Validation of different pediatric triage systems in the emergency department

Predictability of the emergency department triage system during the COVID-19 pandemic

OBJECTIVE

Emergency department (ED) triage systems are used to classify the severity and urgency of emergency patients, and Korean medical institutions use the Korean Triage and Acuity Scale (KTAS). During the COVID-19 pandemic, appropriate treatment for emergency patients was delayed due to various circumstances, such as overcrowding of EDs, lack of medical workforce resources, and increased workload on medical staff. The purpose of this study was to evaluate the accuracy of the KTAS in predicting the urgency of emergency patients during the COVID-19 pandemic.

METHODS

This study retrospectively reviewed patients who were treated in the ED during the pandemic period from January 2020 to June 2021. Patients were divided into COVID-19-screening negative (SN) and COVID-19-screening positive (SP) groups. We compared the predictability of the KTAS for urgent patients between the two groups.

RESULTS

From a total of 107,480 patients, 62,776 patients (58.4%) were included in the SN group and 44,704 (41.6%) were included in the SP group. The odds ratios for severity variables at each KTAS level revealed a more evident discriminatory power of the KTAS for severity variables in the SN group (P<0.001). The predictability of the KTAS for severity variables was higher in the SN group than in the SP group (area under the curve, P<0.001).

CONCLUSION

During the pandemic, the KTAS had low accuracy in predicting patients in critical condition in the ED. Therefore, in future pandemic periods, supplementation of the current ED triage system should be considered in order to accurately classify the severity of patients.

Drinking from the Holy Grail-Does a Perfect Triage System Exist? And Where to Look for It?

The Emergency Department (ED) is a facility meant to treat patients in need of medical assistance. The choice of triage system hugely impactsed the organization of any given ED and it is important to analyze them for their effectiveness. The goal of this review is to briefly describe selected triage systems in an attempt to find the perfect one. Papers published in PubMed from 1990 to 2022 were reviewed. The following terms were used for comparison: "ED" and "triage system". The papers contained data on the design and function of the triage system, its validation, and its performance. After studies comparing the distinct means of patient selection were reviewed, they were meant to be classified as either flawed or non-ideal. The validity of all the comparable segregation systems was similar. A possible solution would be to search for a new, measurable parameter for a more accurate risk estimation, which could be a game changer in terms of triage assessment. The dynamic development of artificial intelligence (AI) technologies has recently been observed. The authors of this study believe that the future segregation system should be a combination of the experience and intuition of trained healthcare professionals and modern technology (artificial intelligence).

Red Code Management in a Pediatric Emergency Department: A Retrospective Study

The "red code" (RC) represents the highest level of emergency in the emergency department (ED). This study retrospectively analyzed RCs in the Regina Margherita Children's Hospital ED, a regional referral center in north Italy, between 1 July 2020 and 30 June 2023. The aim was to describe RC characteristics and to identify significant correlations between presenting complaints and clinical management. The study includes 934 RCs (0.9% of overall ED admissions); 64% were assigned based on the Pediatric Assessment Triangle alteration. Most patients, 86.5%, followed the medical pathway, while 13.5% were surgical cases. Admission complaints were respiratory (46.9%), neuropsychiatric (26.7%), traumatic (11.8%), cardiologic (9.3%), metabolic (3.8%), and surgical (1.5%). Seventy-six percent of patients received vascular access, and intraosseous access was obtained in 2.2% of them. In one-third of RCs, an urgent critical care evaluation was necessary, and 19% of cases required admission to the intensive care unit. The overall mortality rate was 3.4% (0.4% in ED setting). The study identified six distinct diagnostic pathways, each associated with specific characteristics in clinical presentation, management, therapeutic interventions, and outcomes. Our findings underscore the need for a systematic approach in pediatric emergency settings, supported by international and national guidelines but also by clearly defined diagnostic pathways, aiming to enhance the quality of care and patient outcomes.

