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Overview of Hospital Information Systems
Nawanan Theera-Ampornpunt, M.D., Ph.D.Department of Community Medicine
Faculty of Medicine Ramathibodi HospitalMarch 3, 2014
SlideShare.net/Nawanan
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A Bit About Myself...
2003 M.D. (First-Class Honors) (Ramathibodi)2009 M.S. in Health Informatics (U of MN)2011 Ph.D. in Health Informatics (U of MN)2012 Certified HL7 CDA Specialist
• Deputy Executive Director for Informatics (CIO/CMIO) Chakri Naruebodindra Medical Institute
• Lecturer, Department of Community MedicineFaculty of Medicine Ramathibodi HospitalMahidol University
[email protected]://groups.google.com/group/ThaiHealthIT
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Outline
• Healthcare & Information• Why We Need ICT in Healthcare• Health IT• Hospital Information Systems• Health Information Exchange• Q&A
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Let’s start withsomething simple...
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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)
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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.
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Information is Everywhere in Healthcare
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
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“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
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Why We Need ICT in Healthcare?
#1: Because information is everywhere in healthcare
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(IOM, 2001)(IOM, 2000) (IOM, 2011)
Landmark IOM Reports
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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 errorsHealth IT Workforce Curriculum Version 3.0/Spring 2012 Introduction to Healthcare and Public Health in the US: Regulating Healthcare - Lecture d
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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
13Image 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
14Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University
To Err is Human 2: Memory
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To Err is Human 3: Cognition
• Cognitive Errors - Example: Decoy Pricing
The Economist Purchase Options
• Economist.com subscription $59• Print subscription $125• Print & web subscription $125
Ariely (2008)
16084
The Economist Purchase Options
• Economist.com subscription $59• Print & web subscription $125
6832
# of People
# of People
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Cognitive Biases in Healthcare
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”
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Cognitive Biases in Healthcare
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.
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Cognitive Biases in Healthcare
Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med. 2003 Aug;78(8):775-80.
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• Medication Errors
– Drug Allergies
– Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors
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Why We Need ICT in Healthcare?
#2: Because healthcare is error-prone and technology
can help
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Why We Need ICT in Healthcare?
#3: Because access to high-quality patient
information improves care
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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
Health IT
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HealthInformationTechnology
Goal
Value-Add
Tools
Health IT: What’s in a Word?
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• Patient’s Health• Population’s Health• Organization’s Health
(Quality, Reputation & Finance)
“Health” in “Health IT”
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Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic Health
Records (EHRs)
Picture Archiving and Communication System
(PACS)
Various Forms of Health IT
Screenshot Images from Faculty of Medicine Ramathibodi Hospital, Mahidol University
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mHealth
Biosurveillance
Telemedicine & Telehealth
Images from Apple Inc., Geekzone.co.nz, Google, HealthVault.com and American Telecare, Inc.
Personal Health Records (PHRs) and Patient Portals
Still Many Other Forms of Health IT
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• Guideline adherence• Better documentation• Practitioner decision making or
process of care• Medication safety• Patient surveillance & monitoring• Patient education/reminder
Values of Health IT
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• 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
Enterprise-wide Hospital IT
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• 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
Departmental IT in Hospitals
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The Challenge - Knowing What It Means
Electronic Medical Records (EMRs)
Computer-Based Patient Records
(CPRs)
Electronic Patient Records (EPRs)
Electronic Health Records (EHRs)
Personal Health Records (PHRs)
Hospital Information System
(HIS)
Clinical Information System (CIS)
EHRs & HIS
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Computerized Provider Order Entry (CPOE)
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Values
• No handwriting!!!• Structured data entry: Completeness, clarity,
fewer mistakes (?)• No transcription errors!• Streamlines workflow, increases efficiency
Computerized Provider Order Entry (CPOE)
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Ordering Transcription Dispensing Administration
CPOEAutomatic Medication Dispensing
Electronic Medication
Administration Records (e-MAR)
BarcodedMedication
Administration
BarcodedMedication Dispensing
Stages of Medication Process
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• 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, treatment options(Shortliffe, 1976)
Clinical Decision Support Systems (CDS)
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– Alerts & reminders• Based on specified logical conditions• Examples:
– Drug-allergy checks– Drug-drug interaction checks– Reminders for preventive services– Clinical practice guideline integration
Clinical Decision Support Systems (CDS)
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Example of “Reminders”
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• 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)
More CDS Examples
38Image Source: https://webcis.nyp.org/webcisdocs/what-are-infobuttons.html
Infobuttons
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• Pre-defined documents– Order sets, personalized “favorites”– Templates for clinical notes– Checklists– Forms
• Can be either computer-based or paper-based
Other CDS Examples
40Image Source: http://www.hospitalmedicine.org/ResourceRoomRedesign/CSSSIS/html/06Reliable/SSI/Order.cfm
Order Sets
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• Simple UI designed to help clinical decision making– Abnormal lab highlights– Graphs/visualizations for lab results– Filters & sorting functions
Other CDS Examples
42Image Source: http://geekdoctor.blogspot.com/2008/04/designing-ideal-electronic-health.html
Abnormal Lab Highlights
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
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Abnormal lab highlights
Clinical Decision Making
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
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Clinical Decision Making
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIANDrug-Allergy
Checks
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
Drug-Drug Interaction
Checks
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
Clinical Practice Guideline
Reminders
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
Clinical Decision Making
Diagnostic/Treatment Expert Systems
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• 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
Proper Roles of CDS
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Some risks• Alert fatigue
Unintended Consequences of Health IT
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Workarounds
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Hospital A Hospital B
Clinic C
Government
Lab Patient at Home
Health Information Exchange (HIE)
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Outline
Healthcare & InformationWhy We Need ICT in HealthcareHealth ITHospital Information SystemsHealth Information Exchange• Q&A
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Patients Are Counting on Us...
Image Source: http://www.flickr.com/photos/childrensalliance/3191862260/
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More Resources
• American Medical Informatics Association (AMIA)www.amia.org
• International Medical Informatics Association (IMIA)www.imia.org
• Thai Medical Informatics Association (TMI)www.tmi.or.th
• Asia eHealth Information Network (AeHIN)www.aehin.org
• ThaiHealthIT Google Groups Mailing Listhttp://groups.google.com/group/ThaiHealthIT
• Thai Health Informatics Academy
