Emergency Severity Index Triage Research Articles

Comparative analysis of ChatGPT, Gemini and emergency medicine specialist in ESI triage assessment

IntroductionThe term Artificial Intelligence (AI) was first coined in the 1960s and has made significant progress up to the present day. During this period, numerous AI applications have been developed. GPT-4 and Gemini are two of the best-known of these AI models. As a triage system The Emergency Severity Index (ESI) is currently one of the most commonly used for effective patient triage in the emergency department. The aim of this study is to evaluate the performance of GPT-4, Gemini, and emergency medicine specialists in ESI triage against each other; furthermore, it aims to contribute to the literature on the usability of these AI programs in emergency department triage. MethodsOur study was conducted between February 1, 2024, and February 29, 2024, among emergency medicine specialists in Turkey, as well as with GPT-4 and Gemini. Ten emergency medicine specialists were included in our study but as a limitation the emergency medicine specialists participating in the study do not frequently use the ESI triage model in daily practice. In the first phase of our study, 100 case examples related to adult or trauma patients were extracted from the sample and training cases found in the ESI Implementation Handbook. In the second phase of our study, the provided responses were categorized into three groups: correct triage, over-triage, and under-triage. In the third phase of our study, the questions were categorized according to the correct triage responses. ResultsIn the results of our study, a statistically significant difference was found between the three groups in terms of correct triage, over-triage, and under-triage (p < 0.001). GPT-4 was found to have the highest correct triage rate with an average of 70.60 (±3.74), while Gemini had the highest over-triage rate with an average of 35.2 (±2.93) (p < 0.001). The highest under-triage rate was observed in emergency medicine specialists (32.90 (±11.83)). In the ESI 1–2 class, Gemini had a correct triage rate of 87.77%, GPT-4 had 85.11%, and emergency medicine specialists had 49.33%. ConclusionIn conclusion, our study shows that both GPT-4 and Gemini can accurately triage critical and urgent patients in ESI 1&2 groups at a high rate. Furthermore, GPT-4 has been more successful in ESI triage for all patients. These results suggest that GPT-4 and Gemini could assist in accurate ESI triage of patients in emergency departments.

COMPARISON OF PERFORMANCES OF OPEN ACCESS NATURAL LANGUAGE PROCESSING BASED CHATBOT APPLICATIONS IN TRIAGE DECISIONS

Objective: Being publicly available, easy to use, and continuously evolving, next-generation chatbots have the potential to be used in triage, one of the most critical functions of an Emergency Department. The aim of this study was to assess the performance of Generative Pre-trained Transformer 4 (GPT-4), Bard and Claude during decision-making for Emergency Department triage.&#x0D; Material and Methods: This was a preliminary cross-sectional study conducted with 50 case scenarios. Emergency Medicine specialists determined the reference Emergency Severity Index triage category of each scenario. Subsequently, each case scenario was queried using three chatbots. Inconsistent classifications between the chatbots and references were defined as over-triage (false positive) or under-triage (false negative). The primary and secondary outcomes were the predictive performance of chatbots and the difference between them in predicting high acuity triage.&#x0D; Results: F1 Scores for GPT-4, Bard, and Claude for predicting Emergency Severity Index 1 and 2 were 0.899, 0.791, and 0.865 respectively. The ROC Curve of GPT-4 for high acuity predictions showed an area under the curve (AUC) of 0.911 (95% CI: 0,814-1; p

Relationship of Hospital Mortality with Metabolic Acidosis Severity in Critically Ill Patients

Background: Metabolic acidosis (MA) is a common pathologic process with fatal consequences in critically ill (CI) patients. The more the severity of acidosis the more mortality rate is expected. To evaluate the relationship of hospital mortality with MA severity in CI patients admitted to emergency department (ED).&#x0D; Methods: In this prospective cohort study, we enrolled CI patients (based on physician clinical assumption), most at level 1 or 2 emergency severity index triage system. Patients were followed and evaluated in 2 parallel groups, one with and the other without MA. The severity of acidosis, chief complaints, final diagnosis, demographic data, acute physiologic assessment and chronic health evaluation II (APACHE II) score, serum lactate and bicarbonate level, need for intubation and mechanical ventilation, admission ward, hospital length of stay and in hospital mortality were compared between the 2 groups.&#x0D; Results: A total of 1811 CI patients including 60.2% males and 39.8% females with and without MA were evaluated. The most common age range was 65-55 years old (31.7%) with the meanSD of 61.348.23. The most common complaints and diagnoses were weakness (40.5%) and pneumosepsis (35.1%), respectively. Patients with severe acidosis had higher lactate level and APACHE II score (p&lt;0.05). Mortality rate was 10.4%. Most of our cases had severe MA. Expired cases had higher lactate level and APACHE II score (p&lt;0.05).&#x0D; Conclusion: Lactate level, bicarbonate level and APACHE II score were all significant independent predictors of hospital mortality in CI patients.

