Berlin Institute of Health at Charité, Universitätsmedizin Berlin.
Institute of Medical Informatics, Charité Universitätsmedizin Berlin, Berlin.
Stud Health Technol Inform. 2021 May 27;281:88-92. doi: 10.3233/SHTI210126.
Studies investigating the suitability of SNOMED CT in COVID-19 datasets are still scarce. The purpose of this study was to evaluate the suitability of SNOMED CT for structured searches of COVID-19 studies, using the German Corona Consensus Dataset (GECCO) as example. Suitability of the international standard SNOMED CT was measured with the scoring system ISO/TS 21564, and intercoder reliability of two independent mapping specialists was evaluated. The resulting analysis showed that the majority of data items had either a complete or partial equivalent in SNOMED CT (complete equivalent: 141 items; partial equivalent: 63 items; no equivalent: 1 item). Intercoder reliability was moderate, possibly due to non-establishment of mapping rules and high percentage (74%) of different but similar concepts among the 86 non-equal chosen concepts. The study shows that SNOMED CT can be utilized for COVID-19 cohort browsing. However, further studies investigating mapping rules and further international terminologies are necessary.
研究调查 SNOMED CT 在 COVID-19 数据集的适用性仍然很少。本研究的目的是评估 SNOMED CT 用于 COVID-19 研究的结构化搜索的适用性,以德国 Corona 共识数据集(GECCO)为例。国际标准 SNOMED CT 的适用性是通过 ISO/TS 21564 评分系统来衡量的,并评估了两位独立映射专家的编码员可靠性。结果分析表明,大多数数据项在 SNOMED CT 中具有完整或部分等效项(完全等效项:141 项;部分等效项:63 项;无等效项:1 项)。编码员可靠性为中等,可能是由于映射规则尚未建立以及 86 个不等同选择的概念中存在 74%的不同但相似的概念所致。该研究表明,SNOMED CT 可用于 COVID-19 队列浏览。但是,需要进一步研究映射规则和更多的国际术语。