David Topps (University of Calgary)

Synopsis

Using data derived from health service databases to provide physicians with informed selfassessment, the DISECKT program provides personalized virtual patients that encourage reflection and evaluate changes in case management thinking.

Background

The Alberta Physician Learning Program (PLP) aims to enhance physician performance through selfassessment, informed by health services data. But data alone will not promote reflection. This project aims to provide context and comparative peer data, allowing physicians to explore their decision making through a series of data-based virtual patients.

Approach

Based on established quality improvement principles, the project leads physicians through a PDSAlike cycle of reflection and provides them with Personally Linked Analyses of Networked Educational Sources (PLANES) – a template-driven plan based on data derived from multiple services. At the beginning and end of each cycle, participants try a virtual patient scenario, using a modified version of OpenLabyrinth, that is designed to test their judgement, insight and tacit knowledge, in learning designs that are similar in principle to script concordance testing. With simple game scores and feedback mechanisms, the cases provide further links to evidence informed sources. Physicians participate individually or in small groups, the latter facilitated by online collaboration tools. The open design of OpenLabyrinth allows the integration of their PLANES data into the cases, increasing impact by improved personal relevance.

Progress

Challenges so far have included the difficulties of meaningful data aggregation from multiple sources; exploring new approaches to data mining EMR data; and the redesign of OpenLabyrinth to accommodate new data sources. A variety of statistical approaches are being explored to analyse concordance with experts’ navigation of the virtual patient narrative pathways.

Funding Sources

Alberta Physician Learning Program.

Declaration

None.