ICD-11 (JLMMS) and SCT Inter-Operation.

Area of Science:

• Medical Informatics
• Health Data Standards
• Ontology Engineering

Background:

• Healthcare classifications like ICD-11 and clinical terminologies like SNOMED CT are crucial for health data.
• Ensuring seamless interoperability between these systems is vital for accurate data exchange and analysis.
• Existing methods may not fully capture the semantic nuances required for complex health information.

Purpose of the Study:

• To develop and test a method for achieving smooth and semantically sound interoperability between ICD-11 Joint Linearization for Mortality, Morbidity and Statistics (JLMMS) and SNOMED CT (SCT).
• To leverage ontology axioms and SCT's compositional grammar to bridge the gap between a hierarchical classification and an ontology-based terminology.

Main Methods:

• Utilized ontology axioms to logically express generalizable truths for inter-system mapping.
• Employed queries on SNOMED CT axioms to facilitate semantic understanding and alignment.
• Tested the proposed method on the circulatory system chapter of ICD-11 JLMMS.

Main Results:

• Demonstrated the feasibility of using ontology axioms for inter-operability between ICD-11 JLMMS and SNOMED CT.
• Identified specific limitations and outcomes of applying the method to the circulatory chapter.
• The approach facilitates a more robust semantic connection between the two systems.

Conclusions:

• The ontology axiom-based method offers a viable approach to enhance semantic interoperability between ICD-11 JLMMS and SNOMED CT.
• Further refinement and testing are needed to address identified limitations and expand applicability.
• This work contributes to more accurate and consistent use of health data across different coding systems.