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Area of Science:

  • Health Informatics
  • Medical Terminology
  • Ontology Engineering

Background:

  • Semantic interoperability between healthcare terminologies like ICD and SNOMED CT is challenging due to design and policy differences.
  • Existing approaches often rely on either axiom-based or rule-based methods.

Purpose of the Study:

  • To present a novel harmonization process for achieving semantic interoperability between the International Classification of Diseases (ICD) and SNOMED CT (SCT).
  • To introduce a new architecture for ICD-11 and a protocol for semantic alignment.
  • To report preliminary results of this alignment.

Main Methods:

  • Development of a new architecture for ICD-11.
  • Establishment of a protocol for semantic alignment between ICD and SCT.
  • Application of axiom-based (ontology language like OWL) and rule-based (querying axioms) approaches.
  • Preliminary alignment applied to over half of the ICD-11 draft domain.

Main Results:

  • A comprehensive ICD-SCT harmonization process has been developed.
  • Preliminary results demonstrate successful semantic alignment for a significant portion of the ICD-11 draft.
  • The proposed methods facilitate improved interoperability between these critical healthcare terminologies.

Conclusions:

  • Combining axiom-based and rule-based methods is effective for ICD-SCT semantic interoperability.
  • The presented architecture and protocol offer a viable solution for aligning ICD-11 and SCT.
  • The preliminary findings support the feasibility and potential of this harmonization approach.