<b>Common Data Model for Rare Diseases</b> based on the ERDRI-CDS, HL7 FHIR®, and the GA4GH Phenopackets Schema© (v2.0)

ART-DECOR Project: https://art-decor.org/ad/#/erker-/project/overviewWhile rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective RD care and research severely. A significant knowledge gap exists between specialised RD data and data from routine clinical care. This study aims to harmonise the data standards necessary for RD care and research into a novel RD Common Data Model (CDM). The proposed RD CDM integrates the ERDRI-CDS for international registry use and extends it with data elements based on HL7 FHIR for reliable data transactions and the GA4GH Phenopacket Schema for precise bioinformatic analyses. This work does not present an implementation guide but lays the foundation for developing and defining international RD CDMs aligned with these data standards. An ontology-driven approach was selected, encoding data elements and value sets with SNOMED CT and LOINC to find a common denominator between the data standards. The RD CDM was implemented in multiple German university hospitals capturing real RD patient data for registry or analysis purposes, fixing errors, and ensuring semantic consistency. Our RD CDM version 2.0 comprises 66 data elements, extending the ERDRI-CDS by 50 elements. We evaluated our CDM based on (1) Medical Data Granularity, (2) Clinical Reasoning and Medical Relevance, and (3) Interoperability and Harmonisation. Six layers of harmonisation were identified, ranging from data element alignment and terminology binding to value sets. Over 95% of data elements, 80% of data types, and, due to the ontology-based approach, less than 41% of value sets align with either HL7 FHIR or the GA4GH Phenopacket Schema. The novel RD CDM can serve as a basis for developing and implementing RD CDMs in various healthcare information systems, adhering to HL7 FHIR, GA4GH Phenopacket Schema, and ERDRI-CDS requirements for effective RD research and care. While not an implementation guide, recommendations on cardinalities are given, and this template invites further refinement and international collaboration. This work represents a significant step for clinicians to capture precise RD data based on international interoperability standards, regardless of the healthcare information system used.<br>