Sintchenko Vitali, Coiera Enrico
Centre for Infectious Diseases and Microbiology-Public Health, Western Clinical School, The University of Sydney, New South Wales, Australia.
Methods Mol Med. 2008;141:331-51. doi: 10.1007/978-1-60327-148-6_18.
There is a growing demand for tools to support clinicians utilize genomic results generated by molecular diagnostic and cytogenetic methods in support of their decision-making. This chapter reviews existing experience and methods for the design, implementation and evaluation of clinical bioinformatics electronic decision support systems (EDSS). It provides a roadmap for identifying decision tasks for automation and selecting optimal tools for building task-specific systems. Key success factors for EDSS implementation and evaluation are also outlined.
对于支持临床医生利用分子诊断和细胞遗传学方法产生的基因组结果以辅助其决策的工具，需求日益增长。本章回顾了临床生物信息学电子决策支持系统（EDSS）设计、实施和评估的现有经验及方法。它提供了一个路线图，用于确定自动化的决策任务以及选择构建特定任务系统的最佳工具。还概述了EDSS实施和评估的关键成功因素。
