use of ict in healthcare

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บรรยาย ณ กฟผ.นพ.นวนรรน ธีระอัมพรพนัธุ์

17 มีนาคม 2560

2

2546 แพทยศาสตรบัณฑิต2554 Ph.D. (Health Informatics), Univ. of Minnesota

ผู้ช่วยคณบดีฝ่ายนโยบายและสารสนเทศอาจารย์ ภาควิชาเวชศาสตร์ชุมชนคณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล

ความสนใจ: Health IT for Quality of Care,

IT Management, Security & Privacy

nawanan.the@mahidol.ac.th

SlideShare.net/Nawanan

แนะน าตัว

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/ตอบโจทย์โมเดลทางธุรกิจ/

“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?

InputProces

sOutput

Transfer

Banking

Value-Add- Security- Convenience- Customer Service

Location A Location B

12

InputProces

sOutput

Assembling

Manufacturing

Raw Materials Finished Goods

Value-Add- Innovation- Design- QC

But...Are We That Different?

13

InputProces

sOutput

Patient Care

Health care

Sick Patient Well Patient

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

But...Are We That Different?

14

• Large variations & contextual dependence

InputProces

sOutput

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

ถ้าไม่เป็น “Digital Hospital” หรือ “Paperless Hospital”

แล้วจะให้เราเป็นอะไร?

“Smart Hospital”

23

แล้ว “Smart Hospital” ต่างจาก Digital หรือ

Paperless Hospital ตรงไหน?

24

The Road to Digitizing Healthcare

What is a “Smart Hospital”?

Toward a “Smart” Hospital

Outline

25

Microsoft Health Future Vision

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

26

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

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

27

Back to something simple...

28

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?

29

• 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

30

Information is Everywhere in Healthcare

31

31

WHO (2009)

Components of Health Systems

32

32

WHO (2009)

WHO Health System Framework

33

• 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

34

• Efficient

–Faster care

–Time & cost savings

–Reducing unnecessary tests

• Equitable

–Access to providers & knowledge

• Patient-Centered

–Empowerment & better self-care

Being “Smart” in Healthcare

35

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

Landmark Institute of Medicine Reports

36

• 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

37

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

38Image 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

39Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital

To Err is Human 2: Memory

40

• 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

41

• Medication Errors

–Drug Allergies

–Drug Interactions

• Ineffective or inappropriate treatment

• Redundant orders

• Failure to follow clinical practice guidelines

Common Errors

42

Being Smart #3:

“To Err is Human”

43

External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

44

Example of “Alerts & Reminders”

Reducing Errors through “Alerts & Reminders”

45

Documented Values of Health IT

• Guideline adherence

• Better documentation

• Practitioner decision making or process of care

• Medication safety

• Patient surveillance & monitoring

• Patient education/reminder

46

Being Smart #4:

Link IT Values to

Quality (Including Safety)

47

Health

Information

Technology

Goal

Value-Add

Tools

Health IT: What’s in a Word?

48

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

Electronic Health

Records (EHRs)

Picture Archiving and Communication System

(PACS)

Various Forms of Health IT

49

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

50

Health IT for Medication Safety

Ordering Transcription Dispensing Administration

CPOEAutomatic Medication Dispensing

Electronic Medication

Administration Records (e-MAR)

BarcodedMedication

Administration

BarcodedMedication Dispensing

51

Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Health Information Exchange

52

ความฝันอันสูงสุด...

My Life-Long Dream...

53WHO & ITU

Achieving Health Information Exchange (HIE)

54

The Road to Digitizing Healthcare

What is a “Smart Hospital”?

Toward a “Smart” Hospital

Outline

55

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/

56Image Source: socialmediab2b.com

Another Smart Machine: IBM’s Watson

57Image Source: englishmoviez.com

Rise of the Machines?

58

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

59

Being Smart #5:

Don’t Replace Human Users.

Use ICT to Help Them Perform Smarter & Better.

60

Some Risks of Clinical Decision Support Systems

• Alert Fatigue

Unintended Consequences of Health IT

61

Workarounds

Unintended Consequences of Health IT

62

Being Smart #6:

Health IT Also Have

Risks &

Unintended Consequences

63

Balanced Focus of Informatics

Technology

ProcessPeople

64

Being Smart #7:

Balance Your Focus (People, Process, Technology)

65The 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

66

Being Smart #8:

Know Your Context &

Align IT with that Context

67

รพ.มหาวิทยาลัย 900 เตียง

Vision เป็นโรงพยาบาลชั้นน าของภูมิภาคเอเชียที่มีความเป็นเลิศในด้านบริการ การศึกษา และวิจัย

รพ.เอกชน 200 เตียง

Vision เป็นโรงพยาบาล High Tech High Touch ชั้นน าของประเทศ

Vision, Mission & IT Strategies

68Carr (2004) Carr (2003)

IT as “The Sail”

69

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

70

Being Smart #9:

Identify Your

Strategic IT Assets

71

People

Techno-logy

Process

“The Sailors”

72

รพ.มหาวิทยาลัย 900 เตียง

• บุคลากรมีอายุเฉลี่ย 42 ปี (range 20-65)

• แผนก IT มีทั้งบุคลากรใหม่และที่เคยพัฒนาระบบ HIS ตั้งแต่แรกเริ่ม

• แพทย์มีความเป็นตัวของตัวเองสูง, มักท างานเอกชนด้วย, มี turn-over rate สูง

• พยาบาลและวิชาชีพอื่นมักมองว่าแพทย์คืออภิสิทธิ์ชน และมีเรื่องถกเถียงกันบ่อยๆ

รพ.เอกชน 200 เตียง

• บุคลากรมีอายุเฉลี่ย 32 ปี (range 20-57)

• แผนก IT เข้มแข็ง• แพทย์ไม่ค่อยมี interaction กับ

บุคลากรอื่น, รายได้เป็นแรงดึงดูดหลัก• ผู้บริหารได้รับการยอมรับจากบุคลากร

ทุกวิชาชีพว่ามีวิสัยทัศน์และบริหารงานได้ดี

“The Sailors”

73Ash et al. (2003)

The “Special People”

74Ash 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

The “Special People”

75Ash 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

The “Special People”

76Ash 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

The “Special People”

77

Being Smart #10:

Manage Your

“Special People” Well

78

A True Story of Failure to

Involve Users in Hospital IT

Implementation

79

Being Smart #11:

Involve Users Early &

Intensively in Your Process

80Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle

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

Gartner Hype Cycle

81Rogers (2003)

Rogers’ Diffusion of Innovations: Adoption Curve

82

• 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

83

Being Smart #12:

Work Smartly with

Smart People

84

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

85

2546 แพทยศาสตรบัณฑิต2554 Ph.D. (Health Informatics), Univ. of Minnesota

ผู้ช่วยคณบดีฝ่ายนโยบายและสารสนเทศอาจารย์ ภาควิชาเวชศาสตร์ชุมชนคณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล

ความสนใจ: Health IT for Quality of Care,

IT Management, Security & Privacy

nawanan.the@mahidol.ac.th

SlideShare.net/Nawanan

Q&A