Cognitive Engineering for Complex Decision Making & Problem Solving in Acute Care

描述（由申请人提供）：拟议的研究应用认知工程方法来理解和支持复杂的，认知和工作活动在急性护理环境中，使用急诊医学作为研究背景。该研究将提供工作领域复杂性和具有挑战性的意义，决策和规划/重新规划任务的基本和全面的图片;沿着个人和团队的专业知识，以满足这些挑战。这项研究使用急诊医学作为“现场实验室”，因为它既阐明了认知工作中一些最具挑战性的条件-高风险，时间压力和不确定性-因此提供了一个很好的机会将研究结果推广到其他复杂的医疗保健环境;同时提供一种环境，这种环境可以明显地受益于决策辅助，可视化，以及其他支持性技术，这些技术可以从认知工程分析中产生。该项目利用了研究团队在医疗保健工作（包括急诊医学）和其他高风险工作环境的人为因素和认知工程分析方面的丰富经验;并评估了旨在支持复杂认知工作的信息显示和决策支持技术的可用性和有效性。该应用程序解决了基本的，研究性质的呼吁应用程序，包括一个全面的认知工程分析的急诊医学沿着有针对性的发展和评估的可视化，决策支持，和其他辅助解决方案。这项研究的贡献将包括对高强度医疗环境中认知和临床工作性质的基本理解-包括与工作相关的复杂性，以及从业人员的专业知识，知识和技能-这可以为设计支持临床工作的健康IT解决方案提供基础，并提高医疗保健的有效性。此外，该研究将开发和评估通过认知工程分析确定的一组目标需求的范例解决方案，从而为将认知工程分析转化为设计提供方法论示例和“概念验证”。

DESCRIPTION (provided by applicant): The proposed research applies cognitive engineering methods to understand and support complex, cognition and work activities within the acute care environment, using emergency medicine as the research setting. The research will provide a fundamental and comprehensive picture of work domain complexities and challenging sensemaking, decision-making, and planning/replanning tasks; along with the individual and team expertise required to meet those challenges. The research uses emergency medicine as a "field laboratory" because it both explicates some of the most challenging conditions for cognitive work - high risk, time-pressure, and uncertainty - and therefore provides a strong opportunity to generalize findings to other complex health care environments; while at the same time providing an environment which can clearly benefit from the decision aids, visualizations, and other supportive technologies that can result from cognitive engineering analyses. This project utilizes the extensive prior experience of research team in human factors and cognitive engineering analyses of health care work (including emergency medicine) and other high risk work environments; and evaluating the usability and effectiveness of information displays and decision support technologies designed to support complex, cognitive work. The application addresses the fundamental, research nature of the call for applications by including a comprehensive cognitive engineering analysis of emergency medicine along with targeted development and evaluation of visualizations, decision- support, and other aiding solutions. Contributions from this research will include a fundamental understanding of the nature of cognition and clinical work in a high intensity medical environment - including both work related complexities, and practitioner expertise, knowledge, and skills - which can provided a basis for the design of health IT solutions which support clinical work and improve the effectiveness of medical care. Additionally, the research will develop and evaluate exemplar solutions for a targeted set of needs identified through the cognitive engineering analysis, thus providing a methodological example and "proof-of-concept" for translating cognitive engineering analyses into designs.