title: Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial.
abstract: BACKGROUND
  There is little evidence on how best to present diagnostic information to doctors and whether this makes any difference to clinical management. We undertook a randomised controlled trial to see if different data presentations altered clinicians' decision to further investigate or treat a patient with a fictitious disorder ("Green syndrome") and their ability to determine post-test probability.
  
  
  METHODS
  We recruited doctors registered with the United Kingdom's largest online network for medical doctors between 10 July and 6" November 2012. Participants were randomised to one of four arms: (a) text summary of sensitivity and specificity, (b) Fagan's nomogram, (c) probability-modifying plot (PMP), (d) natural frequency tree (NFT). The main outcome measure was the decision whether to treat, not treat or undertake a brain biopsy on the hypothetical patient and the correct post-test probability. Secondary outcome measures included knowledge of diagnostic tests.
  
  
  RESULTS
  917 participants attempted the survey and complete data were available from 874 (95.3%). Doctors randomized to the PMP and NFT arms were more likely to treat the patient than those randomized to the text-only arm. (ORs 1.49, 95% CI 1.02, 2.16) and 1.43, 95% CI 0.98, 2.08 respectively). More patients randomized to the PMP (87/218-39.9%) and NFT (73/207-35.3%) arms than the nomogram (50/194-25.8%) or text only (30/255-11.8%) arms reported the correct post-test probability (p <0.001). Younger age, postgraduate training and higher self-rated confidence all predicted better knowledge performance. Doctors with better knowledge were more likely to view an optional learning tutorial (OR per correct answer 1.18, 95% CI 1.06, 1.31).
  
  
  CONCLUSIONS
  Presenting diagnostic data using a probability-modifying plot or natural frequency tree influences the threshold for treatment and improves interpretation of tests results compared to text summary of sensitivity and specificity or Fagan's nomogram.
authors.affiliation: School of Social & Community Medicine, University of Bristol, Canynge Hall, Bristol, United Kingdom.
authors.forename: Yoav
authors.initials: Y
authors.lastname: Ben-Shlomo
authors.affiliation: School of Social & Community Medicine, University of Bristol, Canynge Hall, Bristol, United Kingdom; Centre for Child & Adolescent Health, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom.
authors.forename: Simon M
authors.initials: SM
authors.lastname: Collin
authors.affiliation: Doctors.net.uk, Milton Park, Abingdon, Oxfordshire, United Kingdom.
authors.forename: James
authors.initials: J
authors.lastname: Quekett
authors.affiliation: School of Social & Community Medicine, University of Bristol, Canynge Hall, Bristol, United Kingdom.
authors.forename: Jonathan A C
authors.initials: JA
authors.lastname: Sterne
authors.affiliation: School of Social & Community Medicine, University of Bristol, Canynge Hall, Bristol, United Kingdom; Kleijnen Systematic Reviews Ltd, York, United Kingdom.
authors.forename: Penny
authors.initials: P
authors.lastname: Whiting
mesh_terms: D019411:Clinical Laboratory Techniques; D006801:Humans; D020407:Internet; D010818:Practice Patterns, Physicians'; D006113:United Kingdom