Literature DB >> 19131417

The influence of types of decision support on physicians' decision making.

C M Sox1, J N Doctor, T D Koepsell, D A Christakis.   

Abstract

OBJECTIVE: To determine whether physicians' post-test probability estimates are influenced by receiving test characteristics and impact their subsequent clinical decisions.
DESIGN: Questionnaire based randomised controlled trial.
SETTING: Mailed survey with a vignette describing an infant whose pretest likelihood of pertussis was 30% and direct fluorescent-antibody (DFA) test was negative for pertussis.
SUBJECTS: Nationally representative sample of US paediatricians (n = 1502).
INTERVENTIONS: Random receipt of no additional information (controls), the DFA's sensitivity and specificity (TC group) or the test's sensitivity and specificity with their definitions (TCD group). MAIN OUTCOME MEASURES: Estimated post-test probability (PTP) of pertussis, PTP of 0.50, "nearly correct" PTP (+/-5%), intended erythromycin management and intended hospital disposition. ANALYSES: Chi2 and t tests.
RESULTS: Despite the negative DFA result, 67% of the 635 (49.7%) participants who responded estimated a PTP higher than the pretest probability of 30%; the overall mean estimated PTP was 0.41 (SD 0.26) (correct answer: 0.18). The TCD group's mean PTP was significantly higher than controls' mean PTP (0.45 vs 0.38, p<0.001), while the TC and control groups' mean PTP did not differ significantly (0.41 vs 0.38, p = 0.16). With decision support significantly more TC and TCD participants compared to controls estimated the PTP as 0.50 (38% vs 17%, p<0.001; 41% vs 17%, p<0.001, respectively) and also estimated a nearly correct PTP more often (20% vs 13%, p = 0.06; 19% vs 13%, p = 0.08, respectively). The mean PTP of participants intending to discontinue erythromycin therapy or discharge the patient home was significantly lower than that of participants who intended continuing erythromycin or hospitalisation (0.20 vs 0.43, p<0.001; 0.40 vs 0.49, p = 0.005, respectively).
CONCLUSIONS: Paediatricians differed in their response to information about test characteristics. For many, it increased errors in estimating post-test probability; for others, it reduced errors. Estimated post-test probability was logically associated with intended clinical management.

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Year:  2009        PMID: 19131417     DOI: 10.1136/adc.2008.141903

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  8 in total

1.  Does prevalence matter to physicians in estimating post-test probability of disease? A randomized trial.

Authors:  Thomas Agoritsas; Delphine S Courvoisier; Christophe Combescure; Marie Deom; Thomas V Perneger
Journal:  J Gen Intern Med       Date:  2010-11-04       Impact factor: 5.128

2.  A Randomised Assessment of Trainee Doctors' Understanding and Interpretation of Diagnostic Test Results.

Authors:  V L Parker; J E Ritchie; T M Drake; J Hookham; S P Balasubramanian
Journal:  World J Surg       Date:  2016-01       Impact factor: 3.352

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4.  Development and Validation of a Mucosal Impedance Contour Analysis System to Distinguish Esophageal Disorders.

Authors:  Dhyanesh A Patel; Tina Higginbotham; James C Slaughter; Muhammad Aslam; Elif Yuksel; David Katzka; C Prakash Gyawali; Melina Mashi; John Pandolfino; Michael F Vaezi
Journal:  Gastroenterology       Date:  2019-01-31       Impact factor: 22.682

5.  Doctors and patients' susceptibility to framing bias: a randomized trial.

Authors:  Thomas V Perneger; Thomas Agoritsas
Journal:  J Gen Intern Med       Date:  2011-07-27       Impact factor: 5.128

6.  Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial.

Authors:  Yoav Ben-Shlomo; Simon M Collin; James Quekett; Jonathan A C Sterne; Penny Whiting
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Review 7.  How well do health professionals interpret diagnostic information? A systematic review.

Authors:  Penny F Whiting; Clare Davenport; Catherine Jameson; Margaret Burke; Jonathan A C Sterne; Chris Hyde; Yoav Ben-Shlomo
Journal:  BMJ Open       Date:  2015-07-28       Impact factor: 2.692

8.  Bayesian reasoning in residents' preliminary diagnoses.

Authors:  Benjamin Margolin Rottman; Micah T Prochaska; Roderick Corro Deaño
Journal:  Cogn Res Princ Implic       Date:  2016-09-22
  8 in total

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