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Using SNOMED CT to Represent Two Interface Terminologies

^a Department of Biomedical Informatics, Vanderbilt University, Nashville-TN
^b Department of Internal Medicine, Vanderbilt University, Nashville-TN
^c Department of Veterans Affairs Tennessee Valley Healthcare System, Nashville, TN
^d Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN

^_* Correspondence: S. Trent Rosenbloom, MD, MPH, Eskind Biomedical Library, Room 440, 2209 Garland Avenue, Nashville, TN (Email: trent.rosenbloom{at}vanderbilt.edu).

Received for publication: 12/12/07; accepted for publication: 09/27/08.

Objective: Interface terminologies are designed to support interactions between humans and structured medical information. In particular, many interface terminologies have been developed for structured computer based documentation systems. Experts and policy-makers have recommended that interface terminologies be mapped to reference terminologies. The goal of the current study was to evaluate how well the reference terminology SNOMED CT could map to and represent two interface terminologies, MEDCIN and the Categorical Health Information Structured Lexicon (CHISL).

Design: Automated mappings between SNOMED CT and 500 terms from each of the two interface terminologies were evaluated by human reviewers, who also searched SNOMED CT to identify better mappings when this was judged to be necessary. Reviewers judged whether they believed the interface terms to be clinically appropriate, whether the terms were covered by SNOMED CT concepts and whether the terms' implied semantic structure could be represented by SNOMED CT.

Measurements: Outcomes included concept coverage by SNOMED CT for study terms and their implied semantics. Agreement statistics and compositionality measures were calculated.

Results: The SNOMED CT terminology contained concepts to represent 92.4% of MEDCIN and 95.9% of CHISL terms. Semantic structures implied by study terms were less well covered, with some complex compositional expressions requiring semantics not present in SNOMED CT. Among sampled terms, those from MEDCIN were more complex than those from CHISL, containing an average 3.8 versus 1.8 atomic concepts respectively, p<0.001.

Conclusion: Our findings support using SNOMED CT to provide standardized representations of information created using these two terminologies, but suggest that enriching SNOMED CT semantics would improve representation of the external terms.