ถอดบทเรียนการพัฒนาระบบเทคโนโลยีสารส...
Health IT Beyond Hospitals (Septemb...
A presentation in March 2012 presented at the Ramathibodi Hospital Administration School, Faculty of Medicine Ramathibodi Hospital, Mahidol University in Bangkok, Thailand. Presentation partly in English and partly in Thai.
, Test Team at Central and North West London NHS Foundation Trust
at Central and North West London NHS Foundation Trust
Ton Sarakul
at Mc Cormick Hospital
IT in HospitalsNawanan Theera‐Ampornpunt, MD, PhD Mar 14, 2012 Ramathibodi Hospital Administration School SlideShare.net/Nawanan 2.
A Few Words About Me... 2003 M.D. (1st-Class Honors) Ramathibodi 2009 M.S. (Health Informatics) University of Minnesota 2011 Ph.D. (Health Informatics) University of Minnesota Currently • Medical Systems Analyst, Health Informatics Division, Ramathibodi Contacts ranta@mahidol.ac.th SlideShare.net/Nawanan www.tc.umn.edu/~theer002 groups.google.com/group/ThaiHealthIT2 3.
Outline Healthcare & Health IT Health IT Applications in Hospitals Health Informatics As A Field  IT Management3 4.
Health care & Health IT4 5.
Manufacturing5 Image Source: Guardian.co.uk 6.
Banking6 Image Source: Cablephet.com 7.
Health care7 ER ‐ Image Source: nj.com 8.
Why Health care Isn’t Like Any Others?  Life‐or‐Death  Many & varied stakeholders  Strong professional values  Evolving standards of care  Fragmented, poorly‐coordinated systems  Large, ever‐growing & changing body of knowledge  High volume, low resources, little time8 9.
Why Health care Isn’t Like Any Others?  Large variations & contextual dependence Input Process Output Patient Decision‐ Biological Presentation Making Responses9 10.
But...Are We That Different? Banking Input Process Output Transfer Location A Location B Value‐Add ‐ Security ‐ Convenience ‐ Customer Service10 11.
But...Are We That Different? Manufacturing Input Process Output Raw Assembling Finished Materials Goods Value‐Add ‐ Innovation ‐ Design ‐ QC11 12.
But...Are We That Different? Health care Input Process Output Sick Patient Patient Care Well Patient Value‐Add ‐ Technology & medications ‐ Clinical knowledge & skills ‐ Quality of care; process improvement ‐ Information12 13.
Information is Everywhere in Health Care13 14.
Various Forms of Health IT Hospital Information System (HIS) Computerized Provider Order Entry (CPOE) Electronic Health Records Picture Archiving and (EHRs) Communication System (PACS)14 15.
Still Many Other Forms of Health IT Health Information Exchange (HIE) m‐Health Biosurveillance Personal Health Records (PHRs) Telemedicine & Information Retrieval Telehealth15 Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, Inc. 16.
Why Adopting Health IT? “To Go paperless” “To Computerize” “To Get a HIS” “Digital Hospital” “To Have EMRs” “To Modernize” “To Share data”16 17.
Some Quotes  “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)17 18.
Health IT: What’s In A Word? Health Goal Information Value‐Add Technology Tools18 19.
Dimensions of Quality Healthcare Safety Timeliness Effectiveness Efficiency Equity Patient‐centeredness19 (IOM, 2001) 20.
Value of Health IT Guideline adherence  Better documentation  Practitioner decision making or process of care  Medication safety  Patient surveillance & monitoring  Patient education/reminder20 21.
Fundamental Theorem of Informatics21 (Friedman, 2009) (Friedman, 2009) 22.
Is There A Role for Health IT?22 (IOM, 2000) 23.
Landmark IOM Reports (IOM, 2000) (IOM, 2001)23 24.
Landmark IOM Reports: Summary  Humans are not perfect and are bound to make errors  Highlight problems in the U.S. health care system that systematically contributes to medical errors and poor quality  Recommends reform that would change how health care works and how technology innovations can help improve quality/safety24 25.
Why We Need Health IT  Health care is very complex (and inefficient)  Health care is information‐rich  Quality of care depends on timely availability & quality of information  Clinical knowledge body is too large  Short time during a visit  Practice guidelines are put “on‐the‐shelf”  “To err is human”25 26.
