Comparing heterogeneous SNOMED CT coding of clinical research concepts by examining normalized expressions.

OBJECTIVE: A continual problem confronting the implementation of standardized vocabularies such as SNOMED CT is that their expressive flexibility and power provide more than one way to represent a given concept. The goal of this study was to investigate how the CliniClue Expression Transformer tool could be used to help in discerning similarities and differences among three separate sets of clinical research concepts coded in SNOMED CT by three different paid expert coding companies.
METHODS: Initial editing of the companies' coded datasets was required to enable accurate input into CliniClue Version: 2006.2.0030 Expression Transformer tool. The normal forms of the company codings for the 319 clinical research question/answer sets were compared to determine whether they were equivalent or otherwise related (e.g., if one was subsumed by the other). Basic frequencies were computed for (957) pairwise comparisons of each of 319 concepts each coded by the three expert coders, and the implications of the results discussed.
RESULTS: The primary finding from this study was that, for each of the paired comparisons, approximately half of the time the companies' codings could be related, primarily via subsumption. The greatest percentage of equivalent concepts between any two companies was 33%. These same two companies also agreed most often on the core clinical concept measure from an earlier study by the authors.
CONCLUSION: Heterogeneity among coders using the same controlled terminology appears inescapable despite the extensive efforts of terminological standards developers and implementers. In our study, the computable determination of equivalence of discordantly coded concepts still failed to yield acceptably comparable data. A clearer articulation, and perhaps a simplification, of rules for the consistent use for terminologies such as SNOMED CT is needed.