DIAGNOSTICITY AND HEURISTICS IN MEDICAL DECISION MAKING

这项研究的重点是增加对 认知过程参与信息获取和临床 医学决策。 这将通过使用理论进行研究 概率论（特别是贝叶斯定理）和认知科学（认知科学） 策略）和实验程序以前开发的这些 地区 这项研究的主要目的是研究如何 医生寻求诊断相关的信息， 信息选择到最可能的诊断的选择。 本研究的具体目标是：（1）检验 一个问题是如何在诊断信息的选择框架， 病例，（2）调查认知行为学在 诊断信息的选择，（3）研究阈值， 影响诊断信息选择的信息，（4） 检查信息选择和诊断之间的关系， （5）确定培养医学生的教育策略 和医生（a）选择最佳的诊断信息， 鉴别诊断中疾病候选者的系统评价 列表和（B）意识到诊断评价中的潜在偏倚， 可能是由于选择了非最佳信息。 一系列 实验涉及医学生，开始内务人员， 执业医师将对这些问题进行研究。 在 此外，信息获取的计算机化模拟模型， 评估和诊断过程中的医疗决策将是 开发 将通过比较医生的选择来分析数据 的诊断数据和最可能的诊断为病人的情况下，以最佳 基于竞争假设启发式和贝叶斯定理的决策。 这些最佳决策要求每一条诊断数据 在鉴别诊断中对所有竞争性疾病进行评价 名单 框架效应和门槛效应的问题将是 研究以确定它们如何影响医生的判断和认知 战略布局 这些实验的结果将对训练有重要的意义 医学生和医生在信息管理和问题 解决 深入了解收集和使用的有效物流（策略）， 将获得评估信息。 非最优策略和偏差 可能导致的结果也将被确定。

The focus of this research is on increasing the understanding of the cognitive processes involved in information acquisition and clinical decision making in medicine. This will be investigated by using theories of probability (specifically, Bayes' theorem) and heuristics (cognitive strategies) and experimental procedures previously developed in these areas. The primary aim of this research is to examine the way in which physicians seek diagnostically relevant information and the relationship of information selection to the selection of a most likely diagnosis. The specific objectives of this research are (1) to examine the effects of how a problem is framed on the selection of diagnostic information in patient cases, (2) to investigate the cognitive heuristics used in the selection of diagnostic information, (3) to study the threshold value of information that influences the selection of diagnostic information, (4)\to examine the relationship between selection of information and a diagnosis, and (5) to identify educational strategies for training medical students and physicians to (a) select optimally diagnostic information for the systematic evaluation of disease candidates in the differential diagnosis list and (b) become aware of potential biases in diagnostic evaluation that may result from the selection of non-optimal information. A series of experiments involving medical students, beginning house officers, and practicing physicians will be conducted to study these issues. In addition, a computerized simulation model of the information acquisition, evaluation, and diagnostic process in medical decision making will be developed. The data will be analyzed by comparing physicians' selections of diagnostic data and most likely diagnosis for patient cases to optimal decisions based on the competing hypotheses heuristic and Bayes' theorem. These optimal decisions dictate that each piece of diagnostic data be evaluated across all competing diseases in the differential diagnosis list. Both framing effects and threshold effects of the problem will be studied to determine how they influence physicians' judgments and cognitive strategies. Results of these experiments will have significant implications in training medical students and physicians in information management and problem solving. Insight into efficient heuristics (strategies) for collecting and evaluating information will be obtained. Non-optimal strategies and biases in judgments that may result will also be identified.