Digital Health Transformation (March 16, 2019)
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This document discusses digital health transformation and the concept of a "smart hospital". It begins by looking at various technologies like artificial intelligence, cloud computing, the internet of things, and how they are impacting healthcare. It then defines what a smart hospital is, differentiating it from just a digital or paperless hospital. Specifically, a smart hospital leverages health information technology to improve the quality of care by making it safer, more timely, effective, patient-centered and efficient. The document outlines how technologies like electronic health records, computerized physician order entry, and clinical decision support systems can help hospitals achieve these goals and move towards becoming truly smart.
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Digital Health Transformation (March 16, 2019)
- 1. Digital Health Transformation Nawanan Theera-Ampornpunt, M.D., Ph.D. March 16, 2019 www.SlideShare.net/Nawanan
- 2. 2003 M.D. (First-Class Honors) 2011 Ph.D. (Health Informatics), Univ. of Minnesota Assistant Dean for Informatics Lecturer, Department of Community Medicine 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. ▪ The Road to Digital Health Transformation ▪ What is a “Smart Hospital”? ▪ Toward a “Smart” Hospital Outline
- 4. What words come to mind when you hear... Digital Health Transformation
- 6. 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
- 7. englishmoviez.com Rise of the Machines?
- 9. “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)
- 10. Hype vs. Hope Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
- 11. Gartner Hype Cycle 2017 https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/
- 14. Let’s take a look at these pictures...
- 15. Image Source: https://en.wikipedia.org/wiki/Industrial_robot (KUKA Roboter GmbH) “Smart” Manufacturing
- 17. ER - Image Source: nj.com Healthcare (On TV)
- 18. (At an undisclosed hospital) Healthcare (Reality)
- 19. • 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”?
- 20. But...Are We That Different? Input Process Output Transfer Banking Value-Add - Security - Convenience - Customer Service Location A Location B
- 21. Input Process Output Assembling Manufacturing Raw Materials Finished Goods Value-Add - Innovation - Design - QC But...Are We That Different?
- 22. 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?
- 23. • Large variations & contextual dependence Input Process Output Patient Presentation Decision- Making Biological Responses Standardizing Healthcare
- 24. 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/
- 25. Digitizing Healthcare Image Source: http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital
- 26. “To computerize the hospital” “To go paperless” “To become a Digital Hospital” “To Have EHRs” Why Adopting Health IT?
- 27. • “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
- 28. Being Smart #1: Stop Your “Drooling Reflex”!!
- 29. Being Smart #2: Focus on Information & Process Improvement, Not Technology
- 30. If not “Digital Hospital” or “Paperless Hospital” Then What Should We Aspire to Be?
- 31. “Smart Hospital”
- 32. So How is a “Smart Hospital” Different from a Digital or Paperless Hospital?
- 33. Smart Healthcare For Policymakers? Image Source: http://healthdata.moph.go.th/kpi/2557/ProvinceKpiTopicListAll.php?provincecode=99
- 34. Smart Healthcare For Health Promoters? Image Source: http://www.hiso.or.th/hiso/picture/reportHealth/ThaiHealth2014/thai2014_3.pdf
- 35. Smart Healthcare For Clinicians? Image Source: http://www.medscape.com/viewarticle/780298
- 36. Smart Healthcare For Patients & Consumers? Image Source: Agence France-Presse/Getty Images
- 37. So What Exactly Is Smart Healthcare? Image Source: http://cdn2.hubspot.net/hub/134568/file-1208368053-jpg/6-blind-men-hans.jpg
- 38. ✓The Road to Digital Health Transformation ▪ What is a “Smart Hospital”? ▪ Toward a “Smart” Hospital Outline
- 39. https://www.youtube.com/watch?v=gxz9ZVvduGc Connecting People to a Healthy Future With Personalized Care – Kaiser Permanente
- 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. Why Aren’t We Talk About These Words? http://hcca-act.blogspot.com/2011/07/reflections-on-patient-centred-care.html
- 43. The Goal of Health Care The answer is already obvious... “Health” “Care”
- 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. Information Is Everywhere in Healthcare
- 46. Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8. “Information” in Medicine
- 47. 47 47 WHO (2009) Components of Health Systems
- 48. 48 48 WHO (2009) WHO Health System Framework
- 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. • 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. (IOM, 2001)(IOM, 2000) (IOM, 2011) Landmark Institute of Medicine Reports
- 52. • 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
- 53. • 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
- 54. 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
- 55. Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital To Err is Human 2: Memory
- 56. • 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 & web subscription $125 68 32 # of People # of People To Err is Human 3: Cognition
- 57. • It already happens.... (Mamede et al., 2010; Croskerry, 2003; Klein, 2005; Croskerry, 2013) What If This Happens in Healthcare?
- 58. Klein 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
- 59. • Medication Errors – Drug Allergies – Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines Common Errors
- 60. Being Smart #3: “To Err is Human”
- 61. External Memory Knowledge Data Long Term Memory Knowledge Data Inference DECISION PATIENT Perception Attention Working Memory CLINICIAN Elson, Faughnan & Connelly (1997) Clinical Decision Making
- 62. Example of “Alerts & Reminders” Reducing Errors through Alerts & Reminders
- 63. • Guideline adherence • Better documentation • Practitioner decision making or process of care • Medication safety • Patient surveillance & monitoring • Patient education/reminder Documented Values of Health IT
- 64. Being Smart #4: Link IT Values to Quality (Including Safety)
- 65. 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
- 66. 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
- 67. eHealth Health IT Slide adapted from: Dr. Boonchai Kijsanayotin eHealth & Health IT
- 69. Hospital Information System (HIS) Computerized Physician Order Entry (CPOE) Electronic Health Records (EHRs) Picture Archiving and Communication System (PACS) Various Forms of Health IT
- 70. 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
- 71. 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
- 72. 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
- 73. Hospital A Hospital B Clinic D Policymakers Patient at Home Hospital C HIE Platform Health Information Exchange (HIE)
- 76. 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
- 77. 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)
- 78. 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
- 79. Healthtech Startup Ecosystem www.facebook.com/HealthTechThailand/ No endorsements implied
- 80. ✓The Road to Digital Health Transformation ✓What is a “Smart Hospital”? ▪ Toward a “Smart” Hospital Outline
- 81. WHO & ITU Achieving Health Information Exchange (HIE)
- 83. 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 about Standards
- 84. 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
- 85. http://www.ibtimes.com/google-deepminds-alphago-program-defeats-human-go-champion-first-time-ever-2283700 http://deepmind.com/ http://socialmediab2b.com Rise of the Machines?
- 86. • 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)
- 87. Being Smart #6: Don’t Replace Human Users. Use ICT to Help Them Perform Smarter & Better.
- 88. Some Risks of Clinical Decision Support Systems • Alert Fatigue Unintended Consequences of Health IT
- 89. Workarounds Unintended Consequences of Health IT
- 90. Being Smart #7: Health IT Also Have Risks & Unintended Consequences
- 91. Technology ProcessPeople Balanced Focus of Informatics
- 92. Being Smart #8: Balance Your Focus (People, Process, Technology)
- 93. WHO & ITU Achieving Digital Health Transformation
- 94. 94 My Plea... Less Fancy Roofs More Enabling Foundations