To Err Is Human  Perception errors26 Image Source: interaction‐dynamics.com 27.
To Err Is Human  Lack of Attention Image Source: aafp.org27 28.
To Err Is Human  Cognitive Errors - Example: Decoy Pricing # of The Economist Purchase Options People • Economist.com subscription $59 16 • Print subscription $125 0 • Print & web subscription $125 84 # of The Economist Purchase Options People • Economist.com subscription $59 68 32 Ariely (2008) • Print & web subscription $12528 29.
What If This Happens in Healthcare? It already happens.... (Mamede et al., 2010; Croskerry, 2003; Klein, 2005) What if health IT can help?29 30.
Adoption of Health IT: Assumptions Adoption Use Outcomes30 31.
U.S.’s Efforts on Health IT Adoption ? “...We will make wider use of electronic records and other health information technology, to help control costs and reduce dangerous medical errors.” President George W. Bush Sixth State of the Union Address, January 31, 200631 Source: Wikisource.org Image Source: Wikipedia.org 32.
Public Policy in Informatics: A US’s Case 1991: IOM’s CPR Report published 1996: HIPAA enacted 2000‐2001: IOM’s To Err Is Human & Crossing the Quality Chasm published 2004: George W. Bush’s Executive Order establishing ONCHIT (ONC) 2009‐2010: ARRA/HITECH Act & “Meaningful use” regulations32 33.
U.S. Adoption of Health IT Ambulatory (Hsiao et al, 2009) Hospitals (Jha et al, 2010) Basic EHRs w/ notes 9.2% Comprehensive EHRs 2.7% CPOE for medications 34% • U.S. lags behind other Western countries (Schoen et al, 2006;Jha et al, 2008) • Money and misalignment of benefits is the biggest reason33 34.
We Need “Change” “...we need to upgrade our medical records by switching from a paper to an electronic system of record keeping...” President Barack Obama June 15, 200934 35.
The Birth of “Meaningful Use” “...Our recovery plan will invest in electronic health records and new technology that will reduce errors, bring down costs, ensure privacy, and save lives.” President Barack Obama Address to Joint Session of Congress February 24, 200935 Source: WhiteHouse.gov 36.
American Recovery & Reinvestment Act  Contains HITECH Act (Health Information Technology for Economic and Clinical Health Act)  ~ 20 billion dollars for Health IT investments  Incentives & penalties for providers36 37.
U.S. National Leadership David Brailer, MD, PhD National Coordinator for Health Information Technology (2004 - 2007) Robert Kolodner, MD National Coordinator for Health Information Technology (2006 - 2009) David Blumenthal, MD, MPP National Coordinator for Health Information Technology (2009 - 2011) Farzad Mostashari, MD, ScM National Coordinator for Health Information Technology (2011 - Present)37 38.
What is in the HITECH Act?38 (Blumenthal, 2010) 39.
“Meaningful Use” “Meaningful Use” Pumpkin of a Pumpkin39 Image Source & Idea Courtesy of Pat Wise at HIMSS, Oct. 2009 40.
“Meaningful Use” of Health IT Better Stage 1 Stage 3 Health ‐ Electronic capture of health information ‐ Information sharing Stage 2 Use of ‐ Data reporting EHRs to Use of EHRs improve to improve outcomes processes of care40 (Blumenthal, 2010) 41.
Adoption Studies: Descriptive Aspect 2004 Pongpirul et al. (2004) 2011 Theera‐ Ampornpunt (unpublished)41 42.
Health IT Applications in Hospitals42 43.
Enterprise‐wide Hospital IT  Master Patient Index (MPI)  Admit‐Discharge‐Transfer (ADT)  Electronic Health Records (EHRs)  Computerized Physician Order Entry (CPOE)  Clinical Decision Support Systems (CDSSs)  Picture Archiving and Communication System (PACS)  Nursing applications  Enterprise Resource Planning (ERP)43 44.
Departmental IT  Pharmacy applications  Laboratory Information System (LIS)  Radiology Information System (RIS)  Specialized applications (ER, OR, LR, Anesthesia, Critical Care, Dietary Services, Blood Bank)  Incident management & reporting system44 45.
