For PHID 682 Integration and Innovation of Public Health class, Mahidol University Faculty of Public Health on November 7, 2014

1. Health Informatics & eHealth:
Application of ICT for Health
PHID 682 Integration and Innovation of Public Health
Mahidol University Faculty of Public Health
November 7, 2014
Nawanan Theera-Ampornpunt, M.D., Ph.D.
Department of Community Medicine
Faculty of Medicine Ramathibodi Hospital
SlideShare.net/Nawanan

2. 2
Outline
• Health & Health Information
• Health IT & eHealth
• Health Informatics as a Discipline
• Thailand’s eHealth Situation
• Current Forces

3. 3
Health &
Health Information

4. 4
Let’s take a look at
these pictures...

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

6. Banking
Image Source: http://www.oknation.net/blog/phuketpost/2013/10/19/entry-3 6

7. Healthcare (on TV)
ER - Image Source: nj.com 7

8. 8
Healthcare (Reality)
(At an undisclosed nearby hospital)

9. 9
Why Healthcare Isn’t Like Any Others
• 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

10. 10
Back to
something simple...

11. 11
What Clinicians Want?
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)

12. 12
• 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

13. 13
Information is Everywhere in Healthcare

14. 14
“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA.
2010 Sep 15;304(11):1227-8.

15. 15
Components of Health Systems
15
WHO (2009)

16. 16
WHO Health System Framework
16
WHO (2009)

17. 17
Outline
Health & Health Information
• Health IT & eHealth
• Health Informatics as a Discipline
• Thailand’s eHealth Situation
• Current Forces

18. 18
Health IT &
eHealth

19. 19
Landmark IOM Reports
(IOM, 2000) (IOM, 2001) (IOM, 2011)

20. 20
Patient Safety
• 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
Health IT Workforce Curriculum Version
3.0/Spring 2012 Introduction to Healthcare and Public Health in the US: Regulating Healthcare - Lecture d

21. 21
IOM Reports Summary
• 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

22. To Err is Human 1: Attention
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
22

23. To Err is Human 2: Memory
Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital 23

24. 24
To Err is Human 3: Cognition
• Cognitive Errors - Example: Decoy Pricing
The Economist Purchase Options
• Economist.com subscription $59
• Print subscription $125
• Print & web subscription $125
Ariely (2008)
# of
People
16
0
84
The Economist Purchase Options
• Economist.com subscription $59
• Print & web subscription $125
# of
People
68
32

25. 25
What If This Happens in Healthcare?
• It already happens....
(Mamede et al., 2010; Croskerry, 2003;
Klein, 2005; Croskerry, 2013)

26. Mamede S, van Gog T, van den Berge K, Rikers RM, van Saase JL, van Guldener C,
Schmidt HG. Effect of availability bias and reflective reasoning on diagnostic accuracy
among internal medicine residents. JAMA. 2010 Sep 15;304(11):1198-203.
26
Cognitive Biases in Healthcare

27. Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them.
Acad Med. 2003 Aug;78(8):775-80.
27
Cognitive Biases in Healthcare

28. 28
Cognitive Biases in Healthcare
“Everyone makes mistakes. But our
reliance on cognitive processes prone to
bias makes treatment errors more likely
Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ. 2005 Apr
2;330(7494):781-3.
than we think”

29. 29
Common Errors
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines

30. 30
Why We Need ICT
in Healthcare?
#1: Because information is
everywhere in healthcare

31. 31
Why We Need ICT
in Healthcare?
#2: Because healthcare is
error-prone and technology
can help

32. 32
Why We Need ICT
in Healthcare?
#3: Because access to
high-quality patient
information improves care

33. 33
Why We Need ICT
in Healthcare?
#4: Because healthcare at
all levels is fragmented &
in need of process
improvement

34. 34
Health IT
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

35. 35
eHealth
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

36. 36
eHealth & Health IT
eHealth  Health IT
Slide adapted from: Dr. Boonchai Kijsanayotin

37. 37
More Terms...
All information about health
HIS
eHealth
HMIS
mHealth
Tele-medicine
Slide adapted from: Karl Brown (Rockefeller Foundation),
via Dr. Boonchai Kijsanayotin

38. 38
Health IT: What’s in a Word?
Health
Information
Technology
Goal
Value-Add
Tools

39. 39
eHealth Components: WHO-ITU Model
 All components are essential
 All components should be balanced
Slide adapted from: Dr. Boonchai Kijsanayotin

40. 40
Various Forms of Health IT
Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic
Health
Records
(EHRs)
Picture Archiving and
Communication System
(PACS)
Screenshot Images from Faculty of Medicine Ramathibodi Hospital, Mahidol University

41. 41
Still Many Other Forms of Health IT
mHealth
Biosurveillance
Telemedicine &
Telehealth
Personal Health Records
(PHRs) and Patient Portals
Images from Apple Inc., Geekzone.co.nz, Google, HealthVault.com and American Telecare, Inc.

