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Rev Esp Salud Publica. 2018 Nov 19;92. pii: e201811082.

[Implementing a population-based rare diseases registry in Spain: the Navarre´s experience].

[Article in Spanish; Abstract available in Spanish from the publisher]

Author information

1
Sección del Observatorio de la Salud Comunitaria. Servicio de Promoción de la Salud Comunitaria. Instituto de Salud Pública y Laboral de Navarra. Pamplona. España.
2
Departamento de Ciencias de la Salud. Universidad Pública de Navarra. Pamplona. España.
3
Instituto de Investigación Sanitaria de Navarra (IdiSNA). Pamplona. España.
4
Centro de Investigación Biomédica En Red de Epidemiología y Salud Pública (CIBERESP). Madrid.España.
5
Servicio de Ciudadanía Sanitaria, Aseguramiento y Garantías. Dirección General de Salud de Gobierno de Navarra. Pamplona. España.
6
Servicio de Genética Médica. Complejo Hospitalario de Navarra. Pamplona. España.
7
Centro de Investigación Biomédica En Red de Epidemiología y Salud Pública (CIBERESP). Madrid. España.

Abstract

in English, Spanish

In 2012, the Spanish Rare Disease Registries Research Network (Spain-RDR) was consolidated with the aim of creating a Spanish population-based Rare Diseases Registry. In order to achieve this, each of the 17 Spanish Regions had to develop its own regional registry with a common agreed methodology. The Population-based Rare Disease Registry of Navarre was created in 2013 and, since then, its implementation is been carried out. Navarre assumed the agreed list within the Spanish Network, which included 934 codes of the International Classification of Diseases, 9th Revision, Clinical Modification. Initially, the main data source used to capture cases was the Assisted Morbidity Registry of Navarre, which includes the Minimum Basic Data Set of every regional hospital discharges (both public and private). Afterwards, new data sources were been added and ongoing validation studies of captured cases were been developed. Population-based rare diseases registries are fundamental for the study and quantification of this type of diseases since the classification and coding systems used in the current healthcare information systems are very nonspecific. The analysis and cross-referencing of data among multiple data sources is essential to maximize case detection capacity. Due to the low prevalence of these diseases, a high false positives rate among the detected cases greatly affects the estimation of epidemiological indicators, which makes it necessary to validate the cases by verifying the diagnoses.

KEYWORDS:

Epidemiology; Information systems; Prevalence; Rare diseases; Registries; Spain

PMID:
30442882
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