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Death foretold: prophecy and prognosis in medical care

·2000·Choice Reviews Online

Abstract

This text explains the act of prognosis in its varying forms - doctors telling patients if their cancer is curable, when their pain will stop, if they will live to see their child graduate from college - from the perspective of doctors. Nicholas Christakis examines why physicians are reluctant to predict the future, what uses doctors make of prognosis, the symbolism it contains, and the practical and emotional difficulties it involves. Drawing on his experiences both as a doctor and as a sociologist, the author conducted interviews with physicians; he searched medical textbooks and medical school curricula for discussions of prognosis; and he developed quantitative data showing that physicians are systematically optimistic in their predictions. With its combination of approaches and methods, this book is a study of a murky area of medical practice that, despite its importance, is only partially understood and rarely discussed. Christakis argues that physicians and the medical profession as a whole have the duty to prognosticate, and shirking the difficult questions - as most doctors tend to do - advances neither medical knowledge nor the care seriously ill patients receive. The book aims to be a clarion call for a renewed effort to understand and improve the art and science of prognostication.

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Metadata

Venue
Choice Reviews Online
Published
2000-10-01
Volume
38
Issue
02
Pages
38-0972-38-0972
ISSN
  • 0009-4978 (ISSN-L)
  • 1523-8253
OpenAlex
W592511698
Cited by
394
References
0
Type
book review
Language
en
Open access
closed

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CoChat. (2026). Citation check: Death foretold: prophecy and prognosis in medical care. https://app.cochat.ai/papers/10.5860/choice.38-0972
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Death foretold: prophecy and prognosis in medical care. (2000). Choice Reviews Online. https://doi.org/10.5860/choice.38-0972

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.