Emergency Department Length of Stay and in-Hospital Mortality of Non-Traumatic Patients in a University Hospital

Objective: To assess the emergency department length of stay (EDLOS) and mortality in each Emergency Severity Index (ESI) triage level. In addition to identifying the cut-off point of EDLOS to predict 72-hour in-hospital mortality among adult non-traumatic patients in the ED of a university hospital.Material and Methods: A cross-sectional study was conducted by retrieving patient data from the hospital information system; from January 1, 2014, to December 31, 2018. Patient characteristics, EDLOS, and in-hospital mortality rates were analyzed using the R program. The cut-off values of EDLOS, via the area under the curve for the best prediction of 72-hour in-hospital mortality in patients at different ESI levels, were analyzed by multivariate analysis. Statistical significance was defined as a p-value of ≤0.05.Results: Data from 71,247 patients with 123,356 visits were enrolled. EDLOS significantly decreased across ESI levels and the in-hospital mortality rates were highest in ESI 1, followed by ESI 2 and ESI 3. The predictive ability of EDLOS was the highest for ESI 4, followed by ESI 3. The cut-off point of EDLOS at 3.58 hours showed the best sensitivity, which was a significant risk factor for mortality after adjusting for other significant variables. An EDLOS longer than 4 hours was a significant factor for poor survival in patients with ESI 2 and ESI 3.Conclusion: A practical cut-off point of 4 hours EDLOS can be used to predict 72-hour in-hospital mortality. Healthcare providers in the ED should consider EDLOS as a safety indicator for quality assurance.

Association between patient-reported onset-to-door time and mortality in patients hospitalized with COVID-19 disease

IntroductionTimely hospital presentation and treatment are critical for recovery from coronavirus disease (COVID-19). However, the relationship between symptom onset-to-door time and key clinical outcomes, such as inpatient mortality, has been poorly understood due to the difficulty of retrospectively measuring symptom onset in observational data. This study examines the association between patient-reported symptom onset-to-door time (ODT) and mortality among patients hospitalized and treated for COVID-19 disease. MethodsWe conducted a retrospective cohort study of emergency department (ED) encounters of patients with COVID-19 disease who were hospitalized and received remdesivir and/or dexamethasone between March 1, 2020, and March 1, 2022. The exposure was patient-reported ODT in days. The outcome of interest was inpatient mortality, including referral to hospice care. We used multivariable logistic regression to examine the association between ODT and mortality while adjusting for patient characteristics, hospital sites, and seasonality. We tested whether severe illness on hospital presentation modified the association between ODT and mortality. Severe illness was defined by Emergency Severity Index triage level 1 or 2 and hypoxia (SpO2 < 94%). ResultsOf the 3451 ED hospitalizations included, 439 (12.7%) resulted in mortality, and 1693 (49.1%) involved patients with severe illness on hospital presentation. Greater ODT was significantly associated with lower odds of inpatient mortality (adjusted odds ratio (AOR) = 0.96, 95% CI = 0.93–1.00, P = 0.023). There was a statistically significant interaction between ODT and severe illness at hospital arrival on mortality, suggesting the negative association between ODT and mortality specifically pertained to patients who were not severely ill upon ED presentation (AOR = 0.93, 95% CI = 0.87–1.00, P = 0.035). The adjusted probability of mortality was significantly lower for non-severely ill, hospitalized patients who presented on days 8–14 (5.2%–3.3%) versus days 0–3 (9.4%–7.5%) after symptom onset. ConclusionMore days between symptom onset and hospital arrival were associated with lower mortality among hospitalized patients treated for COVID-19 disease, particularly if they did not have severe illness at ED presentation. However, onset-to-door time was not associated with mortality among hospitalized patients with severe illness at ED presentation. Collectively, these results suggest that non-severely ill COVID-19 patients who require hospitalization are less likely to decompensate with each passing day without severe illness. These findings may continue to guide clinical care delivery for hospitalized COVID-19 patients.

