title: Am I right when I am sure? Data consistency influences the relationship between diagnostic accuracy and certainty.
abstract: OBJECTIVE
  When gauging diagnostic accuracy cognitive biases may lead to inaccurate estimates of certainty, predisposing clinicians to diagnostic errors. This study explored the relationship between diagnostic accuracy and measures of certainty for diagnoses based on consistent or inconsistent information.
  
  
  METHODS
  The authors analyzed three experiments among 180 to 190 postgraduate trainees performing cardiac physical diagnoses using a simulator from 2010 to 2012. Each asked participants to assess diagnostic certainty. One experiment used a seven-point certainty scale and provided only simulated physical findings. Two assessed certainty continuously (probability 1%-100%) and included cases with inconsistent clinical information in addition to simulated physical findings. Relationships between certainty and accuracy were explored through descriptive statistics and nonparametric tests.
  
  
  RESULTS
  Measures of certainty ranged widely (between 2 and 7, and 5%-100%). Relationships between accuracy and certainty varied depending on information consistency. In experiments providing only simulated findings, or consistent clinical data, diagnostic accuracy was associated with higher certainty (median 90% versus 75%, and 5/7 versus 4/7, both P < .001). Studies providing inconsistent data generated similar certainty among participants regardless of accuracy (median 75% versus 75%, P = .36; and 80% versus 85%, P = .60).
  
  
  CONCLUSIONS
  Diagnostic accuracy was moderately associated with higher certainty only when clinical data were consistent. This correlation disappeared when incon sistent data were provided, possi bly reflecting changes in reasoning strategies among diagnostically success ful trainees. The relationship between certainty and diagnostic accuracy is context dependent. Certainty is an unreliable surrogate for diagnostic accuracy.
authors.affiliation: Dr. Cavalcanti is assistant professor, Department of Medicine, Faculty of Medicine, University of Toronto, and director of scholarship, Ho Ping Kong Center for Excellence in Education and Practice, University Health Network, Toronto, Ontario, Canada. Dr. Sibbald is instructor, Department of Medicine, Faculty of Medicine, University of Toronto, and Chang Scholar in Education Research, Ho Ping Kong Center for Excellence in Education and Practice, University Health Network, Toronto, Ontario, Canada.
authors.forename: Rodrigo B
authors.initials: RB
authors.lastname: Cavalcanti
authors.forename: Matthew
authors.initials: M
authors.lastname: Sibbald
mesh_terms: D002983:Clinical Competence; D003937:Diagnosis, Differential; D003951:Diagnostic Errors / Q000517:prevention & control*; D004503:Education, Medical, Graduate; D005260:Female; D006331:Heart Diseases / Q000175:diagnosis*; D006801:Humans; D007388:Internal Medicine / Q000193:education*; D007396:Internship and Residency; D008297:Male