Disease prevalence in the English population: A comparison of primary care registers and prevalence models

David Martin and James A. Wright

Social Science & Medicine, 2009, vol. 68, issue 2, 266-274

Abstract: The Quality and Outcomes Framework (QOF) is a UK system for monitoring general practitioner (GP) activity and performance, introduced in 2004. The objective of this paper is to explore the potential of QOF datasets as a basis for better understanding geographical variations in disease prevalence in England. In an ecological study, prevalence estimates for four common disease domains (coronary heart disease (CHD), asthma, hypertension and diabetes) were derived from the 2004-2005 QOF primary care disease registers for 354 English Local Authority Districts (LADs). These were compared with synthetic estimates from four prevalence models and with self-reported measures of general health from the 2001 census. Prevalence models were recalculated for LADs using demographic and deprivation data from the census. Results were mapped spatially and cross-tabulated against a national classification of local authorities. The four disease domains display different spatial distributions and different spatial relationships with the corresponding prevalence model. For example, the prevalence model for CHD under-estimated QOF cases in northern England, but this north-south pattern was not evident for the other disease domains. The census-derived health measures were strongly correlated with CHD, but not with the other disease domains. The relationship between modelled prevalence and QOF disease registers differs by disease domain, implying that there is no simple cross-domain effect of the QOF process on prevalence figures. Given reliable synthetic estimates of small area prevalence for the QOF disease domains, one potential application of the QOF dataset may be in assessing the geographical extent of under-diagnosis for each domain.

Keywords: England; Morbidity; Prevalence; Quality; and; Outcomes; Framework; Limiting; long-term; illness; UK (search for similar items in EconPapers)
Date: 2009
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