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
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
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/
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
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
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
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
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Ariely (2008)
16
0
84
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• Economist.com subscription $59
• Print & web subscription $125
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
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
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
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
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
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
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
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
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”
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