BACKGROUND:While several studies have evaluated the performance of the Manchester Triage System (MTS), none have specifically examined its accurate application by triage nurses and its association with clinical outcomes. This study focuses on the agreement between nurse-assigned MTS codes and those assigned by an expert group, as well as their ability to predict clinical outcomes. METHODS:This multicentre simulation study was conducted from January to March 2024 across four EDs in Italy employing MTS in clinical practice. Two emergency physicians developed 30 vignettes derived from real clinical cases to encompass diverse triage scenarios and priority codes. An expert MTS group, composed of three experienced nurses, assigned MTS priority codes following the guidelines outlined in the official MTS textbook. Subsequently, the vignettes were presented to triage nurses, who independently assigned MTS codes. Error rate, agreement between nurse-assigned and expert MTS group codes, and the predictive ability for secondary clinical outcomes (mortality within 72 hours, hospitalisation, life-saving intervention, severe condition in the ED and time-dependent pathology) were compared between the MTS priority assigned by the expert MTS group codes and nurse-assigned triage codes. RESULTS:77 nurses from four EDs participated. The triage code assignment error rate was 28.6% (660/2310). The overall agreement between the triage and expert nurses yielded a Cohen's kappa of 0.59 (95% CI 0.58 to 0.59). Expert MTS group applications performed better compared with nurse-assigned codes in predicting clinical outcomes. The mean error rate per nurse was 30% (9/30). Nurses with more ED experience and triage expertise had higher error rates. CONCLUSION:The application of MTS using case vignettes was suboptimal in our setting, with more senior nurses having higher error rates. Correct application of MTS better predicted clinical outcomes. It is important to conduct future studies to understand how to best support nursing clinical decision-making in triage.

INTRODUCTION:This study aimed to investigate the factors influencing triage duration in emergency departments, comparing the impact of individual nurse characteristics with contextual and patient-related variables. METHODS:This monocentric retrospective observational design, conducted from January 1, 2016, to December 31, 2022, analyzed 382,027 triage events at Merano Hospital. Data from periods affected by the coronavirus disease 2019 pandemic were excluded to ensure analysis under standard emergency conditions. Triage durations were evaluated using statistical models, including random effects, to capture both individual and systemic influences. RESULTS:A total of 51 nurses performed triage, with a median time of 1.9 minutes (interquartile range, 1.1-3.7). Nurse-related factors accounted for only 11.5% of the variability, whereas patient and contextual factors had greater influence. Older patients had longer triage times (+0.0079 min/y; P<.001). Arrival by ambulance increased triage time by 0.287 minutes compared with independent arrivals (P<.001). Higher priority levels were linked to shorter triage times, with priority 1 patients assessed 0.604 minutes faster (P<.001). Night admissions reduced triage times by 2.137 minutes (P<.001), whereas increased emergency department workload prolonged them (+0.692 minutes per additional patient; P<.001). DISCUSSION:Triage models should incorporate a broader range of contextual and patient-related factors rather than focusing predominantly on nurse efficiency. Further research is needed to comprehensively identify the determinants of triage performance, with the goal of optimizing both speed and quality in emergency care.

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.

BACKGROUND:Triage is essential in emergency departments (EDs) to prioritize patient care based on clinical urgency. Recent investigations have explored the role of large language models (LLMs) in triage, but their effectiveness compared to human triage remains uncertain. This study assessed the effectiveness of ChatGPT 4.0 in triaging ED patients. METHODS:This retrospective study analyzed data from 2658 patients. Triage codes assigned by human triage personnel were compared with those assigned by Artificial Intelligence (AI) triage using Chat-GPT 4.0. Agreement between human and AI triage was assessed using Cohen's kappa statistic. Clinical outcomes were evaluated through Receiver Operating Characteristic (ROC) curves to determine predictive accuracy. Sensitivity and specificity of both triage systems were compared across different symptoms using 2 × 2 contingency tables. RESULTS:The Cohen's kappa statistic for agreement between human and AI triage was 0.125 (95 % CI: 0.100-0.134). ROC analysis demonstrated that human triage outperformed AI in predicting all study outcomes, with statistically significant differences. For 30-day mortality, the ROC of human triage was 0.88, while for AI triage it was 0.70, p < 0.001. A similar result was observed for life-saving interventions, where human triage had an ROC of 0.98 and AI triage 0.87, p = 0.014. For specific symptoms, human triage showed superior sensitivity and specificity. CONCLUSIONS:LLMs like Chat-GPT 4.0 have limited utility in ED triage, particularly due to their lower sensitivity for high-risk patients, which lead to under-triage. Human triage remains more reliable than Chat-GPT.

