Exploring the boundaries of plausibility: empirical study of a key problem in the design of computer-based clinical simulations.

Abstract

All clinical simulation designers face the problem of identifying the plausible diagnostic and management options to include in their simulation models. This study explores the number of plausible diagnoses that exist for a given case, and how many subjects must work up a case before all plausible diagnoses are identified. Data derive from 144 residents and faculty physicians from 3 medical centers, each of whom worked 9 diagnostically challenging cases selected from a set of 36. Each subject generated up to 6 diagnostic hypotheses for each case, and each hypothesis was rated for plausibility by a clinician panel. Of the 2091 diagnoses generated, 399 (19.1%), an average of 11 per case, were considered plausible by study criteria. The distribution of plausibility ratings was found to be statistically case dependent. Averaged across cases, the final plausible diagnosis was generated by the 28th clinician (sd = 8) who worked the case. The results illustrate the richness and diversity of human cognition and the challenges these pose for creation of realistic simulations in biomedical domains.