A scalable architecture for incremental specification and maintenance of procedural and declarative clinical decision-support knowledge.

The open medical informatics journal Pub Date : 2010-01-01 Epub Date: 2010-12-14 DOI:10.2174/1874431101004010255
Avner Hatsek, Yuval Shahar, Meirav Taieb-Maimon, Erez Shalom, Denis Klimov, Eitan Lunenfeld
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Abstract

Clinical guidelines have been shown to improve the quality of medical care and to reduce its costs. However, most guidelines exist in a free-text representation and, without automation, are not sufficiently accessible to clinicians at the point of care. A prerequisite for automated guideline application is a machine-comprehensible representation of the guidelines. In this study, we designed and implemented a scalable architecture to support medical experts and knowledge engineers in specifying and maintaining the procedural and declarative aspects of clinical guideline knowledge, resulting in a machine comprehensible representation. The new framework significantly extends our previous work on the Digital electronic Guidelines Library (DeGeL) The current study designed and implemented a graphical framework for specification of declarative and procedural clinical knowledge, Gesher. We performed three different experiments to evaluate the functionality and usability of the major aspects of the new framework: Specification of procedural clinical knowledge, specification of declarative clinical knowledge, and exploration of a given clinical guideline. The subjects included clinicians and knowledge engineers (overall, 27 participants). The evaluations indicated high levels of completeness and correctness of the guideline specification process by both the clinicians and the knowledge engineers, although the best results, in the case of declarative-knowledge specification, were achieved by teams including a clinician and a knowledge engineer. The usability scores were high as well, although the clinicians' assessment was significantly lower than the assessment of the knowledge engineers.

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程序性和声明性临床决策支持知识增量规范和维护的可扩展架构。
事实证明,临床指南可以提高医疗质量,降低医疗成本。然而,大多数指南都是以自由文本的形式存在,如果不实现自动化,临床医生就无法在医疗点充分获取这些指南。自动应用指南的一个先决条件是指南能被机器理解。在这项研究中,我们设计并实施了一个可扩展的架构,以支持医学专家和知识工程师指定和维护临床指南知识的程序性和声明性方面,从而形成机器可理解的表征。新框架大大扩展了我们之前在数字电子指南图书馆(DeGeL)方面的工作。 目前的研究设计并实现了一个用于规范声明性和程序性临床知识的图形框架--Gesher。我们进行了三个不同的实验,以评估新框架主要方面的功能和可用性:程序性临床知识的规范、陈述性临床知识的规范以及对给定临床指南的探索。实验对象包括临床医生和知识工程师(总计 27 人)。评估结果表明,临床医生和知识工程师在指南说明过程中的完整性和正确性都很高,但在陈述性知识说明方面,由一名临床医生和一名知识工程师组成的团队取得的结果最好。可用性得分也很高,尽管临床医生的评估明显低于知识工程师的评估。
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