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ICT and Health Informatics
Nawanan Theera-Ampornpunt
September 3, 2018
2
2003 M.D. (First-Class Honors)
2011 Ph.D. (Health Informatics), Univ. of Minnesota
Assistant Dean for Informatics
Lecturer, Department of Community Medicine
Faculty of Medicine Ramathibodi Hospital
Mahidol University
Interests: Health IT for Quality of Care, Social Media
IT Management, Security & Privacy
nawanan.the@mahidol.ac.th
SlideShare.net/Nawanan
นวนรรน ธีระอัมพรพันธุ์ (Nawanan Theera-Ampornpunt)
Line ID: NawananT
Introduction
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
7
Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทย์โมเดลทางธุรกิจ/
“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
If not “Digital Hospital”
or “Paperless Hospital”
Then What Should We
Aspire to Be?
“Smart Hospital”
23
So How is
a “Smart Hospital”
Different from a Digital or
Paperless Hospital?
24
Healthcare 4.0?
25
Healthcare 1.0
• Thai Traditional Medicine in the Ancient Times
Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health
Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html
http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
การย่อยขนาดตัวยาสมุนไพร โดยใช้ครกตาและหินบดยา
ของโรงศิริราชพยาบาล (ปัจจุบันคือ โรงพยาบาลศิริราช)
คนไทยสมัยก่อนมักให้บุคคลในครอบครัวบีบนวดได้
26
Healthcare 2.0
• Modern (Western) Medicine
Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health
Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html
http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
27
Healthcare 3.0
• Quality-Driven Healthcare
Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health
Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html
http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
28
Healthcare 4.0
• Smart Healthcare & Smart Hospital
Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health
Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html
http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
29
So What Is
Smart Healthcare?
30
Smart Healthcare For Policymakers?
Image Source: http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99
31
Smart Healthcare For Health Promoters?
Image Source: http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf
32
Smart Healthcare For Clinicians?
Image Source: http://www.medscape.com/viewarticle/780298
33
Smart Healthcare For Patients & Consumers?
Image Source: Agence France-Presse/Getty Images
34
So What Exactly Is Smart Healthcare?
Image Source: http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg
35
The Road to Digitizing Healthcare
 What is a “Smart Hospital”?
 Toward a “Smart” Hospital
Outline
36
Connecting People to a Healthy Future With
Personalized Care – Kaiser Permanente
https://www.youtube.com/watch?v=gxz9ZVvduGc
37
Back to
something simple...
38
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?
39
• 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
40
Information is Everywhere in Healthcare
41
“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA.
2010 Sep 15;304(11):1227-8.
42
42
WHO (2009)
Components of Health Systems
43
43
WHO (2009)
WHO Health System Framework
44
• 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
45
• Efficient
–Faster care
–Time & cost savings
–Reducing unnecessary tests
• Equitable
–Access to providers & knowledge
• Patient-Centered
–Empowerment & better self-care
Being “Smart” in Healthcare
46
(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports
47
• 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
48
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
49
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
50Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital
To Err is Human 2: Memory
51
• 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
52
• It already happens....
(Mamede et al., 2010; Croskerry, 2003; Klein,
2005; Croskerry, 2013)
What If This Happens in Healthcare?
53
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
54
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors
55
Being Smart #3:
“To Err is Human”
56
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
Working
Memory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
57
Example of “Alerts & Reminders”
Reducing Errors through “Alerts & Reminders”
58
Why We Need ICT
in Healthcare?
#1: Because information is
everywhere in healthcare
59
Why We Need ICT
in Healthcare?
#2: Because healthcare is
error-prone and technology
can help
60http://www.dplindbenchmark.com/wp-content/uploads/2013/02/HHRI-Our-Health-Care-River.pdf
Fragmented Healthcare
61
Why We Need ICT
in Healthcare?
#3: Because access to
high-quality patient information
should improve care
62
Why We Need ICT
in Healthcare?
#4: Because healthcare at
all levels is fragmented &
in need of process
improvement
63
Documented Values of Health IT
• Guideline adherence
• Better documentation
• Practitioner decision making or
process of care
• Medication safety
• Patient surveillance &
monitoring
• Patient education/reminder
64
Being Smart #4:
Link IT Values to
Quality (Including Safety)
65
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
66
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
67
eHealth  Health IT
Slide adapted from: Dr. Boonchai Kijsanayotin
eHealth & Health IT
68
Health
Information
Technology
Goal
Value-Add
Tools
Health IT: What’s in a Word?
