Wolf F M, Gruppen L D, Billi J E
JAMA. 1985 May 17;253(19):2858-62.
Evaluating the same diagnostic information across the plausible competing diagnoses is a practical strategy (ie, heuristic) to guide decision making in the face of uncertainty. The prevalence of use of this competing-hypotheses heuristic by 89 first-year house officers was examined in three simulated patient cases. Results indicated that only a minority (24%) of the house officers selected optimal diagnostic information consistent with this Bayesian heuristic across all three cases. Almost all (97%) of the house officers selecting optimal diagnostic information were able to identify the most probable diagnosis specified by Bayes' theorem, while only a chance number (53%) of house officers selecting nonoptimal information were able to identify the most probable diagnosis. The competing-hypotheses heuristic is discussed within the context of diagnostic problem-solving models derived from the literature on medical decision making and clinicopathological conference case records. It is suggested that the heuristic, which does not necessitate any mathematical calculations, may be useful as a complement to clinical judgment.
面对不确定性时，在看似合理的相互竞争的诊断中评估相同的诊断信息是一种指导决策的实用策略（即启发法）。在三个模拟患者病例中，研究了89名一年级住院医生使用这种相互竞争假设启发法的情况。结果表明，只有少数（24%）住院医生在所有三个病例中都选择了与这种贝叶斯启发法一致的最佳诊断信息。几乎所有（97%）选择最佳诊断信息的住院医生都能够识别贝叶斯定理指定的最可能诊断，而只有少数（53%）选择非最佳信息的住院医生能够识别最可能诊断。本文在从医学决策文献和临床病理会议病例记录中得出的诊断问题解决模型的背景下讨论了相互竞争假设启发法。建议这种无需任何数学计算的启发法可用作临床判断的补充。