Comparison of body mass index level by triage level in the emergency department

INTRODUCTION: Obesity is a high cause of death in both non-communicable and communicable diseases such as COVID-19. The aim of this study is to increase the awareness of emergency department (ED) managers and employees about this problem by showing obesity rates according to triage level in patients admitted to the ED. MATERIAL AND METHODS: BMI levels and complaints of 1246 patients admitted to the ED according to the 3-level triage were re-evaluated with the 5-level ESI (Emergency Severity Index) triage for this study. RESULTS: The mean BMI of 1246 patients was found to be 27.25 ± 5.88 (overweight). 26% of the ED patients were found to be obese and 37.7% of them were overweight. While the mean BMI score of the 6–11 age group was found to be class 1 obesity, the other pediatric and adult age groups were found to be overweight. The highest mean BMI according to both the 3-stage triage system and the 5-stage ESI triage system was found in triage 1 patients (28.8011 ± 7.98; 28.18 ± 6.78, respectively). Obese patients mostly applied to the ED with orthopedic problems and trauma (26.5%). Also, of the patients with class 3 severe obesity, 50% presented with trauma. CONCLUSIONS: The higher the BMI, the higher the triage severity level. BMI levels should be evaluated in the field of triage together with vital signs, especially in trauma patients, and obesity should be considered in ED and hospital management.

Association of delirium with increased short-term mortality among older emergency department patients: A cohort study

Study objectiveTo evaluate the association between delirium and subsequent short-term mortality in geriatric patients presenting to the emergency department (ED). MethodsThis was an observational cohort study of adults age ≥75 years who presented to an academic ED and were screened for delirium during their ED visit. The Delirium Triage Screen followed by the Brief Confusion Assessment Method were used to ascertain the presence of delirium. In-hospital, 7-day, and 30-day mortality were compared between patients with and without ED delirium. Odds ratios with 95% confidence intervals (CIs) were calculated through logistic regression after adjusting for confounders including age, sex, history of dementia, ED disposition, and acuity. ResultsA total of 967 ED visits were included for analysis among which delirium was detected in 107 (11.1%). The median age of the cohort was 83 years (IQR 79, 88), 526 (54.4%) were female, 285 (29.5%) had documented dementia, and 171 (17.7%) had a high acuity Emergency Severity Index triage level 1 or 2. During the hospitalization, 5/107 (4.7%) of those with delirium and 4/860 (0.5%) of those without delirium died. Within 7 days of ED departure, 6/107 (5.6%) of those with delirium and 6/860 (0.7%) of those without delirium died (unadjusted OR 8.46, 95% CI 2.68–26.71). Within 30 days, 18/107 (16.8%) of those with delirium and 37/860 (4.3%) of those without delirium died (unadjusted OR 4.50, 95% CI 2.46–8.23). ED delirium remained associated with higher 7-day (adjusted OR 5.23, 95% CI 1.44–19.05, p = 0.008) and 30-day mortality (adjusted OR 2.82, 95% CI 1.45–5.46, p = 0.002). ConclusionDelirium is an important prognostic factor that ED clinicians and nurses must be aware of to optimize delirium prevention, management, disposition, and communication with patients and families.

Associated Factors of Under and Over-Triage Based on The Emergency Severity Index; a Retrospective Cross-Sectional Study.

Under-triage increases patients' risks for morbidity and mortality, whereas over-triage limits the resources available to sicker patients. This study aimed to determine the rates as well as associated factors of under-triage and over-triage in emergency department (ED), based on Emergency Severity Index (ESI) triage system. In this retrospective cross-sectional study, triage level of ED patients based on the ESI version 4, was studied during a 9-month period in 2019. Patients' ESI level, which were examined by triage nurses were reevaluated by 3 emergency physicians and the rate of correct, under-, and over-triage as well as their associated factors were analyzed. 1000 cases of triage were evaluated. Triage was correct in 69.1% of cases. The rate of under-triage was 4.9%, and that of over-triage was 26.0%. Over-triage was significantly more common among patients aged 18-30 years than for those aged ≥65 years (adjusted odds ratio [OR] = 1.73; 95% confidence interval [CI]: 1.07-2.81; p = 0.026); those with traumatic injuries (adjusted OR = 1.80; 95% CI: 1.29-2.52; p = 0.001); those arriving at the hospital during the evening shift (adjusted OR = 1.42; 95% CI: 1.01-2.0; p = 0.046); patients who were hospitalized (adjusted OR = 0.35; 95% CI: 0.22-0.54; p < 0.001); and those with severe pain (adjusted OR = 0.28; 95% CI: 0.10-0.84; p = 0.023). Younger age was also significantly associated with under-triage. Patients aged 18-30 years were under-triaged more often than those aged ≥65 years (adjusted OR = 3.05; 95% CI: 1.16-8.00; p = 0.023). Over-triage was substantially more common than under-triage in Vajira Hospital. Factors associated with over-triage were younger age, traumatic injury, arrival time, hospital admission, and severe pain. Younger age was the only factor related to under-triage.

