Cross-Standard Health Data Harmonization using Semantics of Data Elements.

ABSTRACT: Faced with heterogeneity of healthcare data, we propose a novel approach for harmonizing data elements (i.e., attributes) across health data standards. This approach focuses on the implicit concept that is represented by a data element. The process includes the following steps: identifying concepts, clustering similar concepts and constructing mappings between the clusters using the Simple Standard for Sharing Ontological Mappings (SSSOM) and Resource Description Framework (RDF), and enabling the creation of reusable mappings. As proof-of-concept, we applied the approach to five common health data standards - HL7 FHIR, OMOP, CDISC, Phenopackets, and openEHR, across four domains, such as demographics and diagnoses, and nine topics within those domains, such as gender and vital status. These

SUBMITTER: Zhang S 

PROVIDER: S-EPMC11659470 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature