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Multivariate regression analysis of associations between general practitioner prescribing rates for coronary heart disease drugs and healthcare needs indicators
  1. Paul R Ward1,
  2. Peter R Noyce2,
  3. Antony S St Leger3
  1. 1Section of Public Health, School of Health and Related Research, University of Sheffield, Sheffield, UK
  2. 2School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, UK
  3. 3Evidence for Population Health Unit, School of Epidemiology and Health Sciences, University of Manchester
  1. Correspondence to:
 Dr P R Ward
 Section of Public Health, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK; p.r.wardsheffield.ac.uk

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A recent paper in the journal by the authors presented the results of bivariate correlations between prescribing rates for coronary heart disease (CHD) drugs and healthcare needs indicators (HCNIs).1 This paper added further weight to the suggestion that GP practice prescribing rates for statins are inequitable,2–5 although we also provided evidence for a range of other CHD drugs.

One of the letters to the journal suggested that a multivariate analysis would have helped to determine the independent associations between prescribing rates and HCNIs. We have undertaken multivariate regression analysis to determine the amount of variation in prescribing rates that can be explained by a combination of HCNIs and also to understand the strength and direction of independent associations with individual HCNIs. The main results are provided in this letter.

Between 22% to 25% of the variation in prescribing rates for statins, β blockers, and bendrofluazide was explained in the multiple regression models. Slightly more variation was explained for ACE inhibitors (31.6%) and considerably more for aspirin (51.2%). Prescribing rates for all drug groups (except ACE inhibitors) were positively associated with CHD hospital diagnoses and procedures. Prescribing rates for statins and ACE inhibitors were negatively associated with the percentage of patients aged over 75 years in addition to the proportion of patients from minority ethnic groups. Prescribing rates for aspirin, bendrofluazide, and all CHD drugs combined were negatively associated with deprivation.

Overall, this study found that prescribing rates were generally positively related to the rates of CHD hospital procedures and diagnoses, although they were also negatively associated with proxies of deprivation and ethnicity. These findings present further evidence of inequities of GP practice prescribing rates and the continued relevance of the inverse care law in prescribing. However, this ecological study cannot be used to infer inequitable prescribing by GPs, as the lower prescribing rates in GP practice populations with higher proportions of elderly, ethnic minority, and deprived patients may be attributable to lower utilisation of primary healthcare services because of social, psychological, economic, or cultural barriers. Therefore, further work needs to be undertaken in identified GP practice populations to understand the reasons for the low prescribing rates and ultimately to make CHD prescribing commensurate with healthcare need.

Acknowledgments

Paul Ward received a Health Services Research Training Fellowship from the North West NHS Executive to carry out the study on which this paper is based. We thank all health authority, PCT and Local Authority staff who provided access to PACT data, GP practice list data, hospital episode statistics and a variety of other data sources.

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