The project, with a duration of three years, gathers 17 partners from 11 countries for the reusability of information to improve research and care of complex chronic patients.
The Institute of Biomedicine of Seville hosts the kick-off meeting and 1st General Assembly of the European research and innovation project FAIR4Health, which is coordinated by the Technological Innovation Group and the Internal Medicine Unit of the Virgen del Rocío University Hospital with the aim of developing methods to reuse and share information from health research. Researchers from the 11 partner countries of the consortium are invited to this unavoidable appointment for the formal start of the project in which there will be a pooling of tasks to be developed over the next 3 years.
The methods for analysing heterogeneous information from the different data collections in common will be tackled in an attempt to discover the factors that trigger the appearance and relationship of diseases, as well as predicting the risk of re-admission for complex chronic patients. And all this by applying the FAIR principles to the data, which are Findable, Accessible, Interoperable and Reusable.
The conferences, which take place between 28 and 29 January, will serve to review the protocols, economic impact and working tools that can be used during the three-year duration of this project. The initiative joins forces to facilitate and encourage the European Union community of health researchers to share and reuse their datasets derived from publicly funded research initiatives, by demonstrating the impact that such a strategy will have on both health outcomes and health research.
The study, which officially began on 1 December last year, is coordinated by the Andalusian Health Service (SAS) and has 17 partners from 11 countries (Spain, Portugal, Italy, United Kingdom, Germany, Switzerland, Austria, Netherlands, Belgium, Serbia and Turkey). On the other hand, the consortium is composed of 6 health research organizations, 2 internationally recognized universities as experts in data management, 2 universities and 2 institutes with extensive experience in medical informatics, and 5 business actors.
FAIR4Health will apply privacy-preserving distributed data mining techniques to preserve the privacy of the shared data sets and thus be able to develop and pilot two use cases. The first of these will support the discovery of the triggers of disease onset and patterns of disease association in comorbid patients. The second case will be to create a service to predict the risk of readmission in 30 days in complex chronic patients.
The results of this project will serve to guide the future strategy of the European Commission in relation to the management of data from publicly funded research.