Outcomes of Chengdu Pediatric Emergency Triage Criteria: A Retrospective Study of 198,628 Pediatric Patient Records

BACKGROUND The Chengdu pediatric emergency triage criteria were developed at our hospital and consist of 4 triage levels: immediate treatment (level 1), treatment within 10 min (level 2), treatment within 30 min (level 3), and treatment within 240 min (level 4). This study aimed to evaluate outcomes from the levels 1 to 4 of this triage criteria. MATERIAL AND METHODS A self-designed survey form was used to collect pediatric Emergency Department (ED) patients' general data, including age, sex, and chief concern, and clinical data, including triage level, whether the patient had died, and whether the patient was admitted to our hospital. A total of 198,628 patient records that were triaged during January to May 2022 using Chengdu pediatric emergency triage criteria were included in this retrospective study. The numbers of patients triaged to levels 1, 2, 3, and 4 were 128, 1164, 14,560, and 182,776, respectively. RESULTS Statistically significant differences were found in waiting time for treatment, hospital admission rates, admission conversion rates, and case mix index at admission under different triage levels. The higher the triage priority level, the shorter the waiting time for ED treatment, higher the hospital admission and admission conversion rates, and higher case mix index value. CONCLUSIONS The Chengdu pediatric emergency triage criteria developed and applied within our hospital appears to be characterized by good clinical validity. Equipped with this triage criteria, triage nurses are more capable of determining the severity and emergency of the pediatric ED patients' health conditions and effectively triaging the patients.

Comparison between local and three validated triage systems in an emergency department for 2126 children under 3 months

AIM

Triage of patients less than 3 months old was not already studied. The aim was to evaluate Paediatric Emergency Department triage in patients less than 3 months old and newborns using a local system in comparison with three validated paediatric triage systems (Canadian Triage and Acuity Scale, Manchester Triage System and Emergency Severity Index) and to determine inter-system agreement.

METHODS

All admissions of patients less than 3 months old admitted to the Emergency Department of the Saint Vincent University Hospital between April 2018 and December 2019 were included. The local triage system level was determined prospectively for comparison with retrospectively calculated triage levels of the validated systems. Hospitalisation rates were compared and inter-system agreements determined.

RESULTS

Among emergency admissions, 2126 were included (55% males, mean age 45 days). Hospitalisation rate increased with priority severity as determined by all triage systems studied. Cohen's kappa showed slight agreement between the local triage system and the Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System (weighted kappa = 0.133, 0.185 and 0.157 respectively).

CONCLUSION

Whether prospective or retrospective triage used, the systems studied exhibited good association with hospitalisation rate for patients aged less than 3 months and newborn infants.

Development of outcomes for evaluating emergency care triage: a Delphi approach

BACKGROUND

Triage is used as standard of care for prioritization and identification of time-critical patients in the emergency department (ED) globally, but it is unclear what outcomes should be used to evaluate triage. Currently used outcomes do not include important time-critical diagnoses and conditions.

METHOD

We used 18 Swedish triage experts to collect and assess outcomes for the evaluation of 5-level triage systems. The experts suggested 68 outcomes which were then tested through a modified Delphi approach in three rounds. The outcomes aimed to identify correctly prioritized red patients (in need of a resuscitation team), and orange patients (other time critical conditions). Consensus was pre-defined as 70% dichotomized (positive/negative) concordance.

RESULTS

Diagnoses, interventions, mortality, level of care and lab results were included in the outcomes. Positive consensus was reached for 49 outcomes and negative consensus for 7 outcomes, with an 83% response rate. The five most approved outcomes were the interventions Percutaneous coronary intervention, Surgical airway and Massive transfusion together with the diagnoses Tension pneumothorax and Intracerebral hemorrhage that received specific interventions. The outcomes with the clearest disapproval included Admittance to a ward, Treatment with antihistamines and The ordering of a head computed tomography scan. The outcomes were considered valid only if occurring in or from the ED.

CONCLUSION

This study proposes a standard of 49 outcomes divided into two sets tied to red and orange priority respectively, to be used when evaluating 5-level priority triage systems; Lund Outcome Set for Evaluation of Triage (LOSET). The proposed outcomes include diagnoses, interventions and laboratory results. Before widespread implementation of LOSET, prospective testing is needed, preferably at multiple sites.

Machine Learning-Based Prediction of Hospital Admission Among Children in an Emergency Care Center

OBJECTIVES

Machine learning-based prediction of hospital admissions may have the potential to optimize patient disposition and improve clinical outcomes by minimizing both undertriage and overtriage in crowded emergency care. We developed and validated the predictive abilities of machine learning-based predictions of hospital admissions in a pediatric emergency care center.

METHODS

A prognostic study was performed using retrospectively collected data of children younger than 16 years who visited a single pediatric emergency care center in Osaka, Japan, between August 1, 2016, and October 15, 2019. Generally, the center treated walk-in children and did not treat trauma injuries. The main outcome was hospital admission as determined by the physician. The 83 potential predictors available at presentation were selected from the following categories: demographic characteristics, triage level, physiological parameters, and symptoms. To identify predictive abilities for hospital admission, maximize the area under the precision-recall curve, and address imbalanced outcome classes, we developed the following models for the preperiod training cohort (67% of the samples) and also used them in the 1-year postperiod validation cohort (33% of the samples): (1) logistic regression, (2) support vector machine, (3) random forest, and (4) extreme gradient boosting.

RESULTS

Among 88,283 children who were enrolled, the median age was 3.9 years, with 47,931 (54.3%) boys and 1985 (2.2%) requiring hospital admission. Among the models, extreme gradient boosting achieved the highest predictive abilities (eg, area under the precision-recall curve, 0.26; 95% confidence interval, 0.25-0.27; area under the receiver operating characteristic curve, 0.86; 95% confidence interval, 0.84-0.88; sensitivity, 0.77; and specificity, 0.82). With an optimal threshold, the positive and negative likelihood ratios were 4.22, and 0.28, respectively.

CONCLUSIONS

Machine learning-based prediction of hospital admissions may support physicians' decision-making for hospital admissions. However, further improvements are required before implementing these models in real clinical settings.

ABCD approach at the #7119 center, telephone triage system in Tokyo, Japan; a retrospective cohort study

Background

The algorithm and protocol of the #7119 telephone triage in Tokyo, Japan, had been originally established and consists of three steps. In this study, we investigated the outcome of patients treated with physiological abnormality (ABCD approach: A, airway; B, breathing; C, circulation, and D, dysfunction of central nervous system) in step 2 during the #7119 telephone triage and clarified the meaning of evaluation of this approach.

Methods

We retrospectively reviewed data from the Tokyo Fire Department from January 2016 to December 2017. Almost all the patients triaged using the ABCD approach were transferred to the hospital by ambulance and assigned severity by a physician. We divided patients into groups with combinations of 15 patterns including A, B, C, D, AB, AC, AD, BC, BD, CD, ABC, ABD, ACD, BCD, and ABCD. We compared the proportion of severe cases in each group using a Fisher's exact test, followed by residual analysis.

Results

We analyzed 13,793 cases triaged using the ABCD approach. In this analysis, 31% of total cases were assessed as severe cases. Groupwise analysis showed that the proportion of severe cases was significantly higher in the AD, BC, CD, ABD, and ABCD groups, while it was significantly less in the C and AB groups than in the total cases.

Conclusion

At the #7119 telephone triage, we can pick up the severe cases by the ABCD approach. This may contribute to the prompt transportation of severe patients to hospitals by dispatching ambulance cars using the #7119 telephone triage methods.

The association between prehospital vital signs of children and their critical clinical outcomes at hospitals

Vital signs are important for patient assessment, but little is known about interpreting those of children in prehospital settings. We conducted an observational study to investigate the association between prehospital vital signs of children and their clinical outcomes in hospitals. We plotted the data of patients with critical outcomes on published reference ranges, such as those of healthy children to evaluate the clinical relevance. Of the 18,493 children screened, 4477 transported to tertiary hospitals were included in the analysis. The outcomes 12 h after being transported to a tertiary hospital were as follows: deceased, 41; hospitalization with critical deterioration events, 65; hospitalization without critical deterioration events, 1086; returned home, 3090; and unknown, 195. The reference ranges of the heart rates (sensitivity: 57.7%, specificity: 67.5%) and respiratory rates (sensitivity: 54.5%, specificity: 67.7%) of healthy children worked best to detect the critical outcomes. Therefore, the reference ranges of healthy children were concluded to be suitable in prehospital settings; however, excessive reliance on vital signs carried potential risks due to their limited sensitivities and specificities. Future studies are warranted to investigate indicators with higher sensitivities and specificities.

Reliability and validity of the Netherlands Triage Standard in emergency care settings: a case scenario study

BACKGROUND

The Netherlands Triage Standard (NTS) is a triage system that can be used by different types of emergency care organisations. Our objective was to determine the interrater reliability and construct validity of the NTS when applied to self-presenting patients.

METHODS

We performed a cross-sectional case scenario study consisting of two parts: (1) paediatric triage in January-February 2019 and (2) adult triage in October-November 2020. In each part, we invited nurse triagists from three general practitioner cooperatives, three ambulance dispatching centres and three hospital emergency departments in the Netherlands to participate. We used 40 case scenarios involving paediatric patients and 41 involving adult patients who could self-present to any emergency care organisation. In advance, an expert panel determined the urgency (six levels) of the case scenarios (reference standard). The main outcome for reliability was the intraclass correlation coefficient (ICC) for urgency level. The main outcomes for validity were degree of agreement with the reference standard, for urgency level, and sensitivity and specificity for high versus low urgency. We used descriptive statistics and logistic multilevel modelling with both case and triagist as random effects.

RESULTS

218 out of 240 invited triagists participated. The ICC among all triagists was 0.73 for paediatric cases and 0.88 for adult cases and was highest in general practitioner cooperatives. For paediatric cases, there was 62.3% agreement with the reference standard about urgency, 17.4% underestimation and 20.2% overestimation. The sensitivity of the NTS for identifying highly urgent paediatric cases was 85.2%; the specificity was 89.7%. For adult cases, there was 68.3% agreement, 13.7% underestimation and 18.0% overestimation. The sensitivity of triage for high urgency in adults was 94.5% and the specificity 83.3%.

CONCLUSION

NTS appears to have good reliability and construct validity for estimating the urgency of health complaints of non-referred patients presenting themselves in emergency care.

Validation of the Computerized Pediatric Triage Tool, pediaTRI, in the Pediatric Emergency Department of Lenval Children's Hospital in Nice: A Cross-Sectional Observational Study

INTRODUCTION

A reliable pediatric triage tool is essential for nurses working in pediatric emergency departments to quickly identify children requiring priority care (high-level emergencies) and those who can wait (low-level emergencies). In the absence of a gold standard in France, the objective of our study was to validate our 5-level pediatric triage tool -pediaTRI- against the reference tool: the Pediatric Early Warning Score (PEWS) System.

MATERIALS AND METHODS

We prospectively included 100,506 children who visited the Pediatric Emergency Department at Lenval Children's Hospital (Nice, France) in 2016 and 2017. The performance of pediaTRI to identify high-level emergencies (severity levels 1 and 2) was evaluated in comparison with a PEWS ≥ 4/9. Data from 2018-19 was used as an independent validation cohort.

RESULTS

pediaTRI agreed with the PEWS score for 84,896 of the patients (84.5%): 15.0% (14.8-15.2) of the patients were over-triaged and 0.5% (0.5-0.6) under-triaged compared with the PEWS score. pediaTRI had a sensitivity of 76.4% (74.6-78.2), a specificity of 84.7% (84.4-84.9), and positive and negative likelihood ratios of 5.0 (4.8-5.1) and 0.3 (0.3-0.3), respectively, for the identification of high-level emergencies. However, the positive likelihood ratios were lower for patients presenting with a medical complaint [4.1 (4.0-4.2) v 10.4 (7.9-13.7 for trauma), and for younger children [1.2 (1.1-1.2) from 0 to 28 days, and 1.9 (1.8-2.0) from 28 days to 3 months].

CONCLUSION

pediaTRI has a moderate to good validity to triage children in a Pediatric Emergency Department with a tendency to over-triage compared with the PEWS system. Its validity is lower for younger children and for children consulting for a medical complaint.

Revision of the Protocol of the Telephone Triage System in Tokyo, Japan

Introduction

The Emergency Telephone Consultation Center in Tokyo (#7119) was the first telephone triage system in Japan and has operated since 2007. This study examined the revision of the #7119 protocol by referring the linked data to each code of the triage protocol.