42. 42
Documented Values of Health IT
• Guideline adherence
• Better documentation
• Practitioner decision making or
process of care
• Medication safety
• Patient surveillance & monitoring
• Patient education/reminder

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

44. 44
Some Hospital IT - Departmental Systems
• 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

45. 45
The Challenge - Knowing What It Means
Electronic Health
Records (EHRs)
Electronic Medical
Records (EMRs)
Electronic Patient
Records (EPRs)
Computer-Based
Patient Records
(CPRs)
Personal Health
Records (PHRs)
Hospital
Information System
(HIS)
Clinical Information
System (CIS)
EHRs & HIS

46. 46
Computerized Provider Order Entry (CPOE)

47. 47
Computerized Provider Order Entry (CPOE)
Values
• No handwriting!!!
• Structured data entry: Completeness, clarity,
fewer mistakes (?)
• No transcription errors!
• Streamlines workflow, increases efficiency

48. Clinical Decision Support Systems (CDS)
• The real place where most of the
values of health IT can be achieved
48
– Expert systems
• Based on artificial intelligence,
machine learning, rules, or
statistics
• Examples: differential
diagnoses, treatment options
(Shortliffe, 1976)

49. 49
Clinical Decision Support Systems (CDS)
– Alerts & reminders
• Based on specified logical conditions
• Examples:
– Drug-allergy checks
– Drug-drug interaction checks
– Reminders for preventive services
– Clinical practice guideline integration

50. 50
Examples of “Reminders”

51. Some Other CDS - Infobuttons
Image Source: https://webcis.nyp.org/webcisdocs/what-are-infobuttons.html 51

52. Some Other CDS - Order Sets/Checklists
Image Source: http://www.hospitalmedicine.org/ResourceRoomRedesign/CSSSIS/html/06Reliable/SSI/Order.cfm 52

53. Some Other CDS - Abnormal Lab Highlights
Image Source: http://geekdoctor.blogspot.com/2008/04/designing-ideal-electronic-health.html 53

54. 54
Clinical Decision Making & CDS
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
PATIENT
Perception
Attention
Working
Memory
Inference
DECISION
CLINICIAN
Elson, Faughnan & Connelly (1997)

55. IBM’s Watson
Image Source: socialmediab2b.com 55

56. Rise of the Machines
Image Source: englishmoviez.com 56

57. 57
Proper Roles of CDS
• CDS 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

58. 58
Unintended Consequences of Health IT
Some risks
• Alert fatigue

59. 59
The Big Picture: Health Information Exchange (HIE)
Hospital A Hospital B
Clinic C
Government
Lab Patient at Home

60. 60
Outline
Health & Health Information
Health IT & eHealth
• Health Informatics as a Discipline
• Thailand’s eHealth Situation
• Current Forces

61. 61
Health Informatics
as a Discipline

62. 62
M/B/H Informatics As A Field
(Shortliffe, 2002)

63. M/B/H Informatics As a Discipline
(Hersh, 2009) 63

64. 64
M/B/H Informatics & Other Fields
Biomedical/
Health
Informatics
Engineering
Computer &
Information
Science
Cognitive
&
Decision
Science
Social
Sciences
(Psychology,
Sociology,
Linguistics,
Law &
Ethics)
Statistics
&
Research
Methods Medical
Sciences &
Public
Health
Management
Library
Science,
Information
Retrieval,
KM
And More!

65. 65
Outline
Health & Health Information
Health IT & eHealth
Health Informatics as a Discipline
• Thailand’s eHealth Situation
• Current Forces

66. 66
Thailand’s
eHealth Situation

67. 67
Thailand’s eHealth: 2010
eHealth in Thailand: The current status. Stud Health Technol Inform
2010;160:376–80, Presented at MedInfo2010 South Africa

68. Thailand: Unbalanced Development
Slide adapted from: Dr. Boonchai Kijsanayotin 68

69. 69
eHealth Development Model
eHealth Applications
Enabling Policies &
Strategies
Foundation Policies
& Strategies
• Services
• Applications
• Software
• Standards &
Interoperability
• Capability Building
• Leadership &
Governance
• Legislation & Policy
• Strategy & Investment
• Infrastructure
Slide adapted from: Dr. Boonchai Kijsanayotin

70. Thailand’s eHealth Development
Slide adapted from: Dr. Boonchai Kijsanayotin 70

71. 71
Thailand’s eHealth Situation
 Silo-type systems
 Little integration and interoperability
 Mostly aim for administration and management
 40% of work-hours spent on managing reports and
documents
 Lack of national leadership and governance body
 Inadequate HIS foundations development
Slide adapted from: Boonchai Kijsanayotin

72. 72
Thailand’s Health IT Adoption
Section 1 Hospital Profile
Section 2 IT Adoption & Use
Profile
Section 3 Respondent’s
Information

73. 73
Nationwide Survey Results
• 4 of 1,302 hospitals ineligible
• Response rate 69.9%
Characteristic Overall Responding
Hospitals
Non-
Responding
Hospitals
N of eligible hospitals 1,298 908 390
Bed size** 106.9 117.5 82.9
Public status**
Private
24.0%
17.4%
Public
76.0%
82.6%
39.2%
60.8%
Geography*
Central
East
North
Northeast
South
West
33.4%
7.5%
11.1%
27.1%
15.3%
5.6%
31.1%
7.8%
13.5%
26.9%
14.9%
5.8%
39.0%
6.7%
5.4%
27.7%
16.2%
5.1%
*p < 0.01, **p < 0.001.

74. Vendor/Product Distribution (2004)
Pongpirul et al., 2004 74

75. 75
Vendor/Product Distribution (2011)
Theera-Ampornpunt, 2011

76. 76
Health IT Adoption Estimates
Estimate (Partial or Complete Adoption) Nationwide
Basic EHR, outpatient 86.6%
Basic EHR, inpatient 50.4%
Basic EHR, both settings 49.8%
Comprehensive EHR, outpatient 10.6%
Comprehensive EHR, inpatient 5.7%
Comprehensive EHR, both settings 5.3%
Order entry of medications, outpatient 96.5%
Order entry of medications, inpatient 91.4%
Order entry of medications, both settings 90.2%
Order entry of all orders, outpatient 88.6%
Order entry of all orders, inpatient 81.7%
Order entry of all orders, both settings 79.4%

77. 77
THAIS: Discussion
• High IT adoption rates
• Drastic changes in adoption landscape
• Local context might play a role
– Supply Side
– Demand Side
• International Comparison
– Relatively higher adoption

78. 78
Outline
Health & Health Information
Health IT & eHealth
Health Informatics as a Discipline
Thailand’s eHealth Situation
• Current Forces

79. 79
Current Forces

80. 80
Current Forces
International
• Technology Trends
• Standards & Interoperability Trends
• eHealth Successes & Failures
– UK NHS
– US Meaningful Use
– Nordic Countries
• International eHealth Networks
– International Medical Informatics Association (IMIA)
– American Medical Informatics Association (AMIA)
– Asia eHealth Information Network (AeHIN)

81. 81
World Health Assembly Resolution WHA66.24 (2013) on
eHealth Standardization & Interoperability
URGES Member States:
(1) to consider, as appropriate, options to collaborate with
relevant stakeholders, including national authorities, relevant ministries,
health care providers, and academic institutions, in order to draw up a
road map for implementation of ehealth and health data standards at
national and subnational levels;
(2) to consider developing, as appropriate, policies and
legislative mechanisms linked to an overall national eHealth strategy, in
order to ensure compliance in the adoption of ehealth and health data
standards by the public and private sectors, as appropriate, and the
donor community, as well as to ensure the privacy of personal clinical
data;
http://apps.who.int/gb/ebwha/pdf_files/WHA66/A66_R24-en.pdf

82. 82
World Health Assembly Resolution WHA66.24 (2013) on
eHealth Standardization & Interoperability
(3) to consider ways for ministries of health and public
health authorities to work with their national representatives
on the ICANN Governmental Advisory Committee in order to
coordinate national positions towards the delegation,
governance and operation of health-related global top-level
domain names in all languages, including “.health”, in the
interest of public health;
http://apps.who.int/gb/ebwha/pdf_files/WHA66/A66_R24-en.pdf

83. 83
Current Forces
Domestic
• Thailand’s Health Insurance Trends
• Increased Hospital IT Adoption
• Demands for Data & Information Exchange
in Thailand’s Healthcare
• Thailand’s e-Transaction Trends
• Consumer IT Behavior Trends

84. 84
Outline
Health & Health Information
Health IT & eHealth
Health Informatics as a Discipline
Thailand’s eHealth Situation
Current Forces

85. The Journey Beyond:
A Long and Winding Road
Image Source: http://twinstrivia.com/2013/05/20/the-road-to-minnesota-is-long-and-hard/ 85