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

Safe and accurate sharing of healthcare information is essential for good health and well-being. Information must be exchanged among multiple parties, making the transformation between different information structures unavoidable. It has been suggested that such a transformation could be automated if information were sufficiently structured. This study aims to explore whether terminology binding to SNOMED CT can act as a bridge between different information structures.

This study employed a mixed-methods approach using two information structures from the breast cancer pathology domain. Pairs of semantically equivalent user interface terms from these structures were identified by a clinician and verified by two informaticians. The terms were considered semantically equivalent when a clinician would have used them to convey the same information. The pairs of SNOMED CT concepts bound to each of the interface terms were then compared and categorised as transformable, partially transformable, or non-transformable. Non-transformable concept pairs were analysed qualitatively, using an inductive content analysis approach, to identify underlying causes.

73 term pairs were identified. In 70% of these, the user interface terms were terminology bound to the same SNOMED CT concept. Among term pairs with terms bound to different concepts, 9% were fully transformable, 27% partially transformable, and 64% non-transformable. All is-a-related concept pairs were either fully or partially transformable, whereas concept pairs from different hierarchies were never transformable. Major obstacles within the same hierarchy included the use of primitive concepts and nearly identical sibling concepts. For concept pairs across different hierarchies, divergent terminology-binding strategies-such as handling of integers and "other" values-hindered transformability. Additional issues were observed with local user interface terms and SNOMED CT translations.

Although concordance between the two structures was relatively high (70%), transformability among semantically equivalent term pairs bound to different SNOMED CT concepts was low (9%). This can be improved on the terminology-binding side through guidelines and shared terminology bindings, and on the ontology side by increasing the proportion of sufficiently defined concepts and ensuring the quality of descriptions and translations. These findings are significant for practitioners seeking to enhance interoperability, as well as for SNOMED International and researchers focusing on terminology quality and transformation approaches.