Cognitive engineering and health informatics: Applications and intersections

被引:14
|
作者
Hettinger, A. Zachary [1 ,2 ]
Roth, Emilie M. [3 ]
Bisantz, Ann M. [4 ]
机构
[1] Georgetown Univ, Sch Med, Dept Emergency Med, Washington, DC USA
[2] MedStar Hlth, Natl Ctr Human Factors Healthcare, 3007 Tilden St NW,Suite 7M, Washington, DC 20008 USA
[3] Roth Cognit Engn, Stanford, CA USA
[4] Univ Buffalo State Univ New York, Dept Ind & Syst Engn, Buffalo, NY USA
基金
美国医疗保健研究与质量局;
关键词
Cognitive informatics; Cognitive engineering; Health information technology; Emergency medicine; Review; ECOLOGICAL INTERFACE DESIGN; CRITICAL DECISION METHOD; PATIENT SAFETY; TASK-ANALYSIS; SUPPORT-SYSTEMS; WORK ANALYSIS; CARE; COMMUNICATION; TECHNOLOGY; ARTIFACTS;
D O I
10.1016/j.jbi.2017.01.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cognitive engineering is an applied field with roots in both cognitive science and engineering that has been used to support design of information displays, decision support, human-automation interaction, and training in numerous high risk domains ranging from nuclear power plant control to transportation and defense systems. Cognitive engineering provides a set of structured, analytic methods for data collection and analysis that intersect with and complement methods of Cognitive Informatics. These methods support discovery of aspects of the work that make performance challenging, as well as the knowledge, skills, and strategies that experts use to meet those challenges. Importantly, cognitive engineering methods provide novel representations that highlight the inherent complexities of the work domain and traceable links between the results of cognitive analyses and actionable design requirements. This article provides an overview of relevant cognitive engineering methods, and illustrates how they have been applied to the design of health information technology (HIT) systems. Additionally, although cognitive engineering methods have been applied in the design of user-centered informatics systems, methods drawn from informatics are not typically incorporated into a cognitive engineering analysis. This article presents a discussion regarding ways in which data-rich methods can inform cognitive engineering. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:21 / 33
页数:13
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