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Overview of Hospital Information Systems Overview of Hospital Information Systems PHARMACY INFORMATICS EDUCATIONAL SERIES โครงการอบรมการพัฒนาและจัดการระบบขอมูลเภสัชกรรมในโรงพยาบาล : การเตรียมขอมูลยาเพื่อการเบิกจาย วันที่ 18 มิถุนายน 2557 คณะเภสัชศาสตร จุฬาลงกรณมหาวิทยาลัย บุญชัย กิจสนาโยธิน M.D., Ph.D.(Health Informatics) นวนรรน ธีระอัมพรพันธุ M.D., Ph.D.(Health Informatics) Outline • Healthcare & Information • Why We Need ICT in Healthcare • Health IT • Hospital Information Systems • Health Information Exchange • Q&A 2 What Clinicians Want? 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) 3 High Quality Care • 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. 4 Information is Everywhere in Healthcare Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8. 5 Why We Need ICT in Healthcare? #1: Because information is everywhere in healthcare 6 Landmark IOM Reports (IOM, 2000) (IOM, 2001) (IOM, 2003) (IOM, 2011) 7 Patient Safety • 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 Health IT Workforce Curriculum Version 3.0/Spring 2012 Introduction to Healthcare and Public Health in the US: Regulating Healthcare - Lecture d 8 IOM Reports Summary • 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 9 To Err is Human 1: Attention 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 10 To Err is Human 2: Memory Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University 11 To Err is Human 3: Cognition • 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 Ariely (2008) • Print & web subscription $125 32 12 Cognitive Biases in Healthcare “Everyone makes mistakes. But our reliance on cognitive processes prone to bias makes treatment errors more likely than we think” Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ. 2005 Apr 2;330(7494):781-3. 13 Common Errors • Medication Errors – Drug Allergies – Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines 14 Why We Need ICT in Healthcare? #2: Because healthcare is error-prone and technology can help 15 Why We Need ICT in Healthcare? #3: Because access to high-quality patient information improves care 16 Health IT 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: Boonchai Kijsanayotin 17 Health IT: What’s in a Word? Health Goal Information Value-Add Technology Tools 18 “Health” in “Health IT” • Patient’s Health • Population’s Health • Organization’s Health (Quality, Reputation & Finance) 19 Various Forms of Health IT Hospital Information System (HIS) Computerized Provider Order Entry (CPOE) Electronic Health Records Picture Archiving and (EHRs) Communication System (PACS) Screenshot Images from Faculty of Medicine Ramathibodi Hospital, Mahidol University 20 Still Many Other Forms of Health IT Biosurveillance mHealth Personal Health Records Telemedicine & (PHRs) and Patient Portals Telehealth Images from Apple Inc., Geekzone.co.nz, Google, HealthVault.com and American Telecare, Inc. 21 Values of Health IT • Guideline adherence • Better documentation • Practitioner decision making or process of care • Medication safety • Patient surveillance & monitoring • Patient education/reminder 22 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 (CDS) • Picture Archiving and Communication System (PACS) • Nursing applications • Enterprise Resource Planning (ERP) - Finance, Materials Management, Human Resources 23 Departmental IT in Hospitals • 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 system 24 HIS - EHR – EMR – PHR relationship Hospital Information EHR Systems EMR PHR EHR= Electronic Health Record EMR= Electronic Medical Record PHR= Personal Health Record Computerized Provider Order Entry (CPOE) 26 Computerized Provider Order Entry (CPOE) Values • No handwriting!!! • Structured data entry: Completeness, clarity, fewer mistakes (?) • No transcription errors! • Streamlines workflow, increases efficiency 27 Stages of Medication Process Ordering Transcription Dispensing Administration Automatic Electronic CPOE Medication Medication Dispensing Administration Records (e-MAR) Barcoded Medication Barcoded Dispensing Medication Administration 28 Clinical Decision Support Systems (CDS) • 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 (Shortliffe, 1976) diagnoses, treatment options 29 Clinical Decision Support Systems (CDS) – Alerts & reminders • Based on specified logical conditions • Examples: – Drug-allergy checks – Drug-drug interaction checks – Reminders for preventive services – Clinical practice guideline integration 30 Example of “Reminders” 31 More CDS Examples • Reference information or evidence- based knowledge sources – Drug reference databases – Textbooks & journals – Online literature (e.g. PubMed) – Tools that help users easily access references (e.g. Infobuttons) 32 Infobuttons Image Source: https://webcis.nyp.org/webcisdocs/what-are-infobuttons.html 33 Other CDS Examples • Pre-defined documents – Order sets, personalized “favorites” – Templates for clinical notes – Checklists – Forms • Can be either computer-based or paper-based 34 Order Sets Image Source: http://www.hospitalmedicine.org/ResourceRoomRedesign/CSSSIS/html/06Reliable/SSI/Order.cfm 35 Other CDS Examples • Simple UI designed to help clinical decision making – Abnormal lab highlights – Graphs/visualizations for lab results – Filters & sorting functions 36 Abnormal Lab Highlights Image Source: http://geekdoctor.blogspot.com/2008/04/designing-ideal-electronic-health.html 37 Clinical Decision Making PATIENT Perception CLINICIAN Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION Elson, Faughnan & Connelly (1997) 38 Clinical Decision Making PATIENT Perception CLINICIAN Abnormal lab Attention highlights Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION 39 Clinical Decision Making PATIENT Perception CLINICIAN Drug-Allergy Attention Checks Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION 40 Clinical Decision Making PATIENT Perception Drug-Drug CLINICIAN Interaction Attention Checks Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION Elson, Faughnan & Connelly (1997) 41 Clinical Decision Making PATIENT Perception Clinical Practice CLINICIAN Guideline Reminders Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference DECISION Elson, Faughnan & Connelly (1997) 42 Clinical Decision Making PATIENT Perception CLINICIAN Attention Long Term Memory External Memory Working Memory Knowledge Data Knowledge Data Inference Diagnostic/Treatment Expert Systems DECISION Elson, Faughnan & Connelly (1997) 43 Proper Roles of CDS • CDSS as a replacement or supplement of clinicians? – The demise of the “Greek Oracle” model (Miller & Masarie, 1990) The “Greek Oracle” Model Wrong Assumption The “Fundamental Theorem” Model Correct Assumption Friedman (2009) 44 Unintended Consequences of Health IT Some risks • Alert fatigue 45 Workarounds 46 สถานการณ HIS/EHR 2553-54 (N=902) (นพ.นวนรรน ธีระอัมพรพันธุ 2554) Product/Vendor Frequency (%) HOSxP 449 (50.17%) Self-developed or outsourced 142 (15.87%) Hospital OS 64 (7.15%) SSB 32 (3.58%) Mit-Net 22 (2.46%) MRecord 21 (2.35%) H.I.M. Professional 20 (2.23%) MedTrak/TrakCare 19 (2.12%) HoMC 18 (2.01%) No hospital information system used 14 (1.56%) Health Information Exchange (HIE) Government Hospital A Hospital B Clinic C Lab Patient at Home 48 Outline Healthcare & Information Why We Need ICT in Healthcare Health IT Hospital Information Systems Health Information Exchange • Q&A 49 .
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