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.
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
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
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
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
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
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
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)
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)
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)
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
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
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
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
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
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
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
100. References
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