Performance of emergency triage prediction of an open access natural language processing based chatbot application (ChatGPT): A preliminary, scenario-based cross-sectional study.

Artificial intelligence companies have been increasing their initiatives recently to improve the results of chatbots, which are software programs that can converse with a human in natural language. The role of chatbots in health care is deemed worthy of research. OpenAI's ChatGPT is a supervised and empowered machine learning-based chatbot. The aim of this study was to determine the performance of ChatGPT in emergency medicine (EM) triage prediction. This was a preliminary, cross-sectional study conducted with case scenarios generated by the researchers based on the emergency severity index (ESI) handbook v4 cases. Two independent EM specialists who were experts in the ESI triage scale determined the triage categories for each case. A third independent EM specialist was consulted as arbiter, if necessary. Consensus results for each case scenario were assumed as the reference triage category. Subsequently, each case scenario was queried with ChatGPT and the answer was recorded as the index triage category. Inconsistent classifications between the ChatGPT and reference category were defined as over-triage (false positive) or under-triage (false negative). Fifty case scenarios were assessed in the study. Reliability analysis showed a fair agreement between EM specialists and ChatGPT (Cohen's Kappa: 0.341). Eleven cases (22%) were over triaged and 9 (18%) cases were under triaged by ChatGPT. In 9 cases (18%), ChatGPT reported two consecutive triage categories, one of which matched the expert consensus. It had an overall sensitivity of 57.1% (95% confidence interval [CI]: 34-78.2), specificity of 34.5% (95% CI: 17.9-54.3), positive predictive value (PPV) of 38.7% (95% CI: 21.8-57.8), negative predictive value (NPV) of 52.6 (95% CI: 28.9-75.6), and an F1 score of 0.461. In high acuity cases (ESI-1 and ESI-2), ChatGPT showed a sensitivity of 76.2% (95% CI: 52.8-91.8), specificity of 93.1% (95% CI: 77.2-99.2), PPV of 88.9% (95% CI: 65.3-98.6), NPV of 84.4 (95% CI: 67.2-94.7), and an F1 score of 0.821. The receiver operating characteristic curve showed an area under the curve of 0.846 (95% CI: 0.724-0.969, P < 0.001) for high acuity cases. The performance of ChatGPT was best when predicting high acuity cases (ESI-1 and ESI-2). It may be useful when determining the cases requiring critical care. When trained with more medical knowledge, ChatGPT may be more accurate for other triage category predictions.

