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Data Quality in Rare Diseases Registries.
Kodra, Yllka; Posada de la Paz, Manuel; Coi, Alessio; Santoro, Michele; Bianchi, Fabrizio; Ahmed, Faisal; Rubinstein, Yaffa R; Weinbach, Jérôme; Taruscio, Domenica.
Afiliación
  • Kodra Y; Centro Nazionale Malattie Rare, Istituto Superiore di Sanità, Viale Regina Elena 299, CAP, 00161, Rome, Italy. yllka.kodra@iss.it.
  • Posada de la Paz M; RDR and CIBERER, Instituto de Salud Carlos III, Madrid, Spain.
  • Coi A; Institute of Clinical Physiology, National Research Council, Pisa, Italy.
  • Santoro M; Institute of Clinical Physiology, National Research Council, Pisa, Italy.
  • Bianchi F; Institute of Clinical Physiology, National Research Council, Pisa, Italy.
  • Ahmed F; FRCPCH Samson Gemmell Chair of Child Health, Consultant in Paediatric Endocrinology Royal Hospital for Children, Glasgow School of Medicine, University of Glasgow, Glasgow, Scotland, UK.
  • Rubinstein YR; National Information Center of Health Services Research & Health Care Technology, National Library of Medicine/National Institute of Health, Bethesda, MD, USA.
  • Weinbach J; French National Institute of Health and Medical Research, RaDiCo - Inserm UMR S 933, Paris, France.
  • Taruscio D; Centro Nazionale Malattie Rare, Istituto Superiore di Sanità, Viale Regina Elena 299, CAP, 00161, Rome, Italy.
Adv Exp Med Biol ; 1031: 149-164, 2017.
Article en En | MEDLINE | ID: mdl-29214570
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Sistema de Registros / Bases de Datos Factuales / Enfermedades Raras / Investigación Biomédica / Exactitud de los Datos / Interoperabilidad de la Información en Salud Tipo de estudio: Diagnostic_studies / Guideline Límite: Humans Idioma: En Revista: Adv Exp Med Biol Año: 2017 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Sistema de Registros / Bases de Datos Factuales / Enfermedades Raras / Investigación Biomédica / Exactitud de los Datos / Interoperabilidad de la Información en Salud Tipo de estudio: Diagnostic_studies / Guideline Límite: Humans Idioma: En Revista: Adv Exp Med Biol Año: 2017 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos