OHSIRIS: A Federated Data Space for Interoperable Biomedical Research.

Area of Science:

• Health Informatics
• Biomedical Research
• Data Governance

Background:

• Real-world health data (RWD) holds immense potential for biomedical research.
• Current data sharing practices often face challenges in security, scalability, and regulatory compliance.
• Federated data architectures offer a solution for privacy-preserving data access.

Purpose of the Study:

• To implement a federated and interoperable data space (OHSIRIS) for secure and scalable reuse of RWD.
• To establish a protocol-driven approach for translating research questions into standardized analytical workflows.
• To ensure compliance with data protection regulations while enabling collaborative research.

Main Methods:

• Utilized a federated architecture where data remains at the source, with only aggregated results shared.
• Employed the OMOP Common Data Model for data standardization.
• Translated research questions into standardized analytical workflows executed across multiple institutions.
• Validated the framework through three distinct use cases: lung cancer risk factors, RSV immunization cost-effectiveness, and antimicrobial use monitoring.

Main Results:

• Demonstrated the feasibility of executing reproducible and comparable analyses across multiple sites.
• Successfully applied standardized methods and outputs for diverse research questions.
• Validated the OHSIRIS framework's effectiveness in a multicenter setting.

Conclusions:

• OHSIRIS provides a practical implementation of a governed health data space.
• The project supports interoperable, privacy-preserving, and collaborative biomedical research.
• Aligns with European initiatives for advancing health data utilization.