Roberts C
Health Care Trials Unit, School of Epidemiology and Health Sciences, Stopford Building, University of Manchester, Manchester M13 9PT, U.K.
Stat Med. 1999 Oct 15;18(19):2605-15. doi: 10.1002/(sici)1097-0258(19991015)18:19<2605::aid-sim237>3.0.co;2-n.
Methodological work on randomized trials has largely concerned pharmacological interventions in which the effects of the attending health professional may be regarded as minor. In other clinical settings, such as surgery, talk or physical therapies, staff specific variation may make generalization problematic, undermining the value of the trial. Such variation has been the basis of some objections to controlled trial methodology and non-acceptance of trial results. The implication of this source of variation will be considered for studies in which different types of health professional deliver the intervention in each arm of the trial. Such a trial may involve individual patient or group randomization. Whichever method is used, it is argued that variation in outcome between health professionals may lead to design effects. These issues will be illustrated using data from a large trial comparing primary care service delivered by two types of medical doctor. Random effect models are most suitable for analyzing this type of trial, as they allow adjustment for patient characteristics whilst controlling for design effects. This type of model illustrates that there can be substantial variation in the performance within each category of doctor.
随机试验的方法学研究主要关注药物干预，在这类干预中，参与的医护人员的影响可能被视为较小。在其他临床环境中，如外科手术、谈话或物理治疗，工作人员的个体差异可能会使推广变得有问题，从而削弱试验的价值。这种差异一直是对对照试验方法提出一些反对意见以及不接受试验结果的依据。对于在试验的每个组中由不同类型的医护人员实施干预的研究，将考虑这种差异来源的影响。这样的试验可能涉及个体患者或组随机化。无论使用哪种方法，有人认为医护人员之间结果的差异可能导致设计效应。将使用来自一项大型试验的数据来说明这些问题，该试验比较了两种类型的医生提供的初级保健服务。随机效应模型最适合分析这类试验，因为它们允许在控制设计效应的同时对患者特征进行调整。这种类型的模型表明，在每类医生中，表现可能存在很大差异。
