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Overview of Hospital Information Systems
บุญชัย กิจสนาโยธิน M.D., Ph.D.(Health Informatics)
นวนรรน ธีระอัมพรพันธุ M.D., Ph.D.(Health Informatics)
PHARMACY INFORMATICS EDUCATIONAL SERIES
โครงการอบรมการพัฒนาและจัดการระบบขอมูลเภสัชกรรมในโรงพยาบาล
: การเตรียมขอมูลยาเพ่ือการเบิกจาย
วันที่ 18 มิถุนายน 2557
คณะเภสัชศาสตร จุฬาลงกรณมหาวิทยาลัย
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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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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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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
(IOM, 2003)
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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 errors Health 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
10 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
11 Image 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)
16 0 84
The Economist Purchase Options • Economist.com subscription $59 • Print & web subscription $125
68 32
# 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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• 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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Health Information Technology
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
Hospital Information Systems EHR
EMR
PHR
HIS - EHR – EMR – PHR relationship
EHR= Electronic Health Record EMR= Electronic Medical Record PHR= Personal Health Record
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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
CPOE Automatic Medication Dispensing
Electronic Medication
Administration Records (e-MAR)
Barcoded Medication
Administration
Barcoded Medication 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
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Image 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
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Image 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
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Image 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
Working Memory
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
Working Memory
CLINICIAN
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Clinical Decision Making
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
Working Memory
CLINICIAN Drug-Allergy
Checks
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External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
Working Memory
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
Working Memory
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
Working Memory
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
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%)
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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 & Information Why We Need ICT in Healthcare Health IT Hospital Information Systems Health Information Exchange • Q&A