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Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight
BACKGROUND: Record linkage is increasingly used in health research worldwide. Combining the patient information available in healthcare, administrative and clinical databases broadens the research perspectives, particularly for chronic diseases. Recent guidelines highlight the need for transparency...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988267/ https://www.ncbi.nlm.nih.gov/pubmed/31992233 http://dx.doi.org/10.1186/s12882-020-1692-4 |
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author | Raffray, Maxime Bayat, Sahar Lassalle, Mathilde Couchoud, Cécile |
author_facet | Raffray, Maxime Bayat, Sahar Lassalle, Mathilde Couchoud, Cécile |
author_sort | Raffray, Maxime |
collection | PubMed |
description | BACKGROUND: Record linkage is increasingly used in health research worldwide. Combining the patient information available in healthcare, administrative and clinical databases broadens the research perspectives, particularly for chronic diseases. Recent guidelines highlight the need for transparency on the used record linkage processes and the extracted data to be used by researchers. METHODS: Therefore, the aim of this study was to describe the deterministic iterative approach used to link the French Epidemiology and Information Network (REIN), a French national End-Stage Renal Disease registry, with the Système National des Données de Santé (SNDS), a French nationwide medico-administrative healthcare database. RESULTS: Among the 22,073 patients included in the REIN registry who started renal replacement therapy between 2014 and 2015 in France, 19,223 (87.1%) were matched with patients in the SNDS database. Comparison of matched and unmatched patients confirmed the absence of any major selection bias. Then, the record linkage was evaluated using the comorbidity status (diabetes). CONCLUSIONS: This fast and efficient method of record linkage with pseudonymized data and without unique and direct identifier might inspire other research teams. It also opens the path for new research on chronic kidney disease. |
format | Online Article Text |
id | pubmed-6988267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69882672020-01-31 Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight Raffray, Maxime Bayat, Sahar Lassalle, Mathilde Couchoud, Cécile BMC Nephrol Technical Advance BACKGROUND: Record linkage is increasingly used in health research worldwide. Combining the patient information available in healthcare, administrative and clinical databases broadens the research perspectives, particularly for chronic diseases. Recent guidelines highlight the need for transparency on the used record linkage processes and the extracted data to be used by researchers. METHODS: Therefore, the aim of this study was to describe the deterministic iterative approach used to link the French Epidemiology and Information Network (REIN), a French national End-Stage Renal Disease registry, with the Système National des Données de Santé (SNDS), a French nationwide medico-administrative healthcare database. RESULTS: Among the 22,073 patients included in the REIN registry who started renal replacement therapy between 2014 and 2015 in France, 19,223 (87.1%) were matched with patients in the SNDS database. Comparison of matched and unmatched patients confirmed the absence of any major selection bias. Then, the record linkage was evaluated using the comorbidity status (diabetes). CONCLUSIONS: This fast and efficient method of record linkage with pseudonymized data and without unique and direct identifier might inspire other research teams. It also opens the path for new research on chronic kidney disease. BioMed Central 2020-01-28 /pmc/articles/PMC6988267/ /pubmed/31992233 http://dx.doi.org/10.1186/s12882-020-1692-4 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Technical Advance Raffray, Maxime Bayat, Sahar Lassalle, Mathilde Couchoud, Cécile Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title | Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title_full | Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title_fullStr | Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title_full_unstemmed | Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title_short | Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight |
title_sort | linking disease registries and nationwide healthcare administrative databases: the french renal epidemiology and information network (rein) insight |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988267/ https://www.ncbi.nlm.nih.gov/pubmed/31992233 http://dx.doi.org/10.1186/s12882-020-1692-4 |
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