ICT in Healthcare (February 7, 2020)
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This document provides an overview of ICT in healthcare through a presentation by Nawanan Theera-Ampornpunt. It discusses how digitizing healthcare differs from a "paperless hospital" and aims to create a "smart hospital". A smart hospital focuses on using technology like electronic health records and clinical decision support systems to improve the quality of care by making it safer, more timely, effective and patient-centered. The presentation also covers challenges like unintended consequences of health IT and the need to balance technological changes with human factors. The goal of using information and communication technologies in healthcare should be to help clinicians perform better and provide high quality care to patients.
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ICT in Healthcare (February 7, 2020)
- 1. 1 ICT in Healthcare Nawanan Theera-Ampornpunt, M.D., Ph.D. February 7, 2020 www.SlideShare.net/Nawanan
- 2. 2 2003 M.D. (First-Class Honors) 2011 Ph.D. (Health Informatics), Univ. of Minnesota Deputy Dean for Operations Lecturer, Department of Clinical Epidemiology & Biostatistics 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 What words come to mind when you hear... Digital Health Transformation
- 5. 5 http://www.ibtimes.com/google-deepminds-alphago-program-defeats-human-go-champion-first-time-ever-2283700 http://deepmind.com/ http://socialmediab2b.com An Era of Smart Machines
- 6. 6englishmoviez.com Rise of the Machines?
- 8. 8 “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...” -- Dan Ariely @danariely (2013) Substitute “Big data” with “AI”, “Blockchain”, “IoT” of your choice. -- Nawanan Theera-Ampornpunt (2018)
- 9. 9 Hype vs. Hope Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
- 10. 10 Gartner Hype Cycle 2017 https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/
- 12. 12 A Real-Life Personal Story of My Failure (as a Doctor and as a Son) in Misdiagnosing My Mom Would AI Help?
- 13. 13 • Nothing is certain in medicine & health care • Large variations exist in patient presentations, clinical course, underlying genetic codes, patient & provider behaviors, biological responses & social contexts Why Clinical Judgment Is Still Necessary?
- 14. 14 • Most diseases are not diagnosed by diagnostic criteria, but by patterns of clinical presentation and perceived likelihood of different diseases given available information (differential diagnoses) • Human is good at pattern recognition, while machine is good at logic & computations Why Clinical Judgment Is Still Necessary?
- 15. 15 • Machines are (at best) as good as the input data –Not everything can be digitized or digitally acquired –Not everything digitized is accurate (“Garbage In, Garbage Out”) • Experience, context & human touch matters Why Clinical Judgment Is Still Necessary?
- 17. 17 Let’s take a look at these pictures...
- 18. 18Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH) “Smart” Manufacturing
- 20. 20ER - Image Source: nj.com Healthcare (On TV)
- 21. 21 (At an undisclosed hospital) Healthcare (Reality)
- 22. 22 • 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”?
- 23. 23 But...Are We That Different? Input Process Output Transfer Banking Value-Add - Security - Convenience - Customer Service Location A Location B
- 24. 24 Input Process Output Assembling Manufacturing Raw Materials Finished Goods Value-Add - Innovation - Design - QC But...Are We That Different?
- 25. 25 But...Are We That Different? Input Process Output Patient Care Health care Sick Patient Well Patient Value-Add - Technology & medications - Clinical knowledge & skills - Quality of care; process improvement - Information
- 26. 26 • Large variations & contextual dependence Why Health care Isn’t Like Any Others? Input Process Output Patient Presentation Decision- Making Biological Responses
- 27. 27 “To computerize the hospital” “To go paperless” “To become a Digital Hospital” “To Have EHRs” Why Adopting Health IT?
- 28. 28 • “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
- 29. 29 Being Smart #1: Stop Your “Drooling Reflex”!!
- 30. 30 Being Smart #2: Focus on Information & Process Improvement, Not Technology
- 31. 31 If not “Paperless Hospital” Then What Should We Aspire to Be?
- 33. 33 So How is a “Smart Hospital” Different from a Paperless Hospital?
- 34. 34 Smart Healthcare For Policymakers? Image Source: http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99
- 35. 35 Smart Healthcare For Health Promoters? Image Source: http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf
- 36. 36 Smart Healthcare For Clinicians? Image Source: http://www.medscape.com/viewarticle/780298
- 37. 37 Smart Healthcare For Patients & Consumers? Image Source: Agence France-Presse/Getty Images
- 38. 38 So What Exactly Is Smart Healthcare? Image Source: http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg
- 39. 39https://www.youtube.com/watch?v=gxz9ZVvduGc Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente
- 41. 41 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?
