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Health data hubs: an analysis of existing data governance features for research
BACKGROUND: Digital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use of healthcare records in the health research field. Likewise, due to the ethical and legal constraints for using sensitive data, understanding how h...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332005/ https://www.ncbi.nlm.nih.gov/pubmed/37430347 http://dx.doi.org/10.1186/s12961-023-01026-1 |
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author | Alvarez-Romero, Celia Martínez-García, Alicia Bernabeu-Wittel, Máximo Parra-Calderón, Carlos Luis |
author_facet | Alvarez-Romero, Celia Martínez-García, Alicia Bernabeu-Wittel, Máximo Parra-Calderón, Carlos Luis |
author_sort | Alvarez-Romero, Celia |
collection | PubMed |
description | BACKGROUND: Digital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use of healthcare records in the health research field. Likewise, due to the ethical and legal constraints for using sensitive data, understanding how health data are managed by dedicated infrastructures called data hubs is essential to facilitating data sharing and reuse. METHODS: To capture the different data governance behind health data hubs across Europe, a survey focused on analysing the feasibility of linking individual-level data between data collections and the generation of health data governance patterns was carried out. The target audience of this study was national, European, and global data hubs. In total, the designed survey was sent to a representative list of 99 health data hubs in January 2022. RESULTS: In total, 41 survey responses received until June 2022 were analysed. Stratification methods were performed to cover the different levels of granularity identified in some data hubs’ characteristics. Firstly, a general pattern of data governance for data hubs was defined. Afterward, specific profiles were defined, generating specific data governance patterns through the stratifications in terms of the kind of organization (centralized versus decentralized) and role (data controller or data processor) of the health data hub respondents. CONCLUSIONS: The analysis of the responses from health data hub respondents across Europe provided a list of the most frequent aspects, which concluded with a set of specific best practices on data management and governance, taking into account the constraints of sensitive data. In summary, a data hub should work in a centralized way, providing a Data Processing Agreement and a formal procedure to identify data providers, as well as data quality control, data integrity and anonymization methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12961-023-01026-1. |
format | Online Article Text |
id | pubmed-10332005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103320052023-07-11 Health data hubs: an analysis of existing data governance features for research Alvarez-Romero, Celia Martínez-García, Alicia Bernabeu-Wittel, Máximo Parra-Calderón, Carlos Luis Health Res Policy Syst Research BACKGROUND: Digital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use of healthcare records in the health research field. Likewise, due to the ethical and legal constraints for using sensitive data, understanding how health data are managed by dedicated infrastructures called data hubs is essential to facilitating data sharing and reuse. METHODS: To capture the different data governance behind health data hubs across Europe, a survey focused on analysing the feasibility of linking individual-level data between data collections and the generation of health data governance patterns was carried out. The target audience of this study was national, European, and global data hubs. In total, the designed survey was sent to a representative list of 99 health data hubs in January 2022. RESULTS: In total, 41 survey responses received until June 2022 were analysed. Stratification methods were performed to cover the different levels of granularity identified in some data hubs’ characteristics. Firstly, a general pattern of data governance for data hubs was defined. Afterward, specific profiles were defined, generating specific data governance patterns through the stratifications in terms of the kind of organization (centralized versus decentralized) and role (data controller or data processor) of the health data hub respondents. CONCLUSIONS: The analysis of the responses from health data hub respondents across Europe provided a list of the most frequent aspects, which concluded with a set of specific best practices on data management and governance, taking into account the constraints of sensitive data. In summary, a data hub should work in a centralized way, providing a Data Processing Agreement and a formal procedure to identify data providers, as well as data quality control, data integrity and anonymization methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12961-023-01026-1. BioMed Central 2023-07-10 /pmc/articles/PMC10332005/ /pubmed/37430347 http://dx.doi.org/10.1186/s12961-023-01026-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Alvarez-Romero, Celia Martínez-García, Alicia Bernabeu-Wittel, Máximo Parra-Calderón, Carlos Luis Health data hubs: an analysis of existing data governance features for research |
title | Health data hubs: an analysis of existing data governance features for research |
title_full | Health data hubs: an analysis of existing data governance features for research |
title_fullStr | Health data hubs: an analysis of existing data governance features for research |
title_full_unstemmed | Health data hubs: an analysis of existing data governance features for research |
title_short | Health data hubs: an analysis of existing data governance features for research |
title_sort | health data hubs: an analysis of existing data governance features for research |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332005/ https://www.ncbi.nlm.nih.gov/pubmed/37430347 http://dx.doi.org/10.1186/s12961-023-01026-1 |
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