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Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework

机译:基于语义Web服务框架的可共享临床决策支持系统的设计与开发

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Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.
机译:临床决策支持(CDS)系统为临床医生和其他医疗保健利益相关者提供了针对患者的评估或建议,以协助临床决策过程。尽管已证明CDS系统具有改善医疗质量的潜力,但CDS系统的广泛可用性主要受到异构医疗信息系统之间共享CDS知识的难度和成本的限制。这项研究的目的是设计和开发可应对这一挑战的可共享临床决策支持(S-CDS)系统。基本知识库由满足核心CDS需求的独立且可重用的知识模块(KM)组成,其中每个KM在标准信息模型,术语和表示形式主义的基础上在语义上得到了很好的定义。开发了语义Web服务框架,以跨各种CDS应用程序和护理设置识别,访问和利用这些KM。 S-CDS系统已在两个不同的客户端CDS应用程序中得到验证。模型级别的评估结果证实了连贯的知识表示。应用程序级评估结果达到了98.66%的整体准确性和96.98%的完整性。评估结果表明了该方法的技术可行性和应用前景。与其他CDS工程工作相比,我们的方法可促进系统开发和实施,并提高系统的可维护性,可扩展性和效率,这有助于在医疗保健领域广泛采用有效的CDS。

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