Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Artif Intell Med. 2013 Jun;58(2):73-80. doi: 10.1016/j.artmed.2013.03.008. Epub 2013 Apr 18.
By 2015, SNOMED CT (SCT) will become the USA's standard for encoding diagnoses and problem lists in electronic health records (EHRs). To facilitate this effort, the National Library of Medicine has published the "SCT Clinical Observations Recording and Encoding" and the "Veterans Health Administration and Kaiser Permanente" problem lists (collectively, the "PL"). The PL is studied in regard to its readiness to support meaningful use of EHRs. In particular, we wish to determine if inconsistencies appearing in SCT, in general, occur as frequently in the PL, and whether further quality-assurance (QA) efforts on the PL are required.
A study is conducted where two random samples of SCT concepts are compared. The first consists of concepts strictly from the PL and the second contains general SCT concepts distributed proportionally to the PL's in terms of their hierarchies. Each sample is analyzed for its percentage of primitive concepts and for frequency of modeling errors of various severity levels as quality measures. A simple structural indicator, namely, the number of parents, is suggested to locate high likelihood inconsistencies in hierarchical relationships. The effectiveness of this indicator is evaluated.
PL concepts are found to be slightly better than other concepts in the respective SCT hierarchies with regards to the quality measure of the percentage of primitive concepts and the frequency of modeling errors. There were 58% primitive concepts in the PL sample versus 62% in the control sample. The structural indicator of number of parents is shown to be statistically significant in its ability to identify concepts having a higher likelihood of inconsistencies in their hierarchical relationships. The absolute number of errors in the group of concepts having 1-3 parents was shown to be significantly lower than that for concepts with 4-6 parents and those with 7 or more parents based on Chi-squared analyses.
PL concepts suffer from the same issues as general SCT concepts, although to a slightly lesser extent, and do require further QA efforts to promote meaningful use of EHRs. To support such efforts, a structural indicator is shown to effectively ferret out potentially problematic concepts where those QA efforts should be focused.
到 2015 年，SNOMED CT（SCT）将成为美国在电子健康记录（EHR）中对诊断和问题列表进行编码的标准。为了促进这一工作，美国国家医学图书馆已经发布了“SCT 临床观察记录和编码”和“退伍军人事务部和凯撒 Permanente”问题列表（统称“PL”）。正在对 PL 进行研究，以确定其是否为 EHR 的有意义使用做好准备。特别是，我们希望确定在 SCT 中普遍存在的不一致性是否也经常出现在 PL 中，以及是否需要对 PL 进行进一步的质量保证（QA）工作。
进行了一项研究，对两个 SCT 概念的随机样本进行了比较。第一个样本仅包含严格来自 PL 的概念，第二个样本包含一般 SCT 概念，这些概念根据其层次结构按比例分布在 PL 中。对每个样本进行分析，以确定其原始概念的百分比和各种严重程度的建模错误的频率，作为质量度量。提出了一个简单的结构指标，即父母的数量，以定位层次关系中高可能性的不一致性。评估了此指标的有效性。
与各自 SCT 层次结构中的其他概念相比，PL 概念在原始概念百分比和建模错误频率的质量度量方面要好一些。PL 样本中有 58%的原始概念，而对照样本中有 62%。父母数量的结构指标在识别其层次关系中更有可能不一致的概念方面具有统计学意义。基于卡方分析，具有 1-3 个父母的概念组中的错误绝对数量明显低于具有 4-6 个父母的概念组和具有 7 个或更多父母的概念组。
PL 概念与一般 SCT 概念存在相同的问题，尽管程度略低，但仍需要进一步的 QA 工作来促进 EHR 的有意义使用。为了支持这些工作，已经显示出结构指标可以有效地找出潜在的有问题的概念，应将这些 QA 工作集中在这些概念上。