Methods

We selected candidates based on the medical codes targeted by the revision, linking data from the nurses' decisions in triage and the patients' condition severity when the ambulance arrived at the hospital, gathering data from June 1, 2016, to December 31, 2017. Then, several emergency physicians evaluated the cases and decided whether the code should be moved to the more or less urgent category or if new protocols and codes would be established.

Results

In this revision, 371 codes were moved to the less urgent category, 35 codes were moved to the more urgent category, and 128 codes were newly established. In all, 59 red codes (transfer to the ambulance dispatcher) were reduced, while 254 orange codes (attendance at hospital within 1 hour) and yellow codes (within 6 hours) were moved to less urgent, and 12 yellow and green codes (within 24 hours) were moved to more urgent.

Conclusion

We adjusted the triage codes for the revision by linking the call data with the case data. This revision should decrease the inappropriate use of ambulances and reduce the primary care workload. To achieve a more accurate revision, we need to refine the process of evaluating the validity of patients' acuity over the telephone during triage.

Factors Associated with Triage Modifications Using Vital Signs in Pediatric Triage: a Nationwide Cross-Sectional Study in Korea

BACKGROUND

Previous studies on inter-rater reliability of pediatric triage systems have compared triage levels classified by two or more triage providers using the same information about individual patients. This overlooks the fact that the evaluator can decide whether or not to use the information provided. The authors therefore aimed to analyze the differences in the use of vital signs for triage modification in pediatric triage.

METHODS

This was an observational cross-sectional study of national registry data collected in real time from all emergency medical services beyond the local emergency medical centers (EMCs) throughout Korea. Data from patients under the age of 15 who visited EMC nationwide from January 2016 to December 2016 were analyzed. Depending on whether triage modifications were made using respiratory rate or heart rate beyond the normal range by age during the pediatric triage process, they were divided into down-triage and non-down-triage groups. The proportions in the down-triage group were analyzed according to the triage provider's profession, mental status, arrival mode, presence of trauma, and the EMC class.

RESULTS

During the study period, 1,385,579 patients' data were analyzed. Of these, 981,281 patients were eligible for triage modification. The differences in down-triage proportions according to the profession of the triage provider (resident, 50.5%; paramedics, 47.7%; specialist, 44.9%; nurses, 44.2%) was statistically significant (P < 0.001). The triage provider's professional down-triage proportion according to the medical condition of the patients showed statistically significant differences except for the unresponsive mental state (P = 0.502) and the case of air transport (P = 0.468).

CONCLUSION

Down-triage proportion due to abnormal heart rates and respiratory rates was significantly different according to the triage provider's condition. The existing concept of inter-rater reliability of the pediatric triage system needs to be reconsidered.

Mobile technology: Usage and perspective of patients and caregivers presenting to a tertiary care emergency department

BACKGROUND

Developments in information technology (IT) have driven a push in healthcare innovation in the emergency department (ED). Many of these applications rely on mobile technology (MT) such as smartphones but not everyone is comfortable with MT usage. Our study aims to characterize the technology usage behavior of users in the ED so as to guide the implementation of IT interventions in the ED.

METHODS

A cross-sectional survey was conducted in the emergency department of a tertiary hospital. Patients and their caregivers aged 21 and above were recruited. The survey collected demographic information, technology usage patterns, and participant reported comfort level in the usage of MT. We performed descriptive statistics and multivariate logistic regression to identify factors differentially associated with comfort in usage of MT.

RESULTS

A total of 498 participants were recruited, and 299 (60%) were patients. English was the most commonly written and read language (66.9%) and 64.2% reported a comfort level of 3/5 or more in using MT. Factors that were associated with being comfortable in using MT include having a tertiary education, being able to read and write English, as well as being a frequent user of IT. Caregivers were more likely to display these characteristics.

CONCLUSION

A large proportion of ED patients are not comfortable in the usage of MT. Factors that predicted comfort level in the usage of MT were common amongst caregivers. Future interventions should take this into consideration in the design of MT interventions.

