Abstract

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.

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