Scoping review of the recommendations and guidance for improving the quality of rare disease registries.
Guidance
Quality standards
Rare diseases
Registries
Journal
Orphanet journal of rare diseases
ISSN: 1750-1172
Titre abrégé: Orphanet J Rare Dis
Pays: England
ID NLM: 101266602
Informations de publication
Date de publication:
06 May 2024
06 May 2024
Historique:
received:
21
11
2023
accepted:
19
04
2024
medline:
7
5
2024
pubmed:
7
5
2024
entrez:
6
5
2024
Statut:
epublish
Résumé
Rare disease registries (RDRs) are valuable tools for improving clinical care and advancing research. However, they often vary qualitatively, structurally, and operationally in ways that can determine their potential utility as a source of evidence to support decision-making regarding the approval and funding of new treatments for rare diseases. The goal of this research project was to review the literature on rare disease registries and identify best practices to improve the quality of RDRs. In this scoping review, we searched MEDLINE and EMBASE as well as the websites of regulatory bodies and health technology assessment agencies from 2010 to April 2023 for literature offering guidance or recommendations to ensure, improve, or maintain quality RDRs. The search yielded 1,175 unique references, of which 64 met the inclusion criteria. The characteristics of RDRs deemed to be relevant to their quality align with three main domains and several sub-domains considered to be best practices for quality RDRs: (1) governance (registry purpose and description; governance structure; stakeholder engagement; sustainability; ethics/legal/privacy; data governance; documentation; and training and support); (2) data (standardized disease classification; common data elements; data dictionary; data collection; data quality and assurance; and data analysis and reporting); and (3) information technology (IT) infrastructure (physical and virtual infrastructure; and software infrastructure guided by FAIR principles (Findability; Accessibility; Interoperability; and Reusability). Although RDRs face numerous challenges due to their small and dispersed populations, RDRs can generate quality data to support healthcare decision-making through the use of standards and principles on strong governance, quality data practices, and IT infrastructure.
Sections du résumé
BACKGROUND
BACKGROUND
Rare disease registries (RDRs) are valuable tools for improving clinical care and advancing research. However, they often vary qualitatively, structurally, and operationally in ways that can determine their potential utility as a source of evidence to support decision-making regarding the approval and funding of new treatments for rare diseases.
OBJECTIVES
OBJECTIVE
The goal of this research project was to review the literature on rare disease registries and identify best practices to improve the quality of RDRs.
METHODS
METHODS
In this scoping review, we searched MEDLINE and EMBASE as well as the websites of regulatory bodies and health technology assessment agencies from 2010 to April 2023 for literature offering guidance or recommendations to ensure, improve, or maintain quality RDRs.
RESULTS
RESULTS
The search yielded 1,175 unique references, of which 64 met the inclusion criteria. The characteristics of RDRs deemed to be relevant to their quality align with three main domains and several sub-domains considered to be best practices for quality RDRs: (1) governance (registry purpose and description; governance structure; stakeholder engagement; sustainability; ethics/legal/privacy; data governance; documentation; and training and support); (2) data (standardized disease classification; common data elements; data dictionary; data collection; data quality and assurance; and data analysis and reporting); and (3) information technology (IT) infrastructure (physical and virtual infrastructure; and software infrastructure guided by FAIR principles (Findability; Accessibility; Interoperability; and Reusability).
CONCLUSIONS
CONCLUSIONS
Although RDRs face numerous challenges due to their small and dispersed populations, RDRs can generate quality data to support healthcare decision-making through the use of standards and principles on strong governance, quality data practices, and IT infrastructure.
Identifiants
pubmed: 38711103
doi: 10.1186/s13023-024-03193-y
pii: 10.1186/s13023-024-03193-y
doi:
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
187Subventions
Organisme : Canadian Agency for Drugs and Technologies in Health (CADTH).
ID : C-222110
Informations de copyright
© 2024. The Author(s).
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