From SNOMED CT expressions to an FHIR RDF representation: Exploring the benefits of an ontology-based approach

Mercedes Arguello Casteleiro, Catalina Martinez-Costa, Julio Des-Diz, Nava Maroto, Maria Jesus Fernandez-Prieto, Robert Stevens

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We address the problem of semantic interoperability of HL7 standards and propose an ontology-based approach to convert smoothly HL7 C-CDA coded entries containing pre- and post-coordinated SNOMED CT expressions into HL7 FHIR resources in RDF. Our ontology-based approach is based on Content Ontology Design Patterns (ODPs) and seeks to: 1) constrain further the SNOMED CT post-coordination that otherwise can lead to an unmanageable number of possible SNOMED CT expressions; 2) minimise the variability when mapping between the structures and semantics of the HL7 FHIR specification to SNOMED CT expressions; and 3) smooth the transformation of SNOMED CT expressions to an FHIR RDF representation, leveraging on FHIR ShEx schemas to formally describe FHIR RDF data instances. To validate the proposal this study utilises 358 SNOMED CT expressions from 3 sections of anonymised consultation notes in HL7 C-CDA. Besides converting HL7 C-CDA document entries into FHIR RDF data instances, we explore the benefits of the Content ODPs to facilitate largescale data analytics (e.g. cross-compare patients) and Natural Language Generation by generating text from the clinical coded data.
Original languageEnglish
Title of host publicationODLS 2019: Ontologies and Data in Life Sciences 2019
Number of pages13
Publication statusAccepted/In press - 11 Jul 2019
EventThe Joint Onthology Workshop - Medical University of Graz, Graz, Austria
Duration: 23 Sept 201925 Sept 2019


WorkshopThe Joint Onthology Workshop
Abbreviated titleJOWO
Internet address


  • Content ODPs
  • HL7 C-CDA
  • HL7 FHIR
  • NLG


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