电子健康记录 (EHR) 信息模型（例如模板和原型）的重用可能会带来各种好处，包括更高的标准化、集成性、互操作性、提高开发 EHR 系统的生产力，并释放基于医疗记录的潜在人工智能应用程序。该文献介绍了 EHR 建模标准、知识组织系统 (KOS) 和 EHR 数据重用方面的最新进展。然而，改善 EHR 信息模型重用的方法、开发流程和框架仍然匮乏。本研究提出了一个名为BioFrame的软件工程框架，并分析了在EHR系统开发过程中如何改进EHR信息模型的重用。在开发BioFrame框架时考虑了从系统评价中确定的EHR标准和KOS，包括本体。我们使用 OpenEHR 的结构来建模模板和原型，以及它与肿瘤学领域使用的国际 KOS 的关系。我们的框架应用于儿科肿瘤学。对三份有关营养的数据输入表格和第一次儿科肿瘤咨询期间使用的一份数据输入表格进行了分析，以衡量信息模型的重用。国际 KOS 的遵守率比原始表格增加了 18%。在所分析的所有 12 个场景中，概念的重用率都有所增加，原始形式的平均重用率为 6.55%，而使用 BioFrame 的平均重用率为 17.1%，导致显着差异。我们的结果表明，由于工程流程而实现了更高的重用率结合语义工件，可以更好地遵守 EHR 标准。这揭示了开发旨在重用 EHR 信息模型的新方法和框架的潜力。需要进行更多研究来评估 EHR 信息模型的重用对互操作性、EHR 数据重用和数据质量的影响，并评估其他健康领域的拟议框架。版权所有 © 2024 Elsevier Inc. 保留所有权利。

The reuse of Electronic Health Records (EHR) information models (e.g., templates and archetypes) may bring various benefits, including higher standardization, integration, interoperability, increased productivity in developing EHR systems, and unlock potential Artificial Intelligence applications built on top of medical records. The literature presents recent advances in standards for modeling EHR, in Knowledge Organization Systems (KOS) and EHR data reuse. However, methods, development processes, and frameworks to improve the reuse of EHR information models are still scarce. This study proposes a software engineering framework, named BioFrame, and analyzes how the reuse of EHR information models can be improved during the development of EHR systems.EHR standards and KOS, including ontologies, identified from systematic reviews were considered in developing the BioFrame framework. We used the structure of the OpenEHR to model templates and archetypes, as well as its relationship to international KOS used in the oncology domain. Our framework was applied in the context of pediatric oncology. Three data entry forms concerning nutrition and one utilized during the first pediatric oncology consultations were analyzed to measure the reuse of information models.There was an increase in the adherence rate to international KOS of 18% to the original forms. There was an increase in the concepts reused in all 12 scenarios analyzed, with an average reuse of 6.55% in the original forms compared to 17.1% using BioFrame, resulting in significant differences.Our results point to higher reuse rates achieved due to an engineering process that provided greater adherence to EHR standards combined with semantic artifacts. This reveals the potential to develop new methods and frameworks aimed at EHR information model reuse. Additional research is needed to evaluate the impacts of the reuse of the EHR information model on interoperability, EHR data reuse, and data quality and assess the proposed framework in other health domains.Copyright © 2024 Elsevier Inc. All rights reserved.