- 42. 42 Why Aren’t We Talk About These Words? http://hcca-act.blogspot.com/2011/07/reflections-on-patient-centred-care.html
- 43. 43 The Goal of Health Care The answer is already obvious... “Health” “Care”
- 44. 44 • 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
- 45. 45 Information Is Everywhere in Healthcare
- 46. 46 Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8. Information in Medicine
- 47. 47 47 47 WHO (2009) Components of Health Systems
- 48. 48 48 48 WHO (2009) WHO Health System Framework
- 49. 49 • 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
- 50. 50 • Efficient –Faster care –Time & cost savings –Reducing unnecessary tests • Equitable –Access to providers & knowledge • Patient-Centered –Empowerment & better self-care Being “Smart” in Healthcare
- 51. 51 (IOM, 2001)(IOM, 2000) (IOM, 2011) Landmark Institute of Medicine Reports
- 52. 52 • 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 Summary of These Reports
- 53. 53 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
- 54. 54Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital To Err is Human 2: Memory
- 55. 55 • 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 subscription $125 • Print & web subscription $125 68 - 32 # of People # of People To Err is Human 3: Cognition
- 56. 56 • It already happens.... (Mamede et al., 2010; Croskerry, 2003; Klein, 2005) • What if health IT can help? What If This Happens in Healthcare?
- 57. 57 • Medication Errors –Drug Allergies –Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines Common Errors
- 58. 58 Being Smart #3: “To Err is Human”
- 59. 59 External Memory Knowledge Data Long Term Memory Knowledge Data Inference DECISION PATIENT Perception Attention Working Memory CLINICIAN Elson, Faughnan & Connelly (1997) Clinical Decision Making
- 60. 60 Example of “Alerts & Reminders” Reducing Errors through Alerts & Reminders
- 61. 61 Being Smart #4: Link IT Values to Quality (Including Safety)
- 63. 63 Hospital Information System (HIS) Computerized Physician Order Entry (CPOE) Electronic Health Records (EHRs) Picture Archiving and Communication System (PACS) Various Forms of Health IT
- 64. 64 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
- 65. 65 Ordering Transcription Dispensing Administration CPOE Automatic Medication Dispensing Electronic Medication Administration Records (e-MAR) Barcoded Medication Administration Barcoded Medication Dispensing Health IT for Medication Safety
- 66. 66 Strategic Operational ClinicalAdministrative LIS Health Information ExchangeBusiness Intelligence Word Processor Social Media PACS 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 4 Quadrants of Hospital IT
- 68. 68 Hospital A Hospital B Clinic D Policymakers Patient at Home Hospital C HIE Platform Health Information Exchange (HIE)
- 69. 69 Areas of Health Informatics Patients & Consumers Providers & Patients Healthcare Managers, Policy- Makers, Payers, Epidemiologists, Researchers Copyright Nawanan Theera-Ampornpunt (2018) Clinical Informatics Public Health Informatics Consumer Health Informatics
- 70. 70 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)
- 71. 71 Where We Are Today... Copyright Nawanan Theera-Ampornpunt (2018) Clinical Informatics Public Health Informatics Consumer Health Informatics Technology that focuses on the sick, not the healthy Silos of data within hospitalPoor/unstructured data quality Lack of health data outside hospital Poor data integration across hospitals/clinics Poor data integration for monitoring & evaluation Poor data quality (GIGO) Finance leads clinical outcomes Poor IT change management Cybersecurity & privacy risks Few real examples of precision medicine Little access to own health data Poor patient engagement Poor accuracy of wearables Lack of evidence for health values Health literacy Information Behavioral change Few standards Lack of health IT governance
- 72. 72 Healthtech Startup Ecosystem www.facebook.com/HealthTechThailand/ No endorsements implied
- 73. 73WHO & ITU Achieving Health Information Exchange (HIE)
- 74. 74 Being Smart #5: Go for Systems that Use Standards, Not a Unified, Conquer-the-World System Image Source: https://www.businessinsider.in/google-let-users-play-with-thanos-destructive- power/articleshow/69054170.cms
- 75. 75 • 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 Clinical Decision Support Systems (CDS)
- 76. 76 Being Smart #6: Don’t Replace Human Users. Use ICT to Help Them Perform Smarter & Better.
- 77. 77 Some Risks of Clinical Decision Support Systems • Alert Fatigue Unintended Consequences of Health IT
- 78. 78 Workarounds Unintended Consequences of Health IT
- 79. 79 Being Smart #7: Health IT Also Have Risks & Unintended Consequences
- 80. 80 Technology ProcessPeople Balanced Focus of IT Management
- 81. 81 Being Smart #8: Balance Your Focus (People, Process, Technology)
- 82. 82 นวนรรน ธีระอัมพรพันธุ์ (Nawanan Theera-Ampornpunt) Line ID: NawananT SlideShare.net/Nawanan Q&A