A CDE-based data structure for radiotherapeutic decision-making in breast cancer.

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Fabio Dennstädt, Maximilian Schmalfuss, Johannes Zink, Janna Hastings, Roberto Gaio, Max Schmerder, Nikola Cihoric, Paul Martin Putora
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引用次数: 0

Abstract

Background: The growing complexity of oncology and radiation therapy demands structured and precise data management strategies. The National Institutes of Health (NIH) have introduced Common Data Elements (CDEs) as a uniform approach to facilitate consistent data collection. However, there is currently a lack of a comprehensive set of CDEs for describing situations for and within radiation oncology. Specifically for breast cancer, where radiotherapeutic decision-making is complex and based on multiple diverse criteria, there is a clear need for more standardized data. Aim of this study was to create a CDE-based data structure for radiotherapeutic decision-making in breast cancer to promote structured data collection on the level of a local hospital.

Methods: Between May 2023 and May 2024, we conducted a case study at the radiation therapy department of a local hospital to develop a CDE-based data structure for radiotherapeutic decision-making in breast cancer. Local Standard Operating Procedures (SOPs) were analyzed to identify relevant decision-making criteria used in clinical practice. Corresponding CDEs were identified, and a structured data framework based on these CDEs was created. The framework was translated into machine-readable JavaScript Object Notation (JSON) format. Six clinical practice guidelines of the American Society for Radiation Oncology (ASTRO) were analyzed as full text to evaluate how many guideline recommendations and corresponding decision-making criteria could be represented using our framework.

Results: We identified 31 decision-making criteria from local SOPs, formalized into 46 CDEs. A hierarchical structure within an object-oriented data framework was created and converted into JSON format. 94 recommendations with mentioning of decision-making criteria in 216 cases were identified across the six ASTRO guidelines. In 151 cases (70.0%) the mentioned criterion could be presented with the data framework.

Conclusions: The CDE-based data structure provides a standardized, machine-readable framework for documenting and exchanging radiotherapeutic decision-making data in breast cancer patients. While further refinement is needed for broader interoperability, this approach facilitates structured data collection, enhances IT integration and supports standardized communication across different stakeholders.

基于cde的乳腺癌放射治疗决策数据结构。
背景:肿瘤和放射治疗日益复杂,需要结构化和精确的数据管理策略。美国国立卫生研究院(NIH)引入了公共数据元素(CDEs)作为统一的方法,以促进一致的数据收集。然而,目前缺乏一套全面的cde来描述放射肿瘤学的情况。特别是对于乳腺癌,放射治疗的决策是复杂的,并且基于多种不同的标准,显然需要更多的标准化数据。本研究旨在建立基于cde的乳腺癌放射治疗决策数据结构,以促进地方医院层面的结构化数据收集。方法:在2023年5月至2024年5月期间,我们在当地一家医院的放射治疗部门进行了案例研究,以开发基于cde的乳腺癌放射治疗决策数据结构。分析当地标准操作程序(sop),以确定临床实践中使用的相关决策标准。识别相应的cde,并基于这些cde创建结构化数据框架。该框架被翻译成机器可读的JavaScript对象表示法(JSON)格式。对美国放射肿瘤学学会(ASTRO)的6份临床实践指南进行全文分析,以评估有多少指南建议和相应的决策标准可以用我们的框架来表示。结果:我们从地方标准操作程序中确定了31个决策标准,并将其形式化为46个cde。在面向对象的数据框架中创建了一个层次结构,并将其转换为JSON格式。在六项ASTRO准则中确定了94项建议,其中提到了216项决策标准。在151例(70.0%)病例中,上述标准可以与数据框架一起呈现。结论:基于cde的数据结构为记录和交换乳腺癌患者的放疗决策数据提供了一个标准化的、机器可读的框架。虽然需要进一步细化以实现更广泛的互操作性,但这种方法促进了结构化数据收集,增强了IT集成,并支持不同涉众之间的标准化通信。
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
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
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