ICT in Healthcare

ICT in Healthcare

Nawanan Theera-Ampornpunt

October 21, 2016

2

2003 M.D. (First-Class Honors)

2011 Ph.D. (Health Informatics), Univ. of Minnesota

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

[email protected]

SlideShare.net/Nawanan

นวนรรน ธรีะอมัพรพนัธุ์ (Nawanan Theera-Ampornpunt)

Line ID: NawananT

Introduction

3

The Road to Digitizing Healthcare

What is a “Smart Hospital”?

Toward a “Smart” Hospital

Outline

4

Health &

Health Information

5

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

6Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH)

“Smart” Manufacturing

7Image Sources: http://isarapost.net/home/?p=17760

http://www.telecomjournalthailand.com/ตอบโจทยโ์มเดลทางธรุกจิ/

“Smart” Banking

8ER - Image Source: nj.com

Healthcare (On TV)

9

(At an undisclosed hospital)

Healthcare (Reality)

10

• 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”?

11

But...Are We That Different?

Input Process Output

Transfer

Banking

Value-Add- Security- Convenience- Customer Service

Location A Location B

12


Assembling

Manufacturing

Raw Materials Finished Goods

Value-Add- Innovation- Design- QC


13


Patient Care

Health care

Sick Patient Well Patient

Value-Add- Technology & medications- Clinical knowledge & skilled providers- Quality of care; process improvement- Customer service- Information


14

• Large variations & contextual dependence


Patient Presentation

Decision-Making

Biological Responses

Standardizing Healthcare

15

The World of Smart Machines

Image Sources: http://www.ibtimes.com/google-deepminds-alphago-

program-defeats-human-go-champion-first-time-ever-2283700

http://deepmind.com/

16

Digitizing Healthcare

Image Source: http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital

17

“To computerize the hospital”

“To go paperless”

“To become a Digital Hospital”

“To Have EHRs”

Why Adopting Health IT?

18

• “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)

Some “Smart” Quotes

19

Being Smart #1:

Stop Your

“Drooling Reflex”!!

20

Being Smart #2:

Focus on Information &

Process Improvement,

Not Technology

21

If not “Digital Hospital” or “Paperless Hospital”

Then What Should We Aspire to Be?

“Smart Hospital”

23

So How is a “Smart Hospital”

Different from a Digital orPaperless Hospital?

24

Healthcare 4.0?

25

Healthcare 1.0• Thai Traditional Medicine in the Ancient Times

Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public HealthImage & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.htmlhttp://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html

การย่อยขนาดตัวยาสมุนไพร โดยใช้ครกต าและหินบดยาของโรงศิริราชพยาบาล (ปัจจุบันคือ โรงพยาบาลศิริราช)

คนไทยสมัยก่อนมักให้บุคคลในครอบครัวบีบนวดได้

http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html

http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html

26

Healthcare 2.0• Modern (Western) Medicine




27

Healthcare 3.0• Quality-Driven Healthcare




28

Healthcare 4.0• Smart Healthcare & Smart Hospital




29

So What IsSmart Healthcare?

30

Smart Healthcare For Policymakers?

Image Source: http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99

http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99

31

Smart Healthcare For Health Promoters?

Image Source: http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf

http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf

32

Smart Healthcare For Clinicians?

Image Source: http://www.medscape.com/viewarticle/780298

http://www.medscape.com/viewarticle/780298

33

Smart Healthcare For Patients & Consumers?

Image Source: Agence France-Presse/Getty Images

34

So What Exactly Is Smart Healthcare?

Image Source: http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg

http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg

35




Outline

36

Microsoft Health Future Vision

https://www.microsoft.com/en-us/download/details.aspx?id=12801

37

Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente

https://www.youtube.com/watch?v=gxz9ZVvduGc

38

Back to something simple...

39

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?

40

• 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

41

Information is Everywhere in Healthcare

42

“Information” in Medicine

Shortliffe EH. Biomedical informatics in the education of physicians. JAMA.

