title: Structural methodologies for auditing SNOMED.
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 high-level 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's top-level hierarchies. Errors discovered during the auditing process are reported.
authors.affiliation: Computer Science Department, New Jersey Institute of Technology, University Heights, Newark, NJ 07102-1982, USA.
authors.forename: Yue
authors.initials: Y
authors.lastname: Wang
authors.forename: Michael
authors.initials: M
authors.lastname: Halper
authors.forename: Hua
authors.initials: H
authors.lastname: Min
authors.forename: Yehoshua
authors.initials: Y
authors.lastname: Perl
authors.forename: Yan
authors.initials: Y
authors.lastname: Chen
authors.forename: Kent A
authors.initials: KA
authors.lastname: Spackman
mesh_terms: D001185:Artificial Intelligence; D011786:Quality Control; D039061:Systematized Nomenclature of Medicine; D014481:United States