•It is currently unknown whether post-basic triage training improves nurses’ abilities.•The study demonstrates that continuous education improves nurses’ ability in triage.•Continuous education ...pathways are necessary for triage nurses.
This study aimed to compare the performance in risk prediction of various outcomes between specially trained triage nurses and the Manchester Triage System (MTS).
Prospective observational study.
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).
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.
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.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Patient admission is a decision relying on sparsely available data. This study aims to provide prediction models for discharge versus admission for ward observation or intensive care, and 30 ...day-mortality for patients triaged with the Manchester Triage System.
This is a single-centre, observational, retrospective cohort study from data within ten minutes of patient presentation at the interdisciplinary emergency department of the Kepler University Hospital, Linz, Austria. We trained machine learning models including Random Forests and Neural Networks individually to predict discharge versus ward observation or intensive care admission, and 30 day-mortality. For analysis of the features' relevance, we used permutation feature importance.
A total of 58323 adult patients between 1 December 2015 and 31 August 2020 were included. Neural Networks and Random Forests predicted admission to ward observation with an AUC-ROC of 0.842 ± 0.00 with the most important features being age and chief complaint. For admission to intensive care, the models had an AUC-ROC of 0.819 ± 0.002 with the most important features being the Manchester Triage category and heart rate, and for the outcome 30 day-mortality an AUC-ROC of 0.925 ± 0.001. The most important features for the prediction of 30 day-mortality were age and general ward admission.
Machine learning can provide prediction on discharge versus admission to general wards and intensive care and inform about risk on 30 day-mortality for patients in the emergency department.
Ethics Committee of the Medical Faculty at the Johannes Kepler University, Linz, Austria, Study Number 1233/2020.
Zusammenfassung
Hintergrund
Notaufnahmen in Deutschland werden mit steigenden Patientenzahlen konfrontiert. Um den wachsenden Bedarf an medizinischer Versorgung zu managen, wurden flächendeckend ...standardisierte Triagesysteme eingeführt und gesetzlich vorgeschrieben.
Ziel der Arbeit
Nach der Implementation des Manchester Triage System in der chirurgischen Notaufnahme eines überregionalen Traumazentrums gab es Hinweise auf relevante Fehltriagierung. Diese Arbeit untersucht die Prävalenz und die Ursachen der Fehltriagierung und zeigt mögliche Gegenmaßnahmen.
Material und Methoden
Eine Querschnittstudie mit 2 Studienzweigen einer prospektiven Prozessbeobachtung und einer retrospektiven Fallanalyse von Triageepisoden.
Ergebnisse
Von 14.156 im Beobachtungszeitraum behandelten Patienten wurden 497 Triageepisoden prospektiv beobachtet und 720 Triageepisoden retrospektiv untersucht. Es wurden 51,6 % der Dringlichkeitsstufe „Rot“ bzw. 37,1 % „Blau“ fehltriagiert. Mögliche Ursachen fanden sich in den Bereichen der Anwender („Rot“: 88,9 %, „Blau“: 85,7 %), der Prozessgestaltung („Rot“: 91,9 %, „Blau“: 12,8 %) und des Triagesystems („Rot“: 8,1 %, „Blau“: 15,8 %).
Diskussion
Die Studie zeigt das Vorliegen einer relevanten Fehltriagierung und impliziert, dass auch ein standardisiertes Triagesystem nach Implementation einer Überprüfung und Integration in bestehende Strukturen bedarf. Wie sich zeigte, ist die Fehltriage ein multifaktorielles Geschehen, verschiedene mögliche Fehlerquellen bedingen sich gegenseitig und führen zu fehlerhaften Einschätzungen. Dem sollte nicht mit Einzelmaßnahmen, sondern mit einem Maßnahmenpaket begegnet werden, um die Triage sicher und effizient zu gestalten.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Objective
Non‐traumatic headache is a frequent reason for visits to the emergency department (ED). We evaluated the performance of the Manchester Triage System (MTS) in prioritising patients ...presenting to the ED with non‐traumatic headache.
Methods
In this single‐centre observational retrospective study, we compared the association of MTS priority classification codes with a final diagnosis of a severe neurological condition requiring timely management (ischaemic or haemorrhagic stroke, subarachnoid haemorrhage, cerebral sinus venous thrombosis, central nervous system infection or brain tumour). The study was conducted and reported according to the STROBE statement. The overall prioritisation accuracy of MTS was estimated by the area under the receiver operating characteristic (ROC) curve. The correctness of triage prediction was estimated based on the “very urgent” MTS grouping. An undertriage was defined as a patient with an urgent and severe neurological who received a low priority/urgency MTS code (green/yellow).
