Affiliations: [a] Groupe de Recherche Interdisciplinaire sur les Maladies Neuromusculaires (GRIMN), Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay-Lac-Saint-Jean, Saguenay, Québec, Canada
| [b]
Centre de Recherche Charles-Le Moyne-Saguenay-Lac-Saint-Jean sur les Innovations en Santé, Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Québec, Canada
| [c]
Center for Interdisciplinary Research in Rehabilitation and Social Integration, Institut de Réadaptation en Déficience Physique de Québec, Québec, QC, Canada
| [d] Département de Réadaptation, Faculté de Médecine, Université Laval, Québec, QC, Canada
Correspondence:
[*]
Correspondence to: Cynthia Gagnon, Centre de recherche Charles-Le-Moyne-Saguenay-Lac-St-Jean sur les innovations en santé, Université de Sherbrooke, Groupe de recherche interdisciplinaire sur les maladies neuromusculaires, Clinique des maladies neuromusculaires, CIUSSS Saguenay-Lac-St-Jean. 2230 de l’Hôpital PO box 1200. Jonquière, G7X 7X2, QC, Canada. Tel.: +1 418 695 7700/Ext. 2756; E-mail: [email protected].
Abstract: Rare diseases bring on a heavy health, social and economic burden that impacts patients’ lives and puts pressure on the healthcare system. Furthermore, they are often associated with limited published studies to inform multidisciplinary clinical practice thus limiting evidence-based practice. Moreover, the development of knowledge translation products including clinical care guidelines are often very challenging based on the current available methodological frameworks relying mostly on critical appraisal of the published research evidence where randomized clinical trial design is considered as the gold standard. To overcome this barrier, we proposed the Rare Knowledge Mining Methodological Framework (RKMMF). The RKMMF is one possible answer to improve the development of knowledge translation products for rare diseases. This framework includes other sources of evidence including registry information and qualitative studies and the involvement of expert patients. This article documents the RKMMF structure and its application is exemplified through knowledge translation products developed for a neuromuscular population.
