DesAutels Spencer J, Fox Zachary E, Giuse Dario A, Williams Annette M, Kou Qing-Hua, Weitkamp Asli, Neal R Patel, Bettinsoli Giuse Nunzia
Center for Knowledge Management, Vanderbilt University Medical Center, Nashville, TN.
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
AMIA Annu Symp Proc. 2017 Feb 10;2016:504-513. eCollection 2016.
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.
临床决策支持(CDS)知识随着时间推移嵌入到成熟的医疗系统中,为信息组织、维护和重用带来了一个有趣且复杂的机遇。要全面了解所有决策支持,需要深入了解每个临床系统以及最新证据的专业知识。这种临床决策支持方法为统一和外化基于规则的决策支持中的知识提供了契机。受机构将决策支持内容迁移到新临床系统时对其进行优先级排序需求的驱动,知识管理与健康信息技术中心团队运用其独特的专业知识从各个系统中提取内容,通过单一可扩展架构进行组织,并通过新创建的临床支持知识获取与存档工具(CS-KAAT)将其呈现出来以供发现和重用。CS-KAAT可以构建和维护临床系统所需的底层知识基础设施。