The Prediction of Primary Health Care Costs Using Measures of Morbidity and Multi-Morbidity (Centre for Health Economics, University of York)


This paper examines the relationship between the primary care costs of patients (for consultations, tests and drugs) and their age, gender, deprivation and measures of their morbidity and multimorbidity. This information is likely to be of value when calculating budgets for general practices to cover their expenditure on primary care services. It could be useful, also, to explore whether the expenditure between practices varies proportionately as would be predicted according to the characteristics of patient groups served.

The analysis was based on data about 86,100 individuals across 174 English practices. Measures were derived from four morbidity descriptive systems; 17 chronic diseases in the Quality and Outcomes Framework (QOF), 17 chronic diseases in the Charlson scheme, 114 Expanded Diagnosis Clusters (EDCs), and 68 Adjusted Clinical Groups (ACGs). The researchers found that the EDC measures had the best predictive power, followed by the QOF and ACG measures. The Charlson measures fared the worst.

Full Text Link


Brilleman, SL. Gravelle, H. [and] Hollinghurst, S. [et al] (2011). Keep it simple? Predicting primary health care costs with measures of morbidity and multimorbidity. CHE Research Paper 72. York: Centre for Health Economics, University of York, December 2011.

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Dementia and Elderly Care News. Wolverhampton Medical Institute: WMI. (jh)
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