69
Hospital Information System (HIS) Computerized Physician Order Entry (CPOE)
Electronic
Health
Records
(EHRs)
Picture Archiving and
Communication System
(PACS)
Various Forms of Health IT
70
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
71
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
72
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
73
Spectrum of Informatics
Shortliffe (2002)
74
Incarnations of Health IT
Clinical
Informatics
Public
Health
Informatics
Consumer
Health
Informatics
HIS/CIS
EHRs
Computerized Physician
Order Entry (CPOE)
Clinical Decision
Support Systems
(CDS) (including AI)
Closed Loop
Medication
PACS/RIS
LIS
Nursing
Apps
Disease Surveillance
(Active/Passive)
Business
Intelligence &
Dashboards
Telemedicine
Real-time Syndromic
Surveillance
mHealth for Public
Health Workers &
Volunteers
PHRs
Health Information
Exchange (HIE)
eReferral
mHealth for
Consumers
Wearable
Devices
Social
Media
Copyright  Nawanan Theera-Ampornpunt (2018)
75
TEDxMahidolU Talk by Nawanan: “ATM in Healthcare”
76
Hospital A Hospital B
Clinic D
Policymakers
Patient at
Home
Hospital C
HIE Platform
Health Information Exchange (HIE)
77
My Life-Long Dream...
78WHO & ITU
Achieving Health Information Exchange (HIE)
79
• 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?
80
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
81
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
82
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
83
The Road to Digitizing Healthcare
What is a “Smart Hospital”?
 Toward a “Smart” Hospital
Outline
84
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/
85Image Source: socialmediab2b.com
Another Smart Machine: IBM’s Watson
86Image Source: englishmoviez.com
Rise of the Machines?
87
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
88
Being Smart #6:
Don’t Replace
Human Users.
Use ICT to Help Them
Perform Smarter & Better.
89
Some Risks of Clinical Decision Support Systems
• Alert Fatigue
Unintended Consequences of Health IT
90
Workarounds
Unintended Consequences of Health IT
91
Being Smart #7:
Health IT Also Have
Risks &
Unintended Consequences
92
Balanced Focus of Informatics
Technology
ProcessPeople
93
Being Smart #8:
Balance Your Focus
(People, Process, Technology)
94
2003 M.D. (First-Class Honors)
2011 Ph.D. (Health Informatics), Univ. of Minnesota
Assistant Dean for Policy and Informatics
Lecturer, Department of Community Medicine
Faculty of Medicine Ramathibodi Hospital
Mahidol University
Interests: Health IT for Quality of Care, Social Media
IT Management, Security & Privacy
nawanan.the@mahidol.ac.th
SlideShare.net/Nawanan
นวนรรน ธีระอัมพรพันธุ์ (Nawanan Theera-Ampornpunt)
Line ID: NawananT
Q&A

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ICT and Health Informatics (September 3, 2018)

  • 1. ICT and Health Informatics Nawanan Theera-Ampornpunt September 3, 2018
  • 2. 2 2003 M.D. (First-Class Honors) 2011 Ph.D. (Health Informatics), Univ. of Minnesota Assistant Dean for Informatics Lecturer, Department of Community Medicine Faculty of Medicine Ramathibodi Hospital Mahidol University Interests: Health IT for Quality of Care, Social Media IT Management, Security & Privacy nawanan.the@mahidol.ac.th SlideShare.net/Nawanan นวนรรน ธีระอัมพรพันธุ์ (Nawanan Theera-Ampornpunt) Line ID: NawananT Introduction
  • 3. 3  The Road to Digitizing Healthcare  What is a “Smart Hospital”?  Toward a “Smart” Hospital Outline
  • 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
  • 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 If not “Digital Hospital” or “Paperless Hospital” Then What Should We Aspire to Be?
  • 23. 23 So How is a “Smart Hospital” Different from a Digital or Paperless Hospital?
  • 25. 25 Healthcare 1.0 • Thai Traditional Medicine in the Ancient Times Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html การย่อยขนาดตัวยาสมุนไพร โดยใช้ครกตาและหินบดยา ของโรงศิริราชพยาบาล (ปัจจุบันคือ โรงพยาบาลศิริราช) คนไทยสมัยก่อนมักให้บุคคลในครอบครัวบีบนวดได้
  • 26. 26 Healthcare 2.0 • Modern (Western) Medicine Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
  • 27. 27 Healthcare 3.0 • Quality-Driven Healthcare Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
  • 28. 28 Healthcare 4.0 • Smart Healthcare & Smart Hospital Healthcare 1.0 - 4.0 is the speaker’s personal opinion and may not represent official views of the Ministry of Public Health Image & Caption Source: http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-detail.html http://kanchanapisek.or.th/kp6/sub/book/book.php?book=33&chap=8&page=t33-8-infodetail02.html
  • 29. 29 So What Is Smart Healthcare?
  • 30. 30 Smart Healthcare For Policymakers? Image Source: http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99
  • 31. 31 Smart Healthcare For Health Promoters? Image Source: http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf
  • 32. 32 Smart Healthcare For Clinicians? Image Source: http://www.medscape.com/viewarticle/780298
  • 33. 33 Smart Healthcare For Patients & Consumers? Image Source: Agence France-Presse/Getty Images
  • 34. 34 So What Exactly Is Smart Healthcare? Image Source: http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg
  • 35. 35 The Road to Digitizing Healthcare  What is a “Smart Hospital”?  Toward a “Smart” Hospital Outline
  • 36. 36 Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente https://www.youtube.com/watch?v=gxz9ZVvduGc
  • 38. 38 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?