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

43

43

WHO (2009)

Components of Health Systems

44

44

WHO (2009)

WHO Health System Framework

45

• Safe

–Drug allergies

–Medication Reconciliation

• Timely

–Complete information at point of

care

• Effective

–Better clinical decision-making

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

Being “Smart” in Healthcare

46

• Efficient

–Faster care

–Time & cost savings

–Reducing unnecessary tests

• Equitable

–Access to providers & knowledge

• Patient-Centered

–Empowerment & better self-care

Being “Smart” in Healthcare

47

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

Landmark Institute of Medicine Reports

48

• 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 errors

Patient Safety

49

Summary of These Reports

• 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

50Image 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

51Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital

To Err is Human 2: Memory

52

• Cognitive Errors - Example: Decoy Pricing

The Economist Purchase Options

• Economist.com subscription $59

• Print subscription $125

• Print & web subscription $125

Ariely (2008)

16

0

84

The Economist Purchase Options

• Economist.com subscription $59

• Print & web subscription $125

68

32

# of

People

# of

People

To Err is Human 3: Cognition

53

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

2005; Croskerry, 2013)

What If This Happens in Healthcare?

54Klein 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”

Cognitive Biases in Healthcare

55

• Medication Errors

–Drug Allergies

–Drug Interactions

• Ineffective or inappropriate treatment

• Redundant orders

• Failure to follow clinical practice guidelines

Common Errors

56

Being Smart #3:

“To Err is Human”

57

External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

58

Example of “Alerts & Reminders”

Reducing Errors through “Alerts & Reminders”

59

Why We Need ICT

in Healthcare?

#1: Because information is

everywhere in healthcare

60

Why We Need ICT in Healthcare?

#2: Because healthcare is error-prone and technology

can help

61http://www.dplindbenchmark.com/wp-content/uploads/2013/02/HHRI-Our-Health-Care-River.pdf

Fragmented Healthcare

62

Why We Need ICT

in Healthcare?

#3: Because access to

high-quality patient information

should improve care

63

Why We Need ICT in Healthcare?

#4: Because healthcare at all levels is fragmented &

in need of process improvement

64

Documented Values of Health IT

• Guideline adherence

• Better documentation

• Practitioner decision making or process of care

• Medication safety

• Patient surveillance & monitoring

• Patient education/reminder

65

Being Smart #4:

Link IT Values to

Quality (Including Safety)

66

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: Dr. Boonchai Kijsanayotin

Health IT

67

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 & Dr. Boonchai Kijsanayotin

eHealth

68

eHealth Health IT

Slide adapted from: Dr. Boonchai Kijsanayotin

eHealth & Health IT

69

Health

Information

Technology

Goal

Value-Add

Tools

Health IT: What’s in a Word?

70

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

Electronic Health

Records (EHRs)

Picture Archiving and Communication System

(PACS)

Various Forms of Health IT

71

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

72

Health IT for Medication Safety

Ordering Transcription Dispensing Administration

CPOEAutomatic Medication Dispensing

Electronic Medication

Administration Records (e-MAR)

BarcodedMedication

Administration

BarcodedMedication Dispensing

73

Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Health Information Exchange

74

My Life-Long Dream...

75WHO & ITU

Achieving Health Information Exchange (HIE)

76

• The Large N Interfaces Problem

N = 2, Interface = 1

# Interfaces = N(N-1)/2



N = 100, Interface = 4,950

Standards: Why?

77

นวนรรน ธีระอัมพรพันธุ์. ต ำนำนควำมเชื่อและข้อเท็จจริงเกี่ยวกับมำตรฐำนสำรสนเทศทำงสุขภำพ. ใน: Health Data Standards Expo: From Reimbursement to Clinical Excellence; 2011 Aug 8-9; Bangkok, Thailand. Bangkok (Thailand): Mahidol University, Faculty of Medicine Ramathibodi Hospital; 2011 Aug.

http://www.slideshare.net/nawanan/myths-and-truths-on-health-information-standards

Myths & Truths on Standards

78

Myths

• We don’t need standards

• Standards are IT people’s jobs

• We should exclude vendors from this

• We need the same software to share data

• We need to always adopt international standards

• We need to always use local standards

Theera-Ampornpunt (2011)

Myths & Truths on Standards

79

Being Smart #5:

Go for Systems that Use

Standards, Not a Unified,

Conquer-the-World System

Image Source: http://www.denofgeek.com/movies/avengers/37236/why-loki-was-cut-from-avengers-age-of-ultron

80




Outline

81

A Smart Machine: DeepMind

Image Sources: http://www.ibtimes.com/google-deepminds-alphago-

program-defeats-human-go-champion-first-time-ever-2283700

http://deepmind.com/

82Image Source: socialmediab2b.com

Another Smart Machine: IBM’s Watson

83Image Source: englishmoviez.com

Rise of the Machines?

84Image Source: amazon.com

Smart Phones, Dumb People?

85

Smart Hospital,

Dumb...?

86

Clinical Decision Support Systems

• 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

87

Being Smart #6:

Don’t Replace Human Users.

Use ICT to Help Them Perform Smarter & Better.

