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Genia supports learning networks engaged in co-production of health

Genia is a diagnosis independent platform that integrates with healthcare IT environments, such as Electronic Health Records or REDCap databases for use in quality improvement and research. The platform supports learning networks with patient-controlled information flows.

In the last decade, advances in science, healthcare and information technology have made it possible for people with severe and life shortening complex chronic conditions to look forward to long and fully lived lives, with self-care as the new acknowledged principal source of care and often with healthcare as a lifelong partner. With these advances comes a need for a global movement of co-production of health, defined as interdependent work of all stakeholders to design, deliver and evaluate new relationships and actions that can contribute to a radical change in the health of individuals and populations. By using shared resources and learning together.

Genia supports patient-controlled information flows allowing patients and providers to set health goals, make shared decisions and evaluate results. The platform also strengthens quality improvement collaboratives for clinical programs, facilitates support networks for patients and families, patient-centered registries and research efforts.


Genia's model provides researchers and clinicians with an important resources when they develop and adapt their own learning network systems together with patients and families. Researchers at the Dartmouth Institute for Health Policy and Clinical Practice in the US and at the Medical Management Centre at the Medical Management Centre at Karolinska Institutet in Sweden have designed the registry-based learning networks model that Genia builds on.

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Patient-centered self-care kits available in the Genia app. 

Interoperable exchange of personal health information to electronic health records (eg Epic) and research databases (eg REDCap).

Implementation of patient-controlled information flows in self-care and clinical work flows.

Support to quality improvement of single or multiple site research projects in the learning network.

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