Value-Based and Data-Driven Healthcare and Prevention: advancing a citizen-centered thrusted dataspace to reduce the risk of metabolic diseases

Challenges our research addresses:

- standardization of personal lifestyle and quality of life (QoL) data for applications in preventive healthcare - linking QoL data with clinical data - addressing issues of data interoperability (with SOLID technology) enhancing early diagnostics and precise and personalized therapies. This can be AI driven.
- re-use of health data for R&D and pharma (secondary use), population health management - decentralisation (data space components)- implementation of EHDS and the role of AI
- building an ecosystem that actively involves citizens in research and innovation - citizen empowerment
- data solidarity: QoL data as an instrument for community building (caring neighbourhoods)
- practical implementation of ELSA (ethical, legal, societal aspects) when developing new digital technologies in preventive care