88

Some Risks of Clinical Decision Support Systems

• Alert Fatigue

Unintended Consequences of Health IT

89

Workarounds

Unintended Consequences of Health IT

90

Being Smart #7:

Health IT Also Have

Risks &

Unintended Consequences

91

Balanced Focus of Informatics

Technology

ProcessPeople

92

Being Smart #8:

Balance Your Focus (People, Process, Technology)

93The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing

The destination

The boatThe sailor(s) &

people on board

The tailwind The headwind

The direction

The speed

The past journey

The sea

The sail

The current location

IT & Organizational Context

http://en.wikipedia.org/wiki/Sailing

94

Being Smart #9:

Know Your Context &

Align IT with that Context

95

A 900-Bed University Hospital

Vision To be a leading hospital in Asia with excellence in healthcare services, education, and research

A 200-Bed Private Hospital

Vision To be a leading High Tech High Touch hospital in Thailand

Vision, Mission & IT Strategies

96Carr (2004) Carr (2003)

IT as “The Sail”

97

Strategic

Operational

ClinicalAdministrative

LIS

Health Information ExchangeBusiness Intelligence

Word Processor

Social Media

PACS

4 Quadrants of Hospital IT

Personal Health Records

Clinical Decision Support Systems

Computerized Physician Order Entry

Electronic Health Records

Admission-Discharge-Transfer

Master Patient Index

Enterprise Resource Planning

Vendor-Managed Inventory

Customer Relationship Management

98

Being Smart #10:

Identify Your

Strategic IT Assets

99

People

Techno-logy

Process

“The Sailors”

100

A 900-Bed University Hospital• Average age of personnel at 42

years (range 20-65)• IT department consists of new,

young members and senior members who developed the first version of its systems

• Doctors are highly individualistic, most also practice in private hospitals, high turn-over rate

• Nurses and other professions often view doctors as hospital’s “elites” and often have heated debates with them

A 200-Bed Private Hospital

• Average age of personnel at 32 years (range 20-57)

• Strong IT department• Doctors typically don’t interact

with other staff, income is the main motivator

• Executives are highly respected by all professions as visionary and high-performing

“The Sailors”

101Ash et al. (2003)

The “Special People”

102Ash et al. (2003)

• Administrative Leadership Level

– CEO• Provides top level

support and vision• Holds steadfast• Connects with the

staff• Listens• Champions

– CIO• Selects champions• Gains support• Possesses vision• Maintains a thick skin

– CMIO• Interprets• Possesses vision• Maintains a thick skin• Influences peers• Supports the clinical support

staff• Champions


103Ash et al. (2003)

• Clinical Leadership Level– Champions

• Necessary• Hold steadfast• Influence peers• Understand other

physicians

– Opinion leaders• Provide a balanced

view• Influence peers

– Curmudgeons• “Skeptic who is

usually quite vocal in his or her disdain of the system”

• Provide feedback• Furnish leadership

– Clinical advisory committees

• Solve problems• Connect units


104Ash et al. (2003)

• Bridger/Support level

– Trainers & support team

• Necessary• Provide help at the

elbow• Make changes• Provide training• Test the systems

– Skills• Possess clinical

backgrounds• Gain skills on the

job• Show patience,

tenacity, and assertiveness


105

Being Smart #11:

Manage Your

“Special People” Well

106

A True Story of Failure to

Involve Users in Hospital IT

Implementation

107

Being Smart #12:

Involve Users Early &

Intensively in Your Process

108Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle

http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp

Gartner Hype Cycle

http://en.wikipedia.org/wiki/Hype_cycle

http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp

109Rogers (2003)

Rogers’ Diffusion of Innovations: Adoption Curve

110

• Communications of project plans & progresses

• Workflow considerations

• Management support of IT projects

• Common visions

• Shared commitment

• Multidisciplinary user involvement

• Project management

• Training

• Innovativeness

• Organizational learning

Theera-Ampornpunt (2009, 2011)

Success Factors of Hospital IT Adoption

111

Being Smart #13:

Work Smartly with

Smart People

112

To become a smart hospital, you must

• Know what is “smart” all about

• Know how to use smart machinestogether with smart people

• Manage both of them smartly

Summary

113

2003 M.D. (First-Class Honors)

2011 Ph.D. (Health Informatics), Univ. of Minnesota

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

[email protected]

SlideShare.net/Nawanan

นวนรรน ธรีะอมัพรพนัธุ์ (Nawanan Theera-Ampornpunt)

Line ID: NawananT

Q&A