health informatics in digital healthcare
TRANSCRIPT
Health Informatics in Digital Healthcare
9th Thailand Pharmacy Congress: Smart Aging Life & Digital Pharmacy 4.0
นพ.นวนรรน ธีระอัมพรพนัธุ์
18 พฤศจิกายน 2560
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2546 แพทยศาสตรบณัฑติ (เกยีรตนิิยมอนัดบั 1)
2554 Ph.D. (Health Informatics), Univ. of Minnesota
ผูช้ว่ยคณบดฝ่ีายนโยบายและสารสนเทศอาจารย์ ภาควชิาเวชศาสตรช์ุมชนคณะแพทยศาสตรโ์รงพยาบาลรามาธบิดี มหาวทิยาลยัมหดิล
ความสนใจ: Health IT for Quality of Care,
IT Management, Security & Privacy
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แนะน ำตัว
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Health &
Health Information
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Let’s take a look at these pictures...
5Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH)
“Smart” Manufacturing
6Image Sources: http://isarapost.net/home/?p=17760
http://www.telecomjournalthailand.com/ตอบโจทยโ์มเดลทางธรุกจิ/
“Smart” Banking
7ER - Image Source: nj.com
Healthcare (On TV)
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(At an undisclosed hospital)
Healthcare (Reality)
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• 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”?
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But...Are We That Different?
Input Process Output
Transfer
Banking
Value-Add- Security- Convenience- Customer Service
Location A Location B
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Input Process Output
Assembling
Manufacturing
Raw Materials Finished Goods
Value-Add- Innovation- Design- QC
But...Are We That Different?
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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?
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• Large variations & contextual dependence
Input Process Output
Patient Presentation
Decision-Making
Biological Responses
Standardizing Healthcare
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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/
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Digitizing Healthcare
Image Source: http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital
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“To computerize the hospital”
“To go paperless”
“To become a Digital Hospital”
“To Have EHRs”
Why Adopting Health IT?
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• “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
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Being Smart #1:
Stop Your
“Drooling Reflex”!!
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Being Smart #2:
Focus on Information &
Process Improvement,
Not Technology
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ถ้าไม่เป็น “Digital Hospital” หรือ “Paperless Hospital”
แล้วจะให้เรำเป็นอะไร?
“Smart Hospital”
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แล้ว “Smart Hospital” ต่างจาก Digital หรือ
Paperless Hospital ตรงไหน?
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Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente
https://www.youtube.com/watch?v=gxz9ZVvduGc
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Back to something simple...
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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?
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• 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
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My personal story on
why we need doctors to
implement health IT
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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(Shortliffe, 2002)
Spectrum of Biomedical & Health Informatics
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Information is Everywhere in Healthcare
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WHO (2009)
Components of Health Systems
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• 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
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• Efficient
– Faster care
– Time & cost savings
– Reducing unnecessary tests
• Equitable
– Access to providers & knowledge
• Patient-Centered
– Empowerment & better self-care
Being “Smart” in Healthcare
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(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark Institute of Medicine Reports
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• 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
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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
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• Medication Errors
– Drug Allergies
– Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors
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Being Smart #3:
“To Err is Human”
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
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Example of “Alerts & Reminders”
Reducing Errors through “Alerts & Reminders”
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Documented Values of Health IT
• Guideline adherence
• Better documentation
• Practitioner decision making or process of care
• Medication safety
• Patient surveillance & monitoring
• Patient education/reminder
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Being Smart #4:
Link IT Values to
Quality (Including Safety)
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Health
Information
Technology
Goal
Value-Add
Tools
Health IT: What’s in a Word?
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Hospital Information System (HIS) Computerized Physician Order Entry (CPOE)
Electronic Health
Records (EHRs)
Picture Archiving and Communication System
(PACS)
Various Forms of Health IT
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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
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Health IT for Medication Safety
Ordering Transcription Dispensing Administration
CPOEAutomatic Medication Dispensing
Electronic Medication
Administration Records (e-MAR)
BarcodedMedication
Administration
BarcodedMedication Dispensing
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Hospital A Hospital B
Clinic C
Government
Lab Patient at Home
Health Information Exchange
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ความฝันอันสูงสุด...
My Life-Long Dream...
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50WHO & ITU
Achieving Health Information Exchange (HIE)
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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/
52Image Source: socialmediab2b.com
Another Smart Machine: IBM’s Watson
53Image Source: englishmoviez.com
Rise of the Machines?
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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
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Being Smart #5:
Don’t Replace Human Users.
Use ICT to Help Them Perform Smarter & Better.
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Some Risks of Clinical Decision Support Systems
• Alert Fatigue
Unintended Consequences of Health IT
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Workarounds
Unintended Consequences of Health IT
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Being Smart #6:
Health IT Also Have
Risks &
Unintended Consequences
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Balanced Focus of Informatics
Technology
ProcessPeople
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Being Smart #7:
Balance Your Focus (People, Process, Technology)
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Q&A
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