Automating lexical cross-mapping of ICNP to SNOMED CT.

OBJECTIVES

The purpose of this study was to examine the feasibility of automating lexical cross-mapping of a logic-based nursing terminology (ICNP) to SNOMED CT using the Unified Medical Language System (UMLS) maintained by the U.S. National Library of Medicine.

METHODS

A two-stage approach included patterns identification, and application and evaluation of an automated term matching procedure. The performance of the automated procedure was evaluated using a test set against a gold standard (i.e. concept equivalency table) created independently by terminology experts.

RESULTS

There were lexical similarities between ICNP diagnostic concepts and SNOMED CT. The automated term matching procedure was reliable as presented in recall of 65%, precision of 79%, accuracy of 82%, F-measure of 0.71 and the area under the receiver operating characteristics (ROC) curve of 0.78 (95% CI 0.73-0.83). When the automated procedure was not able to retrieve lexically matched concepts, it was also unlikely for terminology experts to identify a matched SNOMED CT concept.

CONCLUSIONS

Although further research is warranted to enhance the automated matching procedure, the combination of cross-maps from UMLS and the automated procedure is useful to generate candidate mappings and thus, assist ongoing maintenance of mappings which is a significant burden to terminology developers.