Data quality in rare diseases registries

Kodra, Y., Posada de la Paz, M., Coi, A., Santoro, M., Bianchi, F., Ahmed, F. , Rubinstein, Y. R., Weinbach, J. and Taruscio, D. (2017) Data quality in rare diseases registries. In: de la Paz, M. P., Taruscio, D. and Groft, S. C. (eds.) Rare Diseases Epidemiology: Update and Overview. Series: Advances in experimental medicine and biology (1031). Springer: Cham, pp. 149-164. ISBN 9783319671420 (doi: 10.1007/978-3-319-67144-4_8)

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In the field of rare diseases, registries are considered power tool to develop clinical research, to facilitate the planning of appropriate clinical trials, to improve patient care and healthcare planning. Therefore high quality data of rare diseases registries is considered to be one of the most important element in the establishment and maintenance of a registry. Data quality can be defined as the totality of features and characteristics of data set that bear on its ability to satisfy the needs that result from the intended use of the data. In the context of registries, the 'product' is data, and quality refers to data quality, meaning that the data coming into the registry have been validated, and ready for use for analysis and research. Determining the quality of data is possible through data assessment against a number of dimensions: completeness, validity; coherence and comparability; accessibility; usefulness; timeliness; prevention of duplicate records. Many others factors may influence the quality of a registry: development of standardized Case Report Form and security/safety controls of informatics infrastructure. With the growing number of rare diseases registries being established, there is a need to develop a quality validation process to evaluate the quality of each registry. A clear description of the registry is the first step when assessing data quality or the registry evaluation system. Here we report a template as a guide for helping registry owners to describe their registry.

Item Type:Book Sections
Keywords:Clinical research registry, data quality indicators, public health registry, quality assurance plan, rare diseases registries, validity.
Glasgow Author(s) Enlighten ID:Ahmed, Professor Syed Faisal
Authors: Kodra, Y., Posada de la Paz, M., Coi, A., Santoro, M., Bianchi, F., Ahmed, F., Rubinstein, Y. R., Weinbach, J., and Taruscio, D.
College/School:College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
Journal Name:Advances in experimental medicine and biology

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