Dissemination of CPRs: focus on Clinical Decision Support Systems (CDSS) Dr Emma Wallace Dissemination of Clinical prediction rules (CPRs) Publicly accessible register of CPRs Clinical decision support systems Overview of presentation • Introduction • Urinary tract infection (UTI) CDSS • Implementation Introduction ‘ Computer systems designed to impact clinician decision making about individual patients at the point in time that these decisions are made’. 1 Key elements; - Integration in electronic patient record - Computerised format - Patient specific information 1. Berner E. S. Clinical Decision Support Systems in Theory and Practice. Birmingham, AL. (2 nd Ed.) 4 Research evidence Clinical decision support systems • Clinician enters clinical data of patient • Matched with system’s knowledge base • Software generates patient specific recommendations • Provides evidence based decision support for the clinician Benefits Prescribing - Improves prescribing practices - Reduces medication errors Preventatative health - Vaccination reminders - Screening Diagnosis- to date more limited role CDSS: Diagnosis • Based on Bayesian reasoning • Pre test probability of disease estimate • Each new piece of clinical information increases or decreases this probability (LRs) • Post test probability Thresholds in diagnosis 100% Test / treatment threshold Probability of disease Test / no treatment threshold 0% CDSS: UTI, Diagnosis CDSS: UTI, Risk stratification CDSS: UTI, Management CDSS: UTI, Prescribing Implementation • Success rates of CDSS increased by; 1. Automatic provision of decision support as part of clinical workflow 2. Provision of decision support at time and location of patient encounter 3. Provision of a recommendation, rather than an assessment Barriers to implementation 1. Poor integration into clinical workflow 2. Low level of uptake by clinicians 3. Cost and time required to develop CDSS 4. GP software companies 5. Inadequate infrastructure (e.g. IT) 6. Competing demands This week in Annals of Internal Medicine... • Computerised handheld CDSS for PE diagnosis • Improved diagnostic decision making • Used Bayesian reasoning • Topical area