., Ph.D.
April 1, 2019
www.SlideShare.net/Nawanan

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2003 M.D. (First-Class Honors)
2011 Ph.D. (Health Informatics), Univ. of Minnesota
Assistant Dean for Informatics
Lecturer, Department of Community Medicine
Faculty of Medicine Ramathibodi Hospital
Mahidol University
Interests: Health IT for Quality of Care, Social Media
IT Management, Security & Privacy
nawanan.the@mahidol.ac.th
SlideShare.net/Nawanan
นพ.นวนรรน ธีระอัมพรพันธุ์ Dr.Nawanan Theera-Ampornpunt
Introduction

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▪ An Informatics Doctor
▪ Digital Health Transformation
▪ Health IT, Smart Hospital & CDS
Outline

4. 4
An Informatics Doctor:
A Real-Life Personal Story

5. 5https://www.youtube.com/watch?v=MuoDaJAqQ6c

6. 6
Class Discussion
What ideas come to mind?
Digital Health
Transformation
When you think of

7. 7https://medium.com/@marwantarek/it-is-the-perfect-storm-ai-cloud-bots-iot-etc-4b7cbb0481bc

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http://www.ibtimes.com/google-deepminds-alphago-program-defeats-human-go-champion-first-time-ever-2283700
http://deepmind.com/ http://socialmediab2b.com
An Era of Smart Machines

9. 9‹#›englishmoviez.com
Rise of the Machines?

10. 10
Digitizing Healthcare?
http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital

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“Big data is like teenage sex:
everyone talks about it,
nobody really knows how to do it,
everyone thinks everyone else is doing it,
so everyone claims they are doing it...”
-- Dan Ariely @danariely (2013)
Substitute “Big data” with “AI”, “Blockchain”, “IoT”
of your choice.
-- Nawanan Theera-Ampornpunt (2018)

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Health &
Health Information

13. 13
Let’s take a look at
these pictures...

14. 14‹#›Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH)
“Smart” Manufacturing

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Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทย์โมเดลทางธุรกิจ/
“Smart” Banking

16. 16‹#›ER - Image Source: nj.com
Healthcare (On TV)

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(At an undisclosed hospital)
Healthcare (Reality)

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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 (Yet) “Smart”?

19. 19
“Smart Hospital”

20. 20https://www.youtube.com/watch?v=gxz9ZVvduGc
Connecting People to a Healthy Future With
Personalized Care – Kaiser Permanente

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Back to
something simple...

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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)
What Clinicians Want?

23. 23
Why Aren’t We Talk About These Words?
http://hcca-act.blogspot.com/2011/07/reflections-on-patient-centred-care.html

24. 24
The Goal of Health Care
The answer is already obvious...
“Health”
“Care”

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• 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.
High Quality Care

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Information Is Everywhere in Healthcare

27. 27
27
27
WHO (2009)
Components of Health Systems

28. 28
Health IT
Health
Information
Technology
Goal
Value-Add
Means

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Hospital Information System (HIS) Computerized Physician Order Entry (CPOE)
Electronic
Health
Records
(EHRs)
Picture Archiving and
Communication System
(PACS)
Various Forms of Health IT

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m-Health
Health Information
Exchange (HIE)
Biosurveillance
Telemedicine &
Telehealth
Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, Inc.
Personal Health Records
(PHRs)
Health IT Beyond Hospitals

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Ordering Transcription Dispensing Administration
Computerized
Physician
Order Entry
(CPOE)
Automatic
Medication
Dispensing
Electronic
Medication
Administration
Records
(e-MAR)
Barcoded
Medication
Administration
Barcoded
Medication
Dispensing
Health IT for Medication Safety

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Hospital A Hospital B
Clinic D
Policymakers
Patient at
Home
Hospital C
HIE Platform
Health Information Exchange (HIE)

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• Safe
–Drug allergies
–Medication Reconciliation
• Timely
–Complete information at point of
care
• Effective
–Better clinical decision-making
Being Smart in Healthcare

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• Efficient
–Faster care
–Time & cost savings
–Reducing unnecessary tests
• Equitable
–Access to providers & knowledge
• Patient-Centered
–Empowerment & better self-care
Being Smart in Healthcare

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(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports

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• 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
Summary of These Reports

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Image 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

38. 38‹#›Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital
To Err is Human 2: Memory

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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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• 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 “Alerts & Reminders”
Reducing Errors through Alerts & 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

44. 44‹#›Image 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
Other CDS Examples

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Image 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

48. 48‹#›Image 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
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
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
Diagnostic/Treatment
Expert Systems (e.g. AI)

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• CDS 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
Clinical Decision Support Systems (CDS)

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▪ An informatics doctor thinks like a doctor but
designs IT applications to help other doctors
▪ Digital Health Transformation is, first and
foremost, about Health Care, not digital
technologies
▪ EHRs & CDS are examples of useful Health IT
▪ Human decisions are still necessary in
healthcare, so many health IT should work to
support human decisions as CDS
Summary