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使用临床质量语言实施临床决策支持服务以检测潜在药物相互作用

Implementation of Clinical Decision Support Services to Detect Potential Drug-Drug Interaction Using Clinical Quality Language.

作者信息

Nguyen Binh-Phi, Reese Thomas, Decker Stefen, Malone Daniel, Boyce Richard D, Beyan Oya

机构信息

Informatik 5, RWTH Aachen University, Aachen, Germany.

Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.

出版信息

Stud Health Technol Inform. 2019 Aug 21;264:724-728. doi: 10.3233/SHTI190318.

Abstract

Potential drug-drug interactions (PDDI) rules are currently represented without any common standard making them difficult to update, maintain, and exchange. The PDDI minimum information model developed by the Semantic Web in the Healthcare and Life Sciences Community Group describes PDDI knowledge in an actionable format. In this paper, we report implementation and evaluation of CDS Services which represent PDDI knowledge with Clinical Quality Language (CQL). The suggested solution is based on emerging standards including CDS Hooks, FHIR, and CQL. Two use cases are selected, implemented with CQL rules and tested at the Connectathon held at the 32nd Annual Plenary & Working Group Meeting of HL7.

摘要

目前,潜在药物相互作用(PDDI)规则的呈现方式缺乏任何通用标准,这使得它们难以更新、维护和交换。医疗保健与生命科学社区组语义网开发的PDDI最小信息模型以一种可操作的格式描述PDDI知识。在本文中,我们报告了使用临床质量语言(CQL)表示PDDI知识的CDS服务的实施与评估情况。所建议的解决方案基于包括CDS挂钩、FHIR和CQL在内的新兴标准。我们选择了两个用例,用CQL规则进行实施,并在HL7第32届年度全体会议和工作组会议举办的互操作性测试大会上进行了测试。

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