Architecture to Summarize Patient-Level Data Across Borders and Countries.

Area of Science:

• Biomedical Research
• Translational Medicine
• Health Informatics

Background:

• Biomedical research requires seamless information flow between basic science and clinical practice for patient benefit.
• Healthcare data is fragmented across diverse databases, institutions, and locations, hindering efficient research.
• Existing solutions for data sharing often face limitations due to privacy concerns, creating data silos.

Purpose of the Study:

• To present a new ecosystem designed to connect owners of dispersed databases with researchers.
• To address the challenge of fragmented healthcare information systems.
• To facilitate the identification of relevant data for specific research questions.

Main Methods:

• Developed a novel ecosystem for connecting database owners and researchers.
• Introduced a common 'fingerprint' to extensively characterize dispersed databases.
• Fingerprint contains aggregated, high-level information for population-level queries.

Main Results:

• The common fingerprint allows for the quick identification of databases relevant to research questions.
• This approach facilitates the connection of disparate data sources.
• The system is being utilized within the European Medical Information Framework (EMIF) project.

Conclusions:

• The developed ecosystem and data fingerprinting method offer a promising solution for overcoming healthcare data fragmentation.
• This approach supports translational medicine by improving access to diverse data.
• The system enhances the ability to identify and utilize relevant data for advancing patient health.