A presentation in March 2012 presented at the Ramathibodi Hospital Administration School, Faculty of Medicine Ramathibodi Hospital, Mahidol University in Bangkok, Thailand. Presentation partly in English and partly in Thai.

1. IT in Hospitals
Nawanan Theera‐Ampornpunt, MD, PhD
Mar 14, 2012
Ramathibodi Hospital Administration School
SlideShare.net/Nawanan

2. A Few Words About Me...
2003 M.D. (1st-Class Honors) Ramathibodi
2009 M.S. (Health Informatics) University of Minnesota
2011 Ph.D. (Health Informatics) University of Minnesota
Currently
• Medical Systems Analyst, Health Informatics Division, Ramathibodi
Contacts
ranta@mahidol.ac.th
SlideShare.net/Nawanan
www.tc.umn.edu/~theer002
groups.google.com/group/ThaiHealthIT
2

3. Outline
Healthcare & Health IT
Health IT Applications in Hospitals
Health Informatics As A Field
 IT Management
3

4. Health care &
Health IT
4

5. Manufacturing
5 Image Source: Guardian.co.uk

6. Banking
6 Image Source: Cablephet.com

7. Health care
7 ER ‐ Image Source: nj.com

8. Why Health care Isn’t Like Any Others?
 Life‐or‐Death
 Many & varied stakeholders
 Strong professional values
 Evolving standards of care
 Fragmented, poorly‐coordinated systems
 Large, ever‐growing & changing body of
knowledge
 High volume, low resources, little time
8

9. Why Health care Isn’t Like Any Others?
 Large variations & contextual dependence
Input Process Output
Patient Decision‐ Biological
Presentation Making Responses
9

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

11. But...Are We That Different?
Manufacturing
Input Process Output
Raw Assembling Finished
Materials Goods
Value‐Add
‐ Innovation
‐ Design
‐ QC
11

12. But...Are We That Different?
Health care
Input Process Output
Sick Patient Patient Care Well Patient
Value‐Add
‐ Technology & medications
‐ Clinical knowledge & skills
‐ Quality of care; process improvement
‐ Information
12

13. Information is Everywhere in Health Care
13

14. Various Forms of Health IT
Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic
Health
Records Picture Archiving and
(EHRs) Communication System
(PACS)
14

15. Still Many Other Forms of Health IT
Health Information
Exchange (HIE)
m‐Health
Biosurveillance
Personal Health Records
(PHRs)
Telemedicine &
Information Retrieval Telehealth
15 Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, Inc.

16. Why Adopting Health IT?
“To Go paperless” “To Computerize”
“To Get a HIS”
“Digital Hospital”
“To Have EMRs”
“To Modernize”
“To Share data”
16

17. Some Quotes
 “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)
17

18. Health IT: What’s In A Word?
Health Goal
Information Value‐Add
Technology Tools
18

19. Dimensions of Quality Healthcare
Safety
Timeliness
Effectiveness
Efficiency
Equity
Patient‐centeredness
19 (IOM, 2001)

20. Value of Health IT
Guideline adherence
 Better documentation
 Practitioner decision making or
process of care
 Medication safety
 Patient surveillance &
monitoring
 Patient education/reminder
20

21. Fundamental Theorem of Informatics
21
(Friedman, 2009)
(Friedman, 2009)

22. Is There A Role for Health IT?
22 (IOM, 2000)

23. Landmark IOM Reports
(IOM, 2000) (IOM, 2001)
23

24. Landmark IOM Reports: Summary
 Humans are not perfect and are bound to make
errors
 Highlight problems in the U.S. health care system
that systematically contributes to medical errors and
poor quality
 Recommends reform that would change how health
care works and how technology innovations can
help improve quality/safety
24

25. Why We Need Health IT
 Health care is very complex (and inefficient)
 Health care is information‐rich
 Quality of care depends on timely availability &
quality of information
 Clinical knowledge body is too large
 Short time during a visit
 Practice guidelines are put “on‐the‐shelf”
 “To err is human”
25

26. To Err Is Human
 Perception errors
26 Image Source: interaction‐dynamics.com

27. To Err Is Human
 Lack of Attention
Image Source: aafp.org
27

28. To Err Is Human
 Cognitive Errors - Example: Decoy Pricing
# of
The Economist Purchase Options People
• Economist.com subscription $59 16
• Print subscription $125 0
• Print & web subscription $125 84
# of
The Economist Purchase Options People
• Economist.com subscription $59 68
32 Ariely (2008)
• Print & web subscription $125
28

29. What If This Happens in Healthcare?
It already happens....
(Mamede et al., 2010; Croskerry, 2003; Klein, 2005)
What if health IT can help?
29

30. Adoption of Health IT: Assumptions
Adoption Use Outcomes
30

31. U.S.’s Efforts on Health IT Adoption
?
“...We will make wider use of electronic records and
other health information technology, to help control
costs and reduce dangerous
medical errors.”
President George W. Bush
Sixth State of the Union Address, January 31, 2006
31 Source: Wikisource.org Image Source: Wikipedia.org

32. Public Policy in Informatics: A US’s Case
1991: IOM’s CPR Report published
1996: HIPAA enacted
2000‐2001: IOM’s To Err Is Human &
Crossing the Quality Chasm published
2004: George W. Bush’s Executive Order
establishing ONCHIT (ONC)
2009‐2010: ARRA/HITECH Act &
“Meaningful use” regulations
32

33. U.S. Adoption of Health IT
Ambulatory (Hsiao et al, 2009) Hospitals (Jha et al, 2010)
Basic EHRs w/ notes 9.2%
Comprehensive EHRs 2.7%
CPOE for medications 34%
• U.S. lags behind other Western countries
(Schoen et al, 2006;Jha et al, 2008)
• Money and misalignment of benefits is the biggest
reason
33

34. We Need “Change”
“...we need to upgrade our medical
records by switching from a paper to
an electronic system of record
keeping...”
President Barack Obama
June 15, 2009
34

35. The Birth of “Meaningful Use”
“...Our recovery plan will invest in
electronic health records and new technology
that will reduce errors, bring down costs,
ensure privacy, and save lives.”
President Barack Obama
Address to Joint Session of Congress
February 24, 2009
35 Source: WhiteHouse.gov

36. American Recovery & Reinvestment Act
 Contains HITECH Act
(Health Information Technology for Economic and
Clinical Health Act)
 ~ 20 billion dollars for Health IT investments
 Incentives & penalties for providers
36

37. U.S. National Leadership
David Brailer, MD, PhD
National Coordinator for
Health Information Technology
(2004 - 2007)
Robert Kolodner, MD
National Coordinator for
Health Information Technology
(2006 - 2009)
David Blumenthal, MD, MPP
National Coordinator for
Health Information Technology
(2009 - 2011)
Farzad Mostashari, MD, ScM
National Coordinator for
Health Information Technology
(2011 - Present)
37

38. What is in the HITECH Act?
38 (Blumenthal, 2010)

39. “Meaningful Use”
“Meaningful Use”
Pumpkin
of a Pumpkin
39 Image Source & Idea Courtesy of Pat Wise at HIMSS, Oct. 2009

40. “Meaningful Use” of Health IT
Better
Stage 1
Stage 3
Health
‐ Electronic capture of
health information
‐ Information sharing Stage 2
Use of
‐ Data reporting EHRs to
Use of EHRs improve
to improve outcomes
processes of
care
40
(Blumenthal, 2010)

41. Adoption Studies: Descriptive Aspect
2004
Pongpirul et al.
(2004)
2011
Theera‐
Ampornpunt
(unpublished)
41

42. Health IT
Applications
in Hospitals
42

43. Enterprise‐wide Hospital IT
 Master Patient Index (MPI)
 Admit‐Discharge‐Transfer (ADT)
 Electronic Health Records (EHRs)
 Computerized Physician Order Entry (CPOE)
 Clinical Decision Support Systems (CDSSs)
 Picture Archiving and Communication System (PACS)
 Nursing applications
 Enterprise Resource Planning (ERP)
43

44. Departmental IT
 Pharmacy applications
 Laboratory Information System (LIS)
 Radiology Information System (RIS)
 Specialized applications (ER, OR, LR,
Anesthesia, Critical Care, Dietary Services,
Blood Bank)
 Incident management & reporting system
44

45. Hospital Information System
Clinical
Medical ADT Notes
Records
Workflow
Pharmacy IS
Operation Master
Patient LIS
Theatre
Index (MPI)
Order
CCIS
RIS
Scheduling
Portals Billing
PACS
45 Modified from Dr. Artit Ungkanont’s slide

