Date and Time
August 6, 2003
1:30 PM - 3:00 PM

Availability
Open to the public
No RSVP required

Speaker
Albert Chan - Fellow at Stanford Medical Informatics and UCSF Family and Community Medicine

The overall aim of implementing decision support is to improve patient outcomes. Evaluation of a DSS on patient outcomes involves a continuum of measures. At the top level, the most stringent and ultimately most important test of a DSS would be its impact on patient outcomes- that is morbidity and mortality. However, decision support is one small factor among many in determining overall patient morbidity and mortality; it would be quite difficult to measure with accuracy the effect of a DSS on such distant outcomes. Clinician feedback about the DSS can provide some insight into the utility of the DSS. Intermediate outcome measures, such as the impact of the DSS on blood pressure control, are more proximate measures of efficacy. Finally, evaluation of provider adherence to a particular recommendation made by the DSS is the most direct indicator of the ability of a DSS to affect clinical decision-making. This seminar will cover several approaches of analysis used in the evaluation of ATHENA DSS (Assessment and Treatment of Hypertension: Evidence-Based Automation Decision Support System), a system that delivers guideline-based, patient-specific treatment recommendations, using a system built with EON technology for guideline-based decision support.