BMJ 1995;311:163-165 (15 July)

General practice

Allocating census data to general practice populations: implications for study of prescribing variation at practice level

Glen Scrivener, social geographer,a David C E F Lloyd, applied research statistician a

a Prescribing Research Unit, Academic Unit of General Practice, University of Leeds, Leeds LS2 9NZ

Correspondence to: Mr Scrivener.

Abstract

Objectives: To assign census data to general practice populations and to test accuracy of different procedures for estimating the proportion of patients aged over 64.
Design: Patients' postcodes from patient register of one family health services authority and the directory linking postcodes to census enumeration districts were used to locate patients in their census area of residence. With different levels of census geography and four different allocation procedures, proportion of patients aged over 64 in each area was used to predict proportion of patients aged over 64 in each general practice. Predicted figures were compared with real figures from each practice register to assess accuracy of allocation methods.
Setting: Data from 1991 census and from 73 practices administered by one family health services authority.
Main outcome measures: Actual and predicted proportions of patients aged over 64 in general practice populations.
Results: Correlations between actual and predicted proportions of patients aged over 64 were significant for all four allocation procedures--values of 0.66, 0.7, 0.84, and 0.84 were achieved (P<0.0005). Predicted ranges of proportions of patients aged over 64, however, were well short of those that actually existed, and significant differences existed between predicted percentages and actual figures for all four methods.
Conclusion: Although predicted values correlated with actual values, the failure of the allocation procedures to correctly predict values, especially at the extremes, casts doubt on the validity of similar techniques for allocating census variables to general practice populations.

Key messages

  • Key messages

  • No clear indicators have emerged from general practice itself, so proxy measures have been sought from data sets such as the census

  • We assigned census data to general practice populations and assessed accuracy of estimating proportions of patients aged over 64 in general practice by comparison with census from each practice register

  • Correlations between actual and predicted proportions of patients aged over 64 were significant, but predicted ranges of proportions were well short of actual ranges and predicted and actual values were significantly different

  • Failure to correctly predict actual values casts doubt on the validity of allocating census data to general practice populations


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