College of Health Care-Professions Claudiana, Lorenz-Böhler-Str. 13, 39100 Bolzano-Bozen, Italy; Institute of Nursing Science, University of Basel, Basel, Switzerland.
Emergency Department, Hospital of Merano (SABES-ASDAA), Rossini-Str. 5, Merano-Meran 39012, Italy.
Int J Nurs Stud. 2021 Jan;113:103788. doi: 10.1016/j.ijnurstu.2020.103788. Epub 2020 Oct 8.
Nurses play a crucial role in correctly prioritizing patients entering emergency departments. However, little is known of the accuracy of nurse-led triage systems.
(1) To determine the frequency of nurse-led triage errors within the Manchester Triage System; (2) to explore patient, work environment and individual nurse factors associated with triage errors; and (3) to explore associations between triage errors and patient outcomes (i.e., length of emergency department stay, hospitalization, and 7- and 30-day mortality).
This study was conducted in one emergency department in Northern Italy.
A random sample of 5% (n = 1,929) of all eligible patients accessing the emergency department over an 18-month period.
For this retrospective observational study, electronic health record data on triage errors (i.e., incorrect presentational flowchart, specific discriminator and/or priority level) and triage nurses were combined with routine data on patient characteristics, outcomes and the work environment. To explore relationships between these variables, we performed univariate and multivariate logistic regression analyses.
We observed triage errors in 16.3% of patients (n = 314). These were significantly associated with patients' emergency department and hospital stays. Analyses revealed that when > one patient was triaged every 15 min (OR: 2.112;95%CI: 1.331-3.354), older patients (OR: 1.009; 95%CI: 1.003-1.015) with > than two chronic conditions (OR: 1.506; 95%CI: 1.091-2.081) and orange or red priority codes (OR: 1.314; 95%CI: 1.046-1.651,) whose triage nurse had previous experience with another triage system (OR: 3.189; 95%CI: 2.455-4.14) had higher odds of triage errors.
We provided primary evidence on triage errors. Confirming our findings on the prevalence, nature and consequences of such errors will require further prospective multicenter studies. Considering patient factors (e.g., age, polychronicity) as additional discriminators could make the nurse-led triage process using the Manchester Triage System more accurate. Investigating the roles of triage nurses' training and background and the emergency department work environment on their mental models regarding the triage process will require qualitative research.
护士在正确优先安排进入急诊部的患者方面发挥着至关重要的作用。然而,对于护士主导的分诊系统的准确性知之甚少。
(1)确定曼彻斯特分诊系统中的护士分诊错误频率;(2)探讨与分诊错误相关的患者、工作环境和个体护士因素;(3)探讨分诊错误与患者结局(即急诊部停留时间、住院时间以及 7 天和 30 天死亡率)之间的关系。
本研究在意大利北部的一个急诊科进行。
在 18 个月的时间内,对进入急诊科的所有符合条件的患者的 5%(n=1929)进行了随机抽样。
对于这项回顾性观察研究,将电子健康记录中的分诊错误(即不正确的表现流程图、特定判别器和/或优先级)和分诊护士的数据与患者特征、结局和工作环境的常规数据相结合。为了探讨这些变量之间的关系,我们进行了单变量和多变量逻辑回归分析。
我们观察到 16.3%的患者(n=314)存在分诊错误。这些错误与患者的急诊和住院时间显著相关。分析表明,当每 15 分钟分诊>1 名患者时(OR:2.112;95%CI:1.331-3.354),年龄较大(OR:1.009;95%CI:1.003-1.015)且患有>2 种慢性疾病(OR:1.506;95%CI:1.091-2.081)和橙色或红色优先级代码(OR:1.314;95%CI:1.046-1.651)的患者,其分诊护士之前曾使用过另一种分诊系统(OR:3.189;95%CI:2.455-4.14),分诊错误的可能性更高。
我们提供了分诊错误的主要证据。进一步的前瞻性多中心研究需要证实我们关于此类错误的发生率、性质和后果的发现。考虑患者因素(例如,年龄、多任务处理)作为额外的判别因素,可以使使用曼彻斯特分诊系统的护士主导分诊过程更加准确。定性研究需要调查分诊护士的培训和背景以及急诊部工作环境对他们关于分诊过程的心理模型的作用。