Computer-Assisted Decision Making in the Twenty-First Century James J. Cimino, M.D. Departments of Medical Informatics and Medicine Columbia University

Overview Analyzing medical errors Evidence-based practice (EBP) Using computers to support EBP Challenges and impediments to achieving EBP

Analyzing Medical Errors Leape, LL. Error in Medicine. JAMA 1995; 272(23): Errors Slips: errors of action Mistakes: errors of conscious thought Solution: MonitoringSolution: Information

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

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

Application of EBP Etiology Prevention Diagnosis Therapy

Computer Support of EBP EBP and: –access to literature –guidelines –diagnostic aids –order checking Identify: –applications –problems –solutions

Literature Applications –Medline –Textbooks Problems –Search expertise –Time constraints Solutions –Infobuttons –Palm-based access

Guidelines Applications –Computer-based text guidelines Problems –Finding applicable guidelines –Navigation –Applying to specific cases Solutions –Indexing text guidelines –Customizing guidelines –Automating guidelines

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

Order Checking Applications –Drug-interaction programs –Alerting systems Problems –Don’t know whole patient –May be inappropriate Solutions –Integration with clinical record –Open-loop

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”

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

Challenges Identifying context-specific information needs Modeling patients and the care process Integration of systems Terminology translation User education

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