The Impact of Multi-System Trauma in Patients with Sickle Cell Disease

The impact of multi-system traumatic injury in patients with Sickle Cell Disease (SCD) is grossly understudied; only three published case studies have described such a relationship between sickle cell and multi-system trauma. These reports do not address prospective health outcomes following injury, despite strong biological plausibility to support adverse effects in trauma patients with sickle cell trait. It is likely, therefore, that trauma may increase acute complications such as vaso-occlusive events (VOC) and thus pain crises in SCD. We examined whether exposure to a traumatic injury is associated with an increase in frequency and duration of VOC. A retrospective chart review of 356 adult patients from 2000-2022 with SCD was performed, using data from electronic health record abstraction. A total of 96 patients were identified with a prior traumatic event (TE), defined as a sudden onset of physical injuries of any severity requiring an Emergency Department (ED) visit. Patients with missing data one-year pre- and post-TE, isolated injuries, or periods of incarceration were excluded. The 62 qualifying patients were then sorted into three primary comparison groups: (A) those with severe injuries (receiving triage by Trauma Team Activation (TTA) and admission), (B) moderate injuries (receiving triage by TTA but no admission), and (C) minor injuries (receiving neither triage by TTA nor admission). To further stratify by triage status alone, groups A and B were combined to compare against those with minor injuries (triage vs no-triage). TE hospital length of stay (LOS) and 30-day mortality were noted for all groups. To determine sickle cell-related outcomes, we recorded the time from TE discharge to first VOC event, as well as the number of VOC requiring an ED visit one-year pre- and post-TE. LOS for the VOC event immediately pre-TE was compared to the first VOC post-TE. We tested statistically significant changes in the frequency of ED visits, hospitalizations, and LOS for TE admission, stratifying pre-post estimates by severity of trauma. Favorable prospective health outcomes were defined as no significant difference in mortality, number of ED visits, hospitalizations, and VOC LOS pre- and post-TE. Our analysis determined that the earliest time to first VOC event post-TE was noted in patients with mild injuries at 826.3 hours, followed by patients with moderate injuries at 2349.2 hours, and patients with severe injuries at 3252.6 hours. This trend may imply that unresolved injuries from a lack of triage by TTA and disease management may contribute to early onset VOC. Two-sample t-tests report that the patient cohort with mild injuries observed a 28% increase in pain crises frequency post-injury (p=0.04), followed by patients with severe injury at 20% (p=0.24), and moderate injuries at 8% (p=0.16). These results may suggest that the cohorts of SCD patients with the most favorable prospective health outcomes were those who were ultimately admitted post-injury. Similarly, duration of first VOC post-injury increased for patients with severe injuries by 472% (p=0.78), followed by patients with moderate injuries by 202% (p=0.16), suggesting that high injury severity may contribute to longer VOC LOS. No statistical difference in 30-day mortality was noted between all cohorts. Our analysis was limited by small cohort sample sizes, retrospective documentation of SCD and trauma outcomes, and lack of precedence. Our findings are the first to provide preliminary evidence for an association between exposure to multi-system traumatic injury and poor SCD outcomes. This was especially true for patients classified as having mild traumatic injuries and thus not requiring triage by TTA or admission. In this subset, lack of further interventions following an injury may result in unforeseen physiologic stressors contributing to occurrence of VOC and prolonged hospital admissions. Only one patient of 356 record reviews had an Emergency Severity Index Triage (ESI) documented, despite NIH SCD Expert Panel's recommendation that all SCD patients be designated an ESI of 2. In SCD patients, further management of traumatic injuries, regardless of severity, may help to minimize future VOC events and other adverse outcomes. Further research is required to identify post-TE triage protocols, predict acute triggers for pain events, and target appropriate medical interventions for SCD patients suffering traumatic injuries. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Assessment of Emergency Department Care for Patients with Acute Pain Crisis after the Formation of a Multidisciplinary Team

Introduction:American Society of Hematology (ASH) guidelines recommend the rapid evaluation and treatment of patients presenting to the Emergency Department (ED) with pain from an acute vaso-occlusive episode (VOE) related to sickle cell disease (SCD). The treatment of severe pain from VOE in SCD is time dependent and time sensitive. Guidelines recommend that treatment for acute VOE with parental opioid analgesia occurs within 60 minutes of ED registration. With respect to the five-level Emergency Severity Index (ESI) triage tool, in which lower numbers indicate higher acuity, patients with SCD are to be assigned an Emergency Severity Index (ESI) of 2 indicating (a) greater disease burden, and (b) the need for high priority bed assignment. Objectives: We aimed to create a multidisciplinary team of providers to assess and address the existing barriers and facilitators to improving guideline adherence for the management of acute crises in our large academic health system. The primary outcome of this initiative was to improve guideline adherence by ensuring 90% or greater adherence to ESI 2 assignment to acknowledge illness severity as well as timely, within 60-minute opioid analgesia. Methods: In March 2020, we convened a multidisciplinary team of stakeholders to discuss the ED care of patients with SCD presenting with an acute VOE. The group comprises ED and infusion center nurse champions, nurse educators, nurse leaders, hematologists, palliative care specialists, primary care physicians, psychologists, advanced practice providers and other allied health professionals including social work and spiritual care. Initial monthly meetings established recommendations based on national guidelines and discussed interventions to improve guideline adherence including 1. a nursing driven pain management orderset with subcutaneous and intranasal opioids, 2. a best practice alert with the recommended guidelines. We conducted a retrospective review of ED visit data including all patients with a known diagnosis of sickle cell disease presenting to the ED with a chief complaint of acute pain related to VOE from January 2018-February 2020 and March 2020 to March 2022. We compared the before and after intervention using descriptive statistics. Results: Of the 760 unique encounters for acute pain related to sickle cell disease from 2018-2022, 406 visits occurred before the group formation and 354 visits occurred after the group formed. Mean age was 30.5 years (+/- 19.5) in the pre-intervention period compared to the 29.5 years (+/- 18.9) in the post intervention period. The time to the first opioid order placed pre-intervention averaged 53.3 mins (+/- 64.9) was not significantly different compared to the post period 75.2 mins (+/- 125.8; p =0.17). The proportion of patients assigned an ESI 2 changed from 49.3% to 50.5%. Conclusion: While there was a marginal increase in the ESI 2 assignment among SCD patients presenting in acute VOE, there was no significant change in the ED time to first opioid after the formation of a multidisciplinary team.

