Yue Wang, Michael Halper, Hua Min, Yehoshua Perl, Yan Chen, Kent A. Spackman. Structural Methodologies for Auditing SNOMED. Pending after revision and Journal of Biomedical Informatics.

Abstract: SNOMED is one of the leading health care terminologies being used worldwide. As such, quality assurance is an important part of its maintenance cycle. Methodologies for auditing SNOMED based on structural aspects of its organization are presented. In particular, automated techniques for partitioning SNOMED into smaller groups of concepts based primarily on relationships patterns are defined. Two abstraction networks, the area taxonomy and p-area taxonomy, are derived from the partitions. The highlevel views afforded by these abstraction networks form the basis for systematic auditing. The networks tend to highlight errors that manifest themselves as irregularities at the abstract level. They also support
group-based auditing, where sets of purportedly similar concepts are focused on for review. The auditing methodologies are demonstrated on one of SNOMED top-level hierarchies. Errors discovered during the auditing process are reported.