Due to their low prevalence and wide distribution, rare kidney diseases pose challenges in diagnosis and management. Registries play a key role in organising data to address these issues.
Objectives:
This study aims to compare the characteristics of existing rare kidney disease registries to gain insights to create new registries or develop available ones.
Method:
This scoping review was conducted in 2024. The searches were performed in four electronic databases: PubMed, Web of Science, Scopus and ProQuest, as well as the Orphanet website. Various components of disease registries were extracted and compared narratively.
Results:
Our review of 1,534 papers revealed 29 rare kidney disease registries, and an additional 8 registries were retrieved from the Orphanet website, established between 1989 and 2023 in various countries. The objectives of these registries were categorised into clinical (15 registries), research (29 registries), and epidemiological ones (11 registries), among these, 15 and 20 registries were international and national, respectively. Data collected included demographic, medical, and family history, paraclinical, therapeutic, genetic testing, comorbidities and treatment outcomes. Various strategies were employed for data quality assurance, including the use of data quality indicators, audits and adherence to established guidelines. Some registries used both prospective and retrospective data collection methods.
Conclusion:
Establishing standardised registries for rare kidney diseases is essential to ensure data consistency and comparability. Due to legal and ethical challenges, and regional differences in disease prevalence, each country or institution may need to create its own registry. Adhering to common standards for data collection, collaboration and establishment of integrated frameworks facilitate comprehensive and comparable data analysis.
Implication for health information management practice:
This study suggests that rare kidney disease registries should adopt patient-centred designs with clearly defined objectives and standardised data elements to enable meaningful data collection and analysis. Registries must implement strong data quality assurance mechanisms and foster inter-institutional collaboration to support clinical decision-making, and drive targeted research.
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