Elsevier

Public Health

Volume 129, Issue 3, March 2015, Pages 271-275
Public Health

Short Communication
Identifying data sources for a national population-based registry: the experience of the Spanish Rare Diseases Registry

https://doi.org/10.1016/j.puhe.2014.12.013Get rights and content

Highlights

  • Population-based disease registries are key instruments for rare diseases (RD) research.

  • The Spain Rare Disease Registry (Spain-RDR) is an IRDiRC project aimed at creating a national population-based RD registry.

  • This paper provides a comprehensive description of rare disease data sources in Spain.

  • The estimated number of RD that may be linked to the Spain-RDR is around 1200.

  • The Spain-RDR will contribute to improving the planning and management of these diseases.

Section snippets

Background

Rare Diseases (RD) are a diverse group of diseases with low prevalence (≤5 cases per 10,000 population), most of them chronic, with disability and premature mortality.1

RD are considered a priority for action in the Public Health Programme of the European Union (EU). The European Commission Communication (November 11, 2008) and the recommendations of the Council of Europe and the European Parliament about RD (June 8, 2009), stressed the need for information on RD and the creation of registries

First steps

Spain is organized administratively and politically into 17 autonomous communities (AC) and two autonomous cities (Ceuta and Melilla). The Spain-RDR project is coordinated by the Institute of Rare Disease Research (IIER-ISCIII). It involves all autonomous health departments, the main Spanish Rare Disease Patient Alliance (FEDER), industry, medical societies and the Ministry of Health. Each AC has a RDR coordinator.

This is a descriptive study. An electronic ad hoc questionnaire was elaborated by

Results

The questionnaires were completed by each AC-RDR coordinator between April 30 and July 30, 2012. The response rate was 100% (17 AC) and variables used to distinguish essential or complementary sources were completed at 100%.

A total of 280 data sources were identified. The median was 14 RD data sources per AC (range: 4–40). Essential sources represented 43.3% and included the hospital discharge Minimum Basic Data Set (MBDS), cancer registries, newborn screening records, health insurance card

Future

Related to the standardization of the databases, every variable with personal information will have a normalization process in order to validate the format. For example, the health insurance number must be alphanumeric with 16 characters. Also, all databases will be coded in ICD9-CM. The data will be linked using the health insurance number or name plus the last name and the date of birth. The variables of personal identification plus the ICD9-CM codes will be used to control cases duplicates.

Author statements

All authors participated in the design, analysis and data interpretation. All authors designed the survey, E. Barceló developed the database and A.C. Zoni wrote the first draft of the manuscript. All authors contributed to successive drafts and approved the final version.

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