46. HIT Systems (Inpatient)
Clinical Decision Support:
“Any system designed to
improve clinical decision making
related to diagnostic or
therapeutic processes of care.”
46 From Dr. Artit Ungkanont’s slide

47. EHRs & HIS
The Challenge ‐ Knowing What It Means
Electronic Health
Records (EHRs)
Hospital
Information System
Electronic Medical (HIS)
Records (EMRs)
Electronic Patient
Records (EPRs)
Clinical Information
System (CIS)
Personal Health
Computer‐Based Records (PHRs)
Patient Records
(CPRs)
47

48. EHR Systems
Just electronic documentation?
History Diag‐ Treat‐
...
& PE nosis ments
Or do they have other values?
48

49. Functions that Should Be Part of EHR Systems
 Computerized Medication Order Entry
 Computerized Laboratory Order Entry
 Computerized Laboratory Results
 Physician Notes
 Patient Demographics
 Problem Lists
 Medication Lists
 Discharge Summaries
 Diagnostic Test Results
 Radiologic Reports
49 (IOM, 2003; Blumenthal et al, 2006)

50. Computerized Physician Order Entry (CPOE)
50

51. Computerized Physician Order Entry (CPOE)
Values
No handwriting!!!
 Structured data entry: Completeness, clarity,
fewer mistakes (?)
 No transcription errors!
 Entry point for CDSSs
 Streamlines workflow, increases efficiency
51

52. Clinical Decision Support Systems (CDSSs)
 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,
(Shortliffe, 1976) treatment options
52

53. Clinical Decision Support Systems (CDSSs)
 Alerts & reminders
 Based on specified logical conditions
 Examples:
 Drug‐allergy checks
 Drug‐drug interaction checks
 Drug‐disease checks
 Drug‐lab checks
 Drug‐formulary checks
 Reminders for preventive services or certain actions
(e.g. smoking cessation)
 Clinical practice guideline integration
53

54. Clinical Decision Support Systems (CDSSs)
 Evidence‐based knowledge sources e.g. drug
database, literature
 Simple UI designed to help clinical decision making
 E.g., Abnormal Lab Highlights
54

55. A Basic Architecture of A CDSS
User User Interface
Inference Engine
Knowledge
Other Data Base Patient Data
• System states • Rules
• Epidemiological/ • Statistical data
surveillance data • Literature
• Etc. • Etc.
55

56. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
56 From a teaching slide by Don Connelly, 2006

57. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Abnormal lab
Attention highlights
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
57

58. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Abnormal lab
Attention highlights
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
58

59. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Drug‐Allergy
Attention Checks
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
59

60. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception Drug‐Drug
CLINICIAN Interaction
Attention Checks
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
60

61. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception Clinical Practice
CLINICIAN Guideline
Reminders
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
61

62. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference Diagnostic/Treatment
Expert Systems
DECISION
62

63. Clinical Decision Support Systems (CDSSs)
 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”
63 (Friedman, 2009)

64. Clinical Decision Support Systems (CDSSs)
Some risks
 Alert fatigue
64

65. Workarounds
65

66. Health IT for Medication Safety
Ordering Transcription Dispensing Administration
Automatic Electronic
CPOE
Medication Medication
Dispensing Administration
Records
(e‐MAR)
Barcoded
Medication Barcoded
Dispensing Medication
Administration
66

67. Health Information Exchange (HIE)
Government
Hospital A Hospital B
Clinic C
Lab Patient at Home
67

68. 4 Quadrants of Hospital IT
Strategic
Business
Intelligence HIE
PHRs
CDSS
Social
Media CPOE
Administrative Clinical
VMI EHRs
ERP PACS
LIS
ADT
Word
Processor MPI
Operational
68

69. Health Informatics
As A Field
69

70. Biomedical/Health Informatics
 “[T]he field that is concerned with the optimal use
of information, often aided by the use of
technology, to improve individual health, health
care, public health, and biomedical research” (Hersh,
2009)
 “[T]he application of the science of information as
data plus meaning to problems of biomedical
interest” (Bernstam et al, 2010)
70

71. DIKW Pyramid
Wisdom
Knowledge
Information
Data
71

72. Task‐Oriented View
Collection Processing Utilization
Communication/
Storage Dissemination/
Presentation
72

73. M/B/H Informatics As A Field
73 (Shortliffe, 2002)

74. M/B/H Informatics and Other Fields
Social Sciences
(Psychology, Statistics &
Sociology, Research
Linguistics, Methods
Cognitive & Law & Ethics) Medical
Decision Sciences &
Science Public Health
Engineering Management
Library
Computer & Biomedical/
Science,
Information Health
Information
Science Informatics
Retrieval, KM
And More!
74

