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Computer-Assisted Decision Making in the Twenty-First Century James J. Cimino, M.D. Departments of Medical Informatics and Medicine Columbia University
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Overview Analyzing medical errors Evidence-based practice (EBP) Using computers to support EBP Challenges and impediments to achieving EBP
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Analyzing Medical Errors Leape, LL. Error in Medicine. JAMA 1995; 272(23):1851-7. Errors Slips: errors of action Mistakes: errors of conscious thought Solution: MonitoringSolution: Information
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Analyzing Medical Errors Reduced reliance on memory Increased vigilance Improved information access Error proofing (“forcing functions”) Training emphasis error prevention Patient education Standardization of practice patterns
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Evidence-Based Practice (EBP) Decisions based on clinical evidence Spectrum of evidence quality Skills needed to: –Access literature –Summarize findings –Apply conclusions Sackett DL, et al. Evidence based medicine: what it is and what it isn’t. BMJ 1996; 312(7023):71-2
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Application of EBP Etiology Prevention Diagnosis Therapy
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Computer Support of EBP EBP and: –access to literature –guidelines –diagnostic aids –order checking Identify: –applications –problems –solutions
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Literature Applications –Medline –Textbooks Problems –Search expertise –Time constraints Solutions –Infobuttons –Palm-based access
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Guidelines Applications –Computer-based text guidelines Problems –Finding applicable guidelines –Navigation –Applying to specific cases Solutions –Indexing text guidelines –Customizing guidelines –Automating guidelines
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Diagnostic Decision Support Applications –Interpretation of tests –Expert systems Problems –Need human intervention –Terminology translation Solutions –Identify where aids are needed –Translate data to clinical terms –Automate data transfer
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Order Checking Applications –Drug-interaction programs –Alerting systems Problems –Don’t know whole patient –May be inappropriate Solutions –Integration with clinical record –Open-loop
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Alerts Problems: Terminology One day, an apparent epidemic of positive results… …but lab showed “No Growth to Date” Alert checked Result not equal “No Growth” “No Growth to Date” “No Growth”
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Alert Problems: No Human Review Alert checks for trends in creatinine level MD receives alert for patient’s Creat=1.7 MD calls patient to come to ER Patient risks storm of decade to come to ER Creatinines are 1.1, 1.3, 1.8, 1.6, 1.3, 1.7
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Challenges Identifying context-specific information needs Modeling patients and the care process Integration of systems Terminology translation User education
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Conclusions Potential areas for errors: –Diagnostic testing –Interpretation of results –Therapeutic interventions –Monitoring Computers and EBP can be brought bear: –Literature at the point of care –Facilitating use of guidelines –Expert systems –Alerting –Patient decision support Enhance, not replace, human decision-making
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