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A model based on age, sex, and morbidity to explain variation in UK general practice prescribing: cohort study

BMJ 2008; 337 doi: https://doi.org/10.1136/bmj.a238 (Published 14 July 2008) Cite this as: BMJ 2008;337:a238
  1. Rumana Z Omar, reader12,
  2. Caoimhe O’Sullivan, statistician12,
  3. Irene Petersen, research fellow3,
  4. Amir Islam, data manager3,
  5. Azeem Majeed, professor4
  1. 1Department of Statistical Science, University College London, London WC1E 6BT
  2. 2University College London Hospital/University College London Biomedical Research Unit, University College London Hospitals NHS Trust, London W1P 9LL
  3. 3Department of Primary Care and Population Sciences, University College London
  4. 4Department of Primary Care and Social Medicine, Imperial College London
  1. Correspondence to: R Z Omar rumana{at}stats.ucl.ac.uk
  • Accepted 30 April 2008

Abstract

Objective To examine whether patient level morbidity based measure of clinical case mix explains variations in prescribing in general practice.

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.

Footnotes

  • Contributors: RZO and AM conceived the study and wrote the manuscript. RZO designed and supervised the statistical analysis and did some of the statistical analysis. CO’S constructed the groups on the basis of the adjusted clinical group, did the statistical analysis, and commented on the manuscript. AI extracted the data from the General Practice Research Database and responded to queries about the data. IP acted as an expert on the General Practice Research Database and commented on the manuscript. RZO and CO’S contributed equally to the paper. RZO, CO’S, and AM are guarantors.

  • Funding: The statistical analysis was partially supported by a primary care researcher award from the Department of Health. The work was undertaken at University College London Hospital/University College London, which received a proportion of funding from the Department of Health’s National Institute of Health Research Biomedical Research Centres funding scheme. The Department of Primary Care and Social Medicine at Imperial College is supported by the National Institute of Health Research Biomedical Research Centre scheme.

  • Competing interests: None declared.

  • Ethical approval: This study was approved by the scientific and ethical advisory committee, responsible for the Medicines and Healthcare products Regulatory Agency General Practice Research Database.

  • Provenance and peer review: Not commissioned; externally peer reviewed.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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