Semantics in action: a guide for representing clinical data elements with SNOMED CT.

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Julien Ehrsam, Christophe Gaudet-Blavignac, Mirjam Mattei, Monika Baumann, Christian Lovis
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引用次数: 0

Abstract

Background: 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.

Results: 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).

Conclusions: 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.

语义的作用:用SNOMED CT表示临床数据元素的指南。
背景:临床数据丰富,但仍缺乏有意义的再利用。使用SNOMED CT的语义表示可以改善研究、公共卫生和护理质量。然而,缺乏将这一过程工业化的适用准则妨碍了可持续性和可重复性。这项工作描述了SNOMED CT数据元素语义表示的指南,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国际和其他团体提出的准则。然而,人工专家驱动表示的大规模应用导致了额外规则的发展。结果:通过焦点小组迭代开发出八条分步指南。通过使用和不断增长的覆盖率不断改进,它们在实践中进行测试,以确保它们达到预期的结果。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。它们被分为四组,分别适用于正确理解数据(上下文)和正确使用SNOMED CT(首先是单一概念,批准后协调,扩展后协调)。结论:这项工作为使用SNOMED CT进行语义表示提供了一个实用的框架,通过推广一种通用方法,提高了准确性和一致性。在解决大规模实施的挑战的同时,该指南支持从以数据为中心的模型转向以语义为中心的方法,利用互操作性和更有效地重用临床数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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