Background Vital signs in triage are essential for effective risk stratification in the emergency department (ED). They are also increasingly used to calculate an early warning score at the time of presentation. However, obtaining a blood pressure is more time-consuming than other vital signs, potentially delaying care for subsequent patients. Additionally, studies indicate that this measure is not always collected. This study aimed to evaluate whether removing systolic blood pressure (SBP) from the National Early Warning Score (NEWS) affects the prediction of mortality. Methods This prospective observational single-centre study included all patients presenting to triage of the General Hospital of Merano, Italy, from 1 June 2022 to 30 June 2023. Vital signs were recorded for each patient. NEWS and NEWS without SBP (NEWS-SBP) were computed. The ability of the two versions of the score to predict mortality at 48 hours, 7 days and 30 days was evaluated using the Area Under the Receiver Operating Characteristic curves (AUROC). Results Data were recorded from 26 249 patients. For predicting 7-day and 30-day mortality, NEWS had a significantly higher AUROC than NEWS-SBP (7-day mortality: 0.84, 95% CI: 0.81 to 0.87 vs 0.83, 95% CI: 0.80 to 0.86; p=0.012, and 30-day mortality: 0.79, 95% CI: 0.77 to 0.81 vs 0.77, 95% CI: 0.75 to 0.79; p<0.001). No significant difference was found in the AUROC for the prediction of 48-hour mortality (NEWS: 0.89, 95% CI: 0.85 to 0.92 vs NEWS-SBP 0.88, 95% CI: 0.85 to 0.91; p=0.139). Conclusion The NEWS-SBP was equivalent to the complete score for prediction of 48-hour mortality, but was less accurate in predicting medium and long-term mortality among ED patients. Further research is needed to clarify potential advantages in reducing triage time and whether these benefits outweigh the loss of prognostic accuracy.

Emergency Departments (EDs) are increasingly managing elderly patients with chronic diseases and complex comorbidities. While the association between chronic conditions and poor clinical outcomes is well established, their impact on ED operational performance, particularly on length of stay (LOS), remains underexplored. We conducted a retrospective, single-center observational study at Merano Hospital (Italy), analyzing a random sample of adults ED visits in 2023. Patients were classified as having chronic conditions if they had ≥ 2 pre-existing chronic conditions. Demographic, clinical, and access-related variables were extracted from electronic health records. The primary outcome was ED LOS, defined as the time from registration to ED chart closure, excluding boarding time. Univariate and multivariable logistic regression analyses were used to identify predictors of prolonged LOS (≥ 75th percentile). Among 4172 patients, 12.9

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: Currently, there is no universally accepted gold standard outcome for assessing the effectiveness of the Triage Systems. This study aimed to comprehensively evaluate and compare various outcomes utilized in triage studies. Methods: A prospective observational study was conducted at the Emergency Department (ED) of Merano Hospital from June 1 to December 31, 2023. We assessed the predictive capability of the Manchester Triage System (MTS) across multiple outcomes using areas under the receiver operating characteristic curve (AUROC), along with their corresponding 95% confidence intervals (95% CI), and frequency distributions. Results: The MTS demonstrated strong performance concerning the most objective outcomes, such as mortality (at 72 h: AUROC 0.914; 95 %CI: 0.815-1; at 7 days: 0.845; 95 %CI: 0.729-0.965; at 30 days: 0.794; 95 %CI: 0.706-0.881), admission to the intensive care unit (0.831; 95 %CI: 0.763-0.899), and need for life-saving interventions (0.870; 95 %CI: 0.806-0.934). Additionally, outcomes such as urgency status and clinical priority, as judged by physicians, exhibited excellent performance and optimal frequency distribution. Conclusions: The performance of the MTS varied significantly depending on the specific outcome under evaluation. Currently, no single outcome appears superior to others, nor does any seem poised to serve as a potential gold standard for the assessment of triage systems. It is advisable for dedicated working groups to convene and reach a consensus on the most effective outcomes for evaluating the performance of MTS and other triage systems. This should be accomplished through a systematic, standardized, and transparent approach, grounded in the best available evidence.

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.

