An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets

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.

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Publication Details

Journal
Scientific Data
Published
2025-02-08
DOI
https://doi.org/10.1038/s41597-025-04558-z
Citations
6
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
10.90

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article

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets

Susanna Wiegand, Peter Kühnen, Miriam Hübner, Peter N. Robinson et al.
6 citations
Scientific Data
Genomics and Rare Diseases
10.90
article

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets

Susanna Wiegand, Peter Kühnen, Miriam Hübner, Peter N. Robinson, Ana Grönke, Daniel Daniš, Sylvia Thun, Samer Alkarkoukly, Oya Beyan, Stanley P. Sander, Jana Zschüntzsch, Sophie Anne Inès Klopfenstein, Adam S L Graefe, Filip Rehburg, E. Nyoungui, Annic Weyersberg
article en
6 citations

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.

Scientific DataVol. 12(1)
University of Cologne (DE), Deutsche Akademie für Kinder- und Jugendmedizin (DE), Jackson Laboratory (US), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), University Hospital Cologne (DE), University of Göttingen (DE), Charité - Universitätsmedizin Berlin (DE)
Universitätsklinikum Köln, National Institutes of Health
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Genomics and Rare Diseases
10.90
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