Background: Over the past few decades, emergency departments (EDs) have experienced an increasing workload. However, the variation in the types of patient accesses to these departments remains poorly understood. Objective: To evaluate the 5-year temporal trend in the volume of patients attending EDs based on the urgency of their conditions. Methods: This multicenter observational retrospective study was conducted from 1 January 2019, to 31 December 2023, across seven Italian EDs located within the same province. All patients accessing the EDs during the study period were included, totaling 1,282,735 patients. The triage code was used as an urgency index; non-urgent patients were defined as those who received a code 4 or 5 in triage, while urgent patients were defined as those who received a code 3, 2, or 1 in triage. Temporal analyses of admissions were conducted, also evaluating individual age groups to understand behavior over time. Results: From 2019 to 2023, there was a significant 10% increase in ED attendances by non-urgent patients. This increase was observed during both daytime and nighttime shifts. Notably, all age groups showed an increase in non-urgent patients, except for pediatric patients aged 0 to 14. Conclusions: Over the past 5 years, there has been a consistent upward trend in ED attendances by non-urgent patients. Healthcare policies should consider implementing strategies to manage or mitigate the overload in EDs, particularly related to non-urgent patient accesses.

Background: This study aimed to evaluate Emergency Department and Intensive Care Unit nurses’ skills in interpreting blood gas analysis results and to use those interpretations in clinical decision-making. Methods: In this prospective, multicenter, simulation-based study, nurses from the Emergency Department (ED) of Merano Hospital and the Intensive Care Unit (ICU) of Bolzano Hospital, Italy, were presented with 16 clinical vignettes based on real patient cases. These vignettes were designed to evaluate the nurses’ ability to identify patients with time-dependent conditions and recommend appropriate therapeutic interventions. Outcomes measured included sensitivity, specificity, and agreement with physician-assigned urgency levels and therapy recommendations. Results: Among the 43 participants (26 ICU and 17 ED nurses), specificity in excluding patients without time-dependent conditions or organ replacement needs was high. However, sensitivity in identifying time-dependent conditions was less than 50%. Agreement with physician-assigned urgency levels was low, with Cohen’s kappa values of 0.139 for ICU nurses and 0.218 for ED nurses. Nurses with lower self-confidence in interpreting BGA results made more errors, while other personal or professional factors did not significantly impact performance. Conclusions: Although critical care nurses can effectively rule out patients without time-dependent conditions, their ability to identify such conditions requires improvement. These findings underscore the need for targeted training programs to enhance nurses’ BGA interpretation skills and clinical decision-making in high-pressure, time-sensitive situations.

Background: Emergency department (ED) triage systems aim to prioritize patients based on clinical severity, ensuring timely intervention for high-risk cases. Recently, the National Early Warning Score (NEWS) has been proposed as an alternative to traditional triage systems, but its efficacy across multiple clinical outcomes remains unclear. This study aimed to compare the predictive performance of the NEWS and the Manchester Triage System (MTS) across multiple clinical outcomes. Methods: We conducted a retrospective, single-center study at Merano Hospital, Italy, from 1 June 2022 to 30 June 2023, comparing the performance of the NEWS and the Manchester Triage System (MTS). All adult ED patients (≥18 years) were included, while exclusions applied to those on fast-track pathways, non-residents, and pregnant patients. Primary outcomes included 30-day mortality, hospitalization, and ICU admission. A random 5% subgroup was analyzed for secondary outcomes, including the need for life-saving interventions (LSIs), physician-defined clinical priority, and severity. Predictive performance was assessed using Receiver Operating Characteristic (ROC) curves, area under the ROC curve (AUROC) comparisons, and Decision Curve Analysis (DCA). Results: Among 27,238 patients, the NEWS predicted 30-day mortality more accurately than the MTS (AUROC 0.745 vs. 0.701, p < 0.001). However, the MTS outperformed the NEWS for hospitalization (AUROC 0.733 vs. 0.609, p < 0.001), ICU admission (AUROC 0.862 vs. 0.672, p < 0.001), and all secondary outcomes. DCA further confirmed MTS’s superiority across clinically relevant ED probability thresholds (20–40%). Conclusions: The NEWS, while effective for predicting mortality, it is inadequate in comprehensive triage decision-making. The MTS remains the superior system for prioritizing high-risk patients based on clinical severity. Rather than replacing triage with the NEWS, efforts should focus on refining existing systems to improve risk stratification. Future multi-center prospective studies are necessary to validate these findings.

Triage systems have remained largely unchanged since the 1990s and rely on expert consensus, with no single system consistently outperforming others in accurately identifying critically ill or urgent patients. This study aimed to determine whether incorporating additional tools improves the predictive accuracy of the Manchester Triage System (MTS). A prospective, monocentric study was conducted at Merano Hospital (Italy) from June 1st to December 31st, 2023. A triage nurse and two ED physicians assigned patient priorities. The cohort was split for model derivation and validation. An ordinal logistic regression model was developed using MTS, the National Early Warning Score, and the Charlson Comorbidity Index, then tested on a validation cohort, bootstrapped to 5000 cases. Of the 1270 patients enrolled, 821 were in the derivation cohort and 449 in the validation cohort. The model outperformed MTS alone in most outcomes, except for predicting death at 72 hours and 7 days. Decision Curve Analysis confirmed its superiority in identifying urgent cases. Integrating multiple tools into triage models can enhance their performance, improving patient prioritization accuracy.

This study addresses the challenge of determining appropriate nurse staffing levels for triage in Emergency Departments (EDs). It evaluates whether existing nurse staffing models, typically designed for other hospital settings, can be effectively applied to triage. The research was conducted at Merano Hospital’s ED from January 1, 2021, to November 30, 2022, and involved an analysis of data from patient triage assessments. The findings indicate that standard ward staffing models are not easily adaptable to the triage environment, underscoring the need for a more systematic approach to calculating triage nurse staffing. The current Italian ministerial guidelines do not account for the unique demands and complexities of the triage setting.