使用语义网进行大规模医疗保健数据集成与分析。
Large scale healthcare data integration and analysis using the semantic web.
作者信息
Timm John, Renly Sondra, Farkash Ariel
机构信息
IBM Almaden Research Center 640 Harry Rd, San Jose, CA 95120, US.
出版信息
Stud Health Technol Inform. 2011;169:729-33.
Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.
只有当内容的语义得到明确界定并在异构数据源之间一致实施时,医疗保健数据的互操作性才能实现。实现这些互操作性目标需要多个领域的专家进行协作。本文介绍了一种工具,该工具将语义网技术与通用工具集成在一起,以促进跨领域协作开发,实现数据互操作性。我们的方法分为数据协调与表示、模型转换和实例生成几个阶段。我们将我们的方法应用于欧盟资助的项目Hypergenes,在该项目中,我们使用我们的方法通过CDA模板对原发性高血压疾病模型进行处理。我们的领域专家合作伙伴包括临床提供者、临床领域研究人员、医疗信息技术专家以及各种临床数据消费者。我们表明,将语义网技术引入医疗保健互操作性工具包增加了有益协作的机会,从而改善了患者护理和临床研究结果。