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用于审核SNOMED的结构化方法。

Structural methodologies for auditing SNOMED.

作者信息

Wang Yue, Halper Michael, Min Hua, Perl Yehoshua, Chen Yan, Spackman Kent A

机构信息

Computer Science Department, New Jersey Institute of Technology, University Heights, Newark, NJ 07102-1982, USA.

出版信息

J Biomed Inform. 2007 Oct;40(5):561-81. doi: 10.1016/j.jbi.2006.12.003. Epub 2006 Dec 24.

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.

摘要

SNOMED是全球使用的主要医疗保健术语集之一。因此,质量保证是其维护周期的重要组成部分。本文介绍了基于SNOMED组织结构方面进行审核的方法。特别地,定义了主要基于关系模式将SNOMED划分为较小概念组的自动化技术。从这些划分中导出了两个抽象网络,即领域分类法和p领域分类法。这些抽象网络提供的高层视图构成了系统审核的基础。这些网络往往会突出在抽象层面表现为不规则性的错误。它们还支持基于组的审核,即关注一组据称相似的概念进行审查。在SNOMED的一个顶级层次结构上演示了审核方法。报告了审核过程中发现的错误。

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