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Invited Commentary
April 5, 2021

Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common Clinical Scenarios

Author Affiliations
  • 1Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
  • 2Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
JAMA Intern Med. Published online April 5, 2021. doi:10.1001/jamainternmed.2021.0240

An enviably close and influential collaboration during the 1970s between the psychologists Amos Tversky and Daniel Kahneman reshaped our beliefs about intuitive probabilistic reasoning. One of their many contributions was a demonstration of the base-rate fallacy, the tendency for people to neglect prior probabilities, or “base rates,” when calculating the chances of an event given more specific data.1 For example, the chances that a patient has a disease being tested reflects not only the test result and the test’s sensitivity and specificity, but also the relevant base rate, which is the prevalence of disease in a specific population.

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