The Accuracy of Sepsis Screening Score for Mortality Prediction at Emergency Department Triage.

IntroductionSepsis has a mortality rate of 10–40% worldwide. Many screening tools for sepsis prediction and for emergency department (ED) triage are controversial. This study compared the accuracy of the scores for predicting 28-day mortality in adult patients with sepsis in the triage area of the ED.MethodsAdult patients who presented to the ED of a tertiary-care university hospital from January–December 2019 with an initial diagnosis of sepsis or other infection-related conditions were enrolled. We calculated predictive scores using information collected in the ED triage area. Prognostic accuracy was measured by the area under the receiver operating characteristic curve (AUROC) for predicting 28-day mortality as a primary outcome. The secondary outcomes included mechanical ventilation usage and vasopressor usage for 28 days.ResultsWe analyzed a total of 550 patients. The 28-day mortality rate was 12.4% (n = 68). The 28-day mortality rate was best detected by the National Early Warning Score (NEWS) (AUROC = 0.770; 95% confidence interval [CI]: 0.705–0.835), followed by the quick Sequential Organ Failure Assessment (qSOFA) score (AUROC = 0.7473; 95% CI: 0.688–0.806), Search Out Severity (SOS) score (AUROC = 0.749; 95% CI: 0.685–0.815), Emergency Severity Index (ESI) triage (AUROC = 0.599; 95% CI: 0.542–0.656, and the Systemic Inflammatory Response System (SIRS) criteria (AUROC = 0.588; 95% CI: 0.522–0.654]). The NEWS also provided a higher AUROC and outperformed for 28-day mechanical ventilator usage and 28-day vasopressor usage.ConclusionThe NEWS outperforms qSOFA, SOS, SIRS, and ESI triage in predicting 28-day mortality, mechanical ventilator, and vasopressor usage of a patient with sepsis who is seen at ED triage.

Effect of Emergency Severity Index Annual Competency Assessment on Mistriage

There is limited evidence identifying best practices to promote competency of accurate assignment of the Emergency Severity Index (ESI) acuity level to patients who present to the emergency department (ED) triage. Triage-trained nurses do not receive competency training in an ESI triage tool. A retrospective chart review of 150 patients was completed to evaluate mistriage rates before and after triage-trained nurses completed an ESI competency assessment. The retrospective chart review showed no statistically significant difference in mistriage from pre- to postintervention ( P = .8535). Implementation of an ESI annual competency assessment aligns well with an emerging theme in the literature that ED nurses should be provided with ongoing education that reinforces knowledge and implementation of ESI triaging.

Comparison the Emergency Severity Index and Manchester Triage System in Trauma Patients.

Objective:To compare the emergency severity index (ESI) and Manchester triage system (MTS) in trauma patients.Methods:This cross-sectional study was conducted by census method in Hasheminejad hospital during 2019. Patients referred to a trauma center triaged by five trained triage nurses based on ESI and MTS. Outcomes were considered as length of stay at the emergency department, admission to the other sectors and discharge or leave the hospital. Information from the triage form, nursing registry office and hospital registry system were extracted and analyzed by SPSS software.Results:Totally 447 and 468 patients triaged with the ESI and MTS were included, respectively. Seventy percent of patients triaged with ESI and 34% with MTS were placed in level 3 or the yellow group (equivalent group 3 triage). The hospitalization rate is approximately equal at each triage level in the both systems. The mortality rate in both groups was 0%. Mean length of stay was significantly lower in the MTS group compared to ESI in the emergency department (p<0.05).Conclusion:Using of ESI triage in the trauma center causes to arrive more patients to the emergency department instead of the fast track and leads to waste the time and energy of staff’. However, further studies are needed to prove this result.

