Das A K, Shahar Y, Tu S W, Musen M A
Section on Medical Informatics, Stanford University School of Medicine, California 94305-5479.
Proc Annu Symp Comput Appl Med Care. 1994:320-4.
The inability of many clinical decision-support applications to integrate with existing databases limits the wide-scale deployment of such systems. To overcome this obstacle, we have designed a data-interpretation module that can be embedded in a general architecture for protocol-based reasoning and that can support the fundamental task of detecting temporal abstractions. We have developed this software module by coupling two existing systems--RESUME and Chronus--that provide complementary temporal-abstraction techniques at the application and the database levels, respectively. Their encapsulation into a single module thus can resolve the temporal queries of protocol planners with the domain-specific knowledge needed for the temporal-abstraction task and with primary time-stamped data stored in autonomous clinical databases. We show that other computer methods for the detection of temporal abstractions do not scale up to the data- and knowledge-intensive environments of protocol-based decision-support systems.
许多临床决策支持应用程序无法与现有数据库集成,这限制了此类系统的大规模部署。为克服这一障碍,我们设计了一个数据解释模块,该模块可嵌入基于协议推理的通用架构中,并支持检测时间抽象这一基本任务。我们通过耦合两个现有系统——RESUME和Chronus——开发了这个软件模块,这两个系统分别在应用程序和数据库级别提供互补的时间抽象技术。因此,将它们封装到一个模块中,可以利用时间抽象任务所需的特定领域知识以及存储在自主临床数据库中的原始时间戳数据来解析协议规划器的时间查询。我们表明,其他用于检测时间抽象的计算机方法无法扩展到基于协议的决策支持系统的数据密集型和知识密集型环境。