Hospital Information System Clinical Medical ADT Notes Records Workflow Pharmacy IS Operation Master Patient LIS Theatre Index (MPI) Order CCIS RIS Scheduling Portals Billing PACS45 Modified from Dr. Artit Ungkanont’s slide 46.
HIT Systems (Inpatient) Clinical Decision Support: “Any system designed to improve clinical decision making related to diagnostic or therapeutic processes of care.”46 From Dr. Artit Ungkanont’s slide 47.
EHRs & HIS The Challenge ‐ Knowing What It Means Electronic Health Records (EHRs) Hospital Information System Electronic Medical (HIS) Records (EMRs) Electronic Patient Records (EPRs) Clinical Information System (CIS) Personal Health Computer‐Based Records (PHRs) Patient Records (CPRs)47 48.
EHR Systems Just electronic documentation? History Diag‐ Treat‐ ... & PE nosis ments Or do they have other values?48 49.
Functions that Should Be Part of EHR Systems  Computerized Medication Order Entry  Computerized Laboratory Order Entry  Computerized Laboratory Results  Physician Notes  Patient Demographics  Problem Lists  Medication Lists  Discharge Summaries  Diagnostic Test Results  Radiologic Reports49 (IOM, 2003; Blumenthal et al, 2006) 50.
Computerized Physician Order Entry (CPOE)50 51.
Computerized Physician Order Entry (CPOE) Values No handwriting!!!  Structured data entry: Completeness, clarity, fewer mistakes (?)  No transcription errors!  Entry point for CDSSs  Streamlines workflow, increases efficiency51 52.
Clinical Decision Support Systems (CDSSs)  The real place where most of the values of health IT can be achieved  Expert systems  Based on artificial intelligence, machine learning, rules, or statistics  Examples: differential diagnoses, (Shortliffe, 1976) treatment options52 53.
Clinical Decision Support Systems (CDSSs)  Alerts & reminders  Based on specified logical conditions  Examples:  Drug‐allergy checks  Drug‐drug interaction checks  Drug‐disease checks  Drug‐lab checks  Drug‐formulary checks  Reminders for preventive services or certain actions (e.g. smoking cessation)  Clinical practice guideline integration53 54.
Clinical Decision Support Systems (CDSSs)  Evidence‐based knowledge sources e.g. drug database, literature  Simple UI designed to help clinical decision making  E.g., Abnormal Lab Highlights54 55.
A Basic Architecture of A CDSS User User Interface Inference Engine Knowledge Other Data Base Patient Data • System states • Rules • Epidemiological/ • Statistical data surveillance data • Literature • Etc. • Etc.55 56.
Clinical Decision Support Systems (CDSSs) PATIENT Perception CLINICIAN Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION56 From a teaching slide by Don Connelly, 2006 57.
Clinical Decision Support Systems (CDSSs) PATIENT Perception CLINICIAN Abnormal lab Attention highlights Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION57 58.
Clinical Decision Support Systems (CDSSs) PATIENT Perception CLINICIAN Abnormal lab Attention highlights Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION58 59.
Clinical Decision Support Systems (CDSSs) PATIENT Perception CLINICIAN Drug‐Allergy Attention Checks Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION59 60.
Clinical Decision Support Systems (CDSSs) PATIENT Perception Drug‐Drug CLINICIAN Interaction Attention Checks Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION60 61.
Clinical Decision Support Systems (CDSSs) PATIENT Perception Clinical Practice CLINICIAN Guideline Reminders Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION61 62.
Clinical Decision Support Systems (CDSSs) PATIENT Perception CLINICIAN Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference Diagnostic/Treatment Expert Systems DECISION62 63.
Clinical Decision Support Systems (CDSSs)  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”63 (Friedman, 2009) 64.
Clinical Decision Support Systems (CDSSs) Some risks  Alert fatigue64 65.
Workarounds65 66.
Health IT for Medication Safety Ordering Transcription Dispensing Administration Automatic Electronic CPOE Medication Medication Dispensing Administration Records (e‐MAR) Barcoded Medication Barcoded Dispensing Medication Administration66 67.