Effect of age adjustment on two triage methods

BackgroundMost emergency departments rely on acuity assessment, triage, to recognize critically ill patients that need urgent treatment, and to allocate resources according to need. The accuracy of commonly used triage instruments such as the Emergency Severity Index (ESI) is lower for older adults compared to young patients. We aim to examine, whether adjusting the triage category by age leads to improvement in sensitivity without excessive increase in patient numbers in the higher triage categories. The primary outcome measure was 3-day mortality and secondary outcomes were 30-day mortality, hospital admission, and HDU/ICU admissions.MethodsWe gathered data of all adult patients who had an unscheduled visit to any of our three emergency departments within one month. The data was analysed for 3-day mortality, 30-day mortality, hospital admission, and high dependency unit or intensive care unit (HDU/ICU) admission. The analysis was run for both the standard ESI triage method and a local 3-level Helsinki University Hospital (HUH) method. A further analysis was run for both triage methods with age adjustment. Net reclassification improvement values were calculated to demonstrate the effect of age adjustment.ResultsThirteen thousand seven hundred fifty-nine patients met the study criteria, median age was 57. 3-day mortality AUCs for unadjusted HUH and ESI triage were 0.77 (0.65–0.88) and 0.72 (0.57–0.87); 30-day mortality AUCs were 0.64 (0.59–0.69) and 0.69 (0.64–0.73); hospital admission AUCs were 0.60 (0.68–0.71) and 0.66 (0.65–0.68) and HDU/ICU admission AUCs were 0.67 (0.64–0.70) and 0.82 (0.79–0.86), respectively. Age adjustment improved accuracy for 30-day mortality and hospital admission. With the threshold age of 80, AUCs for 30-day mortality were 0.73 (0.68–0.77) and 0.77 (0.73–0.81) and for hospital admission, 0.66 (0.65–0.67) and 0.72 (0.71–0.73) for the HUH and ESI triage. The effect was similar with all cut off ages.ConclusionMoving older adults into a more urgent triage category based on age, improved the triage instruments’ performance slightly in predicting 30-day mortality and hospital admission without excessive increase in patient numbers in the higher triage categories. Age adjustment did not improve HDU/ICU admission or 3-day mortality prediction.

Characteristics and Demographics of Patients Requiring Emergent Air Medical.

Background As integrated health systems become more common, interfacility patient transfers will increase and air transport programs will be prioritized. Understanding characteristics of patients triaged to air medical transport will assist with resource allocation and needs assessment. The objective of this study was to investigate the demographics and clinical characteristics of patients that presented to the emergency department (ED) and subsequently required emergent air medical interfacility transport. Methods This was a retrospective, multicenter study conducted at eight hospitals within Northwell Health, the largest academic health system in New York state. The study was conducted between December 1, 2014, and July 31, 2020, and included patients who presented to an ED and subsequently required emergent air medical interfacility transport. Results Overall, the median age was 37 years (IQR 4–66), and 231 (54%) subjects were males. The majority of subjects (59%) had no reported comorbidities, arrived by ambulance (52%), and were emergency severity index triage 2 (48%). Frequent indications for transfer were nontraumatic neurologic (37%), pulmonary or respiratory (13%), trauma (12%), and cardiovascular (12%). Most patients were not ventilated before transport (71%). The median time to call for transport at the sending institution was 2:42 hours (IQR 1:14–6:54), and the median length of stay was 4:12 (IQR 2:31–8:48). Most patients were subsequently admitted (96%) at the receiving institution to an intensive care unit (72%). Conclusions This study describes patients' demographic and clinical characteristics who required emergent air medical transport. Helicopter transport is costly, and data from these patients may further help our understanding of who is transported by air and how important air transport is to the health system.

Accuracy of Emergency Severity Index in older adults.

