An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets
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...
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| Format: | Article |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04558-z |
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| author | Adam S. L. Graefe Miriam R. Hübner Filip Rehburg Steffen Sander Sophie A. I. Klopfenstein Samer Alkarkoukly Ana Grönke Annic Weyersberg Daniel Danis Jana Zschüntzsch Elisabeth F. Nyoungui Susanna Wiegand Peter Kühnen Peter N. Robinson Oya Beyan Sylvia Thun |
| author_facet | Adam S. L. Graefe Miriam R. Hübner Filip Rehburg Steffen Sander Sophie A. I. Klopfenstein Samer Alkarkoukly Ana Grönke Annic Weyersberg Daniel Danis Jana Zschüntzsch Elisabeth F. Nyoungui Susanna Wiegand Peter Kühnen Peter N. Robinson Oya Beyan Sylvia Thun |
| author_sort | Adam S. L. Graefe |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e882ed426567406dbc60b8f73dd6c091 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-e882ed426567406dbc60b8f73dd6c0912025-02-09T12:11:28ZengNature PortfolioScientific Data2052-44632025-02-0112112210.1038/s41597-025-04558-zAn ontology-based rare disease common data model harmonising international registries, FHIR, and PhenopacketsAdam S. L. Graefe0Miriam R. Hübner1Filip Rehburg2Steffen Sander3Sophie A. I. Klopfenstein4Samer Alkarkoukly5Ana Grönke6Annic Weyersberg7Daniel Danis8Jana Zschüntzsch9Elisabeth F. Nyoungui10Susanna Wiegand11Peter Kühnen12Peter N. Robinson13Oya Beyan14Sylvia Thun15Berlin Institute of Health at Charité – Universitätsmedizin BerlinBerlin Institute of Health at Charité – Universitätsmedizin BerlinBerlin Institute of Health at Charité – Universitätsmedizin BerlinBerlin Institute of Health at Charité – Universitätsmedizin BerlinBerlin Institute of Health at Charité – Universitätsmedizin BerlinMedical Data Integration Center (MeDIC), University of Cologne, Faculty of Medicine and University Hospital CologneMedical Data Integration Center (MeDIC), University of Cologne, Faculty of Medicine and University Hospital CologneDepartment of Paediatrics, University Hospital CologneBerlin Institute of Health at Charité – Universitätsmedizin BerlinDepartment of Neurology, University Medical Center GoettingenDepartment of Medical Informatics, University Medical Center GoettingenDepartment of Pediatric Endocrinology and Diabetology, Charité University HospitalDepartment of Pediatric Endocrinology and Diabetology, Charité University HospitalBerlin Institute of Health at Charité – Universitätsmedizin BerlinInstitute for Biomedical Informatics, University Hospital CologneBerlin Institute of Health at Charité – Universitätsmedizin BerlinAbstract 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.https://doi.org/10.1038/s41597-025-04558-z |
| spellingShingle | Adam S. L. Graefe Miriam R. Hübner Filip Rehburg Steffen Sander Sophie A. I. Klopfenstein Samer Alkarkoukly Ana Grönke Annic Weyersberg Daniel Danis Jana Zschüntzsch Elisabeth F. Nyoungui Susanna Wiegand Peter Kühnen Peter N. Robinson Oya Beyan Sylvia Thun An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets Scientific Data |
| title | An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets |
| title_full | An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets |
| title_fullStr | An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets |
| title_full_unstemmed | An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets |
| title_short | An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets |
| title_sort | ontology based rare disease common data model harmonising international registries fhir and phenopackets |
| url | https://doi.org/10.1038/s41597-025-04558-z |
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