the road toward a smart hospital (presented at roi et hospital) (2 feb 2016)
TRANSCRIPT
แนวทางการบริหาร รพ.ร้อยเอ็ดสู่ Smart Hospital
นพ.นวนรรน ธีระอัมพรพนัธุ์
2 กุมภาพันธ์ 2559
2
2546 แพทยศาสตรบณัฑติ2554 Ph.D. (Health Informatics), Univ. of Minnesota
อาจารย์ ภาควชิาเวชศาสตรช์ุมชนคณะแพทยศาสตรโ์รงพยาบาลรามาธบิดี มหาวทิยาลยัมหดิล
ความสนใจ: Health IT for Quality of Care,
IT Management, Security & Privacy
SlideShare.net/Nawanan
Nawanan Theera-Ampornpunt
Line ID: NawananT
แนะน าตัว
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
7Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทยโ์มเดลทางธรุกจิ/
“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
ถ้าไม่เป็น “Digital Hospital” หรือ “Paperless Hospital”
แล้วจะให้เราเป็นอะไร?
“Smart Hospital”
23
แล้ว “Smart Hospital” ต่างจาก Digital หรือ
Paperless Hospital ตรงไหน?
24
The Road to Digitizing Healthcare
What is a “Smart Hospital”?
Toward a “Smart” Hospital
Outline
25
Microsoft Health Future Vision
https://www.microsoft.com/en-us/download/details.aspx?id=12801
26
Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente
https://www.youtube.com/watch?v=gxz9ZVvduGc
27
Back to something simple...
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
• 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
30
Information is Everywhere in Healthcare
31
“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA.
2010 Sep 15;304(11):1227-8.
32
32
WHO (2009)
Components of Health Systems
33
33
WHO (2009)
WHO Health System Framework
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
• Efficient
–Faster care
–Time & cost savings
–Reducing unnecessary tests
• Equitable
–Access to providers & knowledge
• Patient-Centered
–Empowerment & better self-care
Being “Smart” in Healthcare
36
(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports
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
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
39Image 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
40Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital
To Err is Human 2: Memory
41
• Cognitive Errors - Example: Decoy Pricing
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Ariely (2008)
16
0
84
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68
32
# of
People
# of
People
To Err is Human 3: Cognition
42
• It already happens....(Mamede et al., 2010; Croskerry, 2003; Klein,
2005; Croskerry, 2013)
What If This Happens in Healthcare?
43Klein 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
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors
45
Being Smart #3:
“To Err is Human”
46
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
47
Example of “Alerts & Reminders”
Reducing Errors through “Alerts & Reminders”
48
Why We Need ICT
in Healthcare?
#1: Because information is
everywhere in healthcare
49
Why We Need ICT in Healthcare?
#2: Because healthcare is error-prone and technology
can help
50http://www.dplindbenchmark.com/wp-content/uploads/2013/02/HHRI-Our-Health-Care-River.pdf
Fragmented Healthcare
51
Why We Need ICT
in Healthcare?
#3: Because access to
high-quality patient information
should improve care
52
Why We Need ICT in Healthcare?
#4: Because healthcare at all levels is fragmented &
in need of process improvement
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
54
Being Smart #4:
Link IT Values to
Quality (Including Safety)
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
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
eHealth Health IT
Slide adapted from: Dr. Boonchai Kijsanayotin
eHealth & Health IT
58
Health
Information
Technology
Goal
Value-Add
Tools
Health IT: What’s in a Word?
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
60
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
61
Health IT for Medication Safety
Ordering Transcription Dispensing Administration
CPOEAutomatic Medication Dispensing
Electronic Medication
Administration Records (e-MAR)
BarcodedMedication
Administration
BarcodedMedication Dispensing
62
Hospital A Hospital B
Clinic C
Government
Lab Patient at Home
Health Information Exchange
63
ความฝันอันสูงสุด...
My Life-Long Dream...
