Feldman H A, McKinlay J B, Potter D A, Freund K M, Burns R B, Moskowitz M A, Kasten L E
New England Research Institutes, Watertown, MA 02172, USA.
Health Serv Res. 1997 Aug;32(3):343-66.
To study nonmedical influences on the doctor-patient interaction. A technique using simulated patients and "real" doctors is described.
A random sample of physicians, stratified on such characteristics as demographics, specialty, or experience, and selected from commercial and professional listings.
A medical appointment is depicted on videotape by professional actors. The patient's presenting complaint (e.g., chest pain) allows a range of valid interpretation. Several alternative versions are taped, featuring the same script with patient-actors of different age, sex, race, or other characteristics. Fractional factorial design is used to select a balanced subset of patient characteristics, reducing costs without biasing the outcome.
Each physician is shown one version of the videotape appointment and is asked to describe how he or she would diagnose or treat such a patient.
Two studies using this technique have been completed to date, one involving chest pain and dyspnea and the other involving breast cancer. The factorial design provided sufficient power, despite limited sample size, to demonstrate with statistical significance various influences of the experimental and stratification variables, including the patient's gender and age and the physician's experience. Persistent recruitment produced a high response rate, minimizing selection bias and enhancing validity.
These techniques permit us to determine, with a degree of control unattainable in observational studies, whether medical decisions as described by actual physicians and drawn from a demographic or professional group of interest, are influenced by a prescribed set of nonmedical factors.
研究医患互动中的非医学影响因素。本文描述了一种使用模拟患者和“真实”医生的技术。
从商业和专业名录中选取医生的随机样本,按照人口统计学、专业或经验等特征进行分层。
专业演员在录像带上呈现一次医疗预约场景。患者的主诉(如胸痛)可有多种合理的解读。录制了几个不同版本,脚本相同,但患者演员具有不同的年龄、性别、种族或其他特征。采用分数析因设计来选择患者特征的均衡子集,在不影响结果的前提下降低成本。
向每位医生展示录像预约的一个版本,并要求其描述将如何诊断或治疗这样的患者。
迄今为止,已完成两项使用该技术的研究,一项涉及胸痛和呼吸困难,另一项涉及乳腺癌。尽管样本量有限,但析因设计仍具有足够的效力,能够在统计学上显著证明实验变量和分层变量的各种影响,包括患者的性别和年龄以及医生的经验。持续招募产生了较高的应答率,将选择偏倚降至最低并提高了效度。
这些技术使我们能够在一定程度上进行控制,而这在观察性研究中是无法实现的,从而确定来自特定人口统计学或专业群体的实际医生所描述的医疗决策是否受到一组规定的非医学因素的影响。