Document Type
Article
Publication Date
2-8-2025
Publication Title
Sci Data
Keywords
JGM, Rare Diseases, Humans, Registries, Biological Ontologies, Health Information Interoperability
JAX Source
Sci Data. 2025;12(1):234.
Volume
12
Issue
1
First Page
234
Last Page
234
ISSN
2052-4463
PMID
39922817
DOI
https://doi.org/10.1038/s41597-025-04558-z
Abstract
Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health Level 7 Fast Healthcare Interoperability Base Resources, and the Global Alliance for Genomics and Health Phenopacket Schema into a novel rare disease common data model (RD-CDM), laying the foundation for developing international RD-CDMs aligned with these data standards. We developed a modular-based GitHub repository and documentation to account for flexibility, extensions and further development. Recommendations on the model's cardinalities are given, inviting further refinement and international collaboration. An ontology-based approach was selected to find a common denominator between the semantic and syntactic data standards. Our RD-CDM version 2.0.0 comprises 78 data elements, extending the ERDRI-CDS by 62 elements with previous versions implemented in four German university hospitals capturing real world data for development and evaluation. We identified three categories for evaluation: Medical Data Granularity, Clinical Reasoning and Medical Relevance, and Interoperability and Harmonisation.
Recommended Citation
Graefe A,
Hübner M,
Rehburg F,
Sander S,
Klopfenstein S,
Alkarkoukly S,
Grönke A,
Weyersberg A,
Danis D,
Zschüntzsch J,
Nyoungui E,
Wiegand S,
Kühnen P,
Robinson P,
Beyan O,
Thun S.
An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets. Sci Data. 2025;12(1):234.