JMIR research protocols · 2026
HealthData@MAD-R&I: Protocol for Design and Development of a Regional Health Data Infrastructure to Enable Secondary Use of Health Data in Research and Innovation.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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León-García Montserrat, Álvarez-Pérez Sergio, Gesto-Gómez Janire, Urbano-Molina Clara, Soto-Díaz Sonia, Cárdenas-Valladolid Juan, Rodríguez-Rodríguez Luis, Díaz-Holgado Antonio, Del Cura-González Isabel, De La Cruz-Bertolo Javier, García-Barrio Noelia, Cruz-Bermúdez Juan Luis, García-Fernández Cristina, Rodríguez-Antolín Carlos, García-Aldars Laila, Moreda-Sánchez Elsa María, Roldán López Álvaro, Veganzones Alonso-Cortés José María, Gonzalez Gonzalez Ana Isabel, Salinero-Fort Miguel A, HealthData@MAD-R&I Working Group
Аннотация
BACKGROUND: The exponential growth of electronic health records (EHRs), together with the recent entry into force of the European Health Data Space (EHDS) Regulation, highlights the urgent need for secure, interoperable environments that support the secondary use of health data. In response, HealthData@MAD-R&I emerges as a pioneering initiative in Madrid (Spain), aligned with the EHDS strategy and the European Commission's vision for data sovereignty and trustworthy data reuse.
OBJECTIVE: This study aims to design and implement HealthData@MAD-R&I, a regional health data space that enables responsible access to high-quality health data to support clinical research, health care innovation, and evidence-informed decision-making.
METHODS: HealthData@MAD-R&I aims to establish an ethically governed, scalable, and sustainable health data space. The project adopts a structured, iterative methodology based on the Data Management Association (DAMA) framework. and it is organized into 9 work packages across three thematic areas: (1) project management and sustainability, (2) governance and technological infrastructure, and (3) validation through 4 real-world use cases. The technical architecture adopts a hybrid federated model built with open-source components, and data harmonization is performed using the Observational Medical Outcomes Partnership (OMOP) common data model to ensure semantic and syntactic interoperability. Artificial intelligence, machine learning, natural language processing, and privacy-preserving techniques are applied for data curation and secure access.
RESULTS: As of November 2025, the main achievements include (1) the development of a data governance model that articulates principles of quality, transparency, and regulatory compliance; (2) the design of a secure, interoperable technological architecture with federated capabilities based on international standards (DAMA and OMOP); and (3) the implementation of 4 use cases-optimizing rheumatology referrals, characterizing care pathways for long-term survivors of breast cancer, predicting unplanned hospitalizations, and evaluating the effectiveness of statins in older adults-to validate the data space while addressing diverse clinical and policy challenges. Together, these components demonstrate the potential of regional data spaces to support evidence-based clinical practice and public policy.
CONCLUSIONS: HealthData@MAD-R&I seeks to strengthen Madrid's role in digital health innovation and contribute to the broader European health data ecosystem by promoting interoperable, privacy-compliant secondary use of health data. The project's evaluation framework includes indicators for data quality, research outputs, and health care system impact.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/82815.
OBJECTIVE: This study aims to design and implement HealthData@MAD-R&I, a regional health data space that enables responsible access to high-quality health data to support clinical research, health care innovation, and evidence-informed decision-making.
METHODS: HealthData@MAD-R&I aims to establish an ethically governed, scalable, and sustainable health data space. The project adopts a structured, iterative methodology based on the Data Management Association (DAMA) framework. and it is organized into 9 work packages across three thematic areas: (1) project management and sustainability, (2) governance and technological infrastructure, and (3) validation through 4 real-world use cases. The technical architecture adopts a hybrid federated model built with open-source components, and data harmonization is performed using the Observational Medical Outcomes Partnership (OMOP) common data model to ensure semantic and syntactic interoperability. Artificial intelligence, machine learning, natural language processing, and privacy-preserving techniques are applied for data curation and secure access.
RESULTS: As of November 2025, the main achievements include (1) the development of a data governance model that articulates principles of quality, transparency, and regulatory compliance; (2) the design of a secure, interoperable technological architecture with federated capabilities based on international standards (DAMA and OMOP); and (3) the implementation of 4 use cases-optimizing rheumatology referrals, characterizing care pathways for long-term survivors of breast cancer, predicting unplanned hospitalizations, and evaluating the effectiveness of statins in older adults-to validate the data space while addressing diverse clinical and policy challenges. Together, these components demonstrate the potential of regional data spaces to support evidence-based clinical practice and public policy.
CONCLUSIONS: HealthData@MAD-R&I seeks to strengthen Madrid's role in digital health innovation and contribute to the broader European health data ecosystem by promoting interoperable, privacy-compliant secondary use of health data. The project's evaluation framework includes indicators for data quality, research outputs, and health care system impact.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/82815.