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

用于了解急诊科诊断过程和相关安全隐患的人为因素和系统工程方法

• 批准号: 10016288
• 负责人: AYSE PINAR GURSES
• 金额: $ 35万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2022-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10016288
• 关键词: Human; Factors; Systems; Engineering; Approach

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.

诊断错误是常见，致命且昂贵的。一二百万美国人年度经验诊断 卧床护理的错误，包括急诊科（EDS），其中一半以上有可能受到伤害。 ED临床实践尤其容易诊断错误，这是一种快节奏的社会技术工作系统， 高风险，高度适应性和复杂。 2016年国家医学院（NAM）报告是 紧急呼吁有关诊断安全性的更多研究，特别提及ED。 是认知强度的工作，分布在可能会或可能不会共同置于的团队成员之间。有 对ED诊断过程的显着“实时”细节的理解有限 工作系统上的性能塑造因素。没有对ED诊断的深入分析 作为“实时ED工作”的一部分，这是“工作的工作”，我们将继续进行设计的斗争 有效，可持续的干预措施，以改善诊断安全性。根据，我们提出了为期3年的多次 基于社会技术系统方法和宏观认知的地点，急诊室中的多方法现场研究 框架，这是对人们在自然环境中思考方式的认知任务的研究。我们 具有3个具体目标：（1）目标1。了解提供商（医师和高级执业提供者）工作 参与ED诊断并确定相关的性能塑造因素。 （2）目标2。 与ED诊断有关的协作（面向团队的）工作并确定相关的性能成型 因素。 （3）目的3。对ED中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，例如过程图，宏观认知和诊断涉及的程序任务， 信息流程图，角色网络图等。 AIM 3将使用两个完整的主动 评估失败模式和性能塑造因素并确定可能的风险评估方法 改善ED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） 功能共振分析方法（FRAM）基于“ what-if”风险分析。此外，我们将开发一个 研究方法的汇编/指南，为有兴趣进行诊断安全性研究的人。 该研究将以3种不同的ED（城市，郊区，农村）为6 AHRQ优先级的患者进行 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，交流，急诊医学和 护士。该研究具有创新性，这是由于其整个ED诊断过程的镜头，其使用人为因素 - 基于概念的方法，其对ED团队在诊断中的作用的投资以及其对多样性的使用 认知任务分析技术和主动风险评估方法。