RAPID:Triaging decisions during catastrophic events: a study of frontline triage nurses

该RAPID项目的目标是模拟护士在COVID-19大流行期间对患者进行分诊时的决策。在大流行期间，分诊护士扮演着一线看门人的角色，发挥着艰难的平衡作用。他们不仅必须确保需要立即护理的病人及时得到护理，而且必须过滤来的病人，以防止感染，并减少对医院资源的不适当负担。护士自身对大流行风险的认知，以及他们如何将自己的风险认知与患者提供的信息联系起来并投射出来，都影响着护士决策的复杂性和风险。传统的分诊决策标准、方案和程序仅基于线性、离散、“一次单一症状”的风险筛查方法，严重不足于在这种规模和复杂性的大流行中处理分诊决策。护士在确保安全和及时的患者护理和限制covid -19样大流行的传播方面发挥着关键作用。从这个项目中获得的关于危机期间决策和基于证据的实践的知识，将通过证明决策因素的数据，使世界各地的组织受益。这些数据可以推动培训和指导方针的制定。分诊护士通常会对病人做出分诊决定。但是，在大流行期间，他们会做出特别复杂和冒险的决定。分诊决策标准和方案必须反映出对护士如何衡量患者症状并将其与疾病状况相匹配的深刻理解，同时还要在具有重大安全后果的大流行中管理大量复杂的、相互关联的决策约束，包括他们自己的风险认知以及有限的、不确定的、混杂的信息。为了确定护士在做出分诊决定时面临的限制，并为他们在分诊时使用的策略建模，该项目研究了来自两个大型学术医疗中心的分诊护士。该项目回顾性地分析了患者风险筛查的分诊电话，前瞻性地记录了护士用作信息来源的筛查，并采访了护士，了解她们的约束条件、策略、风险感知和认知工作量。该项目绘制了护士针对具体病人的决策轨迹，以揭示他们的制约因素以及他们如何管理这些制约因素。总的来说，这些数据有望揭示在灾难性事件中进行分类决策的通用策略。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The goal of this RAPID project is to model decision-making among nurses when they triage patients during the COVID-19 pandemic. Triage nurses act as frontline gatekeepers and perform a difficult balancing act during a pandemic. They must not only ensure that patients who need immediate care get it in a timely manner but must also filter incoming patients to prevent infections and to reduce undue burden on hospital resources. The complexity and risk in their decisions are influenced by how the nurses themselves perceive the risk of a pandemic, and how they associate and project their risk perception with the information a patient provides. Conventional triage decision making criteria, protocols and processes based only on a linear, discrete, “single-symptom at a time” risk screening approach are woefully inadequate to tackle triage decisions in a pandemic of this scale and complexity. Nurses play a pivotal role in ensuring safe and timely patient care and in limiting the spread of COVID-19-like pandemics. The knowledge gained from this project about decision making and evidence-based practices during crises will benefit organizations worldwide, by proving data on factors that make decision-making. These data can drive training and guidelines development. Triage nurses routinely make triage decisions about patients. But, during a pandemic, they make particularly complex and risky decisions. Triage decision making criteria and protocols must reflect a deep understanding of how nurses weigh patient symptoms, and match them to disease conditions, while also managing a multitude of complex, interrelated decision constraints, including their own risk perceptions, and limited, uncertain, confounding information, in the midst of a pandemic with major safety consequences. To identify the constraints nurses face when making triaging decisions, and to model the strategies they use when triaging, the project studies triage nurses from two large academic medical centers. The project retrospectively analyzes triage phone calls for patient risk screening, prospectively records screens nurses use as information sources, and interviews nurses about their constraints, strategies, risk perception and cognitive workload. The project maps a nurse’s patient-specific decision-making trajectories to reveal their constraints and how they managed them. Cumulatively, the data is expected to reveal generalizable strategies for triage decisions during catastrophic events.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.