64WHO & ITU
Achieving Health Information Exchange (HIE)
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
นวนรรน ธีระอัมพรพันธุ์. ต ำนำนควำมเชื่อและข้อเท็จจริงเกี่ยวกับมำตรฐำนสำรสนเทศทำงสุขภำพ. 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
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
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
The Road to Digitizing Healthcare
What is a “Smart Hospital”?
Toward a “Smart” Hospital
Outline
70
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/
71Image Source: socialmediab2b.com
Another Smart Machine: IBM’s Watson
72Image Source: englishmoviez.com
Rise of the Machines?
73Image Source: amazon.com
Smart Phones, Dumb People?
74
Smart Hospital,
Dumb...?
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
76
Being Smart #6:
Don’t Replace Human Users.
Use ICT to Help Them Perform Smarter & Better.
77
Some Risks of Clinical Decision Support Systems
• Alert Fatigue
Unintended Consequences of Health IT
78
Workarounds
Unintended Consequences of Health IT
79
Being Smart #7:
Health IT Also Have
Risks &
Unintended Consequences
80
Balanced Focus of Informatics
Technology
ProcessPeople
81
Being Smart #8:
Balance Your Focus (People, Process, Technology)
82The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
The destination
The boatThe 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
83
Being Smart #9:
Know Your Context &
Align IT with that Context
84
รพ.มหาวิทยาลัย 900 เตียง
Vision เป็นโรงพยำบำลชั้นน ำของภูมิภำคเอเชียที่มีควำมเป็นเลิศในด้ำนบริกำร กำรศึกษำ และวิจัย
รพ.เอกชน 200 เตียง
Vision เป็นโรงพยำบำล High Tech High Touch ชั้นน ำของประเทศ
Vision, Mission & IT Strategies
85Carr (2004) Carr (2003)
IT as “The Sail”
86
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
87
Being Smart #10:
Identify Your
Strategic IT Assets
88
People
Techno-logy
Process
“The Sailors”
89
รพ.มหาวิทยาลัย 900 เตียง
• บุคลำกรมีอำยุเฉลี่ย 42 ปี (range 20-65)
• แผนก IT มีทั้งบุคลำกรใหม่และที่เคยพัฒนำระบบ HIS ตั้งแต่แรกเริ่ม
• แพทย์มีควำมเป็นตัวของตัวเองสูง, มักท ำงำนเอกชนด้วย, มี turn-over rate สูง
• พยำบำลและวิชำชีพอื่นมักมองว่ำแพทย์คืออภิสิทธิ์ชน และมีเรื่องถกเถียงกันบ่อยๆ
รพ.เอกชน 200 เตียง
• บุคลำกรมีอำยุเฉลี่ย 32 ปี (range 20-57)
• แผนก IT เข้มแข็ง• แพทย์ไม่ค่อยมี interaction กับ
บุคลำกรอื่น, รำยได้เป็นแรงดึงดูดหลัก• ผู้บริหำรได้รับกำรยอมรับจำกบุคลำกร
ทุกวิชำชีพว่ำมีวิสัยทัศน์และบริหำรงำนได้ดี
“The Sailors”
90Ash et al. (2003)
The “Special People”
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”
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”
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”
94
Being Smart #11:
Manage Your
“Special People” Well
95
A True Story of Failure to
Involve Users in Hospital IT
Implementation
96
Being Smart #12:
Involve Users Early &
Intensively in Your Process
97Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle
http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
Gartner Hype Cycle
98Rogers (2003)
Rogers’ Diffusion of Innovations: Adoption Curve
99
• Communications of project plans & progresses
• Workflow considerations
• Management support of IT projects
• Common visions
• Shared commitment
• Multidisciplinary user involvement
• Project management
• Training
• Innovativeness
• Organizational learning
Theera-Ampornpunt (2009, 2011)
Success Factors of Hospital IT Adoption
100
Being Smart #13:
Work Smartly with
Smart People
101
To become a smart hospital, you must
• Know what is “smart” all about
• Know how to use smart machinestogether with smart people
• Manage both of them smartly
Summary
102
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