title: Bayes' theorem and the physical examination: probability assessment and diagnostic decision making.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: Section of General Internal Medicine, Veterans Affairs Pittsburgh Healthcare System, Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15240-1001, USA. herrles@pitt.edu
authors: Scott R
authors: SR
authors: Herrle
authors: Eugene C
authors: EC
authors: Corbett
authors: Mark J
authors: MJ
authors: Fagan
authors: Charity G
authors: CG
authors: Moore
authors: D Michael
authors: DM
authors: Elnicki
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D003430:Cross-Sectional Studies; D003657:Decision Making; D003937:Diagnosis, Differential; D003955:Diagnostic Tests, Routine / Q000592:standards / Q000639:trends; D005260:Female; D006801:Humans; D007396:Internship and Residency / Q000706:statistics & numerical data*; D008297:Male; D008505:Medical Staff, Hospital / Q000706:statistics & numerical data*; D008875:Middle Aged; D010808:Physical Examination / Q000592:standards* / Q000639:trends; D010865:Pilot Projects; D011336:Probability; D013337:Students, Medical / Q000706:statistics & numerical data*; D014481:United States; D055815:Young Adult