Terminology binding with SNOMED CT to bridge differences in information structures: a feasibility study

Area of Science:

• Health Informatics
• Medical Terminology
• Data Interoperability

Background:

• Sharing healthcare information is crucial for patient well-being.
• Transforming between different data structures is often necessary for information exchange.
• Automating data transformation requires sufficiently structured information.

Purpose of the Study:

• To investigate if terminology binding to SNOMED CT can serve as a bridge between disparate information structures.
• To assess the transformability of semantically equivalent terms bound to SNOMED CT concepts.

Main Methods:

• A mixed-methods approach was used with two breast cancer pathology information structures.
• Clinicians and informaticians identified and verified semantically equivalent user interface terms.
• SNOMED CT concept pairs were categorized as transformable, partially transformable, or non-transformable.

Main Results:

• 70% of user interface terms mapped to the same SNOMED CT concept.
• Only 9% of term pairs bound to different SNOMED CT concepts were fully transformable.
• Obstacles included primitive concepts, sibling concepts, divergent binding strategies, and translation issues.

Conclusions:

• While SNOMED CT concept concordance was high (70%), transformability between different concepts was low (9%).
• Improving transformability requires better terminology-binding guidelines and enhanced SNOMED CT ontology definitions.
• Findings offer insights for enhancing healthcare data interoperability and terminology quality.