Why clinicians are natural bayesians

doi:10.1136/bmj.330.7499.1080

BMJ 2005;330:1080-1083 (7 May), doi:10.1136/bmj.330.7499.1080

Education and debate

Why clinicians are natural bayesians

Christopher J Gill, assistant professor¹, Lora Sabin, assistant professor¹, Christopher H Schmid, associate professor²

¹ Center for International Health and Development, Department of International Health, Boston University School of Public Health, Boston, MA 02118, USA, ² Biostatistics Research Center, Division of Clinical Care Research, Department of Medicine, Tufts University—New England Medical Center, Boston, MA 02111, USA

Correspondence to: C J Gill cgill@bu.edu

Thought you didn't understand bayesian statistics? Read on andfind out why doctors are expert in applying the theory, whetherthey realise it or not

The first 150 words of the full text of this article appear below.

Introduction

Two main approaches are used to draw statistical inferences:frequentist and bayesian. Both are valid, although they differmethodologically and perhaps philosophically. However, the frequentistapproach dominates the medical literature and is increasinglyapplied in clinical settings. This is ironic given that cliniciansapply bayesian reasoning in framing and revising differentialdiagnoses without necessarily undergoing, or requiring, anyformal training in bayesian statistics. To justify this assertion,this article will explain how bayesian reasoning is a naturalpart of clinical decision making, particularly as it pertainsto the clinical history and physical examination, and how bayesianapproaches are a powerful and intuitive approach to the differentialdiagnosis.

A sick child in Ethiopia

On a recent trip to southern Ethiopia, my colleagues and I encountereda severely ill child at a rural health clinic. The child's palms,soles, tongue, and conjunctivae were all white from severe anaemiaand his spleen was swollen and firm; he was . . . [Full text of this article]

Interpreting diagnostic test results from the bayesian perspective

Bayes's theorem and its application to clinical diagnosis

Conditional probability of tests in series

Bayesian reasoning in the pursuit of esoteric diagnoses

Conclusions

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