SNOMED CT Coding Variation and Grouping for “other findings” in a Longitudinal Study on Urea Cycle Disorders

Semantic interoperability and data sharing require consistent use of controlled terminologies. However, non-terminology experts (although perhaps experts in a particular domain or context) are prone to produce variant coding of the same concepts using the same terminology. This study examines this problem by investigating SNOMED CT coding variation for “other findings” reported on case report forms used in a clinical research study on urea cycle disorders. The natural language findings from the forms were normalized, and the SNOMED CT concept descriptions associated with each normalized string were compared. The subset of normalized strings associated with two different concept descriptions were further compared to determine the relationship among the associated SNOMED CT concepts. We found that 45% of the concept description pairs were associated with two hierarchically related concepts or with the same concept, while 55% were associated with two unrelated concepts. Clearer guidelines for use of SNOMED CT in particular contexts, or structured data entry tools tailored to the needs of non-expert coders, are needed to better manage coding variation.