Designing the model patient: Data-driven virtual patients in medical education

Abstract

In this paper we describe ModelPatient, a software application developed to allow health sciences educators to create and deliver educational cases that are based on and simulate real patient behavior. ModelPatient uses data from Electronic Medical Record Systems (EMRS) or from publically available medical data sets in combination with Bayesian network (BN) models to generate virtual patient (VP) cases. Because the underlying models are based on real data, each decision made by a learner affects outcome probabilities. Therefore the behavior of a VP reflects how a real patient with the same medical condition would have reacted to the learners' actions. We believe that data- and model-driven approaches to creating VPs would allow educators to create higher-fidelity teaching cases and offer richer educational experience to learners.