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Providing Semantic Interoperability Between Clinical Care and Clinical Research Domains

机译:提供临床护理和临床研究领域之间的语义互操作性

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Improving the efficiency with which clinical research studies are conducted can lead to faster medication innovation and decreased time to market for new drugs. To increase this efficiency, the parties involved in a regulated clinical research study, namely, the sponsor, the clinical investigator and the regulatory body, each with their own software applications, need to exchange data seamlessly. However, currently, the clinical research and the clinical care domains are quite disconnected because each use different standards and terminology systems. In this paper, we describe an initial implementation of the Semantic Framework developed within the scope of SALUS project to achieve interoperability between the clinical research and the clinical care domains. In our Semantic Framework, the core ontology developed for semantic mediation is based on the shared conceptual model of both of these domains provided by the Biomedical Research Integrated Domain Group (BRIDG) initiative. The core ontology is then aligned with the extracted semantic models of the existing clinical care and research standards as well as with the ontological representations of the terminology systems to create a “model of meaning” for enabling semantic mediation. Although SALUS is a research and development effort rather than a product, the current SALUS knowledge base contains around 4.7 million triples representing BRIDG DAM, HL7 CDA model, Clinical Data Interchange Standards Consortium standards, and several terminology ontologies. In order to keep the reasoning process within acceptable limits without sacrificing the quality of mediation, we took an engineering approach by developing a number of heuristic mechanisms. The results indicate that it is possible to build a robust and scalable semantic framework with a solid theoretical foundation for achieving interoperability between the clinical research and clinical care domains.
机译:提高进行临床研究的效率可以加快药物创新速度,并缩短新药上市时间。为了提高这种效率,参与受监管的临床研究的各方,即申办者,临床研究者和监管机构,各自都有自己的软件应用程序,需要无缝地交换数据。但是,目前,由于各自使用不同的标准和术语系统,因此临床研究和临床护理领域之间存在很大的脱节。在本文中,我们描述了在SALUS项目范围内开发的语义框架的初始实现,以实现临床研究与临床护理领域之间的互操作性。在我们的语义框架中,为语义中介开发的核心本体基于由生物医学研究集成域小组(BRIDG)计划提供的这两个域的共享概念模型。然后,将核心本体与现有临床护理和研究标准的提取语义模型以及术语系统的本体表示相匹配,以创建用于语义中介的“意义模型”。尽管SALUS是一项研发工作,而不是产品,但当前的SALUS知识库包含约470万个三元组,分别代表BRIDG DAM,HL7 CDA模型,临床数据交换标准联盟标准和几种术语本体。为了将推理过程保持在可接受的范围内而又不影响调解的质量,我们通过开发多种启发式机制采取了一种工程方法。结果表明,有可能建立一个强大而可扩展的语义框架,并为实现临床研究与临床护理领域之间的互操作性奠定坚实的理论基础。

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