Results
Over 30 months, 3002 triage evaluations of non‐traumatic headache occurred (1.7% of ED visits). Of these, 2.3% (68/3002) were eventually diagnosed with an urgent and severe neurological condition. The MTS had an acceptable prioritisation accuracy, with an area under the ROC curve of 0.734 (95% CI 0.668–0.799). The sensitivity of the MTS for urgent codes (yellow, orange and red) was 79.4% (95% CI 74.5–84.3), with a specificity of 54.1% (95% CI 52.9–55.3). The triage prediction was incorrect in only 6.3% (190/3002) of patients with headache.
Conclusion
The MTS is a safe and accurate tool for prioritising patients with non‐traumatic headache in the ED. However, MTS may need further specific tools for evaluating the more complicated symptoms and for correctly identifying patients with urgent and severe underlying pathologies.
Relevance to clinical practice
The triage nurse using MTS may need additional tools to improve the assessment of patients with headache, although MTS provides a good safety profile.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK, VSZLJ
Aims
The objective was to evaluate whether the error rate in the application of the triage system decreased after the introduction of daily auditing, and it was also evaluated if the agreement rate ...between physician and nurse on triage priority levels increased after the introduction of daily auditing and if the error‐related variables in the pre‐intervention period changed in the post‐intervention period.
Design
A quasi‐experimental study was performed with a pre–post design, between June 2019 and June 2021 in one emergency department.
Methods
The accuracy and error rate of triage in the pre‐ and post‐intervention period were compared. Univariate and multivariate logistic regression analyses were performed to explore the relationships between the variables related to the error. The comparison between the priority level assigned by the physician and the triage nurse was analysed using Cohen's K.
Results
Nine hundred four patients were enrolled in the pre‐intervention period and 869 in the post‐intervention period. The error rate in the pre‐intervention period was 23.3% and in the post‐intervention period was 9.7%.
The concordance between the degree of priority expressed by the physician and the nurse varied from a quadratically weighted Cohen's K of 0.447 in the pre‐intervention period to 0.881 in the post‐intervention period.
Conclusion
Daily auditing is a clinical procedure that improves the nurse's application of the triage system. Daily auditing has reduced errors by the nurse, improving performance and concordance with the physician.
Impact
Triage systems are a key point for the stratification of the priority level of patients and it is therefore evident that they maintain high‐quality standards. Through the practice of daily auditing, not only a reduction in the error rate, which ensures patient safety, but also an improvement in triage performance has been demonstrated.
No Patient or Public Contribution
The study did not involve any patients during its conduction.
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Triage and redirection of patients to alternative care providers is one tool used to overcome the growing issue of crowding in emergency departments (EDs). Electronic patient self-triage (eTriage) ...may reduce waiting times and required face-to-face contact. There are limited studies into its efficacy, accuracy and validity in an ED setting.
The aim of this study was to assess the agreement and validity of eTriage with a reference standard of nurse face-to-face triage. A secondary aim was to assess the ability of both systems to predict high and low acuity outcomes.
This was a retrospective study conducted over 8 months in two UK hospitals. Inclusion criteria were all ambulatory patients aged ≥18. All patients completed an eTriage and nurse-led triage using the Manchester Triage System (MTS).
During the study period, 43 788 adult patients attended one of the two ED sites and 26 757 used eTriage. A total of 1424 patient episodes had no recorded MTS and were excluded from the study leaving 25 333 paired triages for the final cohort. Agreement between eTriage and nurse triage was low with a weighted Kappa coefficient of 0.14 (95% CI, 0.14-0.15) with an associated weak positive correlation (rs 0.321). Level of undertriage by eTriage compared with nurse triage was 10.1%, and overtriage was 59.2%. The sensitivity for prediction of high acuity outcomes was 88.5% (95% CI, 77.9-95.3%) for eTriage and 53.8% (95% CI 41.1-66.0%) for nurse MTS. The specificity for predicting low risk patients was 88.5% (95% CI, 87.4-89.5%) for eTriage and 80.6% (95% CI, 79.3-81.8%) for nurse MTS.
Agreement and correlation of eTriage with the reference standard of nurse MTS was low; patients using eTriage tended to over triage when compared to the triage nurse. eTriage had a higher sensitivity for high acuity presentations and demonstrated similar specificity for low acuity presentations when compared to triage nurse MTS. Further work is necessary to validate eTriage as a potential tool for safe redirection of ED attenders to alternative care providers.
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.
Chat-GPT is rapidly emerging as a promising and potentially revolutionary tool in medicine. One of its possible applications is the stratification of patients according to the severity of clinical ...conditions and prognosis during the triage evaluation in the emergency department (ED).
Using a randomly selected sample of 30 vignettes recreated from real clinical cases, we compared the concordance in risk stratification of ED patients between healthcare personnel and Chat-GPT. The concordance was assessed with Cohen's kappa, and the performance was evaluated with the area under the receiver operating characteristic curve (AUROC) curves. Among the outcomes, we considered mortality within 72 h, the need for hospitalization, and the presence of a severe or time-dependent condition.
