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Use of ICT in Healthcare
A document discusses introducing information technology systems into healthcare services. It begins by introducing the speaker, Dr. Nawanan Theeramamphorn, who has a PhD in health informatics. The presentation then outlines the topics to be covered, including the road to digitizing healthcare, what a "smart hospital" is, and how to move toward a smart hospital.
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Use of ICT in Healthcare
- 1. การนาระบบเทคโนโลยีสารสนเทศ มาใช้ในงานให้บริการทางการแพทย์ บรรยาย ณ กฟผ. นพ.นวนรรนธีระอัมพรพันธุ์ 17 มีนาคม 2560
- 2. 2 2546 แพทยศาสตรบัณฑิต 2554 Ph.D.(Health Informatics), Univ. of Minnesota ผู้ช่วยคณบดีฝ่ายนโยบายและสารสนเทศ อาจารย์ ภาควิชาเวชศาสตร์ชุมชน คณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล ความสนใจ: Health IT for Quality of Care, IT Management, Security & Privacy nawanan.the@mahidol.ac.th SlideShare.net/Nawanan แนะนาตัว
- 3. 3 The Roadto Digitizing Healthcare What is a “Smart Hospital”? Toward a “Smart” Hospital Outline
- 4.
- 5. 5 Let’s take alook at these pictures...
- 6. 6Image Source: https://en.wikipedia.org/wiki/Industrial_robot(KUKA Roboter GmbH) “Smart” Manufacturing
- 7.
- 8. 8ER - ImageSource: nj.com Healthcare (On TV)
- 9. 9 (At an undisclosedhospital) Healthcare (Reality)
- 10. 10 • Life-or-Death • Difficultto 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. 11 But...Are We ThatDifferent? Input Proces s Output Transfer Banking Value-Add - Security - Convenience - Customer Service Location A Location B
- 12. 12 Input Proces s Output Assembling Manufacturing Raw Materials Finished Goods Value-Add -Innovation - Design - QC But...Are We That Different?
- 13. 13 Input Proces s Output Patient Care Health care SickPatient Well Patient Value-Add - Technology & medications - Clinical knowledge & skilled providers - Quality of care; process improvement - Customer service - Information But...Are We That Different?
- 14. 14 • Large variations& contextual dependence Input Proces s Output Patient Presentation Decision- Making Biological Responses Standardizing Healthcare
- 15. 15 The World ofSmart Machines Image Sources: http://www.ibtimes.com/google-deepminds-alphago- program-defeats-human-go-champion-first-time-ever-2283700 http://deepmind.com/
- 16. 16 Digitizing Healthcare Image Source:http://www.bloomberg.com/bw/stories/2005-03-27/cover-image-the-digital-hospital
- 17. 17 “To computerize the hospital” “Togo paperless” “To become a Digital Hospital” “To Have EHRs” Why Adopting Health IT?
- 18. 18 • “Don’t implementtechnology 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. 19 Being Smart #1: StopYour “Drooling Reflex”!!
- 20. 20 Being Smart #2: Focuson Information & Process Improvement, Not Technology
- 21. 21 ถ้าไม่เป็น “Digital Hospital” หรือ“Paperless Hospital” แล้วจะให้เราเป็นอะไร?
- 22.
- 23. 23 แล้ว “Smart Hospital” ต่างจากDigital หรือ Paperless Hospital ตรงไหน?
- 24. 24 The Road toDigitizing Healthcare What is a “Smart Hospital”? Toward a “Smart” Hospital Outline
- 25.
- 26. 26 Connecting People toa Healthy Future With Personalized Care – Kaiser Permanente https://www.youtube.com/watch?v=gxz9ZVvduGc
- 27.
- 28. 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. 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. 30 Information is Everywherein Healthcare
- 31. 31 31 WHO (2009) Components ofHealth Systems
- 32. 32 32 WHO (2009) WHO HealthSystem Framework
- 33. 33 • Safe –Drug allergies –MedicationReconciliation • 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
- 34. 34 • Efficient –Faster care –Time& cost savings –Reducing unnecessary tests • Equitable –Access to providers & knowledge • Patient-Centered –Empowerment & better self-care Being “Smart” in Healthcare
- 35. 35 (IOM, 2001)(IOM, 2000)(IOM, 2011) Landmark Institute of Medicine Reports
- 36. 36 • To Erris 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
- 37. 37 Summary of TheseReports • 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
- 38. 38 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
- 39. 39Image Source: SuthanSrisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital To Err is Human 2: Memory
- 40. 40 • 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
- 41. 41 • Medication Errors –DrugAllergies –Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines Common Errors
- 42. 42 Being Smart #3: “ToErr is Human”
- 43. 43 External Memory Knowledge Data LongTerm Memory Knowledge Data Inference DECISION PATIENT Perception Attention Working Memory CLINICIAN Elson, Faughnan & Connelly (1997) Clinical Decision Making
- 44. 44 Example of “Alerts& Reminders” Reducing Errors through “Alerts & Reminders”
- 45. 45 Documented Values ofHealth IT • Guideline adherence • Better documentation • Practitioner decision making or process of care • Medication safety • Patient surveillance & monitoring • Patient education/reminder
- 46. 46 Being Smart #4: LinkIT Values to Quality (Including Safety)
- 47.
