Problem to be solved
Integrated, high-quality personal health data (PHD) represents a potential wealth of knowledge for health care systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale across institutions, at national and EU level.
The European Commission has set itself an ambitious goal: by 2030 citizens shall have full possession of their data, including health data, and have the necessary skills for making competent decisions about that data. However, reuse of personal health care data is particularly difficult as each individual’s data is typically scattered across different clinics, surgeries or hospitals and, increasingly, across providers of medical devices and personal health apps. In addition, much information is still in paper and in narrative form. Despite attempts to streamline and modernise health data management systems, seamless access and use of high-quality and integrated personal health data remains challenging for individual patients, health care providers, researchers, public health authorities and national insurances across Europe.
Additionally, the data curation and publishing process of legacy data keeps being costly, time-consuming and manageable only by experts. As a consequence, much of the available personal health data is neither curated nor reusable for advanced algorithms supporting preventive and personalised medicine and clinical research; an unfortunate situation considering the wealth of information personal health data holds for entire healthcare systems.
AIDAVA sets out for a quantum leap in automating personal health data curation and publishing by orchestrating multiple Artificial Intelligence (AI)-based solutions.