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department

OBJECTIVE

To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

METHODS

Pediatric patients' data from the 2012-2016 United States National Hospital Ambulatory Medical Care Survey was included to build the models to predict the use of imaging in children presenting to the ED. Multivariable logistic regression models were built with structured variables such as temperature, heart rate, age, and unstructured variables such as reason for visit, free text nursing notes and combined data available at triage. NLP techniques were used to extract information from the unstructured data.

RESULTS

Of the 27,665 pediatric ED visits included in the study, 8394 (30.3%) received medical imaging in the ED, including 6922 (25.0%) who had an X-ray and 1367 (4.9%) who had a computed tomography (CT) scan. In the predictive model including only structured variables, the c-statistic was 0.71 (95% CI: 0.70-0.71) for any imaging use, 0.69 (95% CI: 0.68-0.70) for X-ray, and 0.77 (95% CI: 0.76-0.78) for CT. Models including only unstructured information had c-statistics of 0.81 (95% CI: 0.81-0.82) for any imaging use, 0.82 (95% CI: 0.82-0.83) for X-ray, and 0.85 (95% CI: 0.83-0.86) for CT scans. When both structured variables and free text variables were included, the c-statistics reached 0.82 (95% CI: 0.82-0.83) for any imaging use, 0.83 (95% CI: 0.83-0.84) for X-ray, and 0.87 (95% CI: 0.86-0.88) for CT.

CONCLUSIONS

Both CT and X-rays are commonly used in the pediatric ED with one third of the visits receiving at least one. Patients' socioeconomic, demographic and clinical factors presented at ED triage period were associated with the medical imaging utilization. Predictive models combining structured and unstructured variables available at triage performed better than models using structured or unstructured variables alone, suggesting the potential for use of NLP in determining resource utilization.

The performance of the EMS triage (RETTS-p) and the agreement between the field assessment and final hospital diagnosis: a prospective observational study among children < 16 years

Background

The rapid triage and treatment system for paediatrics (RETTS-p) has been used by the emergency medical services (EMS) in the west of Sweden since 2014. The performance of the RETTS-p in the pre-hospital setting and the agreement between the EMS nurse’s field assessment and the hospital diagnosis is unknown. The aim of this study was to evaluate the performance of the RETTS-p in the EMS and the agreement between the EMS field assessment and the hospital diagnosis.

Methods

A prospective observational study was conducted among 454 patients < 16 years of age who were assessed and transported to the PED. Two instruments were used for comparison: 1) Classification of an emergent patient according to predefined criteria as compared to the RETTS-p and 2) Agreement between the EMS nurse’s field assessment and the hospital diagnosis.

Results

Among all children, 11% were identified as having vital signs associated with an increased risk of death and 7% were diagnosed in hospital with a potentially life-threatening condition. Of the children triaged with RETTS-p (85.9%), 149 of 390 children (38.2%) were triaged to RETTS-p red or orange (life-threatening, potentially life-threatening), of which 40 (26.8%) children were classified as emergent. The hospitalised children were triaged with the highest frequency to level yellow (can wait; 41.5%). In children with RETTS-p red or orange, the sensitivity for a defined emergent patient was 66.7%, with a corresponding specificity of 67.0%. The EMS field assessment was in agreement with the final hospital diagnosis in 80% of the cases.

Conclusions

The RETTS-p sensitivity in this study is considered moderate. Two thirds of the children triaged to life threatening or potentially life threatening were later identified as non-emergent. Of those, one in six was discharged from the PED without any intervention. Further, one third of the children were under triaged, the majority were found in the yellow triage level (can wait). The highest proportion of hospitalised patients was found in the yellow triage level. Our result is in agreement with previous studies using other triage instruments. A computerised decision support system might help the EMS triage to increase sensitivity and specificity.

Comparison between Emergency Severity Index and Heart Failure Triage Scale in heart failure patients: A randomized clinical trial

BACKGROUND

It is not clear whether Emergency Severity Index (ESI) is valid to triage heart failure (HF) patients and if HF patients benefit more from a customized triage scale or not. The aim of study is to compare the effect of Heart Failure Triage Scale (HFTS) and ESI on mistriage among patients with HF who present to the emergency department (ED).

