A Validation Tool (VaPCE) for Postcoordinated SNOMED CT Expressions: Development and Usability Study.

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS
Tessa Ohlsen, Viola Hofer, Josef Ingenerf
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引用次数: 0

Abstract

Background: The digitalization of health care has increased the demand for efficient data exchange, emphasizing semantic interoperability. SNOMED Clinical Terms (SNOMED CT), a comprehensive terminology with over 360,000 medical concepts, supports this need. However, it cannot cover all medical scenarios, particularly in complex cases. To address this, SNOMED CT allows postcoordination, where users combine precoordinated concepts with new expressions. Despite SNOMED CT's potential, the creation and validation of postcoordinated expressions (PCEs) remain challenging due to complex syntactic and semantic rules.

Objective: This work aims to develop a tool that validates postcoordinated SNOMED CT expressions, focusing on providing users with detailed, automated correction instructions for syntactic and semantic errors. The goal is not just validation, but also offering user-friendly, actionable suggestions for improving PCEs.

Methods: A tool was created using the Fast Healthcare Interoperability Resource (FHIR) service $validate-code and the terminology server Ontoserver to check the correctness of PCEs. When errors are detected, the tool processes the SNOMED CT Concept Model in JSON format and applies predefined error categories. For each error type, specific correction suggestions are generated and displayed to users. The key added value of the tool is in generating specific correction suggestions for each identified error, which are displayed to the users. The tool was integrated into a web application, where users can validate individual PCEs or bulk-upload files. The tool was tested with real existing PCEs, which were used as input and validated. In the event of errors, appropriate error messages were generated as output.

Results: In the validation of 136 PCEs from 304 FHIR Questionnaires, 18 (13.2%) PCEs were invalid, with the most common errors being invalid attribute values. Additionally, 868 OncoTree codes were evaluated, resulting in 161 (20.9%) PCEs containing inactive concepts, which were successfully replaced with valid alternatives. A user survey reflects a favorable evaluation of the tool's functionality. Participants found the error categorization and correction suggestions to be precise, offering clear guidance for addressing issues. However, there is potential for enhancement, particularly regarding the level of detail in the error messages.

Conclusions: The validation tool significantly improves the accuracy of postcoordinated SNOMED CT expressions by not only identifying errors but also offering detailed correction instructions. This approach supports health care professionals in ensuring that their PCEs are syntactically and semantically valid, enhancing data quality and interoperability across systems.

后协调SNOMED CT表达的验证工具(VaPCE):开发和可用性研究。
背景:医疗数字化对高效数据交换的需求增加,强调语义互操作性。SNOMED临床术语(SNOMED CT)是一个包含超过360,000个医学概念的综合术语,可满足这一需求。但是,它不能涵盖所有的医疗情况,特别是在复杂的情况下。为了解决这个问题,SNOMED CT允许后协调,用户将预先协调的概念与新的表达式结合起来。尽管SNOMED CT具有潜力,但由于复杂的语法和语义规则,后协调表达式(pce)的创建和验证仍然具有挑战性。目的:本工作旨在开发一种验证后协调SNOMED CT表达式的工具,重点是为用户提供详细的、自动的语法和语义错误纠正指导。目标不仅仅是验证,而且还为改进pce提供用户友好的、可操作的建议。方法:使用快速医疗保健互操作性资源(FHIR)服务$validate-code和术语服务器Ontoserver创建一个工具来检查pce的正确性。当检测到错误时,工具以JSON格式处理SNOMED CT概念模型,并应用预定义的错误类别。针对每种错误类型,系统会生成具体的纠正建议,并显示给用户。该工具的关键附加价值在于为每个已识别的错误生成特定的纠正建议,并将其显示给用户。该工具被集成到一个web应用程序中,用户可以在其中验证单个pce或批量上传文件。该工具使用真实的现有pce进行测试,这些pce用作输入并进行验证。如果发生错误,将生成适当的错误消息作为输出。结果:在304份FHIR问卷的136份pce验证中,18份(13.2%)pce无效,最常见的错误是属性值无效。此外,对868个OncoTree代码进行了评估,其中161个(20.9%)pce包含无效概念,这些概念被有效的替代方案成功替换。用户调查反映了对工具功能的良好评价。与会者认为,错误分类和纠正建议是精确的,为解决问题提供了明确的指导。但是,存在增强的潜力,特别是关于错误消息中的详细级别。结论:验证工具不仅能识别错误,还能提供详细的纠正指导,显著提高了后协调SNOMED CT表达的准确性。该方法支持医疗保健专业人员确保其pce在语法和语义上有效,从而增强数据质量和跨系统的互操作性。
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
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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