- 48. 48 Hospital Information System(HIS) Computerized Physician Order Entry (CPOE) Electronic Health Records (EHRs) Picture Archiving and Communication System (PACS) Various Forms of Health IT
- 49. 49 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
- 50. 50 Health IT forMedication Safety Ordering Transcription Dispensing Administration CPOE Automatic Medication Dispensing Electronic Medication Administration Records (e-MAR) Barcoded Medication Administration Barcoded Medication Dispensing
- 51. 51 Hospital A HospitalB Clinic C Government Lab Patient at Home Health Information Exchange
- 52.
- 53. 53WHO & ITU AchievingHealth Information Exchange (HIE)
- 54. 54 The Road toDigitizing Healthcare What is a “Smart Hospital”? Toward a “Smart” Hospital Outline
- 55. 55 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/
- 56. 56Image Source: socialmediab2b.com AnotherSmart Machine: IBM’s Watson
- 57. 57Image Source: englishmoviez.com Riseof the Machines?
- 58. 58 Clinical Decision SupportSystems • 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
- 59. 59 Being Smart #5: Don’tReplace Human Users. Use ICT to Help Them Perform Smarter & Better.
- 60. 60 Some Risks ofClinical Decision Support Systems • Alert Fatigue Unintended Consequences of Health IT
- 61.
- 62. 62 Being Smart #6: HealthIT Also Have Risks & Unintended Consequences
- 63. 63 Balanced Focus ofInformatics Technology ProcessPeople
- 64. 64 Being Smart #7: BalanceYour Focus (People, Process, Technology)
- 65. 65The sailboat imagesource: Uwe Kils via http://en.wikipedia.org/wiki/Sailing The destination The boat The 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
- 66. 66 Being Smart #8: KnowYour Context & Align IT with that Context
- 67. 67 รพ.มหาวิทยาลัย 900 เตียง Visionเป็นโรงพยาบาลชั้นนาของ ภูมิภาคเอเชียที่มีความเป็นเลิศใน ด้านบริการ การศึกษา และวิจัย รพ.เอกชน 200 เตียง Vision เป็นโรงพยาบาล High Tech High Touch ชั้นนาของประเทศ Vision, Mission & IT Strategies
- 68. 68 Carr (2004) Carr(2003) IT as “The Sail”
- 69. 69 Strategic Operational ClinicalAdministrative LIS Health Information ExchangeBusiness Intelligence Word Processor Social Media PACS 4Quadrants 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
- 70. 70 Being Smart #9: IdentifyYour Strategic IT Assets
- 71.
- 72. 72 รพ.มหาวิทยาลัย 900 เตียง •บุคลากรมีอายุเฉลี่ย 42 ปี (range 20-65) • แผนก IT มีทั้งบุคลากรใหม่และที่เคย พัฒนาระบบ HIS ตั้งแต่แรกเริ่ม • แพทย์มีความเป็นตัวของตัวเองสูง, มักทางานเอกชนด้วย, มี turn-over rate สูง • พยาบาลและวิชาชีพอื่นมักมองว่า แพทย์คืออภิสิทธิ์ชน และมีเรื่อง ถกเถียงกันบ่อยๆ รพ.เอกชน 200 เตียง • บุคลากรมีอายุเฉลี่ย 32 ปี (range 20-57) • แผนก IT เข้มแข็ง • แพทย์ไม่ค่อยมี interaction กับ บุคลากรอื่น, รายได้เป็นแรงดึงดูดหลัก • ผู้บริหารได้รับการยอมรับจากบุคลากร ทุกวิชาชีพว่ามีวิสัยทัศน์และ บริหารงานได้ดี “The Sailors”
- 73. 73Ash et al.(2003) The “Special People”
- 74. 74Ash 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”
- 75. 75Ash 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”
- 76. 76Ash 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”
- 77. 77 Being Smart #10: ManageYour “Special People” Well
- 78. 78 A True Storyof Failure to Involve Users in Hospital IT Implementation
- 79. 79 Being Smart #11: InvolveUsers Early & Intensively in Your Process
- 80. 80 Image source: JeremyKemp via http://en.wikipedia.org/wiki/Hype_cycle http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp Gartner Hype Cycle
- 81. 81 Rogers (2003) Rogers’ Diffusionof Innovations: Adoption Curve
- 82. 82 • Communications ofproject 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
- 83. 83 Being Smart #12: WorkSmartly with Smart People
- 84. 84 To become asmart hospital, you must • Know what is “smart” all about • Know how to use smart machines together with smart people • Manage both of them smartly Summary
- 85. 85 2546 แพทยศาสตรบัณฑิต 2554 Ph.D.(Health Informatics), Univ. of Minnesota ผู้ช่วยคณบดีฝ่ายนโยบายและสารสนเทศ อาจารย์ ภาควิชาเวชศาสตร์ชุมชน คณะแพทยศาสตร์โรงพยาบาลรามาธิบดี มหาวิทยาลัยมหิดล ความสนใจ: Health IT for Quality of Care, IT Management, Security & Privacy nawanan.the@mahidol.ac.th SlideShare.net/Nawanan Q&A