BACKGROUND: The focus on the quality of the procedures for data collection, storing, and analysis in the definition and implementation of a rare disease registry (RDR) is the basis for developing a valid and long-term sustainable tool. The aim of this study was to provide useful information for characterizing a quality profile for RDRs using an analytical approach applied to RDRs participating in the European Platform for Rare Disease Registries 2011-2014 (EPIRARE) survey. METHODS: An indicator of quality was defined by choosing a small set of quality-related variables derived from the survey. The random forest method was used to identify the variables best defining a quality profile for RDRs. Fisher's exact test was employed to assess the association with the indicator of quality, and the Cochran-Armitage test was used to check the presence of a linear trend along different levels of quality. RESULTS: The set of variables found to characterize high-quality RDRs focused on ethical and legal issues, governance, communication of activities and results, established procedures to regulate access to data and security, and established plans to ensure long-term sustainability. CONCLUSIONS: The quality of RDRs is usually associated with a good oversight and governance mechanism and with durable funding. The results suggest that RDRs would benefit from support in management, information technology, epidemiology, and statistics.
The Quality of Rare Disease Registries: Evaluation and Characterization.
Coi A;Santoro M;Bianchi F
2016
Abstract
BACKGROUND: The focus on the quality of the procedures for data collection, storing, and analysis in the definition and implementation of a rare disease registry (RDR) is the basis for developing a valid and long-term sustainable tool. The aim of this study was to provide useful information for characterizing a quality profile for RDRs using an analytical approach applied to RDRs participating in the European Platform for Rare Disease Registries 2011-2014 (EPIRARE) survey. METHODS: An indicator of quality was defined by choosing a small set of quality-related variables derived from the survey. The random forest method was used to identify the variables best defining a quality profile for RDRs. Fisher's exact test was employed to assess the association with the indicator of quality, and the Cochran-Armitage test was used to check the presence of a linear trend along different levels of quality. RESULTS: The set of variables found to characterize high-quality RDRs focused on ethical and legal issues, governance, communication of activities and results, established procedures to regulate access to data and security, and established plans to ensure long-term sustainability. CONCLUSIONS: The quality of RDRs is usually associated with a good oversight and governance mechanism and with durable funding. The results suggest that RDRs would benefit from support in management, information technology, epidemiology, and statistics.File | Dimensione | Formato | |
---|---|---|---|
prod_352604-doc_114270.pdf
non disponibili
Descrizione: The Quality of Rare Disease Registries: Evaluation and Characterization
Tipologia:
Versione Editoriale (PDF)
Dimensione
3.62 MB
Formato
Adobe PDF
|
3.62 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.