Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report.

Anna Schultze ORCID logo; ChrisBates; JonathanCockburn; BrianMacKenna; Emily Nightingale ORCID logo; Helen JCurtis; William J Hulme ORCID logo; Caroline EMorton; Richard Croker ORCID logo; SebBacon; +29 more... Helen I McDonald ORCID logo; Christopher T Rentsch ORCID logo; Krishnan Bhaskaran ORCID logo; Rohini Mathur ORCID logo; Laurie A Tomlinson ORCID logo; Elizabeth J Williamson ORCID logo; HarrietForbes; John Tazare ORCID logo; Daniel J Grint ORCID logo; Alex JWalker; PeterInglesby; Nicholas J DeVito ORCID logo; AmirMehrkar; GeorgeHickman; SimonDavy; TomWard; LouisFisher; DavidEvans; Kevin Wing ORCID logo; Angel Ys Wong ORCID logo; RobertMcManus; John Parry ORCID logo; FrankHester; SamHarper; Stephen Jw Evans ORCID logo; Ian JDouglas; Liam Smeeth ORCID logo; Rosalind M Eggo ORCID logo; Ben Goldacre ORCID logo; (2021) Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report. Wellcome open research, 6. 90-. ISSN 2398-502X DOI: 10.12688/wellcomeopenres.16737.1
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Background: Care home residents have been severely affected by the COVID-19 pandemic. Electronic Health Records (EHR) hold significant potential for studying the healthcare needs of this vulnerable population; however, identifying care home residents in EHR is not straightforward. We describe and compare three different methods for identifying care home residents in the newly created OpenSAFELY-TPP data analytics platform.  Methods: Working on behalf of NHS England, we identified individuals aged 65 years or older potentially living in a care home on the 1st of February 2020 using (1) a complex address linkage, in which cleaned GP registered addresses were matched to old age care home addresses using data from the Care and Quality Commission (CQC); (2) coded events in the EHR; (3) household identifiers, age and household size to identify households with more than 3 individuals aged 65 years or older as potential care home residents. Raw addresses were not available to the investigators. Results: Of 4,437,286 individuals aged 65 years or older, 2.27% were identified as potential care home residents using the complex address linkage, 1.96% using coded events, 3.13% using household size and age and 3.74% using either of these methods. 53,210 individuals (32.0% of all potential care home residents) were classified as care home residents using all three methods. Address linkage had the largest overlap with the other methods; 93.3% of individuals identified as care home residents using the address linkage were also identified as such using either coded events or household age and size.  Conclusion: We have described the partial overlap between three methods for identifying care home residents in EHR, and provide detailed instructions for how to implement these in OpenSAFELY-TPP to support research into the impact of the COVID-19 pandemic on care home residents.



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