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Desiderata for discoverability and FAIR adoption of health data hubs.
Alvarez-Romero, Celia; Bernabeu-Wittel, Máximo; Luis Parra-Calderón, Carlos; Rodríguez Mejías, Silvia; Martínez-García, Alicia.
Afiliación
  • Alvarez-Romero C; Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain. Electronic address: celia.alvarez@juntadeandalucia.es.
  • Bernabeu-Wittel M; Internal Medicine Department, Virgen del Rocío University Hospital, Faculty of Medicine, University of Seville, Seville, Spain.
  • Luis Parra-Calderón C; Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.
  • Rodríguez Mejías S; Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.
  • Martínez-García A; Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.
J Biomed Inform ; 157: 104700, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39079607
ABSTRACT

BACKGROUND:

The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens.

OBJECTIVE:

This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best. practices for new data hubs joining the HRIC ecosystem. In this line, the compliance of health data hubs with FAIR principles and data discovery were assessed, and a set of best practices for health data hubs was concluded.

METHODS:

A survey was conducted in January 2022, involving 99 representative health data hubs from multiple countries, and 42 responses were obtained in June 2022. Stratification methods were employed to cover different levels of granularity. The survey data was analysed to assess compliance with FAIR and data discovery principles. The study started with a general analysis of survey responses, followed by the creation of specific profiles based on three categories organization type, function, and level of data aggregation.

RESULTS:

The study produced specific best practices for data hubs regarding the adoption of FAIR principles and data discoverability. It also provided an overview of the survey study and specific profiles derived from category analysis, considering different types of data hubs.

CONCLUSIONS:

The study concluded that a significant number of health data hubs in Europe did not fully comply with FAIR and data discovery principles. However, the study identified specific best practices that can guide new data hubs in adhering to these principles. The study highlighted the importance of aligning health data management mechanisms with FAIR principles to enhance interoperability and reusability in the future HRIC.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nube Computacional Límite: Humans País/Región como asunto: Europa Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nube Computacional Límite: Humans País/Región como asunto: Europa Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos