title: How well do health professionals interpret diagnostic information? A systematic review.
abstract: OBJECTIVE
  To evaluate whether clinicians differ in how they evaluate and interpret diagnostic test information.
  
  
  METHODS
  Systematic review.
  
  
  METHODS
  MEDLINE, EMBASE and PsycINFO from inception to September 2013; bibliographies of retrieved studies, experts and citation search of key included studies.
  
  
  METHODS
  Primary studies that provided information on the accuracy of any diagnostic test (eg, sensitivity, specificity, likelihood ratios) to health professionals and that reported outcomes relating to their understanding of information on or implications of test accuracy.
  
  
  RESULTS
  We included 24 studies. 6 assessed ability to define accuracy metrics: health professionals were less likely to identify the correct definition of likelihood ratios than of sensitivity and specificity. -25 studies assessed Bayesian reasoning. Most assessed the influence of a positive test result on the probability of disease: they generally found health professionals' estimation of post-test probability to be poor, with a tendency to overestimation. 3 studies found that approaches based on likelihood ratios resulted in more accurate estimates of post-test probability than approaches based on estimates of sensitivity and specificity alone, while 3 found less accurate estimates. 5 studies found that presenting natural frequencies rather than probabilities improved post-test probability estimation and speed of calculations.
  
  
  CONCLUSIONS
  Commonly used measures of test accuracy are poorly understood by health professionals. Reporting test accuracy using natural frequencies and visual aids may facilitate improved understanding and better estimation of the post-test probability of disease.
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK The National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care West at University Hospitals Bristol NHS Foundation Trust.
authors.forename: Penny F
authors.initials: PF
authors.lastname: Whiting
authors.affiliation: Unit of Public Health, Epidemiology and Biostatistics, School of Health and Population Sciences, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham, UK.
authors.forename: Clare
authors.initials: C
authors.lastname: Davenport
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Catherine
authors.initials: C
authors.lastname: Jameson
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Margaret
authors.initials: M
authors.lastname: Burke
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Jonathan A C
authors.initials: JA
authors.lastname: Sterne
authors.affiliation: Peninsula Technology Assessment Group, Peninsula College of Medicine & Dentistry, Exeter, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Hyde
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Yoav
authors.initials: Y
authors.lastname: Ben-Shlomo
mesh_terms: D001499:Bayes Theorem; D002983:Clinical Competence; D003627:Data Interpretation, Statistical; D019937:Diagnostic Techniques and Procedures / Q000706:statistics & numerical data*; D006282:Health Personnel; D006801:Humans; D016013:Likelihood Functions; D012680:Sensitivity and Specificity
keywords: EPIDEMIOLOGY; MEDICAL EDUCATION & TRAINING; STATISTICS & RESEARCH METHODS