Introduction

The current model of medical knowledge production, transfer, and application suffers from serious shortcomings. Learning health systems (LHS) have recently emerged as a potential solution—systems in which health information generated from patients is continuously analyzed to improve knowledge that will be transferred to patient care.
Method

Various approaches of data integration already exist and could be considered for the implementation of a LHS. We discuss what are the possible informatics approaches to address the functional requirements of LHS, in the specific context of primary care, and present the experience and lessons learned from the TRANSFoRm project.
Result

Implemented in 4 countries around 5 systems, TRANSFoRm is based on a local‐as‐view data mediation approach integrating the structural and terminological models in the same framework. It clearly demonstrated that it has the potential to address the requirements for a LHS in primary care, by dealing with data fragmented across multiple points of service. Also, it has the potential to support the generation of hypotheses from the context of clinical care, retrospective and prospective research, and decision support systems that improve the relevance of medical decisions.
Conclusion

The LHS approach embodies a shift from an institution‐centered to a patient‐centered perspective in knowledge production and transfer and can address important challenges in the primary care setting.