We aim to develop 1° data collection procedures and tools to create data that is F.A.I.R. (=findable, accessible, interoperable and re-usable), 2° IT solutions to allow (temporarily) pooling and linking of F.A.I.R dataset, 3° statistical methods to define minimal requirements for datasets and 4° new analytical methods for optimal mining of connected and pooled F.A.I.R datasets. Two pilot studies are performed. Pilot study 1 develops F.A.I.R. data collection procedures for a local consortium involved in care, rehabilitation and research and connects the datasets involved. Pilot study 2 develops a statistical method to evaluate the relative importance of prognostic risk factors.
For pilot study 1, we have the unique opportunity to collaborate with the healtdata.be platform. Healthdata is an initiative of the Belgian Scientific Institute of public health WIV-ISP to simplify the registration and storage of health care data in Belgium. Healthdata and the MS DataConnect consortium will collaborate to set up a multidisciplinary MS register combining information collected by care givers, patients and researchers.
A collaboration with healthdata enables us to create F.A.I.R. data collection tools and procedures for MS relevant data. The key principle of healthdata is the “only once”-principle referring to 1° data capture from primary (operational) sources of health care actors and 2° re-use of previously collected data. The generic HD architecture is approved by the Sectoral Committee of Health (privacy commission) and the e-health platform, guaranteeing privacy and covering ethical concerns.
The figure below provides a schematic overview of the project plan.