Ehrsam Julien, Gaudet-Blavignac Christophe, Mattei Mirjam, Baumann Monika, Lovis Christian
Division of Medical Information Sciences, Diagnostic Department, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, Geneva, 1205, Switzerland.
Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, Geneva, 1205, Switzerland.
J Biomed Semantics. 2025 Mar 27;16(1):7. doi: 10.1186/s13326-025-00326-5.
Clinical data is abundant, but meaningful reuse remains lacking. Semantic representation using SNOMED CT can improve research, public health, and quality of care. However, the lack of applied guidelines to industrialise the process hinders sustainability and reproducibility. This work describes a guide for semantic representation of data elements with SNOMED CT, addressing challenges encountered during its application. The representation of the institutional data warehouse started with the guidelines proposed by SNOMED International and other groups. However, the application at large scale of manual expert-driven representation led to the development of additional rules.
An eight-rule step-by-step guide was developed iteratively through focus groups. Continuously refined by usage and growing coverage, they are tested in practice to ensure they achieve the desired outcome. All rules prioritize maintaining semantic accuracy, which is the main goal of our strategy. They are divided into four groups which apply to understanding the data correctly (Context), and to using SNOMED CT properly (Single concepts first, Approved post-coordination, Extending post-coordination).
This work provides a practical framework for semantic representation using SNOMED CT, enabling greater accuracy and consistency by promoting a common method. While addressing challenges of large-scale implementation, the guide supports the drive from data centric models to a semantic centric approach, leveraging interoperability and more effective reuse of clinical data.
临床数据丰富，但仍缺乏有意义的再利用。使用SNOMED CT进行语义表示可改善研究、公共卫生和医疗质量。然而，缺乏将该过程工业化的应用指南阻碍了其可持续性和可重复性。这项工作描述了一个使用SNOMED CT对数据元素进行语义表示的指南，解决了其应用过程中遇到的挑战。机构数据仓库的表示始于SNOMED国际组织和其他团体提出的指南。然而，大规模应用手动专家驱动的表示方法导致了额外规则的制定。
通过焦点小组迭代制定了一个八步指南。通过使用和不断扩大的覆盖范围不断完善，这些规则在实践中进行了测试，以确保它们能达到预期结果。所有规则都优先考虑保持语义准确性，这是我们策略的主要目标。它们分为四组，分别适用于正确理解数据（上下文）以及正确使用SNOMED CT（先使用单个概念、批准的后置协调、扩展的后置协调）。
这项工作提供了一个使用SNOMED CT进行语义表示的实用框架，通过推广一种通用方法实现更高的准确性和一致性。在应对大规模实施挑战的同时，该指南支持从以数据为中心的模型向以语义为中心的方法转变，利用临床数据的互操作性和更有效的再利用。
