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IJERPH, Vol. 15, Pages 1644: Recommendations for Improving the Quality of Rare Disease Registries

03 Aug 2018

IJERPH, Vol. 15, Pages 1644: Recommendations for Improving the Quality of Rare Disease Registries

International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15081644

Authors:
Yllka Kodra
Jérôme Weinbach
Manuel Posada-de-la-Paz
Alessio Coi
S. Lydie Lemonnier
David van Enckevort
Marco Roos
Annika Jacobsen
Ronald Cornet
S. Faisal Ahmed
Virginie Bros-Facer
Veronica Popa
Marieke Van Meel
Daniel Renault
Rainald von Gizycki
Michele Santoro
Paul Landais
Paola Torreri
Claudio Carta
Deborah Mascalzoni
Sabina Gainotti
Estrella Lopez
Anna Ambrosini
Heimo Müller
Robert Reis
Fabrizio Bianchi
Yaffa R. Rubinstein
Hanns Lochmüller
Domenica Taruscio

Rare diseases (RD) patient registries are powerful instruments that help develop clinical research, facilitate the planning of appropriate clinical trials, improve patient care, and support healthcare management. They constitute a key information system that supports the activities of European Reference Networks (ERNs) on rare diseases. A rapid proliferation of RD registries has occurred during the last years and there is a need to develop guidance for the minimum requirements, recommendations and standards necessary to maintain a high-quality registry. In response to these heterogeneities, in the framework of RD-Connect, a European platform connecting databases, registries, biobanks and clinical bioinformatics for rare disease research, we report on a list of recommendations, developed by a group of experts, including members of patient organizations, to be used as a framework for improving the quality of RD registries. This list includes aspects of governance, Findable, Accessible, Interoperable and Reusable (FAIR) data and information, infrastructure, documentation, training, and quality audit. The list is intended to be used by established as well as new RD registries. Further work includes the development of a toolkit to enable continuous assessment and improvement of their organizational and data quality.

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