Linguistic Mapping of Terminologies to SNOMED CT

In this study we develop some linguistic bases for mapping between terminologies and demonstrate their application on mapping ICPC-2 PLUS to SNOMED CT (SCT). The Unified Medical Language System (UMLS) metathesau-rus mapping, which utilises the links between ICPC-2 PLUS and SCT terms in the UMLS library mapped 46.5% of ICPC-2 PLUS terms to SCT. Lexical mapping explored the lexical similarities between terms in these two termi-nologies, and mapped 60.3 % of ICPC-2 PLUS terms overall. Post-coordination of remaining unmapped terms was performed, allowing one ICPC-2 PLUS term to be mapped into composition with two SCT terms, which gives an increase of about 20 % in mapped terms. Overall we have mapped 80.58 % of ICPC-2 PLUS terms to SCT terminology with different level of accuracy. A manual review of the mapping shows that about 90 % of string-based mappings are accurate. Unmapped terms and mismatched terms are due to the differences in the structures between ICPC-2 PLUS and SCT. Terms con-tained in ICPC-2 PLUS but not in SCT caused a large proportion of failures in the mappings