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

诊断错误很常见、致命且代价高昂。每年有 1200 万美国人经历诊断 门诊护理中的错误，包括急诊室 (ED) 中的错误，其中一半以上具有潜在的伤害。 急诊科临床实践作为一个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、高度适应性和复杂性。 2016 年美国国家医学院 (NAM) 的报告 紧急呼吁对诊断安全性进行更多研究，特别是急诊室。急诊诊断 是认知密集型工作，分布在可能位于同一地点或不同地点的团队成员中。有非常 对 ED 诊断过程和相关的“实时”显着细节的了解有限 工作系统中的绩效塑造因素。没有对 ED 诊断进行结构化深入分析 作为“实时 ED 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，我们提议一项为期 3 年的多 基于社会技术系统方法和宏观认知的 ED 现场多方法实地研究 框架，这是对表征人们在自然环境中如何思考的认知任务的研究。我们 有 3 个具体目标： (1) AIM 1. 了解提供者（医生和高级实践提供者）的工作 参与 ED 诊断并确定相关的绩效塑造因素。 (2) 目标 2. 理解 参与 ED 诊断和确定相关绩效塑造的协作（面向团队）工作 因素。 (3) 目标 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，例如流程图、诊断中涉及的宏观认知和程序任务， 信息流程图、角色网络图等。 AIM 3将使用两种互补的主动 风险评估方法来评估故障模式和性能塑造因素并识别可能的 提高急诊诊断安全性的干预措施：（1）医疗保健失败模式和效果分析（HFMEA）； (2) 基于功能共振分析方法 (FRAM) 的“假设”风险分析。此外，我们将开发一个 研究方法纲要/指南，供有兴趣对诊断安全性进行类似研究的人使用。 该研究将在 3 个不同的急诊室（城市、郊区、农村）进行，为来自 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、传播学、急救医学等 护理。这项研究的创新之处在于它对整个 ED 诊断过程的关注，以及对人为因素的利用—— 基于概念的方法，对急诊室团队在诊断中的作用的调查，以及对各种方法的使用 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.