75. Balanced Focus of Informatics
People
Techno‐
Process
logy
75

76. IT Management
76

77. ความเดิมตอนที่แล้ว...
Health IT: ของดี (อาจจะ) มีประโยชน์
(แต่ก็อาจมีโทษ)
บริบท (local contexts) มีความสําคัญ
 ต้องมีการบริหารจัดการที่เหมาะสม
ประเด็นพิจารณา
อะไรคือบริบทที่เกี่ยวข้อง?
จะจัดการมันอย่างไร?
77

78. Context
The current location
The tailwind The headwind
The past journey The
direction The destination
The speed
The sailor(s) & The sail
people on board The boat
The sea
78 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing

79. Direction & Destination
Visionรพ.มหาวิทยาลัย 900 าเตียง
เป็นโรงพยาบาลชั้นนํ ของ Vision รพ.เอกชน 200High ง
เป็นโรงพยาบาล เตีย Tech
ภูมิภาคเอเชียทีมีความเป็นเลิศใน
่ High Touch ชั้นนําของประเทศ
ด้านบริการ การศึกษา และวิจัย
79

80. “The Sail”
Carr (2004) Carr (2003)
80

81. 4 Quadrants of Hospital IT
Strategic
Business
Intelligence HIE
PHRs
CDSS
Social
Media CPOE
Administrative Clinical
VMI EHRs
ERP PACS
LIS
ADT
Word
Processor MPI
Operational
81

82. IT As A Strategic Advantage
Sustainable
Yes
competitive
advantage
Yes Inimitable ?
Yes Rare ?
No
Preemptive
Yes Non-Substitutable? No advantage
Competitive
Valuable ? parity
No
Competitive
No necessity
Competitive
Resources/ Disadvantage
capabilities
82 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management

83. “The Sail”
Vision เป็นโรงพยาบาลชั้นนําของ Vision เป็นโรงพยาบาล High Tech
ภูมิภาคเอเชียทีมยาลัย 900 ศใน ง
รพ.มหาวิท่ ีความเป็นเลิ เตีย Highรพ.เอกชน นําของประเทศ
Touch ชั้น 200 เตียง
ด้านบริการ การศึกษา และวิจัย
Current IT Environment
Current IT Environment  มี MPI, ADT, EHRs, CPOE แต่ยังมี
 เป็น รพ.แรกๆ ที่มี HIS ซึ่งพัฒนาเอง และ CDSS จํากัด
ต่อยอดจาก MPI, ADT ไปสู่ CPOE (แต่  ยังไม่มี Customer Relationship Management
ยังขาด advanced CDSS) ระบบ HIS (CRM)
เข้ากับ workflow ของ รพ. เป็นอย่างดี  ยังไม่มี Personal Health Records (PHRs)
 ปัจจุบัน ระบบ HIS ยังใช้เทคโนโลยี
เดียวกับช่วงที่พฒนาใหม่ๆ (20 ปีก่อน)
ั
เป็นหลัก มีการนําเทคโนโลยีใหม่ๆ มาใช้
อย่างช้าๆ
83

84. IT As A Strategic Advantage
Sustainable
Yes
competitive
advantage
Yes Inimitable ?
Yes Rare ?
No
Preemptive
Yes Non-Substitutable? No advantage
Competitive
Valuable ? parity
No
Competitive
No necessity
Competitive
Resources/ Disadvantage
capabilities
84 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management

85. “The Sailors”
People
Techno‐
Process
logy
85

86. “The Sailors”
 บุคลากรมีอายุเฉลีย 42 ปี
่  บุคลากรมีอายุเฉลีย 32 ปี
่
(range 20-65) ยาลัย 900 เตียง
รพ.มหาวิท (range 20-57) 200 เตียง
รพ.เอกชน
 แผนก IT มีทั้งบุคลากรใหม่และทีเคย
่  แผนก IT เข้มแข็ง
พัฒนาระบบ HIS ตั้งแต่แรกเริ่ม  แพทย์ไม่ค่อยมี interaction กับ
 แพทย์มีความเป็นตัวของตัวเองสูง,
บุคลากรอื่น, รายได้เป็นแรงดึงดูดหลัก
มักทํางานเอกชนด้วย, มี turn-over
rate สูง  ผู้บริหารได้รับการยอมรับจากบุคลากร
 พยาบาลและวิชาชีพอื่นมักมองว่า ทุกวิชาชีพว่ามีวิสัยทัศน์และบริหารงาน
แพทย์คืออภิสทธิ์ชน และมีเรื่อง
ิ ได้ดี
ถกเถียงกันบ่อยๆ
86