BACKGROUND:Emergency Departments (EDs) across Italy use different triage systems, which vary from region to region. This study aimed to assess whether nurses working in different EDs assign triage codes in a similar and standardized manner. METHODS:A multicenter observational simulation study involved the EDs of Bolzano Hospital, Merano Hospital, Pisa University Hospital, and Rovereto Hospital. All participating nurses were given 30 simulated clinical cases (vignettes) and asked to assign triage codes according to the triage systems used in their EDs. Subsequently, we assessed inter-rater agreement and evaluated if code assignment had different performance among hospitals in relation to different clinical outcomes. RESULTS:Eighty-seven nurses participated in this study. There was marked variation in assigned triage codes both across hospitals and among individual operators. The kappa values for inter-rater agreement were 0.632 for Bolzano Hospital, 0.589 for Merano Hospital, 0.464 for Pisa University Hospital, and 0.574 for Rovereto Hospital. Sensitivity and specificity levels varied considerably for the same outcomes when comparing different hospitals. CONCLUSION:There is a high degree of subjectivity in triage code assignment by ED nurses. In the interest of equitable care for patients, this variability within the same country is hardly acceptable.

BackgroundStandardised triage systems have been in place for decades with minor modifications, while nurses' skills and knowledge have significantly advanced.AimTo determine whether nurses' clinical expertise outperforms triage systems in simulated clinical cases.DesignA multicenter simulated observational study.MethodsThe study was conducted from January 1, 2024 to March 31, 2024, in four Italian emergency departments, enrolling triage-performing nurses. Thirty clinical cases, based on real patients representing daily emergency department influx, were reconstructed. The primary outcome was the agreement between the triage code assigned by the Manchester Triage System and the code assigned based on clinical expertise. The secondary outcome compared the predictive ability of the codes assigned by nurses regarding clinical outcomes, such as death within 72 h, the need for hospitalisation, and the need for life-saving intervention. The study was reported in accordance with the STROBE statement.ResultsSeventy-seven triage nurses completed the 30 vignettes. The agreement between the MTS-assigned code and the clinical expertise triage reported a Cohen's kappa of 0.576 (95% CI: 0.564-0.598). For death within 72 h, the clinical expertise code reported better results than the Manchester Triage System. For life-saving interventions, the Manchester Triage System reported a lower performance than clinical expertise. The variability in triage code assignment was higher for clinical expertise compared to the Manchester Triage System.ConclusionsTriage codes assigned by nurses based on clinical expertise perform better in terms of clinical outcomes, suggesting a need to update triage systems to incorporate nurses' knowledge and skills. However, standardised triage systems should be maintained to reduce variability and ensure consistent patient classification.Reporting MethodThe study was conducted and reported according to the STROBE statement.Patient or Public ContributionNo patient or public contribution.

Assessing patient frailty in the Emergency Department (ED) is crucial; however, triage frailty and comorbidity assessment scores developed in recent years are unsatisfactory. The underlying causes of this phenomenon could reside in the nature of the tools used, which were not designed specifically for the emergency context and, thus, are difficult to adapt to the emergency environment. The objective of this study was to create and internally validate a nomogram for identifying different levels of patient frailty during triage. Multicenter, prospective, observational exploratory study conducted in two ED. The study was conducted from April 1 to October 31, 2022. Following the triage assessment, the nurse collected variables related to the patient’s comorbidities and chronic conditions using a predefined form. The primary outcome was the 90-day mortality rate. A total of 1345 patients were enrolled in this study; 6

Currently, there is conflicting evidence regarding the efficacy of frailty scales and their ability to enhance or support triage operations. This study aimed to assess the utility of three common frailty scales (CFS, PRISMA-7, ISAR) and determine their utility in the triage setting. This prospective observational monocentric study was conducted at Merano Hospital's Emergency Department (ED) from June 1st to December 31st, 2023. All patients attending this ED during the 80-day study period were included, and frailty scores were correlated with three outcomes: hospitalization, 30-day mortality, and severity of condition as assessed by ED physicians. Patients were categorized by age, and analyses were performed for the entire study population, patients aged 18–64, and those aged 65 or older. Univariate analysis was followed by multivariable analysis to evaluate whether frailty scores were independently associated with the outcomes. In multivariable analysis, none of the frailty scores were found to be associated with the study outcomes, except for the CFS, which was associated with an increased risk of 30-day mortality, with an odds ratio of 1.752 (95

