MedStar Institute for Innovation, National Center for Human Factors in Healthcare, Washington, DC.
Georgetown University School of Medicine, Washington, DC.
Acad Emerg Med. 2018 Oct;25(10):1164-1168. doi: 10.1111/acem.13496. Epub 2018 Jul 19.
Interruptions can adversely impact human performance, particularly in fast-paced and high-risk environments such as the emergency department (ED). Understanding physician behaviors before, during, and after interruptions is important to the design and promotion of safe and effective workflow solutions. However, traditional human factors-based interruption models do not accurately reflect the complexities of real-world environments like the ED and may not capture multiple interruptions and multitasking.
We present a more comprehensive framework for understanding interruptions that is composed of three phases, each with multiple levels: interruption start transition, interruption engagement, and interruption end transition. This three-phase framework is not constrained to discrete task transitions, providing a robust method to categorize multitasking behaviors around interruptions. We apply this framework in categorizing 457 interruption episodes.
A total of 457 interruption episodes were captured during 36 hours of observation. The interrupted task was immediately suspended 348 (76.1%) times. Participants engaged in new self-initiated tasks during the interrupting task 164 (35.9%) times and did not directly resume the interrupted task in 284 (62.1%) interruption episodes.
Using this framework provides a more detailed description of physician behaviors in complex environments. Understanding the different types of interruption and resumption patterns, which may have a different impact on performance, can support the design of interruption mitigation strategies.
中断会对人类的表现产生不利影响,尤其是在急诊室(ED)等快节奏和高风险的环境中。了解医生在中断之前、期间和之后的行为对于设计和推广安全有效的工作流程解决方案至关重要。然而,传统的基于人为因素的中断模型不能准确反映 ED 等真实环境的复杂性,也可能无法捕获多个中断和多任务。
我们提出了一个更全面的中断理解框架,该框架由三个阶段组成,每个阶段都有多个层次:中断开始转换、中断参与和中断结束转换。这个三阶段框架不受离散任务转换的限制,为围绕中断进行多任务行为分类提供了一种强大的方法。我们应用该框架对 457 个中断事件进行分类。
在 36 小时的观察中,共记录了 457 个中断事件。中断任务立即暂停了 348 次(76.1%)。参与者在中断任务期间主动发起新的任务 164 次(35.9%),在 284 次中断事件中(62.1%)没有直接恢复中断任务。
使用此框架可以更详细地描述复杂环境中的医生行为。了解不同类型的中断和恢复模式,这些模式可能对性能产生不同的影响,可以支持中断缓解策略的设计。