He Zhe, Halper Michael, Perl Yehoshua, Elhanan Gai
Computer Science Dept., NJIT Newark, NJ 07102 1-973-596-2867
Information Technology Department, NJIT Newark, NJ 07102 1-973-596-5752
MIXHS 12 (2012). 2012 Oct-Nov;2012:1-6. doi: 10.1145/2389672.2389674.
As SNOMED usage becomes more ingrained within applications, its range of concept descriptors, and particularly its synonym adequacy, becomes more important. A simulated clinical scenario involving various term-based concept searches is used to assess whether SNOMED's concept descriptors provide sufficient differentiation to enable possible concept selection between similar terms. Four random samples from different SNOMED concept populations are utilized. Of particular interest are concepts mapped duplicately into UMLS concepts due to shared term patterns. While overall synonym problems are rare (1%), some concept populations exhibited a high rate of potential problems for clinical use (17-62%). The vast majority of issues are due to SNOMED's inherent structure and fine granularity. Many findings hint at a lack of clear delineation between reference and interface terminological qualities. Closer attention should be given to practical clinical use-case scenarios. Reducing SNOMED's structural complexity may alleviate many of the described findings and encourage clinical adoption.
随着SNOMED在应用程序中的使用越来越深入，其概念描述符的范围，尤其是其同义词的充分性变得越来越重要。一个涉及各种基于术语的概念搜索的模拟临床场景被用来评估SNOMED的概念描述符是否提供了足够的区分度，以便在相似术语之间进行可能的概念选择。使用了来自不同SNOMED概念群体的四个随机样本。特别令人感兴趣的是由于共享术语模式而被重复映射到UMLS概念中的概念。虽然总体同义词问题很少见（1%），但一些概念群体在临床使用中表现出较高的潜在问题发生率（17%-62%）。绝大多数问题是由于SNOMED的固有结构和精细粒度造成的。许多发现暗示在参考术语和接口术语质量之间缺乏明确的界定。应更加关注实际的临床用例场景。降低SNOMED的结构复杂性可能会缓解许多上述发现，并促进临床应用。
