Presented at Roi Et Hospital, Roi Et, Thailand on February 2, 2016

1. แนวทางการบริหาร รพ.ร้อยเอ็ด
สู่ Smart Hospital
นพ.นวนรรน ธีระอัมพรพันธุ์
2 กุมภาพันธ์ 2559

2. 2
2546 แพทยศาสตรบัณฑิต
2554 Ph.D. (Health Informatics), Univ. of Minnesota
อาจารย์ ภาควิชาเวชศาสตร์ชุมชน
คณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล
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
แนะนาตัว

3. 3
 The Road to Digitizing Healthcare
 What is a “Smart Hospital”?
 Toward a “Smart” Hospital
Outline

4. 4
Health &
Health Information

5. 5
Let’s take a look at
these pictures...

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

7. 7
Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทย์โมเดลทางธุรกิจ/
“Smart” Banking

8. 8ER - Image Source: nj.com
Healthcare (On TV)

9. 9
(At an undisclosed hospital)
Healthcare (Reality)

10. 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. 11
But...Are We That Different?
Input Process Output
Transfer
Banking
Value-Add
- Security
- Convenience
- Customer Service
Location A Location B

12. 12
Input Process Output
Assembling
Manufacturing
Raw Materials Finished
Goods
Value-Add
- Innovation
- Design
- QC
But...Are We That Different?

13. 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. 14
• Large variations & contextual dependence
Input Process Output
Patient
Presentation
Decision-
Making
Biological
Responses
Standardizing Healthcare

15. 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. 16
Digitizing Healthcare
Image Source: http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital

17. 17
“To computerize
the hospital”
“To go paperless”
“To become a
Digital Hospital”
“To Have
EHRs”
Why Adopting Health IT?

18. 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. 19
Being Smart #1:
Stop Your
“Drooling Reflex”!!

20. 20
Being Smart #2:
Focus on Information &
Process Improvement,
Not Technology

21. 21
ถ้าไม่เป็น “Digital Hospital”
หรือ “Paperless Hospital”
แล้วจะให้เราเป็นอะไร?

22. “Smart Hospital”

23. 23
แล้ว “Smart Hospital”
ต่างจาก Digital หรือ
Paperless Hospital ตรงไหน?

24. 24
The Road to Digitizing Healthcare
 What is a “Smart Hospital”?
 Toward a “Smart” Hospital
Outline

25. 25
Microsoft Health Future Vision

26. 26
Connecting People to a Healthy Future With
Personalized Care – Kaiser Permanente
https://www.youtube.com/watch?v=gxz9ZVvduGc

27. 27
Back to
something simple...

28. 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. 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. 30
Information is Everywhere in Healthcare

31. 31
“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA.
2010 Sep 15;304(11):1227-8.

32. 32
32
WHO (2009)
Components of Health Systems

33. 33
33
WHO (2009)
WHO Health System Framework

34. 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. 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. 36
(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports

37. 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. 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

39. 39
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

40. 40Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital
To Err is Human 2: Memory

41. 41
• Cognitive Errors - Example: Decoy Pricing
The Economist Purchase Options
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Ariely (2008)
16
0
84
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68
32
# of
People
# of
People
To Err is Human 3: Cognition

42. 42
• It already happens....
(Mamede et al., 2010; Croskerry, 2003; Klein,
2005; Croskerry, 2013)
What If This Happens in Healthcare?

43. 43
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”
Cognitive Biases in Healthcare

44. 44
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors

45. 45
Being Smart #3:
“To Err is Human”

46. 46
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
Working
Memory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making

47. 47
Example of “Alerts & Reminders”
Reducing Errors through “Alerts & Reminders”

48. 48
Why We Need ICT
in Healthcare?
#1: Because information is
everywhere in healthcare

49. 49
Why We Need ICT
in Healthcare?
#2: Because healthcare is
error-prone and technology
can help

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

51. 51
Why We Need ICT
in Healthcare?
#3: Because access to
high-quality patient information
should improve care

52. 52
Why We Need ICT
in Healthcare?
#4: Because healthcare at
all levels is fragmented &
in need of process
improvement

53. 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. 54
Being Smart #4:
Link IT Values to
Quality (Including Safety)

55. 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. 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. 57
eHealth  Health IT
Slide adapted from: Dr. Boonchai Kijsanayotin
eHealth & Health IT

58. 58
Health
Information
Technology
Goal
Value-Add
Tools
Health IT: What’s in a Word?

