Ryu Hyejin, Sung Sumi, Park Kuenyoul, Kim Min-Sun, Oh YeJin, Yu Shinae, Cho Eun-Jung, Kim Sollip
Department of Laboratory Medicine, Seegene Medical Foundation, Seoul 04805, Republic of Korea.
College of Nursing, Research Institute of Nursing Science, Chungbuk National University, Cheongju 28644, Republic of Korea.
Int J Med Inform. 2025 Dec;204:106055. doi: 10.1016/j.ijmedinf.2025.106055. Epub 2025 Jul 21.
We aimed to evaluate and compare the applicability of Logical Observation Identifiers Names and Codes (LOINC) and SNOMED CT in mapping frequently requested panel tests.
Frequently requested panel tests were identified from the test records of two major referral laboratories. Subsequently, LOINC and SNOMED CT mappings were cross-validated, and the results were classified based on pre-defined criteria. A consensus was reached among the teams. A comparative structural analysis was performed by aligning the mapped SNOMED CT concepts with LOINC codes and visualizing the selected items with conditionality to evaluate the differences in representation.
We conducted 23 panel tests. Exact mapping was achieved for 87.0% of the panel tests using LOINC: two failures were recorded due to the lack of a suitable code, and one panel test was classified as narrowly mapped. In contrast, SNOMED CT achieved the exact mapping for 78.2% of the panel tests, with 12 mappings requiring post-coordination to represent the test concepts. SNOMED CT mapping failures stemmed from missing primitive concepts and limited pre-coordinated codes. LOINC offered detailed component specifications and predefined panel codes. In contrast, SNOMED CT relied on post-coordination to address gaps in the pre-defined codes, allowing the addition of new combinations where necessary.
LOINC demonstrated advantages in mapping frequently performed panel tests with higher exact mapping rates and structured panel codes. However, leveraging SNOMED CT's flexibility through initiatives such as the LOINC Ontology project could enhance interoperability and standardization in laboratory data exchange.
我们旨在评估和比较逻辑观察标识符名称和代码（LOINC）与医学系统命名法临床术语（SNOMED CT）在映射常见组合检验中的适用性。
从两家主要转诊实验室的检验记录中识别出常见组合检验。随后，对LOINC和SNOMED CT映射进行交叉验证，并根据预定义标准对结果进行分类。团队之间达成了共识。通过将映射的SNOMED CT概念与LOINC代码对齐，并以条件性方式可视化所选项目，进行了比较结构分析，以评估表示方式的差异。
我们进行了23项组合检验。使用LOINC对87.0%的组合检验实现了精确映射：由于缺乏合适代码记录了2次失败，1项组合检验被归类为狭义映射。相比之下，SNOMED CT对78.2%的组合检验实现了精确映射，有12项映射需要进行后协调以表示检验概念。SNOMED CT映射失败源于缺少原始概念和预协调代码有限。LOINC提供了详细的组件规范和预定义组合代码。相比之下，SNOMED CT依靠后协调来弥补预定义代码中的空白，允许在必要时添加新的组合。
LOINC在映射频繁执行的组合检验方面表现出优势，具有更高的精确映射率和结构化组合代码。然而，通过诸如LOINC本体项目等举措利用SNOMED CT的灵活性，可以增强实验室数据交换中的互操作性和标准化。
