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一种用于临床指南协作制定与评估方法的定量评估。

A quantitative assessment of a methodology for collaborative specification and evaluation of clinical guidelines.

作者信息

Shalom Erez, Shahar Yuval, Taieb-Maimon Meirav, Bar Guy, Yarkoni Avi, Young Ohad, Martins Susana B, Vaszar Laszlo, Goldstein Mary K, Liel Yair, Leibowitz Akiva, Marom Tal, Lunenfeld Eitan

机构信息

Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University of Negev, Beer-Sheva 84105, Israel.

出版信息

J Biomed Inform. 2008 Dec;41(6):889-903. doi: 10.1016/j.jbi.2008.04.009. Epub 2008 May 6.

DOI:10.1016/j.jbi.2008.04.009
PMID:18550447
Abstract

We introduce a three-phase, nine-step methodology for specification of clinical guidelines (GLs) by expert physicians, clinical editors, and knowledge engineers and for quantitative evaluation of the specification's quality. We applied this methodology to a particular framework for incremental GL structuring (mark-up) and to GLs in three clinical domains. A gold-standard mark-up was created, including 196 plans and subplans, and 326 instances of ontological knowledge roles (KRs). A completeness measure of the acquired knowledge revealed that 97% of the plans and 91% of the KR instances of the GLs were recreated by the clinical editors. A correctness measure often revealed high variability within clinical editor pairs structuring each GL, but for all GLs and clinical editors the specification quality was significantly higher than random (p<0.01). Procedural KRs were more difficult to mark-up than declarative KRs. We conclude that given an ontology-specific consensus, clinical editors with mark-up training can structure GL knowledge with high completeness, whereas the main demand for correct structuring is training in the ontology's semantics.

摘要

我们介绍了一种由专家医师、临床编辑和知识工程师制定临床指南(GL)并对制定质量进行定量评估的三相九步法。我们将此方法应用于一个用于增量式GL结构化(标记)的特定框架以及三个临床领域的GL。创建了一个金标准标记,包括196个计划和子计划,以及326个本体知识角色(KR)实例。对所获取知识的完整性测量表明,临床编辑重新创建了97%的GL计划和91%的KR实例。正确性测量经常显示,在构建每个GL的临床编辑对中存在很大差异,但对于所有GL和临床编辑而言,制定质量显著高于随机水平(p<0.01)。程序性KR比声明性KR更难标记。我们得出结论,在给定特定本体共识的情况下,经过标记培训的临床编辑可以高度完整地构建GL知识,而正确构建的主要需求是对本体语义的培训。

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