  • 39. 39 • 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
  • 41. 41 “Information” in Medicine Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
  • 43. 43 43 WHO (2009) WHO Health System Framework
  • 44. 44 • 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
  • 45. 45 • Efficient –Faster care –Time & cost savings –Reducing unnecessary tests • Equitable –Access to providers & knowledge • Patient-Centered –Empowerment & better self-care Being “Smart” in Healthcare
  • 46. 46 (IOM, 2001)(IOM, 2000) (IOM, 2011) Landmark Institute of Medicine Reports
  • 47. 47 • 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
  • 48. 48 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
  • 49. 49 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
  • 50. 50Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital To Err is Human 2: Memory
  • 51. 51 • 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
  • 52. 52 • It already happens.... (Mamede et al., 2010; Croskerry, 2003; Klein, 2005; Croskerry, 2013) What If This Happens in Healthcare?
  • 53. 53 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
  • 54. 54 • Medication Errors –Drug Allergies –Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines Common Errors
  • 55. 55 Being Smart #3: “To Err is Human”
  • 56. 56 External Memory Knowledge Data Long Term Memory Knowledge Data Inference DECISION PATIENT Perception Attention Working Memory CLINICIAN Elson, Faughnan & Connelly (1997) Clinical Decision Making
  • 57. 57 Example of “Alerts & Reminders” Reducing Errors through “Alerts & Reminders”
  • 58. 58 Why We Need ICT in Healthcare? #1: Because information is everywhere in healthcare
  • 59. 59 Why We Need ICT in Healthcare? #2: Because healthcare is error-prone and technology can help
  • 61. 61 Why We Need ICT in Healthcare? #3: Because access to high-quality patient information should improve care
  • 62. 62 Why We Need ICT in Healthcare? #4: Because healthcare at all levels is fragmented & in need of process improvement
  • 63. 63 Documented Values of Health IT • Guideline adherence • Better documentation • Practitioner decision making or process of care • Medication safety • Patient surveillance & monitoring • Patient education/reminder
  • 64. 64 Being Smart #4: Link IT Values to Quality (Including Safety)
  • 65. 65 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
  • 66. 66 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
  • 67. 67 eHealth  Health IT Slide adapted from: Dr. Boonchai Kijsanayotin eHealth & Health IT
  • 69. 69 Hospital Information System (HIS) Computerized Physician Order Entry (CPOE) Electronic Health Records (EHRs) Picture Archiving and Communication System (PACS) Various Forms of Health IT
  • 70. 70 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
  • 71. 71 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
  • 72. 72 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
  • 74. 74 Incarnations of Health IT Clinical Informatics Public Health Informatics Consumer Health Informatics HIS/CIS EHRs Computerized Physician Order Entry (CPOE) Clinical Decision Support Systems (CDS) (including AI) Closed Loop Medication PACS/RIS LIS Nursing Apps Disease Surveillance (Active/Passive) Business Intelligence & Dashboards Telemedicine Real-time Syndromic Surveillance mHealth for Public Health Workers & Volunteers PHRs Health Information Exchange (HIE) eReferral mHealth for Consumers Wearable Devices Social Media Copyright  Nawanan Theera-Ampornpunt (2018)
  • 75. 75 TEDxMahidolU Talk by Nawanan: “ATM in Healthcare”
  • 76. 76 Hospital A Hospital B Clinic D Policymakers Patient at Home Hospital C HIE Platform Health Information Exchange (HIE)
  • 78. 78WHO & ITU Achieving Health Information Exchange (HIE)
  • 79. 79 • 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?
  • 80. 80 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
  • 81. 81 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
  • 82. 82 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
  • 83. 83 The Road to Digitizing Healthcare What is a “Smart Hospital”?  Toward a “Smart” Hospital Outline
  • 84. 84 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/
  • 85. 85Image Source: socialmediab2b.com Another Smart Machine: IBM’s Watson
  • 87. 87 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
  • 88. 88 Being Smart #6: Don’t Replace Human Users. Use ICT to Help Them Perform Smarter & Better.
  • 89. 89 Some Risks of Clinical Decision Support Systems • Alert Fatigue Unintended Consequences of Health IT
  • 91. 91 Being Smart #7: Health IT Also Have Risks & Unintended Consequences
  • 92. 92 Balanced Focus of Informatics Technology ProcessPeople
  • 93. 93 Being Smart #8: Balance Your Focus (People, Process, Technology)
  • 94. 94 2003 M.D. (First-Class Honors) 2011 Ph.D. (Health Informatics), Univ. of Minnesota Assistant Dean for Policy and Informatics Lecturer, Department of Community Medicine Faculty of Medicine Ramathibodi Hospital Mahidol University Interests: Health IT for Quality of Care, Social Media IT Management, Security & Privacy nawanan.the@mahidol.ac.th SlideShare.net/Nawanan นวนรรน ธีระอัมพรพันธุ์ (Nawanan Theera-Ampornpunt) Line ID: NawananT Q&A