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Project #25:
Representativeness of TPP data.

The OpenSAFELY framework allows analysis of the full pseudonymised patient primary care records for 57 million people registered at a general practice in England. This comprises 24m patients from practices that use TPP and 33m patients from practices that use EMIS. Use of the TPP and EMIS systems is known to be geographically clustered, however little is currently known about the extent to which the separate populations within these systems is representative of the population at large.

OpenSAFELY has been, and continues to be, used to support research that delivered urgent results related to the global COVID-19 emergency.

Assessing sample representativeness is a critical component of health research and provides context for researchers to understand the validity / applicability of their research. Understanding differences in geographic spread, sex, age, IMD and ethnicity distributions between TPP patients and non-TPP patients is important for the interpretation of COVID-19 research analysis and generalization to the background population.

In order to understand the representativeness of TPP data we will compare broad demographic data to ONS estimates for England for Index of Multiple Deprivation (IMD); age and sex and population per MSOA / STP. We will also compare ethnic breakdowns of TPP to the 2011 ONS Census and compare the 5 most common underlying causes of death in England in 2020 ONS to the equivalent in TPP.

  • Study lead: Colm Andrews
  • Organisation: University of Oxford and London School of Hygiene and Tropical Medicine
  • Project type: Audit
  • Topic area: Other/indirect impacts of COVID on health/healthcare