Health Information Exchange (HIE) Government Hospital A Hospital B Clinic C Lab Patient at Home67 68.
4 Quadrants of Hospital IT Strategic Business Intelligence HIE PHRs CDSS Social Media CPOE Administrative Clinical VMI EHRs ERP PACS LIS ADT Word Processor MPI Operational68 69.
Health Informatics As A Field69 70.
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)  “[T]he application of the science of information as data plus meaning to problems of biomedical interest” (Bernstam et al, 2010)70 71.
DIKW Pyramid Wisdom Knowledge Information Data71 72.
Task‐Oriented View Collection Processing Utilization Communication/ Storage Dissemination/ Presentation72 73.
M/B/H Informatics As A Field73 (Shortliffe, 2002) 74.
M/B/H Informatics and Other Fields Social Sciences (Psychology, Statistics & Sociology, Research Linguistics, Methods Cognitive & Law & Ethics) Medical Decision Sciences & Science Public Health Engineering Management Library Computer & Biomedical/ Science, Information Health Information Science Informatics Retrieval, KM And More!74 75.
Balanced Focus of Informatics People Techno‐ Process logy75 76.
IT Management76 77.
ความเดิมตอนที่แล้ว... Health IT: ของดี (อาจจะ) มีประโยชน์ (แต่ก็อาจมีโทษ) บริบท (local contexts) มีความสําคัญ  ต้องมีการบริหารจัดการที่เหมาะสม ประเด็นพิจารณา อะไรคือบริบทที่เกี่ยวข้อง? จะจัดการมันอย่างไร?77 78.
Context The current location The tailwind The headwind The past journey The direction The destination The speed The sailor(s) & The sail people on board The boat The sea78 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing 79.
Direction & Destination Visionรพ.มหาวิทยาลัย 900 าเตียง เป็นโรงพยาบาลชั้นนํ ของ Vision รพ.เอกชน 200High ง เป็นโรงพยาบาล เตีย Tech ภูมิภาคเอเชียทีมีความเป็นเลิศใน ่ High Touch ชั้นนําของประเทศ ด้านบริการ การศึกษา และวิจัย79 80.
“The Sail” Carr (2004) Carr (2003)80 81.
4 Quadrants of Hospital IT Strategic Business Intelligence HIE PHRs CDSS Social Media CPOE Administrative Clinical VMI EHRs ERP PACS LIS ADT Word Processor MPI Operational81 82.
IT As A Strategic Advantage Sustainable Yes competitive advantage Yes Inimitable ? Yes Rare ? No Preemptive Yes Non-Substitutable? No advantage Competitive Valuable ? parity No Competitive No necessity Competitive Resources/ Disadvantage capabilities82 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management 83.
“The Sail” Vision เป็นโรงพยาบาลชั้นนําของ Vision เป็นโรงพยาบาล High Tech ภูมิภาคเอเชียทีมยาลัย 900 ศใน ง รพ.มหาวิท่ ีความเป็นเลิ เตีย Highรพ.เอกชน นําของประเทศ Touch ชั้น 200 เตียง ด้านบริการ การศึกษา และวิจัย Current IT Environment Current IT Environment  มี MPI, ADT, EHRs, CPOE แต่ยังมี  เป็น รพ.แรกๆ ที่มี HIS ซึ่งพัฒนาเอง และ CDSS จํากัด ต่อยอดจาก MPI, ADT ไปสู่ CPOE (แต่  ยังไม่มี Customer Relationship Management ยังขาด advanced CDSS) ระบบ HIS (CRM) เข้ากับ workflow ของ รพ. เป็นอย่างดี  ยังไม่มี Personal Health Records (PHRs)  ปัจจุบัน ระบบ HIS ยังใช้เทคโนโลยี เดียวกับช่วงที่พฒนาใหม่ๆ (20 ปีก่อน) ั เป็นหลัก มีการนําเทคโนโลยีใหม่ๆ มาใช้ อย่างช้าๆ83 84.
IT As A Strategic Advantage Sustainable Yes competitive advantage Yes Inimitable ? Yes Rare ? No Preemptive Yes Non-Substitutable? No advantage Competitive Valuable ? parity No Competitive No necessity Competitive Resources/ Disadvantage capabilities84 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management 85.
“The Sailors” People Techno‐ Process logy85 86.
“The Sailors”  บุคลากรมีอายุเฉลีย 42 ปี ่  บุคลากรมีอายุเฉลีย 32 ปี ่ (range 20-65) ยาลัย 900 เตียง รพ.มหาวิท (range 20-57) 200 เตียง รพ.เอกชน  แผนก IT มีทั้งบุคลากรใหม่และทีเคย ่  แผนก IT เข้มแข็ง พัฒนาระบบ HIS ตั้งแต่แรกเริ่ม  แพทย์ไม่ค่อยมี interaction กับ  แพทย์มีความเป็นตัวของตัวเองสูง, บุคลากรอื่น, รายได้เป็นแรงดึงดูดหลัก มักทํางานเอกชนด้วย, มี turn-over rate สูง  ผู้บริหารได้รับการยอมรับจากบุคลากร  พยาบาลและวิชาชีพอื่นมักมองว่า ทุกวิชาชีพว่ามีวิสัยทัศน์และบริหารงาน แพทย์คืออภิสทธิ์ชน และมีเรื่อง ิ ได้ดี ถกเถียงกันบ่อยๆ86 87.
Context The current location The tailwind The headwind The past journey The direction The destination The speed The sailor(s) & The sail people on board The boat The sea87 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing 88.
“The Boat”  Size  Resources  Structures  Work Processes  Facilities/Geography  Etc.88 89.
“The Sea”  Target customers  Local competitiveness  Relationship of hospital to local players  Inter‐organizational collaboration  IT market environment  National/international trend  Regulations  Standard of care  Etc.89 90.
SWOT Analysis “The Boat” “The Sea” “The Tailwind” Strengths Opportunities “The Tailwind” “The Headwind” Weaknesses Threats “The Headwind”90 91.
IT Outsourcing Decision Tree Keep Internal No Is external delivery No reliable and lower cost? Does service offer Yes OUTSOURCE! competitive advantage? Yes Keep Internal91 From a teaching slide by Nelson F. Granados, 2006 92.
IT Outsourcing Decision Tree: Ramathibodi’s Case External delivery unreliable • Non‐Core HIS External delivery higher cost • ERP maintenance/ongoing customization Keep Internal No Is external delivery No reliable and lower cost? Does service offer Yes OUTSOURCE! competitive advantage? ERP initial implementation, Yes Keep Internal PACS, RIS, Core HIS, CPOE Departmental Strategic advantages systems, • Agility due to local workflow accommodations IT Training • Secondary data utilization (research, QI) • Roadmap to national leader in informatics92 93.
Gartner Hype Cycle Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle93 http://www.gartner.com/technology/research/methodologies/hype‐cycle.jsp 94.
Rogers’ Diffusion of Innovations: Adoption Curve Rogers (2003)94 95.
Hospital IT Adoption Success Factors  Communications of project plans & progresses  Workflow considerations  Management support of IT projects  Common visions  Shared commitment  Multidisciplinary user involvement  Project management  Training  Innovativeness  Organizational learning95 Theera‐Ampornpunt (2009, 2011) [Unpublished] 96.
Resources on Change Management Lorenzi & Riley (2004) Leviss (Editor) (2010)96 97.
Summary  Healthcare is complex  Health IT can benefit healthcare through  Information delivery  Process improvement  Empowering providers & patients  The world is moving toward health IT  Health informatics is related to & relies on the field of IT, but they are not the same  Management of hospital IT is crucial to success  Know your organization (“context”)  Strategic mindset  Project & change management97 98.
Final Words...  Don’t forget our real aim... Adoption Use Outcomes98 99.
Q & A... Download Slides SlideShare.net/Nawanan Contacts ranta@mahidol.ac.th www.tc.umn.edu/~theer002 groups.google.com/group/ThaiHealthIT99 100.