Aim This study aimed to compare the performance in risk prediction of various outcomes between specially trained triage nurses and the Manchester Triage System (MTS). Design Prospective observational study. Methods The study was conducted from June 1st to December 31st, 2023, at the Emergency Department of Merano Hospital. Triage nurses underwent continuous training through dedicated courses and daily audits. We compared the risk stratification performed by expert nurses with that of MTS on various outcomes such as mortality, hospitalisation, and urgency defined by the physicians. Comparisons were made using the Areas Under the Receiver Operating Characteristic curve (AUROC). Results The agreement in code classification between the MTS and the expert nurse was very low. The AUROC curve analysis showed that the expert nurse outperformed the MTS in all outcomes. The triage nurse’s experience led to statistically significant better stratification in admission rates, ICU admissions, and all outcomes based on the physician’s assessment. Conclusions The continuous training of nurses enables them to achieve better risk prediction compared to standardized triage systems like MTS, emphasizing the utility and necessity of implementing continuous training pathways for these highly specialised personnel.

Background: An immediate ECG on arrival of a patient with cardiovascular symptoms in the ED may anticipate the need for life-saving intervention. The aim was to evaluate whether ECG interpretation during nurse triage can improve triage system performance in patients with cardiovascular symptoms.Methods: All patients who required an assessment for cardiovascular symptoms were considered for this obser-vational study. During triage assessment, the nurses assessed the patient's level of urgency applying the MTS, then again after this evaluation (confirming or modifying the level of urgency based on personal clinical experience) and after interpretation of the patient's ECG. The main study outcome was the diagnosis of an acute cardiovascular event. Results: Of the 1211 patients in the study, 10.5% presented the main study outcome. ECG interpretation in triage exhibited a nurse-physician agreement of 92.9% (p<0.001). increased patient priority in 7.5% of cases and reduced it in 39.6%. The discriminatory ability of the triage system had an area under the ROC of 0.712 and 0.845 after ECG interpretation. ECG interpretation improved the baseline assessment of priority, with an NRI of 60.1% (p<0.001).Conclusions: ECG interpretation in triage can be a simple and safe tool that improves the assessment of patient priority.

The study aimed to validate the Manchester Triage System in a hospital setting using data for short- and medium-term death rates. A prospective observational study was conducted at the Emergency Department of Merano Hospital for two years. The discriminatory ability of MTS was tested using AUROCs and contingency tables, reporting sensitivity and specificity levels for each study outcome. A total of 98,443 patients were enrolled, 237 of whom died within 72h; 422 patients died within seven days, and 1025 died within 30 days. The MTS demonstrated excellent discriminatory ability, reporting AUROC values of 0.890 for death within 72h, 0.853 for death within seven days, and 0.781 for death within 30 days. A sensitivity of 87.7% and a specificity of 79.4% were reported for death at 72h, while a sensitivity of 69.6% and a specificity of 79.8% were reported for death at 30 days. The MTS has proven to be a good triage system capable of accurately identifying patients who are at risk of death in the short or medium term.

Background The Manchester Triage System (MTS) is one of the most widely used and studied triage systems in emergency departments (ED). MTS does not have a specific presentational flow chart for patients with transient global amnesia (TGA). The goal of this study was to determine the adequacy of priority code assignment for patients with TGA presenting at the ED and triaged using the MTS.Methods This is a single-center observational retrospective study from January 01, 2013 to June 31, 2020. All patients with a medical diagnosis of TGA were considered. An audit was conducted on these triages to assess the correct application of MTS by the triage nurses. Correct triage was considered as a patient classified as yellow.Results During the study period, 216 patients with a diagnosis of TGA were considered. Of these 49.5% were classified as yellow, 13.0% were undertriage and classified as green or blue and 37.5% were overtriaged and classified as orange or red. The audit demonstrated that 98.8% of overtriaged patients and 57.1% of undertriage patients were triaged incorrectly. In addition, in 38 patients the triage nurse confused TGA with an acute neurological deficit suggestive of stroke or transient ischemic attack.Conclusion The present study demonstrates an inability of MTS to correctly stratify patients with TGA. The results of the present study indicate the need for a specific flow chart for patients with neurological problems to improve the performance of MTS.

