Presentation

Jean-François Ethier is a clinician scientist and professor in the Department of Medicine and the Department of Computer Science at the Université de Sherbrooke. He also practices as an incumbent physician in the Internal Medicine Department of the Centre hospitalier universitaire de Sherbrooke (CHUS).

Pr Ethier leads the technological development the Health Data Research Network and co-leads the Groupe de recherche interdisciplinaire en informatique de la santé. His research program is also deployed, in collaboration with French colleagues, through his work as an associate researcher at INSERM. This collaboration has led to the creation of the French-Canadian network Ensemble, for rare diseases, which he co-leads with Pr Anita Burgun.

Jean-François Ethier’s work explores the issues surrounding learning health systems (LHS). His research focuses more specifically on the development of safe, ethical and effective methods for using health data in care, research and knowledge transfer contexts, through decision support and reflective practice tools such as the ReflexD tool.

Positioning the citizen at the center of his or her data requires radical changes in data access processes and in the ways different sources are aligned to fully represent the health trajectories of patients, both within the health system and in everyday life.

The development of biomedical ontologies is an essential component of this work. These automatable knowledge models allow the representation of knowledge in an unambiguous and coherent way, which allows the interlinking of different data models and heterogeneous sources for a unified access.

Jean-François Ethier participated to the TRANSFoRm project in Europe (a project funded by the European Community under the FP7 program). TRANSFoRm has created the first prototype of a LHS supporting primary health care and services. This work served as the foundation of the Plateforme apprenante pour recherche en santé et les services sociaux (PARS3), a decentralized and distributed system, offered under an open license, that allows for the secure use of data (including distributed analysis) without requiring bulk data pooling.