Presented at the King Prajadhipok's Institute on May 12, 2018

1. การใช้เทคโนโลยีอนาคตกับผู้บริหารในยุค 4.0
บรรยายในหลักสูตรประกาศนียบัตรธรรมาภิบาลทางการแพทย์
สาหรับผู้บริหารระดับสูง รุ่นที่ 6
นพ.นวนรรน ธีระอัมพรพันธุ์
12 พฤษภาคม 2561

2. 2
2546 แพทยศาสตรบัณฑิต (เกียรตินิยมอันดับ 1)
2554 Ph.D. (Health Informatics), Univ. of Minnesota
ผู้ช่วยคณบดีฝ่ายสารสนเทศ
อาจารย์ ภาควิชาเวชศาสตร์ชุมชน
คณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล
ความสนใจ: Health IT for Quality of Care,
IT Management, Security & Privacy,
Social Media in Healthcare
nawanan.the@mahidol.ac.th
SlideShare.net/Nawanan
แนะนาตัว

3. 3
Health &
Health Information

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

5. 5Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH)
“Smart” Manufacturing

6. 6
Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทย์โมเดลทางธุรกิจ/
“Smart” Banking

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

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

9. 9
• 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”?

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

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

12. 12
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?

13. 13
• Large variations & contextual dependence
Input Process Output
Patient
Presentation
Decision-
Making
Biological
Responses
Standardizing Healthcare

14. 14
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/

15. 15
Digitizing Healthcare
Image Source: http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital

16. 16
“To computerize
the hospital”
“To go paperless”
“To become a
Digital Hospital”
“To Have
EHRs”
Why Adopting Health IT?

17. 17
• “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

18. 18
Being Smart #1:
Stop Your
“Drooling Reflex”!!

19. 19
Being Smart #2:
Focus on Information &
Process Improvement,
Not Technology

20. 20
ถ้าไม่เป็น “Digital Hospital”
หรือ “Paperless Hospital”
แล้วจะให้เราเป็นอะไร?

21. “Smart Hospital”

22. 22
แล้ว “Smart Hospital”
ต่างจาก Digital หรือ
Paperless Hospital ตรงไหน?

23. 23
Connecting People to a Healthy Future With
Personalized Care – Kaiser Permanente
https://www.youtube.com/watch?v=gxz9ZVvduGc

24. 24
Back to
something simple...

25. 25
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?

26. 26
• 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

27. 27
My personal story on
why we need doctors to
implement health IT

28. 28
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)

29. 29(Shortliffe, 2002)
Spectrum of Biomedical & Health Informatics

30. 30
Information is Everywhere in Healthcare

31. 31
31
WHO (2009)
Components of Health Systems

32. 32
• 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

33. 33
• Efficient
–Faster care
–Time & cost savings
–Reducing unnecessary tests
• Equitable
–Access to providers & knowledge
• Patient-Centered
–Empowerment & better self-care
Being “Smart” in Healthcare

34. 34
(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports

35. 35
• 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

36. 36
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

37. 37
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors

38. 38
Being Smart #3:
“To Err is Human”

39. 39
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
Working
Memory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making

40. 40
Example of “Alerts & Reminders”
Reducing Errors through “Alerts & Reminders”

41. 41
Documented Values of Health IT
• Guideline adherence
• Better documentation
• Practitioner decision making or
process of care
• Medication safety
• Patient surveillance &
monitoring
• Patient education/reminder

42. 42
Being Smart #4:
Link IT Values to
Quality (Including Safety)

43. 43
Health
Information
Technology
Goal
Value-Add
Tools
Health IT: What’s in a Word?

44. 44
Hospital Information System (HIS) Computerized Physician Order Entry (CPOE)
Electronic
Health
Records
(EHRs)
Picture Archiving and
Communication System
(PACS)
Various Forms of Health IT

45. 45
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

46. 46
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

47. 47
Health Information Exchange
Hospital A Hospital B
Clinic D
Policymakers
Patient at
Home
Hospital C
HIE Broker

48. 48
ความฝันอันสูงสุด...
My Life-Long Dream...

49. 49

50. 50WHO & ITU
Achieving Health Information Exchange (HIE)

51. 51
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/

52. 52Image Source: socialmediab2b.com
Another Smart Machine: IBM’s Watson

53. 53Image Source: englishmoviez.com
Rise of the Machines?

