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Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report
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 co...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374378/ https://www.ncbi.nlm.nih.gov/pubmed/34471703 http://dx.doi.org/10.12688/wellcomeopenres.16737.1 |
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author | Schultze, Anna Bates, Chris Cockburn, Jonathan MacKenna, Brian Nightingale, Emily Curtis, Helen J Hulme, William J Morton, Caroline E Croker, Richard Bacon, Seb McDonald, Helen I Rentsch, Christopher T Bhaskaran, Krishnan Mathur, Rohini Tomlinson, Laurie A Williamson, Elizabeth J Forbes, Harriet Tazare, John Grint, Daniel J Walker, Alex J Inglesby, Peter DeVito, Nicholas J Mehrkar, Amir Hickman, George Davy, Simon Ward, Tom Fisher, Louis Evans, David Wing, Kevin Wong, Angel YS McManus, Robert Parry, John Hester, Frank Harper, Sam Evans, Stephen JW Douglas, Ian J Smeeth, Liam Eggo, Rosalind M Goldacre, Ben |
author_facet | Schultze, Anna Bates, Chris Cockburn, Jonathan MacKenna, Brian Nightingale, Emily Curtis, Helen J Hulme, William J Morton, Caroline E Croker, Richard Bacon, Seb McDonald, Helen I Rentsch, Christopher T Bhaskaran, Krishnan Mathur, Rohini Tomlinson, Laurie A Williamson, Elizabeth J Forbes, Harriet Tazare, John Grint, Daniel J Walker, Alex J Inglesby, Peter DeVito, Nicholas J Mehrkar, Amir Hickman, George Davy, Simon Ward, Tom Fisher, Louis Evans, David Wing, Kevin Wong, Angel YS McManus, Robert Parry, John Hester, Frank Harper, Sam Evans, Stephen JW Douglas, Ian J Smeeth, Liam Eggo, Rosalind M Goldacre, Ben |
author_sort | Schultze, Anna |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8374378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-83743782021-08-31 Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report Schultze, Anna Bates, Chris Cockburn, Jonathan MacKenna, Brian Nightingale, Emily Curtis, Helen J Hulme, William J Morton, Caroline E Croker, Richard Bacon, Seb McDonald, Helen I Rentsch, Christopher T Bhaskaran, Krishnan Mathur, Rohini Tomlinson, Laurie A Williamson, Elizabeth J Forbes, Harriet Tazare, John Grint, Daniel J Walker, Alex J Inglesby, Peter DeVito, Nicholas J Mehrkar, Amir Hickman, George Davy, Simon Ward, Tom Fisher, Louis Evans, David Wing, Kevin Wong, Angel YS McManus, Robert Parry, John Hester, Frank Harper, Sam Evans, Stephen JW Douglas, Ian J Smeeth, Liam Eggo, Rosalind M Goldacre, Ben Wellcome Open Res Research Article 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. F1000 Research Limited 2021-04-27 /pmc/articles/PMC8374378/ /pubmed/34471703 http://dx.doi.org/10.12688/wellcomeopenres.16737.1 Text en Copyright: © 2021 Schultze A et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Schultze, Anna Bates, Chris Cockburn, Jonathan MacKenna, Brian Nightingale, Emily Curtis, Helen J Hulme, William J Morton, Caroline E Croker, Richard Bacon, Seb McDonald, Helen I Rentsch, Christopher T Bhaskaran, Krishnan Mathur, Rohini Tomlinson, Laurie A Williamson, Elizabeth J Forbes, Harriet Tazare, John Grint, Daniel J Walker, Alex J Inglesby, Peter DeVito, Nicholas J Mehrkar, Amir Hickman, George Davy, Simon Ward, Tom Fisher, Louis Evans, David Wing, Kevin Wong, Angel YS McManus, Robert Parry, John Hester, Frank Harper, Sam Evans, Stephen JW Douglas, Ian J Smeeth, Liam Eggo, Rosalind M Goldacre, Ben Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title | Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title_full | Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title_fullStr | Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title_full_unstemmed | Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title_short | Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report |
title_sort | identifying care home residents in electronic health records - an opensafely short data report |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374378/ https://www.ncbi.nlm.nih.gov/pubmed/34471703 http://dx.doi.org/10.12688/wellcomeopenres.16737.1 |
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