Non-medical influences on medical decision-making
Non-medical influences on medical decision-making
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DOI：
10.1016/0277-9536(95)00342-8
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发表时间：
1996-03-01
影响因子：
5.4
通讯作者：
Feldman, HA
中科院分区：
文献类型：
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作者：
McKinlay, JB;Potter, DA;Feldman, HA
背景非医学因素对医生决策的影响已经在许多观察性研究中被记录下来，但很少在能够证明因果关系的实验环境中。我们进行了一项对照析因实验，以评估在两种常见的医疗情况下，内科医生的诊断和治疗决策的非医疗因素的影响。方法. 192名白色男性内科医生单独观看专业制作的视频场景，其中演员-患者表现为胸痛或呼吸困难，具有性别、种族、年龄、社会经济地位和健康保险范围的各种平衡组合。从私人执业、医院执业和健康维护组织的内科医生名单中随机抽取两种经验水平的医生。结果胸痛和呼吸困难最常见的诊断是心因性起源和心脏问题。戒烟是这两种疾病最常见的治疗建议。年轻患者（所有其他因素相同）更有可能接受心因性诊断。老年患者更有可能因胸痛而接受心脏诊断，特别是如果他们有保险的话。基于HMO的医生更有可能建议对胸痛进行随访。除了主效应外，患者和医生因素的几个相互作用也很重要。结论.在这个实验中，医生证明的决策的可变性并不完全由严格理性的贝叶斯推理（医疗决策的常见规范模型）解释，因为非医疗因素显著影响了他们所做的决定。在任何综合性的医疗决策理论中，都需要对理想化的医疗模式进行补充，同时考虑社会行为。
Background. The influence of non-medical factors on physicians' decision-making has been documented in many observational studies, but rarely in an experimental setting capable of demonstrating cause and effect. We conducted a controlled factorial experiment to assess the influence of non-medical factors on the diagnostic and treatment decisions made by practitioners of internal medicine in two common medical situations. Methods. One hundred and ninety-two white male internists individually viewed professionally produced video scenarios in which the actor-patient, presenting with either chest pain or dyspnea, possessed various balanced combinations of sex, race, age, socioeconomic status, and health insurance coverage. Physician subjects were randomly drawn from lists of internists in private practice, hospital-based practice, and HMO's, at two levels of experience. Results. The most frequent diagnoses for both chest pain and dyspnea were psychogenic origin and cardiac problems. Smoking cessation was the most frequent treatment recommendation for both conditions. Younger patients (all other factors being the same) were significantly more likely to receive the psychogenic diagnosis. Older patients were more likely to receive the cardiac diagnosis for chest pain, particularly if they were insured. HMO-based physicians were more likely to recommend a follow-up visit for chest pain. Several interactions of patient and physician factors were significant in addition to the main effects. Conclusions. The variability in decision-making evidenced by physicians in this experiment was not entirely accounted for by strictly rational Bayesian inference (the common prescriptive model for medical decision-making), in-as-much as non-medical factors significantly affected the decisions that they made. There is a need to supplement idealized medical schemata with considerations of social behavior in any comprehensive theory of medical decision-making.