METHODS article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1630351
This article is part of the Research TopicElectronic Health Records in Emergency Medicine: From Accountability to OpportunityView all 5 articles
Ethical and Secure Evidence Generation from Regionwide Clinical Data through a Collaborative Environment for Advancing Predictive Care
Provisionally accepted
Dolores Muñoyerro-Muñiz1Roman Villegas1Víctor De La Oliva2Alberto Esteban-Medina2Patricia Fernández Del Valle2Ana Sánchez2M. Belen Susin2Isidoro Gutierrez-Alvarez2Marta Reboredo2
Laura Alejos1
Carlos Loucera2
Joaquin Dopazo2*- 1Subdireccion Tecnica Asesora de Gestion de la Informacion. Servicio Andaluz de Salud., Sevilla, Spain
- 2Bioinformatics, Andalusian Public Foundation for Progress and Health, Junta de Andalucía, Sevilla, Spain
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Ensuring data protection is a major challenge in clinical research involving sensitive patient information. However, secure processing environments (SPEs) enable the ethical and compliant secondary use of real-world data (RWD) for evidence generation. This study presents a collaborative infrastructure integrating a comprehensive Health Population Database (BPS) with a legal and computational framework to facilitate secure, large-scale clinical studies.The Andalusian Platform for Medical Evidence Generation is an SPE embedded within the Andalusian healthcare network, leveraging RWD from over 15 million patients from the BPS. It supports diverse studies, including treatment efficacy, survival analyses, and predictive modelling, while ensuring alignment with the General Data Protection Regulation (GDPR) and proactively designed to meet forthcoming European Health Data Space (EHDS) requirements. Data are processed within a secure ecosystem, preventing unauthorized access and enabling legally compliant research collaborations.By combining clinical RWD with a robust ethical and legal framework, we present a scalable model for secure, data-driven region-level healthcare innovation. The platform supports cost-effective predictive models, particularly relevant for aging populations, and establishes a blueprint for regional and international adaptation. This approach strengthens the role of healthcare systems in both knowledge generation and sustainable economic growth, ensuring that patient data is leveraged for scientific and societal benefit.
Keywords: Real-world data, Electronic Health Records, predictive medicine, secure processing environment, artificial intelligence, Data privacy
Received: 17 May 2025; Accepted: 21 Jul 2025.
Copyright: © 2025 Muñoyerro-Muñiz, Villegas, De La Oliva, Esteban-Medina, Fernández Del Valle, Sánchez, Susin, Gutierrez-Alvarez, Reboredo, Alejos, Loucera and Dopazo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Joaquin Dopazo, Bioinformatics, Andalusian Public Foundation for Progress and Health, Junta de Andalucía, Sevilla, 46012, Spain
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