References  Ariely D. Predictably irrational: the hidden forces that shape our decisions. New York City (NY):HarperCollins; 2008. 304 p.  Bernstam EV, Smith JW, Johnson TR. What is biomedical informatics? J Biomed Inform. 2010 Feb;43(1):104‐10.  Blumenthal D. Launching HITECH. N Engl J Med. 2010 Feb 4;362(5):382‐5.  Blumenthal D, DesRoches C, Donelan K, Ferris T, Jha A, Kaushal R, Rao S, Rosenbaum S. Health information technology in the United States: the information base for progress [Internet]. Princeton (NJ): Robert Wood Johnson Foundation; 2006.  Carr NG. Does IT matter? Information technology and the corrosion of competitive advantage. Boston (MA):Harvard Business Press;2004. 208 p.  Carr NG. IT doesn’t matter. Harvard Bus Rev. 2003 May 1;81(5):41‐9.  Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med. 2003 Aug;78(8):775‐80. 81 p. Available from: http://www.rwjf.org/files/publications/other/EHRReport0609.pdf  Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc. 2009 Apr;16(2):169‐70.  Gladwell M. The Tipping Point: how little things can make a big difference. New York City (NY):Little Brown;2000. 304 p.  Hersh W. A stimulus to define informatics and health information technology. BMC Med Inform Decis Mak. 2009;9:24.  Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov 10:292(18):2273‐4.100 101.
References  Hsiao C, Beatty PC, Hing ES, Woodwell DA. Electronic medical record/electronic health record use by office‐based physicians: United States, 2008 and preliminary 2009 [Internet]. 2009 [cited 2010 Apr 12]; Available from: http://www.cdc.gov/nchs/data/hestat/emr_ehr/ emr_ehr.pdf  Institute of Medicine, Board on Health Care Services, Committee on Data Standards for Patient Safety. Key Capabilities of an electronic health record system: letter report [Internet]. Washington, DC: National Academy of Sciences;2003. 31 p. Available from: http://www.nap.edu/catalog/10781.html  Institute of Medicine, Committee on Quality of Health Care in America. To err is human: building a safer health system. Kohn LT, Corrigan JM, Donaldson MS, editors. Washington, DC: National Academy Press;2000. 287 p.  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.  Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG, Shields A, Rosenbaum S, Blumenthal D. Use of electronic health records in U.S. hospitals. N Engl J Med. 2009;360(16):1628‐38.  Jha AK, Doolan D, Grandt D, Scott T, Bates DW. The use of health information technology in 101 seven nations. Int J Med Inform. 2008;77(12):848‐54. 102.
References  Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ. 2005 Apr 2;330(7494):781‐3.  Leviss J (editor). H.I.T. or Miss: lessons learned from health information technology implementations. Chicago (IL):AHIMA Press;2010.  Lorenzi NM, Riley RT. Managing technological change: organizational aspects of health informatics. New York City (NY): Springer;2004.  Mamede S, van Gog T, van den Berge K, Rikers RM, van Saase JL, van Guldener C, Schmidt HG. Effect of availability bias and reflective reasoning on diagnostic accuracy among internal medicine residents. JAMA. 2010 Sep 15:304(11):1198‐203.  Miller RA, Masarie FE. The demise of the "Greek Oracle" model for medical diagnostic systems. Methods Inf Med. 1990 Jan;29(1):1‐2.  Pongpirul K, Sriratana S. Computerized information system in hospitals in Thailand: a national survey. J Health Sci. 2005 Sep‐Oct;14(5):830‐9. Thai.  Rogers EM. Diffusion of innovations. 5th ed. New York City (NY): Free Press;2003. 551 p.  Schoen C, Osborn R, Huynh PT, Doty M, Puegh J, Zapert K. On the front lines of care: primary care doctors’ office systems, experiences, and views in seven countries. Health Aff (Millwood). 2006;25(6):w555‐71.  Shortliffe EH. JBI status report. Journal of Biomedical Informatics. 2002 Oct;35(5‐6):279‐80.  Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Quart. 2003 Sep;27(3):425‐78.  Background designs are the property of Geetesh Bajaj. Used with permission. © Copyright, Geetesh Bajaj. All Rights Reserved.102 Recommended
ระบบสารสนเทศโรงพยาบาล (สอนนักศึกษาพยาบาล โรงเรียนพยาบาลรามาธิบดี 25 ก.พ. 2557)
Health IT Beyond Hospitals (September 15, 2016)