Background and importanceEmergency Severity Index is a five-level triage tool in the emergency department that predicts the need for emergency department resources and the degree of emergency. However, it is unknown whether this is valid in patients aged greater than or equal to 65 years.ObjectiveThe aim of the study was to compare the accuracy of the Emergency Severity Index triage system between emergency department patients aged 18–64 and greater than or equal to 65 years.Design, settings, and participantsThis was a retrospective observational cohort study of adults who presented to a Finnish emergency department between 1 February 2018 and 28 February 2018. All data were collected from electronic health records.Outcome measures and analysisThe primary outcome was 3-day mortality. The secondary outcomes were 30-day mortality, hospital admission, high dependency unit or ICU admission, and emergency department length of stay. The area under the receiver operating characteristic curve and cutoff performances were used to investigate significant associations between triage categories and outcomes. The results of the two age groups were compared.Main resultsThere were 3141 emergency department patients aged 18–64 years and 2370 patients aged greater than or equal to 65 years. The 3-day mortality area under the curve in patients aged greater than or equal to 65 years was greater than that in patients aged 18–64 years. The Emergency Severity Index was associated with high dependency unit/ICU admissions in both groups, with moderate sensitivity [18–64 years: 61.8% (50.9–71.9%); greater than or equal to 65 years: 73.3% (63.5–81.6%)] and high specificity [18–64 years: 93.0% (92.0–93.8%); greater than or equal to 65 years: 90.9% (90.0–92.1%)]. The sensitivity was high and specificity was low for 30-day mortality and hospital admission in both age groups. The emergency department length of stay was the longest in Emergency Severity Index category 3 for both age groups. There was no significant difference in accuracy between age groups for any outcome.ConclusionEmergency Severity Index performed well in predicting high dependency unit/ICU admission rates for both 18–64 years and greater than or equal to 65-year-old patients. It predicted the 3-day mortality for patients aged greater than or equal to 65 years with high accuracy. It was inaccurate in predicting 30-day mortality and hospital admission for both age groups.

ESI Triage Distribution in U.S. Emergency Departments.

The accurate triage of arriving emergency department (ED) patients is a key component of emergency nursing practice. Overtriage assignment of patients misallocates scarce resources in a time of department overcrowding, whereas patient undertriage can create risks for negative patient outcomes secondary to care delays. Limited evidence is available regarding ED triage accuracy. It is estimated that appropriate adherence to the Emergency Severity Index (ESI) triage tool and assigning triage categories could be as low as 60% (McFarlane, 2019a, 2019b). The purpose of this retrospective observational study was to examine the 2019 triage distribution of 954,847 ED encounters at 25 hospitals. Comparisons were then made with the spreads identified in the ESI Implementation Handbook (Gilboy, Tanabe, Travers, & Rosenau, 2020). Study results reflect the presence of wide variations in distribution when compared with the expected spread published by Gilboy et al. (2020). These variations illustrate the need for further facility-level evaluation. ESI Level 2 percentages varied from as little as 2.6% to as high as 69% of each facility's ED visit population. Examining an individual facility's annualized triage distribution may serve as a swift method in determining whether additional investigation into triage accuracy is warranted. EDs must implement and sustain an ongoing quality control program to achieve and maintain triage inter- and intrarater reliability. Further research is needed on the value of triage inaccuracy with real-time feedback on nurses' clinical decision-making and patient outcomes. It is also imperative that the expected and observed ESI triage distribution in U.S. EDs is updated when established accuracy quality control programs are present.

Implementation and evaluation of the five-level emergency triage (emergency severity index tool): A hospital-based, prospective, observational study

Objective: To implement the 5-level Emergency Severity Index (ESI) triage tool into nursing practice in the emergency department (ED) and validate it with a population-based cohort using hospitalization and length of stay (LOS) as outcome measures. Methods: The study included 850 patients, irrespective of age and gender, reporting to the ED of a tertiary care hospital. Each patient was assessed by the triage nurse as per the 5-level ESI triage tool and categorized. The number and type of resources used by the patient, LOS in the ED and the outcome were noted. Data were statistically analyzed by using RStudio Team software, 2015. A P value of&lt;0.05 was considered to be statistically significant. Results: The majority of patients belonged to ESI-4 (46.82%), followed by ESI-1 (19.41%), ESI-2 (17.06%), ESI-3 (10.35%), and ESI-5 (6.35%). In most patients, the LOS in the ED was&lt;120 minutes (55.65%). ESI showed a statistically significant association with all the clinical characteristics, as well as resources used, interventions needed, maximum time allowed before initiating physician assessment, duration of stay in ED, and patient outcomes (P=0.000). ESI was found to have a sensitivity of 100% and specificity of 78%. Conclusion: ESI is a useful and valid tool for the emergency triage and has the potential to become the standard triage acuity assessment in EDs in India.

335 Emergency Severity Index Triage Equivalency to Sort Assess Life Saving Interventions Treatment and Transport Disaster Triage

Disaster triage methodologies in the field are relatively established, but there is less guidance for first receivers and emergency departments (ED) once patients arrive. The relationship between general operational triage methodology, such as the Emergency Severity Index (ESI), and disaster-based triage, such as Sort Assess Life Saving Interventions Treatment And Transport Disaster Triage (SALT), is of immediate practical importance for an ED experiencing a disaster situation. The ability to quickly convert triage classifications from ESI to SALT could conserve precious time and resources already at a premium.