José Martín Solórzano González | Scientific Coordinator
Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol (IDIAP )
Martín Solórzano is a Mexican medical doctor and public health expert with extensive experience leading health programs in Mexico and Spain, focusing on vulnerable populations. A former Mexican Youth Delegate to the United Nations, he has collaborated with international organizations on public health and social development policies. He holds a Master’s in Public Health and Health Management from the University of Valencia and is a Ph.D. candidate in Epidemiology at the University Medical Center Utrecht. Martín is currently a scientific coordinator at the Institut Universitari d’Investigació en Atenció Primària (IDIAP Jordi Gol) in Barcelona. He oversees projects on vaccine Adverse Events of Special Interest (AESIs) and has contributed to global initiatives such as VAC4EU and the Global Vaccine Data Network. His expertise also extends to health evaluation and the implementation of innovative healthcare initiatives.
Appearances:
Main Congress Day 2 - 23rd April @ 12:40
Integrating SIDIAP Health Database into the ConCEPTION Common Data Model: Advancing Vaccine Safety Studies within the VAC4EU Consortium
This session explores the integration of SIDIAP (Sistema de Información para el Desarrollo de la Investigación en Atención Primaria), a Spanish health database, into the ConCEPTION Common Data Model (CDM). This initiative represents a significant advancement in vaccine safety research within the VAC4EU (Vaccine Monitoring Collaboration for Europe) Consortium. Managed by IDIAP Jordi Gol, SIDIAP contains comprehensive primary care data from over 5.8 million individuals in Catalonia, providing a robust platform for pharmacoepidemiologic investigations. Aligning SIDIAP with the ConCEPTION CDM standardizes its data, enabling interoperable, scalable, and reproducible research across diverse healthcare systems. This alignment enhances the capacity to detect and analyze vaccine-related adverse events effectively.
The presentation will detail the technical steps involved in this transformation, including data mapping, harmonization, validation, and the use of privacy-preserving Extract, Transform, Load (ETL) methodologies. It will also present case studies, such as analyses of adverse events following vaccination, to demonstrate the practical benefits of harmonized data for vaccine safety monitoring. This integration underscores the importance of standardized data models in bridging localized healthcare datasets with global research frameworks, supporting evidence-based public health decision-making, and fostering multinational collaboration in pharmacovigilance and pharmaepidemiology.
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