54. 54
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

55. 55
Being Smart #5:
Don’t Replace
Human Users.
Use ICT to Help Them
Perform Smarter & Better.

56. 56
Some Risks of Clinical Decision Support Systems
• Alert Fatigue
Unintended Consequences of Health IT

57. 57
Workarounds
Unintended Consequences of Health IT

58. 58
Being Smart #6:
Health IT Also Have
Risks &
Unintended Consequences

59. 59
Balanced Focus of Informatics
Technology
ProcessPeople

60. 60
Being Smart #7:
Balance Your Focus
(People, Process, Technology)

61. (Extra Slides)
Telemedicine:
Current Status & Issues
นพ.นวนรรน ธีระอัมพรพันธุ์
คณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล
12 พ.ค. 2561

62. Thailand’s Healthtech Ecosystem
Courtesy of Phongchai Petsanghan & Health Tech Startup Thailand (May 2018)

63. State of TeleHealth
Dorsey & Topol (2015)

64. • Current Trends
–Change from using telehealth to increase access to
health care to providing convenience and reducing
cost
–Expansion of telehealth to chronic conditions
–Migration of telehealth from hospitals and clinics to
home and mobile devices
State of TeleHealth
Dorsey & Topol (2015)

65. • Limitations of Telehealth
–Reimbursement
• Limited & fragmented insurance coverage of telehealth
• Potential for excess health care utilization
–Clinical issues
• Patient-physician relationship
• Quality of physical examination
• Quality of care with remote visits than with in-person
visits
State of TeleHealth
Dorsey & Topol (2015)

66. Dorsey & Topol (2015)
• Limitations of Telehealth
–Clinical issues (continued)
•Potential for abuse (e.g. overprescribing of
narcotics)
•Fragmentation of care among multiple providers
–Legal issues (e.g., state licensure, liability)
–Social issues (digital divide)
State of TeleHealth

67. Legal Issues
• Privacy & Security Issues
• Liability due to Risks of Medical Errors
 Misdiagnosis
 Delayed Diagnosis & Treatment
 Miscommunication & Information Reliability
• Legal Compliance
 พรบ.สถานพยาบาล, พรบ.วิชาชีพ, พรบ.ยา, พรบ.เครื่องมือ
แพทย์ ฯลฯ
 Legal Documentation

68. Legal Issues
• Roles of Professionals & Human-Technology
Balance

69. Medical Practice Issues
• Benefits of Telemedicine
–Patient accessibility/Convenience/Engagement
–Clinical outcomes (evidence still needed in most
cases)
–Reduced patient waiting time at the hospital
–Improved logistics (Medications, Materials, Patients)
–More longitudinal data for patient care

70. Medical Practice Issues
• Risks of Telemedicine
– Data accuracy, reliability & timeliness
– Limitations of technology in medical practice
– Diagnostic errors
– Treatment delays
– Miscommunication / Unrealistic expectations
– Doctor-patient relationship & trust
– Abuse
– Provider burden
– Legal compliance

71. Legal Aspect of Telemedicine
• Telemedicine เป็นการประกอบวิชาชีพเวชกรรม (หรือวิชาชีพอื่นๆ ที่เกี่ยวข้อง)
หรือไม่ มีมาตรฐานกากับอย่างไร (Patient Care, Documentation)
• Telemedicine ถูกบังคับโดย พรบ.สถานพยาบาลหรือไม่
• อุปกรณ์และเทคโนโลยี มีมาตรฐานกากับอย่างไร ถูกบังคับโดย พรบ.เครื่องมือแพทย์
หรือไม่
• กรณีมีข้อผิดพลาด/ผลเสียหายเกิดขึ้นจาก Telemedicine Practice ต้องรับผิดชอบ
หรือไม่ ความรับผิดชอบอยู่กับใคร (ผู้สั่งการรักษา, ผู้ให้การรักษา, ผู้ป่วย, เจ้าของ
ระบบ Telemedicine)
• สามารถส่งยาทางไกลให้ผู้ป่วยได้หรือไม่ ถูกบังคับโดย พรบ.ยา, พรบ.วัตถุออกฤทธิ์
ต่อจิตและประสาท, พรบ.ยาเสพติดให้โทษ, พรบ.วิชาชีพเภสัชกรรม หรือไม่ อย่างไร
• การดูแล Security & Privacy มีมาตรฐานอย่างไร

72. Q&A
SlideShare.net/Nawanan