Zheng Ling, Liu Hao, Perl Yehoshua, Geller James, Ochs Christopher, Case James T
Monmouth University, West Long Branch, NJ, US.
New Jersey Institute of Technology, Newark, NJ, US.
AMIA Annu Symp Proc. 2018 Dec 5;2018:1157-1166. eCollection 2018.
SNOMED CT is a large, complex and widely-used terminology. Auditing is part of the life cycle of terminologies. A review of terminologies' content can identify two error categories: commission errors, such as an incorrect parent or attribute relationship, indicating errors in a concept's modeling, and omission errors, such as missing a parent or attribute relationship, representing incomplete modeling of a concept. According to our experience, terminology curators are mostly interested in commission errors. In recent years, a long-term remodeling project has addressed modeling issues in SNOMED CT's Infectious disease and Congenital disease subhierarchies. In this longitudinal study, we investigated a posteriori the efficacy of complex concepts, called overlapping concepts, to identify commission errors during intensive auditing periods and during maintenance periods over several releases. The algorithmic implication is that when auditing resources are scarce, a methodology of auditing first, or only, the overlapping concepts will obtain a higher auditing yield.
SNOMED CT是一个庞大、复杂且广泛使用的术语集。审核是术语集生命周期的一部分。对术语集内容的审查可识别出两类错误：编撰错误，例如父级或属性关系不正确，表明概念建模存在错误；以及遗漏错误，例如缺少父级或属性关系，代表概念建模不完整。根据我们的经验，术语集管理者大多关注编撰错误。近年来，一个长期的重塑项目解决了SNOMED CT传染病和先天性疾病子层次结构中的建模问题。在这项纵向研究中，我们事后调查了一种称为重叠概念的复杂概念在多个版本的密集审核期和维护期识别编撰错误的功效。算法层面的含义是，当审核资源稀缺时，首先或仅审核重叠概念的方法将获得更高的审核产出率。
