the road toward a smart hospital (presented at roi et hospital) (2 feb 2016)

แนวทางการบริหาร รพ.ร้อยเอ็ดสู่ Smart Hospital

นพ.นวนรรน ธีระอัมพรพนัธุ์

2 กุมภาพันธ์ 2559

2

2546 แพทยศาสตรบณัฑติ2554 Ph.D. (Health Informatics), Univ. of Minnesota

อาจารย์ ภาควชิาเวชศาสตรช์ุมชนคณะแพทยศาสตรโ์รงพยาบาลรามาธบิดี มหาวทิยาลยัมหดิล

ความสนใจ: Health IT for Quality of Care,

IT Management, Security & Privacy

nawanan.the@mahidol.ac.th

SlideShare.net/Nawanan

Nawanan Theera-Ampornpunt

Line ID: NawananT

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/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

Input Process Output

Assembling

Manufacturing

Raw Materials Finished Goods

Value-Add- Innovation- Design- QC

But...Are We That Different?

13

Input Process Output

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

Input Process Output

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

“Information” in Medicine

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

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

32

32

WHO (2009)

Components of Health Systems

33

33

WHO (2009)

WHO Health System Framework

34

• 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

35

• Efficient

–Faster care

–Time & cost savings

–Reducing unnecessary tests

• Equitable

–Access to providers & knowledge

• Patient-Centered

–Empowerment & better self-care

Being “Smart” in Healthcare

36

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

Landmark Institute of Medicine Reports

37

• 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

38

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

39Image 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

40Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital

To Err is Human 2: Memory

41

• 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

42

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

2005; Croskerry, 2013)

What If This Happens in Healthcare?

43Klein 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

44

• Medication Errors

–Drug Allergies

–Drug Interactions

• Ineffective or inappropriate treatment

• Redundant orders

• Failure to follow clinical practice guidelines

Common Errors

45

Being Smart #3:

“To Err is Human”

46

External Memory

Knowledge Data

Long Term Memory

Knowledge Data

Inference

DECISION

PATIENT

Perception

Attention

WorkingMemory

CLINICIAN

Elson, Faughnan & Connelly (1997)

Clinical Decision Making

47

Example of “Alerts & Reminders”

Reducing Errors through “Alerts & Reminders”

48

Why We Need ICT

in Healthcare?

#1: Because information is

everywhere in healthcare

49

Why We Need ICT in Healthcare?

#2: Because healthcare is error-prone and technology

can help

50http://www.dplindbenchmark.com/wp-content/uploads/2013/02/HHRI-Our-Health-Care-River.pdf

Fragmented Healthcare

51

Why We Need ICT

in Healthcare?

#3: Because access to

high-quality patient information

should improve care

52

Why We Need ICT in Healthcare?

#4: Because healthcare at all levels is fragmented &

in need of process improvement

53

Documented Values of Health IT

• Guideline adherence

• Better documentation

• Practitioner decision making or process of care

• Medication safety

• Patient surveillance & monitoring

• Patient education/reminder

54

Being Smart #4:

Link IT Values to

Quality (Including Safety)

55

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

56

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

57

eHealth Health IT

Slide adapted from: Dr. Boonchai Kijsanayotin

eHealth & Health IT

58

Health

Information

Technology

Goal

Value-Add

Tools

Health IT: What’s in a Word?

59

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

Electronic Health

Records (EHRs)

Picture Archiving and Communication System

(PACS)

Various Forms of Health IT

60

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

61

Health IT for Medication Safety

Ordering Transcription Dispensing Administration

CPOEAutomatic Medication Dispensing

Electronic Medication

Administration Records (e-MAR)

BarcodedMedication

Administration

BarcodedMedication Dispensing

62

Hospital A Hospital B

Clinic C

Government

Lab Patient at Home

Health Information Exchange

63

ความฝันอันสูงสุด...

My Life-Long Dream...

64WHO & ITU

Achieving Health Information Exchange (HIE)

65

• The Large N Interfaces Problem

N = 2, Interface = 1

# Interfaces = N(N-1)/2

N = 3, Interface = 3

N = 5, Interface = 10

N = 100, Interface = 4,950

Standards: Why?

66

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

67

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

68

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

69

The Road to Digitizing Healthcare

What is a “Smart Hospital”?

Toward a “Smart” Hospital

Outline

70

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/

71Image Source: socialmediab2b.com

Another Smart Machine: IBM’s Watson

72Image Source: englishmoviez.com

Rise of the Machines?

73Image Source: amazon.com

Smart Phones, Dumb People?

74

Smart Hospital,

Dumb...?

75

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

76

Being Smart #6:

Don’t Replace Human Users.

Use ICT to Help Them Perform Smarter & Better.

77

Some Risks of Clinical Decision Support Systems

• Alert Fatigue

Unintended Consequences of Health IT

78

Workarounds

Unintended Consequences of Health IT

79

Being Smart #7:

Health IT Also Have

Risks &

Unintended Consequences

80

Balanced Focus of Informatics

Technology

ProcessPeople

81

Being Smart #8:

Balance Your Focus (People, Process, Technology)

82The 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

83

Being Smart #9:

Know Your Context &

Align IT with that Context

84

รพ.มหาวิทยาลัย 900 เตียง

Vision เป็นโรงพยำบำลชั้นน ำของภูมิภำคเอเชียที่มีควำมเป็นเลิศในด้ำนบริกำร กำรศึกษำ และวิจัย

รพ.เอกชน 200 เตียง

Vision เป็นโรงพยำบำล High Tech High Touch ชั้นน ำของประเทศ

Vision, Mission & IT Strategies

85Carr (2004) Carr (2003)

IT as “The Sail”

86

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

87

Being Smart #10:

Identify Your

Strategic IT Assets

88

People

Techno-logy

Process

“The Sailors”

89

รพ.มหาวิทยาลัย 900 เตียง

• บุคลำกรมีอำยุเฉลี่ย 42 ปี (range 20-65)

• แผนก IT มีทั้งบุคลำกรใหม่และที่เคยพัฒนำระบบ HIS ตั้งแต่แรกเริ่ม

• แพทย์มีควำมเป็นตัวของตัวเองสูง, มักท ำงำนเอกชนด้วย, มี turn-over rate สูง

• พยำบำลและวิชำชีพอื่นมักมองว่ำแพทย์คืออภิสิทธิ์ชน และมีเรื่องถกเถียงกันบ่อยๆ

รพ.เอกชน 200 เตียง

• บุคลำกรมีอำยุเฉลี่ย 32 ปี (range 20-57)

• แผนก IT เข้มแข็ง• แพทย์ไม่ค่อยมี interaction กับ

บุคลำกรอื่น, รำยได้เป็นแรงดึงดูดหลัก• ผู้บริหำรได้รับกำรยอมรับจำกบุคลำกร

ทุกวิชำชีพว่ำมีวิสัยทัศน์และบริหำรงำนได้ดี

“The Sailors”

90Ash et al. (2003)

The “Special People”

91Ash 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”

92Ash 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”

93Ash 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”

94

Being Smart #11:

Manage Your

“Special People” Well

95

A True Story of Failure to

Involve Users in Hospital IT

Implementation

96

Being Smart #12:

Involve Users Early &

Intensively in Your Process

97Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle

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

Gartner Hype Cycle

98Rogers (2003)

Rogers’ Diffusion of Innovations: Adoption Curve

99

• 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

100

Being Smart #13:

Work Smartly with

Smart People

101

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

102

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Nawanan Theera-Ampornpunt

Line ID: NawananT

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