Bayes' theorem and the physical examination: probability assessment and diagnostic decision making

To determine how examination findings influence the probability assessment and diagnostic decision making of third- and fourth-year medical students, internal medicine residents, and academic general internists.

In a 2008 cross-sectional, Web-based survey, participants from three medical schools were asked questions about their training and eight examination scenarios representing four conditions. Participants were given literature-derived preexamination probabilities for each condition and were asked to (1) estimate postexamination probabilities (post-EPs) and (2) select a diagnostic choice (report that condition is present, order more tests, or report that condition is absent). Participants' inverse transformed logit (ITL) mean post-EPs were compared with corresponding literature-derived post-EPs.

Of 906 individuals invited to participate, 684 (75%) submitted a completed survey. In two of four scenarios with positive findings, the participants' ITL mean post-EPs were significantly less than corresponding literature-derived post-EP point estimates (P<.001 for each). In three of four scenarios with negative findings, ITL mean post-EPs were significantly greater than corresponding literature-derived post-EP point estimates (P<.001 for each). In the four scenarios with positive findings, 17% to 38% of participants ordered more diagnostic tests when the literature indicated a >85% probability that the condition was present. In the four scenarios with largely negative findings, 70% to 85% chose to order diagnostic tests to further reduce diagnostic uncertainty.

All three groups tended to similarly underestimate the impact of examination findings on condition probability assessment, especially negative findings, and often ordered more tests when probabilities indicated that additional testing was unnecessary.