AimsThe prompt recording of the electrocardiogram (ECG) and its correct interpretation is crucial to the management of patients who present to the emergency department (ED) with cardiovascular symptoms. Since triage nurses represent the first healthcare professionals evaluating the patient, improving their ability in interpreting the ECG could have a positive impact on clinical management. This real-world study investigates whether triage nurses can accurately interpret the ECG in patients presenting with cardiovascular symptoms. DesignProspective, single-centre observational study conducted in a general ED of General Hospital of Merano in Italy. MethodsFor all patients included, the triage nurses and the emergency physicians were asked to independently interpret and classify the ECGs answering to dichotomous questions. We correlated the interpretation of the ECG made by the triage nurses with the occurrence of acute cardiovascular events. The inter-rater agreement in ECG interpretation between physicians and triage nurses was evaluated with Cohen's kappa analysis. ResultsFour hundred and ninety-one patients were included. The inter-rater agreement between triage nurses and physicians in classifying an ECG as abnormal was good. Patients who developed an acute cardiovascular event were 10.6% (52/491), and in 84.6% (44/52) of them, the nurse accurately classified the ECG as abnormal, with a sensitivity of 84.6% and a specificity of 43.5%. ConclusionTriage nurses have a moderate ability in identifying alterations in specific components of the ECG but a good ability in identifying patterns indicative of time-dependent conditions correlated with major acute cardiovascular events. Impact for NursingTriage nurses can accurately interpret the ECG in the ED to identify patients at high risk of acute cardiovascular events. Reporting MethodThe study was reported according to the STROBE guidelines. No Patient or Public ContributionThe study did not involve any patients during its conduction.

Aims and ObjectiveThe study aimed to assess the triage nurse's skill in the recognition of abnormal electrocardiogram during actual clinical practice and to identify nurse- and patient-related factors associated with errors in electrocardiogram interpretation. BackgroundThe nurse's ability to interpret the electrocardiogram has only been evaluated in simulation settings and has reported conflicting results. DesignA prospective single-centre observational study. MethodsDuring the evaluation of a patient with a cardiovascular symptom, the triage nurses were asked to define whether the 12-lead electrocardiogram performed during the triage evaluation was pathological or non-pathological for the presenting symptom. Patient characteristics and some nurse-related variables were recorded. Inter-rater agreement between the physician and nurse in the electrocardiogram interpretation was considered the primary outcome, while the association of a major acute cardiovascular event related to patient access in the Emergency Department was the secondary outcome. We have followed the STROBE checklist for the preparation of this manuscript. ResultsTwenty nurses agreed to participate to the study and collect data. Of the 644 patients enrolled, 21.6% (139/644) reported a pathological electrocardiogram according to the ED Physician. The concordance between nurse and physician was modest with Cohen's Kappa of 0.666.An error in the electrocardiogram interpretation was present in 11% of the patients. Nurses who performed an electrocardiogram course within 1 year and studied electrocardiogram interpretation autonomously presented a lower error rate, while older patients and patients with more previous cardiovascular disease were found to be more associated with an error in electrocardiogram interpretation. ConclusionsThe study demonstrates that triage nurses have a fair ability to interpret the electrocardiogram. Relevance to Clinical PracticeSpecific educational programmes for electrocardiogram interpretation could improve the skill of electrocardiogram interpretation by the nurse and enable this instrument to become an indispensable tool in triage assessment.

BACKGROUND:The exponential growth of tourism worldwide could have consequences for healthcare services in tourist locations. The impact of the tourist population on access to emergency departments (EDs) is currently unknown.AIM:To describe the characteristics of tourist access in an ED of an alpine tourist area in a period prior to the COVID-19 pandemic.METHODS:All patients evaluated at the ED of the Merano Hospital from January 1, 2017, to December 31, 2019, were considered and divided into two study groups: locals and tourists. Analyses were conducted to assess the impact of tourists in terms of weighted ED admissions and differences in admission characteristics. Finally, for tourist patients only, an analysis of severity according to their type of healthcare system of provenance was performed.RESULTS:A total of 208,875 ED presentations were considered, of which 90.7% (189,406) were by local patients and 9.3% (19,469) were by tourists. The median ED admission rate was 1.65 admissions per 1000 overnight stays for locals versus 0.90 admissions per 1000 overnight stays for tourists. The time series analysis revealed a greater seasonal variation in accesses by tourists than by resident patients. A higher proportion of accesses with a severe code was found among tourist patients, while the local population exhibited a higher proportion of patients with a non-urgent code. In the tourist population, patients from a country with a free-market healthcare system had a higher number of ED presentations for severe conditions or that required hospitalisation than tourists from countries with Bismarck or Beveridge healthcare systems.CONCLUSIONS:The tourist population can have an important impact on EDs in high-impact tourist areas. The seasonality of the tourist population indicates the need for health policies that focus on educating the tourist population on the correct use of the ED.