Cargando…
Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration
BACKGROUND: The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842203/ https://www.ncbi.nlm.nih.gov/pubmed/36647111 http://dx.doi.org/10.1186/s12911-022-02093-0 |
_version_ | 1784870057006858240 |
---|---|
author | Abbasizanjani, Hoda Torabi, Fatemeh Bedston, Stuart Bolton, Thomas Davies, Gareth Denaxas, Spiros Griffiths, Rowena Herbert, Laura Hollings, Sam Keene, Spencer Khunti, Kamlesh Lowthian, Emily Lyons, Jane Mizani, Mehrdad A. Nolan, John Sudlow, Cathie Walker, Venexia Whiteley, William Wood, Angela Akbari, Ashley |
author_facet | Abbasizanjani, Hoda Torabi, Fatemeh Bedston, Stuart Bolton, Thomas Davies, Gareth Denaxas, Spiros Griffiths, Rowena Herbert, Laura Hollings, Sam Keene, Spencer Khunti, Kamlesh Lowthian, Emily Lyons, Jane Mizani, Mehrdad A. Nolan, John Sudlow, Cathie Walker, Venexia Whiteley, William Wood, Angela Akbari, Ashley |
author_sort | Abbasizanjani, Hoda |
collection | PubMed |
description | BACKGROUND: The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt. METHODS: Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer. RESULTS: Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information. CONCLUSIONS: We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-02093-0 |
format | Online Article Text |
id | pubmed-9842203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98422032023-01-17 Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration Abbasizanjani, Hoda Torabi, Fatemeh Bedston, Stuart Bolton, Thomas Davies, Gareth Denaxas, Spiros Griffiths, Rowena Herbert, Laura Hollings, Sam Keene, Spencer Khunti, Kamlesh Lowthian, Emily Lyons, Jane Mizani, Mehrdad A. Nolan, John Sudlow, Cathie Walker, Venexia Whiteley, William Wood, Angela Akbari, Ashley BMC Med Inform Decis Mak Research BACKGROUND: The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt. METHODS: Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer. RESULTS: Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information. CONCLUSIONS: We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-02093-0 BioMed Central 2023-01-16 /pmc/articles/PMC9842203/ /pubmed/36647111 http://dx.doi.org/10.1186/s12911-022-02093-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Abbasizanjani, Hoda Torabi, Fatemeh Bedston, Stuart Bolton, Thomas Davies, Gareth Denaxas, Spiros Griffiths, Rowena Herbert, Laura Hollings, Sam Keene, Spencer Khunti, Kamlesh Lowthian, Emily Lyons, Jane Mizani, Mehrdad A. Nolan, John Sudlow, Cathie Walker, Venexia Whiteley, William Wood, Angela Akbari, Ashley Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title | Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title_full | Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title_fullStr | Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title_full_unstemmed | Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title_short | Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration |
title_sort | harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a uk-wide covid-19 research collaboration |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842203/ https://www.ncbi.nlm.nih.gov/pubmed/36647111 http://dx.doi.org/10.1186/s12911-022-02093-0 |
work_keys_str_mv | AT abbasizanjanihoda harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT torabifatemeh harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT bedstonstuart harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT boltonthomas harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT daviesgareth harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT denaxasspiros harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT griffithsrowena harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT herbertlaura harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT hollingssam harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT keenespencer harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT khuntikamlesh harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT lowthianemily harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT lyonsjane harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT mizanimehrdada harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT nolanjohn harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT sudlowcathie harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT walkervenexia harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT whiteleywilliam harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT woodangela harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT akbariashley harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration AT harmonisingelectronichealthrecordsforreproducibleresearchchallengessolutionsandrecommendationsfromaukwidecovid19researchcollaboration |