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Published 14 July 2008, doi:10.1136/bmj.a238
Cite this as: BMJ 2008;337:a238
Rumana Z Omar, reader1,2, Caoimhe OSullivan, statistician1,2, Irene Petersen, research fellow3, Amir Islam, data manager3, Azeem Majeed, professor4
1 Department of Statistical Science, University College London, London WC1E 6BT, 2 University College London Hospital/University College London Biomedical Research Unit, University College London Hospitals NHS Trust, London W1P 9LL, 3 Department of Primary Care and Population Sciences, University College London, 4 Department of Primary Care and Social Medicine, Imperial College London
Correspondence to: R Z Omar rumana{at}stats.ucl.ac.uk
Design Retrospective study of a cohort of patients followed for one year.
Setting UK General Practice Research Database.
Participants 129 general practices, with a total list size of 1 032 072.
Main outcome measures Each patient was assigned a morbidity group on the bases of diagnoses, age, and sex using the Johns Hopkins adjusted clinical group case mix system. Multilevel regression models were used to explain variability in prescribing, with age, sex, and morbidity as predictors.
Results The median number of prescriptions issued annually to a patient is 2 (90% range 0 to 18). The number of prescriptions issued to a patient increases with age and morbidity. Age and sex explained only 10% of the total variation in prescribing compared with 80% after including morbidity. When variation in prescribing was split between practices and within practices, most of the variation was at the practice level. Morbidity explained both variations well.
Conclusions Inclusion of a diagnosis based patient morbidity measure in prescribing models can explain a large amount of variability, both between practices and within practices. The use of patient based case mix systems may prove useful in allocation of budgets and therefore should be investigated further when examining prescribing patterns in general practices in the UK, particularly for specific therapeutic areas.
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