A Human Factors and Systems Engineering Approach for Understanding the Diagnostic Process and Associated Safety Hazards in the Emergency Department

诊断错误是常见的，致命的，昂贵的。每年有1200万美国人经历诊断性疾病 门诊护理中的错误，包括急诊科（ED）中的错误，其中一半以上具有潜在的伤害。 艾德临床实践作为快节奏的社会技术工作系统特别容易出现诊断错误， 高风险、高适应性和复杂性。2016年美国国家医学院（NAM）的报告是一份 迫切需要更多关于诊断安全性的研究，特别是关于ED的研究。艾德诊断 是认知密集型的工作，分布在可能位于同一地点或不位于同一地点的团队成员之间。有很 对艾德诊断过程的显著“实时”细节的理解有限， 工作系统中的绩效塑造因素。没有对艾德诊断进行结构化深入分析 作为“实时艾德工作”的一部分，即“完成工作”，我们将继续努力设计 有效、可持续的干预措施，以提高诊断安全性。因此，我们提出了一个为期三年的多- 基于社会技术系统方法和宏观认知的艾德现场多方法实地研究 框架，这是对认知任务的研究，这些任务表征了人们在自然环境中如何思考。我们 有三个具体目标：（1）目标1。了解提供者（医生和高级实践提供者）的工作 参与艾德诊断并识别相关的绩效塑造因素。(2)AIM 2.了解 参与艾德诊断的协作（面向团队）工作，并确定相关的绩效塑造 因素(3)AIM 3.对急诊室的诊断过程进行主动风险评估。 AIM 1和AIM 2将通过使用各种数据进行深入的定性研究来实现 收集方法（观察，访谈）和认知任务分析技术。数据分析将 产生一系列输出，如过程图，诊断中涉及的宏观认知和程序任务， 信息流图、角色网络图等。AIM 3将使用两个互补的主动 风险评估方法，以评估故障模式和性能形成因素，并确定可能的 改善艾德诊断安全性的干预措施：（1）医疗保健失效模式和效应分析（HFMEA）;（2） 基于功能共振分析方法（弗拉姆）的“假设”风险分析。此外，我们将开发一个 研究方法概要/指南，供有兴趣进行类似的诊断安全性研究者参考。 本研究将在3个不同的ED（城市、郊区、农村）进行，这些ED为6个AHRQ优先级的患者提供服务 人口群体。研究团队是跨学科的，由国际知名的患者专家组成。 安全、人为因素、系统工程、认知心理学、通信、急救医学，以及 护理学这项研究是创新的，因为它的透镜对艾德诊断过程作为一个整体，它的使用人为因素- 基于概念的方法，其调查的艾德队的作用，在诊断，及其使用的各种 认知任务分析技术和主动风险评估方法。

Diagnostic errors are common, deadly, and costly. Twelve million Americans annually experience diagnostic error in ambulatory care, including in Emergency Department (EDs), over half of these with potential for harm. ED clinical practice is especially prone to diagnostic error as a sociotechnical work system that is fast-paced, high-stakes, highly adaptive and complex. The 2016 National Academy of Medicine (NAM) report was an urgent call for more research regarding diagnostic safety, making particular reference to the ED. ED diagnosis is cognitively-intense work, distributed across team members who may or may not be co-located. There is very limited understanding of the salient `real-time' details of the ED diagnostic process and associated performance shaping factors on the work system. Without structured in-depth analysis of ED diagnosis occurring as part of `real-time ED work,' that is “work-as-done,” we will continue the struggle with the design of effective, sustainable interventions to improve diagnostic safety. Accordingly, we are proposing a 3-year, multi- site, multi-method field study in the ED based on a sociotechnical systems approach and a macrocognition framework, which is the study of cognitive tasks that characterize how people think in natural settings. We have 3 specific aims: (1) AIM 1. To understand provider (physician and advanced practice provider) work involved in ED diagnosis and identify associated performance shaping factors. (2) AIM 2. To understand collaborative (team-oriented) work involved in ED diagnosis and identify associated performance shaping factors. (3) AIM 3. To conduct a proactive risk assessment of the diagnostic process in the ED. AIM 1 and AIM 2 will be achieved by conducting in-depth qualitative studies using a variety of data collection methods (observations, interviews) and cognitive task analyses techniques. Data analysis will produce a range of outputs such as process maps, macrocognitive and procedural tasks involved in diagnosis, information flow diagrams, role network graphs, among others. AIM 3 will use two complementary proactive risk assessment methods to assess failure modes and performance shaping factors and to identify possible interventions to improve ED diagnostic safety: (1) Health Care Failure Mode and Effect Analysis (HFMEA); (2) Functional Resonance Analysis Method (FRAM) Based “What-if” Risk Analysis. Additionally, we will develop a research methods compendium/guide for those interested in conducting similar research on diagnostic safety. The study will be conducted in 3 different EDs (urban, suburban, rural) that serve patients from 6 AHRQ priority population groups. The research team is interdisciplinary, composed of internationally known experts in patient safety, human factors, systems engineering, cognitive psychology, communication, emergency medicine, and nursing. The study is innovative due to its lens on ED diagnostic process as a whole, its use of human factors- based conceptual approaches, its investigation of the ED team's role in the diagnosis, and its use of a variety of cognitive task analysis techniques and proactive risk assessment methods.