59. 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. 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. 61
Health IT for Medication Safety
Ordering Transcription Dispensing Administration
CPOE
Automatic
Medication
Dispensing
Electronic
Medication
Administration
Records
(e-MAR)
Barcoded
Medication
Administration
Barcoded
Medication
Dispensing

62. 62
Hospital A Hospital B
Clinic C
Government
Lab Patient at Home
Health Information Exchange

63. 63
ความฝันอันสูงสุด...
My Life-Long Dream...

64. 64WHO & ITU
Achieving Health Information Exchange (HIE)

65. 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. 66
นวนรรน ธีระอัมพรพันธุ์. ตำนำนควำมเชื่อและข้อเท็จจริงเกี่ยวกับมำตรฐำนสำรสนเทศทำงสุขภำพ. 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. 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. 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. 69
The Road to Digitizing Healthcare
What is a “Smart Hospital”?
 Toward a “Smart” Hospital
Outline

70. 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/

71. 71Image Source: socialmediab2b.com
Another Smart Machine: IBM’s Watson

72. 72Image Source: englishmoviez.com
Rise of the Machines?

73. 73Image Source: amazon.com
Smart Phones, Dumb People?

74. 74
Smart Hospital,
Dumb...?

75. 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. 76
Being Smart #6:
Don’t Replace
Human Users.
Use ICT to Help Them
Perform Smarter & Better.

77. 77
Some Risks of Clinical Decision Support Systems
• Alert Fatigue
Unintended Consequences of Health IT

78. 78
Workarounds
Unintended Consequences of Health IT

79. 79
Being Smart #7:
Health IT Also Have
Risks &
Unintended Consequences

80. 80
Balanced Focus of Informatics
Technology
ProcessPeople

81. 81
Being Smart #8:
Balance Your Focus
(People, Process, Technology)

82. 82The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
The destination
The boat
The 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. 83
Being Smart #9:
Know Your Context &
Align IT with that Context

84. 84
รพ.มหาวิทยาลัย 900 เตียง
Vision เป็นโรงพยำบำลชั้นนำของ
ภูมิภำคเอเชียที่มีควำมเป็นเลิศใน
ด้ำนบริกำร กำรศึกษำ และวิจัย
รพ.เอกชน 200 เตียง
Vision เป็นโรงพยำบำล High Tech
High Touch ชั้นนำของประเทศ
Vision, Mission & IT Strategies

85. 85
Carr (2004) Carr (2003)
IT as “The Sail”

86. 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. 87
Being Smart #10:
Identify Your
Strategic IT Assets

88. 88
People
Techno-
logy
Process
“The Sailors”

89. 89
รพ.มหาวิทยาลัย 900 เตียง
• บุคลำกรมีอำยุเฉลี่ย 42 ปี
(range 20-65)
• แผนก IT มีทั้งบุคลำกรใหม่และที่เคย
พัฒนำระบบ HIS ตั้งแต่แรกเริ่ม
• แพทย์มีควำมเป็นตัวของตัวเองสูง,
มักทำงำนเอกชนด้วย, มี turn-over
rate สูง
• พยำบำลและวิชำชีพอื่นมักมองว่ำ
แพทย์คืออภิสิทธิ์ชน และมีเรื่อง
ถกเถียงกันบ่อยๆ
รพ.เอกชน 200 เตียง
• บุคลำกรมีอำยุเฉลี่ย 32 ปี
(range 20-57)
• แผนก IT เข้มแข็ง
• แพทย์ไม่ค่อยมี interaction กับ
บุคลำกรอื่น, รำยได้เป็นแรงดึงดูดหลัก
• ผู้บริหำรได้รับกำรยอมรับจำกบุคลำกร
ทุกวิชำชีพว่ำมีวิสัยทัศน์และ
บริหำรงำนได้ดี
“The Sailors”

90. 90Ash et al. (2003)
The “Special People”

91. 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”

92. 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”

93. 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. 94
Being Smart #11:
Manage Your
“Special People” Well

95. 95
A True Story of Failure to
Involve Users in Hospital IT
Implementation

96. 96
Being Smart #12:
Involve Users Early &
Intensively in Your Process

97. 97
Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle
http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
Gartner Hype Cycle

98. 98
Rogers (2003)
Rogers’ Diffusion of Innovations:
Adoption Curve

99. 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. 100
Being Smart #13:
Work Smartly with
Smart People

101. 101
To become a smart hospital, you must
• Know what is “smart” all about
• Know how to use smart machines
together with smart people
• Manage both of them smartly
Summary

102. 102
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Nawanan Theera-Ampornpunt
Line ID: NawananT
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