Data Quality in Rare Diseases Registries
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Updated: Feb 17, 2026

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
Published on: August 15, 2019
Yllka Kodra1, Manuel Posada de la Paz2, Alessio Coi3
1Centro Nazionale Malattie Rare, Istituto Superiore di Sanità, Viale Regina Elena 299, CAP, 00161, Rome, Italy. yllka.kodra@iss.it.
Abstract:
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.
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