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)
• 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 InformationEHR 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