Fung Kin Wah, Xu Junchuan, Rosenbloom S Trent, Mohr David, Maram Naveen, Suther Thomas
National Library of Medicine, Bethesda, MD, USA.
AMIA Annu Symp Proc. 2011;2011:445-54. Epub 2011 Oct 22.
Three Problem List Terminologies (PLT) were tested using a web-based application simulating a clinical data entry environment to evaluate coverage and coding efficiency. The three PLTs were: the CORE Problem List Subset of SNOMED CT, a clinical subset extracted from the full SNOMED CT and the PLT currently used at the Mayo Clinic. Candidate problem statements were randomly extracted from free text problem list entries contained in two electronic medical record systems. Physician reviewers searched for concepts in one of the three PLTs that most closely matched a problem statement. Altogether 45 reviewers reviewed 15 problems each. The coverage of the much smaller CORE Subset was comparable to Clinical SNOMED for combined exact or partial matches. The CORE Subset required the shortest time to find a concept. This may be related to the smaller size of the pick lists for the CORE Subset.
使用一个基于网络的应用程序模拟临床数据录入环境，对三种问题列表术语（PLT）进行了测试，以评估其覆盖范围和编码效率。这三种PLT分别是：SNOMED CT的核心问题列表子集，从完整的SNOMED CT中提取的临床子集，以及梅奥诊所目前使用的PLT。候选问题陈述是从两个电子病历系统中包含的自由文本问题列表条目中随机提取的。医生评审人员在三种PLT之一中搜索与问题陈述最匹配的概念。共有45名评审人员，每人评审15个问题。对于精确匹配或部分匹配的组合，小得多的核心子集的覆盖范围与临床SNOMED相当。核心子集找到一个概念所需的时间最短。这可能与核心子集的选择列表规模较小有关。
