Q J Med 2004; 97: 53-55
© Association of Physicians 2004; all rights reserved.
Correspondence |
Do medical students and physicians understand probability?
Sir,We read with great interest the recent article by Dr Cahan and colleagues regarding the inability of residents to accurately determine probability.1 Despite the recent surge in teaching Evidence Based Medicine (EBM) in medical schools, the effectiveness of current teaching strategies remains unclear. We sought to determine how readily medical students and physicians identify the diagnostic terms often stressed in EBM.
Relevant articles were identified by searching various database including Medline (1980–2003), Embase (1988–2003), PsychInfo (1984–2003), Web of Science (1993–2003), educational websites, and bibliography of relevant articles. Study design, quality of study, and limitations of study were abstracted by two independent reviewers. Review articles, letters of editors, editorials of innumeracy, and diagnostic tests were excluded.
We identified eight articles (5 case scenarios, 2 questionnaires, and 1 telephone survey) that met the inclusion criteria (Table 1). 2–9 The number of participants in the studies varied from 31 to 300. There was considerable heterogeneity in the various studies. The commonest physician error was in overestimating the PPV (78–95%). One study described that the number of physicians using Bayesian calculations, ROC and LR was 3%, 1% and 0.66%, respectively. Medical students could not rule out diseases in low and intermediate probability case scenarios applying Bayesian estimates. In one study from Australia, 13 of 50 (26%) physicians stated that they could describe PPV, although on direct interviewing only one could actually illustrate it with an example. In another study, presenting the data in Natural frequency format increased the accuracy of determining PPV to 46%.
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Despite the heterogeneity in the various studies, the results are generalizable as they have been carried out in four continents and yield similar results. Physician innumeracy remains an impediment in popularizing EBM. Inattention to pre-test probability, and inability to assess the PPV accurately, could result in increased anxiety in patients by generating unnecessary tests and consultations. Increased attention to EBM instructions and presentation of data in alternative formats (e.g. natural frequency) may be indicated. The limitations of our analysis include the small number of studies, their sometimes small number of subjects, and the variation in study design.
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Division of General Internal Medicine BioMedical Library Mayo Clinic Rochester USA e-mail: ghosh.amit{at}mayo.edu
References
1. Cahan A, Gilon D, Manor O, Paltiel O. Probabilistic reasoning and clinical decision-making: do doctors overestimate diagnostic probabilities? Q J Med 2003; 96:763–9.
2. Reid MC, Lane DA, Feinstein Academic calculations versus clinical judgements: Practicing physicians use of quantitative measures of test accuracy. Am J Med 1998; 104:374–80.[CrossRef][Web of Science][Medline]
3. Steurer J, Fischer JE, Bachman LM, et al. Communicating accuracy of tests to general practioners: a controlled study. Br Med J 2002; 324:824.
4. Young JM, Glasziou P, Ward JE. General practitioners’ self rating of skills in evidence based medicine: a validation study. Br Med J 2002; 324:950.
5. Hoffrage U, Gigenzenger G. Using natural frequencies to improve diagnostic inferences. Acad Med 1998; 73:538–40.[Web of Science][Medline]
6. Lyman GH, Balducci L The effect of changing disease risk on clinical reasoning. J Gen Intern Med 1994; 9:488–94.[Web of Science][Medline]
7. Lyman G,.Balducci L. Overestimation of test effects in clinical judgement. J Cancer Edu 1993; 8:297–307.[Medline]
8. Noguchi Y, Matsui K, Imura H, et al. Quantitative evaluation of the diagnostic thinking process in medical students. J Gen Intern Med 2002; 17:839.[Medline]
9. Eddy DM. Probabilistic reasoning in clinical medicine: problems and opportunities. In: Kahneman D, Sloviv, Tversky A, eds. Judgement under uncertainty: Heuristics and Biases. Cambridge UK, Cambridge University Press, 1982:249–67.
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