87. Context
The current location
The tailwind The headwind
The past journey The
direction The destination
The speed
The sailor(s) & The sail
people on board The boat
The sea
87 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing

88. “The Boat”
 Size
 Resources
 Structures
 Work Processes
 Facilities/Geography
 Etc.
88

89. “The Sea”
 Target customers
 Local competitiveness
 Relationship of hospital to local players
 Inter‐organizational collaboration
 IT market environment
 National/international trend
 Regulations
 Standard of care
 Etc.
89

90. SWOT Analysis
“The Boat” “The Sea”
“The Tailwind” Strengths Opportunities “The Tailwind”
“The Headwind” Weaknesses Threats “The Headwind”
90

91. IT Outsourcing Decision Tree
Keep Internal
No
Is external delivery
No reliable and lower cost?
Does service offer Yes OUTSOURCE!
competitive advantage?
Yes Keep Internal
91 From a teaching slide by Nelson F. Granados, 2006

92. IT Outsourcing Decision Tree: Ramathibodi’s Case
External delivery unreliable
• Non‐Core HIS
External delivery higher cost
• ERP maintenance/ongoing
customization
Keep Internal
No
Is external delivery
No reliable and lower cost?
Does service offer Yes OUTSOURCE!
competitive advantage?
ERP initial
implementation,
Yes Keep Internal
PACS, RIS,
Core HIS, CPOE Departmental
Strategic advantages systems,
• Agility due to local workflow accommodations IT Training
• Secondary data utilization (research, QI)
• Roadmap to national leader in informatics
92

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

94. Rogers’ Diffusion of Innovations: Adoption Curve
Rogers (2003)
94

95. Hospital IT Adoption Success Factors
 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
95 Theera‐Ampornpunt (2009, 2011) [Unpublished]

96. Resources on Change Management
Lorenzi & Riley (2004) Leviss (Editor) (2010)
96

97. Summary
 Healthcare is complex
 Health IT can benefit healthcare through
 Information delivery
 Process improvement
 Empowering providers & patients
 The world is moving toward health IT
 Health informatics is related to & relies on the field of IT, but they
are not the same
 Management of hospital IT is crucial to success
 Know your organization (“context”)
 Strategic mindset
 Project & change management
97

98. Final Words...
 Don’t forget our real aim...
Adoption Use Outcomes
98

99. Q & A...
Download Slides
SlideShare.net/Nawanan
Contacts
ranta@mahidol.ac.th
www.tc.umn.edu/~theer002
groups.google.com/group/ThaiHealthIT
99

100. References
 Ariely D. Predictably irrational: the hidden forces that shape our decisions. New York City
(NY):HarperCollins; 2008. 304 p.
 Bernstam EV, Smith JW, Johnson TR. What is biomedical informatics? J Biomed Inform. 2010
Feb;43(1):104‐10.
 Blumenthal D. Launching HITECH. N Engl J Med. 2010 Feb 4;362(5):382‐5.
 Blumenthal D, DesRoches C, Donelan K, Ferris T, Jha A, Kaushal R, Rao S, Rosenbaum S. Health
information technology in the United States: the information base for progress [Internet]. Princeton
(NJ): Robert Wood Johnson Foundation; 2006.
 Carr NG. Does IT matter? Information technology and the corrosion of competitive advantage.
Boston (MA):Harvard Business Press;2004. 208 p.
 Carr NG. IT doesn’t matter. Harvard Bus Rev. 2003 May 1;81(5):41‐9.
 Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad
Med. 2003 Aug;78(8):775‐80. 81 p. Available from:
http://www.rwjf.org/files/publications/other/EHRReport0609.pdf
 Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc. 2009
Apr;16(2):169‐70.
 Gladwell M. The Tipping Point: how little things can make a big difference. New York City (NY):Little
Brown;2000. 304 p.
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 Background designs are the property of Geetesh Bajaj. Used with permission. © Copyright, Geetesh
Bajaj. All Rights Reserved.
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