Development of an Interactive Dashboard for OSSE Rare Disease Registries

Vasseur, Jessica; Zieschank, Axel; Göbel, Jens; Schaaf, Jannik; Dahmer-Heath, Mareike; König, Jens; Kadioglu, Dennis; Storf, Holger

doi:10.3233/shti220367

Cited by 1 publication

(1 citation statement)

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“…Registries can safeguard their systems through several processes (e.g., analysis of threats and countermeasures [ 63 ]) and tools (e.g. data software and access policies [ 63 , 81 , 82 ]). An independent external security or threat risk assessment is recommended to document compliance with security and privacy standards [ 83 ].…”

Section: Resultsmentioning

confidence: 99%

Scoping review of the recommendations and guidance for improving the quality of rare disease registries

Tarride,

Okoh,

Aryal

et al. 2024

Orphanet J Rare Dis

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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 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 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 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 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.

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