Davis Peter, Gribben Barry, Lay-Yee Roy, Scott Alastair
Department of Public Health and General Practice, Christchurch School of Medicine and Health Sciences, University of Otago, PO Box 4345, Christchurch, New Zealand.
J Health Serv Res Policy. 2002 Oct;7(4):202-8. doi: 10.1258/135581902320432723.
There is considerable policy interest in medical practice variation (MPV). Although the extent of MPV has been quantified for secondary care, this has not been investigated adequately in general practice. Technical obstacles to such analyses have been presented by the reliance on ecological small area variation (SAV) data, the binary nature of many clinical outcomes in primary care and by diagnostic variability. The study seeks to quantify the extent of variation in clinical activity between general practitioners by addressing these problems.
A survey of nearly 10 000 encounters drawn from a representative sample of general practitioners in the Waikato region of New Zealand was carried out in the period 1991-1992. Participating doctors recorded all details of clinical activity for a sample of encounters. Measures used in this analysis are the issuing of a prescription, the ordering of a laboratory test or radiology examination, and the recommendation of a future follow-up office visit at a specified date. An innovative statistical technique is adopted to assess the allocation of variance for binary outcomes within a multi-level analysis of decision-making.
As expected, there was considerable variability between doctors in levels of prescribing, ordering of investigations and requests for follow up. These differences persisted after controlling for case-mix and patient and practitioner attributes. However, analysis of the components of variance suggested that less than 10% of remaining variability occurred at the practitioner level for any of the measures of clinical activity. Further analysis of a single diagnostic group--upper respiratory tract infection--marginally increased the practitioner contribution.
The amount of variability in clinical activity that can definitively be linked to the practitioner in primary care is similar to that recorded in studies of the secondary sector. With primary care doctors increasingly being grouped into larger professional organisations, we can expect application of multi-level techniques to the analysis of clinical activity in primary care at different levels of organisational complexity.
医疗实践差异(MPV)受到了相当大的政策关注。尽管已经对二级医疗中的MPV程度进行了量化,但在全科医疗中尚未得到充分研究。依赖生态小区域差异(SAV)数据、初级医疗中许多临床结局的二元性质以及诊断变异性给此类分析带来了技术障碍。本研究旨在通过解决这些问题来量化全科医生之间临床活动的差异程度。
1991 - 1992年期间,对从新西兰怀卡托地区具有代表性的全科医生样本中抽取的近10000次诊疗进行了调查。参与的医生记录了一部分诊疗的临床活动的所有细节。本分析中使用的指标包括开具处方、安排实验室检查或放射学检查,以及建议在特定日期进行未来的随访门诊。采用了一种创新的统计技术来评估在多层次决策分析中二元结局的方差分配。
正如预期的那样,医生在处方开具、检查安排和随访要求水平上存在相当大的差异。在控制了病例组合、患者和从业者属性后,这些差异仍然存在。然而,方差成分分析表明,对于任何临床活动指标,在从业者层面上剩余差异的不到10%。对单个诊断组——上呼吸道感染——的进一步分析略微增加了从业者的贡献。
在初级医疗中能够明确与从业者相关的临床活动差异量与二级医疗研究中记录的相似。随着初级医疗医生越来越多地被组织成更大的专业机构,我们可以预期多层次技术将应用于分析不同组织复杂性水平下的初级医疗临床活动。