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Project #124:
Describing patterns of BMI recordings in primary care records

  • Type: Research
  • Topic areas: Other/indirect impacts of COVID on health/healthcare

BMI has been identified as a risk factor for clinical outcomes in patients with COVID-19. Electronic Health Records (EHR) hold significant potential for studying the association between BMI and COVID-19. This depends on the validity, completeness, and currency of BMI information that is available in or can be derived from EHR. Thus, this study aims to describe and compare methods for identifying BMI in EHR.

The study will check for consistency, completeness, and precision of the BMI variable, comparing the two methods of identifying BMI in OpenSAFELY: (1) calculation from height and weight and (2) GP-recorded values. It will evaluate the validity of each method (e.g., identify proportion of missing values or values out of range) and summarise any discrepancies across the two methods. Furthermore, it will aim to evaluate whether there are any patterns in missingness by relevant subgroups in the population.

The analysis will be completed using primary care EHRs of adults between 21 and 110 years registered with a GP-surgery using TPP and EMIS on 1 March 2020. Descriptive tables will be produced to describe missing and out of range values. Between 1 March 2015 to 1 March 2020, unique BMI for each patient will be considered to summarise how often BMI records are updated (average number of unique records over 5 years, average duration between BMI updates). Analyses will be performed for the overall population as well as by demographic categories, clinical conditions, and practice/region/STP.


  • Study leads: Robin Park
  • Organisation: University of Oxford and London School of Hygiene and Tropical Medicine