The concordance in triage code assignment between triage nurses and Chat-GPT was 0.278 (unweighted Cohen's kappa; 95% confidence intervals: 0.231–0.388). For all outcomes, the ROC values were higher for the triage nurses. The most relevant difference was found in 72-h mortality, where triage nurses showed an AUROC of 0.910 (0.757–1.000) compared to only 0.669 (0.153–1.000) for Chat-GPT.
The current level of Chat-GPT reliability is insufficient to make it a valid substitute for the expertise of triage nurses in prioritizing ED patients. Further developments are required to enhance the safety and effectiveness of AI for risk stratification of ED patients.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Aim
To establish how the Manchester Triage System can correctly prioritize patients admitted to the emergency department for transitory loss of consciousness in relation to their risk of presenting ...severe acute disease.
Design
A observational retrospective study.
Methods
A total of 2291 patients who required a triage evaluation for a transitory loss of consciousness at the emergency department of Merano Hospital between 1 January 2017 and 30 June 2019 were considered. Transitory loss of consciousness was classified according to European Society of Cardiology guidelines. The baseline characteristics of the patients were collected and divided according to the priority level assigned at triage into two different study groups: high priority (red/orange) and low priority (blue/green/yellow). The composite outcome of the study was defined as the diagnosis of a severe acute disease.
Results
Of the patients enrolled, 17% (390/2291) had a high‐priority code and 83% (1901/2291) received a low‐priority code. Overall, a severe acute disease was present in 16.9% of patients (387/2291). The Manchester Triage System had a sensitivity of 42.4%, a specificity of 88.1% and an accuracy of 80.4% for predicting severe acute disease. The discriminatory ability had an area under the receiver operating characteristic curve of 0.651 (CI 95%: 0.618–0.685).
Conclusions
Despite the good specificity, the low sensitivity does not currently allow the Manchester Triage System to completely exclude patients with a severe acute disease who presented in the emergency department for a transitory loss of consciousness. Therefore, it is important to develop precise nursing tools or assessments that can improve triage performance.
Impact
The assessment of a complex symptom can create difficulties in the stratification of patients in triage, assigning low‐priority codes to patients with a severe disease. Additional tools are needed to allow the correct triage assessment of patients presenting with transitory loss of consciousness.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK, VSZLJ
•The Manchester Triage System does not have a specific flow chart for the common symptom of dizziness.•The predictive power of the MTS for admission to different treatment levels, was lower in ...patients with dizziness.•Stroke patients with dizziness were significantly less accurately triaged than those without the symptom of dizziness.•An additional flow chart for dizziness should be included in the MTS, to reliably classify time-critical patients.
Dizziness is a common symptom with diverse causes, including ear-nose-throat, internal, neurological, or psychiatric origins. While for most parts treatable in nonemergency settings, it can also signal time-critical conditions, like an unnoticed stroke, requiring prompt diagnosis and treatment to prevent lasting harm or death. The aim of this study was to evaluate the validity of the Manchester Triage System in classifying patients presenting with dizziness based on final diagnoses and patient outcomes, as no specific flow chart exists for this symptom in the MTS.
Monocentric, retrospective observational study. To test the validity of the MTS in the triage of dizziness patients, the treatment level was used as a surrogate parameter. We grouped the patients into outpatient, normal ward and intermediate care/intensive care unit (IMC/ICU) patients. Furthermore, we analyzed the dizziness patients in subgroups based on the origin of their dizziness to identify potential improvements for the MTS. Patients with dizziness and stroke, who represent the most vulnerable group of dizziness patients, were also evaluated separately.
During the observation period, 2958 patients presented at the ED with the symptom dizziness and 52 017 without, who formed the reference group. When examining the relationship between triage level and subsequent treatment level, a larger deviation is observed compared to the reference group. The receiver operating characteristics (ROC) regarding hospital admission in general showed an area under the curve (AUC) in the subgroup with dizziness due to a central nervous system causes (n=838) of 0.69 (95% CI 0.65 - 0.72) and in the subgroup of dizziness by other organic cause (n=901), an AUC of 0.64 (95% CI 0.60 - 0.68). The reference group had an AUC 0.75 (95% CI 0.75 - 0.76) here. In relation to admission to IMC/ICU, the results were similar. The sensitivity of the MTS in terms of an adequate initial assessment of dizziness patients with stroke or transient ischemic attack (TIA) was 0.39, the specificity was 0.91 (reference group sensitivity 0.72, specificity 0.82).
In terms of construct validity, the present study revealed that the use of MTS as a priority triage assessment tool was found to be less accurate in emergency patients with dizziness, particularly those diagnosed with stroke/TIA, when compared to other emergency patients.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
