Expected Outcome: This topic aims at supporting activities that are enabling or contributing
to one or several expected impacts of destination 5 “Unlocking the full potential of new tools,
technologies and digital solutions for a healthy society”. To that end, proposals under this
topic should aim for delivering results that are directed, tailored and contributing to all of the
following expected outcomes:
Novel solutions improve quality, ensure interoperability and enable re-use of health data,
data analytics and metadata from different repositories across countries by health
professionals, researchers and health authorities, in compliance with FAIR data
management principles as well as national and EU legal and ethical requirements (in
particular with regard to personal data protection).
Health professionals, researchers and health authorities make effective use of tools
enabling them to exploit unstructured and heterogeneous data from different sources to
improve the delivery of care and advance health research.
Increased use and valorisation of health data by patients, researchers and clinicians
thanks to better data portability due to the standardization of meta knowledge (meta data,
ontologies and reference repositories) and clinical data, especially health data coming
from different clinical services and sites, and/or from multiple countries.
Health care professionals use more efficient and cost-effective health care procedures
and workflows that contribute to improved disease prevention, early detection/diagnosis
and more effective treatment.
Scope: Health data exists in many forms and multiple fragmented repositories; there is still
significant room for improvement in the way both structured and unstructured health data is
stored, analysed and interpreted. Sharing and analysing data from multiple countries in a safe
and legally compliant manner (in particular with regard to personal data protection) remains a
challenge. Powerful analytic tools are already helping providers to use structured data in
increasingly impactful ways. On the other hand, the heterogeneity, diversity of sources,
quality of data and various representations of unstructured data in health care increase the
number of challenges as compared to structured data.
Advances in AI and machine learning, however, have the potential to transform the way
clinicians, providers and researchers use unstructured data. Furthermore, developing data
interoperability standards, trust and harmonization of GDPR’s interpretation across the EU for
the sharing and processing of personal health data will support establishing a sound health
data culture in view of the European Health Data Space.
Proposals should address all of the following aspects:
Developing robust novel solutions compliant with legal requirements (in particular
concerning personal data protection) that will improve the quality, interoperability,
machine-readability and re-use of health data and metadata in compliance with FAIR
data management principles, making these data more accessible to clinicians, researchers
and citizens. The focus should be on data in electronic health records (EHRs) and/or
patient registries, taking into account the Commission Recommendation on a European
Electronic Health Record exchange format.
Developing innovative natural language processing tools, including computational
semantics, ontologies, text mining, associated machine learning and deep learning, to
improve accessibility, interoperability, translation, transcription, and analysis of health
data (e.g. to predict risks). Tools should extract health information from unstructured
data in different clinical and medical sources, and bring that data into EHRs/patient
registries in a structured form. The innovative solutions should also address missing data
in EHRs and/or patient registries and their related metadata, to reduce bias and improve
the quality of conclusions.Developing and piloting AI-powered virtual assistants that will utilise the tools and
solutions developed (as mentioned above) in order to demonstrate improved usability of
health data for end-users.
Proposals are expected to build on and contribute to existing European and international data
standards, specifications and schemas for health data. The use of open standards should be
considered and interactions with relevant ongoing research infrastructure efforts are
encouraged. Applicants should focus on health data coming from a number of EU Member
States and EEA countries, constituting as much as possible a representative sample of the
European healthcare landscape, so as to contribute to the work on the creation of the
European Health Data Space.
To guarantee their adoption, the developed solutions should be quick and easy to use by
researchers and clinicians. Therefore active involvement of end-users from the onset is
encouraged. In particular, patient advocacy groups and citizens should be involved to ensure
adequate consideration of diverse patient needs, with respect to their gender, ethnicity, age,
ability, and socio-economic background, to underpin acceptance by patients and other data
subjects. SMEs participation is also encouraged.
The proposals should duly take into account requirements stipulated in the relevant European
regulations (Data protection, in vitro diagnostics and medical devices) and must meet
appropriate ethical standards.