METHODS

A randomized clinical trial was conducted from April to June 2017. HF patients with dyspnea were randomly assigned to HFTS or ESI groups. Triage level, used resources and time to electrocardiogram (ECG) were compared between both groups among HF patients who were admitted to coronary care unit (CCU), cardiac unit (CU) and discharged patients from the ED. Content validity was examined using Kappa designating agreement on relevance (K*). Reliability of both scale was evaluated using inter-observer agreement (Kappa).

RESULTS

Seventy-three and 74 HF patients were assigned to HFTS and ESI groups respectively. Time to ECG in HFTS group was significantly shorter than that of ESI group (2.05 vs. 16.82 minutes). Triage level between HFTS and ESI groups was significantly different among patients admitted to CCU (1.0 vs. 2.8), cardiac unit (2.26 vs. 3.06) and discharged patients from the ED (3.53 vs. 2.86). Used resources in HFTS group was significantly different among triage levels (H=25.89; df=3; P<0.001).

CONCLUSION

HFTS is associated with less mistriage than ESI for triaging HF patients. It is recommended to make use of HFTS to triage HF patients in the ED.

["Triage"-primary assessment of patients in the emergency department : An overview with a systematic review]

BACKGROUND

"Triage" means the primary assessment of a previously unknown patient with an acute health disorder, initially considered a medical emergency. The initial triage is part of the primary assessment, which also includes the registration of administrative data and patient's mode of arrival.

OBJECTIVES

The aim of the work is to provide an overview of frequently used structured primary assessment tools and the underlying evidence for their use in the emergency room.

METHODS

Based on a systematic literature search in PubMed, 41 articles were selected according to predefined criteria.

RESULTS

The most frequently used primary assessment systems in Germany are the Emergency Severity Index (ESI) and the Manchester Triage System (MTS). Scientific evidence exists for the accuracy and reliability of the primary assessment with these instruments. However, there are no gold standards for measuring urgency, so that separate criteria must be defined. Sufficient data to determine a treatment sector or the necessary staffing levels are lacking.

CONCLUSIONS

Structured primary assessment using formalized systems alone is inadequate to categorize the urgency of emergency and acute patients. In fact, a combination of different measures in an interprofessional team is required. Primary assessment systems and processes generally do not allow patients to be referred to downstream structures without a thorough medical examination.

Emergency department patient experience: Same location, same provider, different scores by different survey methods

BACKGROUND

Recent findings on emergency department (ED) patient experience surveys and concerns for the low response rates challenge the quality and reliability of the survey reports. We assessed the consistency of an ED patient experience survey report and identified the effects of patient demographics on ED patient experiences.

METHODS

We conducted a prospective, cross-sectional study at a university-based ED from July to December 2017. We obtained ED patient experience scores from an institutional version (IS) survey and the Press Ganey Associates-distributed survey (PGA). We compared top box scores from the two reports using frequency analysis and performed multivariable logistic regressions to identify associations between IS patient demographics and scores.

RESULTS

We obtained 289 PGA and 234 IS responses. The IS reported significant, higher top box scores in doctor-specific patient questions compared to PGA (all four P-values < 0.01). Female, Christian and White patients were more likely to give top box scores (OR 3.07, OR 2.22 and OR 2.41, P-value < 0.05, respectively).

CONCLUSION

We found significant differences in ED patient experience scores between the IS and PGA surveys. We recommend that healthcare providers consider patient demographic variables when interpreting ED experience score reports. Multiple survey techniques and distribution methods may be adopted to best capture ED patient experiences.

Performance of triage systems in emergency care: a systematic review and meta-analysis

OBJECTIVE

To assess and compare the performance of triage systems for identifying high and low-urgency patients in the emergency department (ED).

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

EMBASE, Medline OvidSP, Cochrane central, Web of science and CINAHL databases from 1980 to 2016 with the final update in December 2018.

ELIGIBILITY CRITERIA

Studies that evaluated an emergency medical triage system, assessed validity using any reference standard as proxy for true patient urgency and were written in English. Studies conducted in low(er) income countries, based on case scenarios or involving less than 100 patients were excluded.

REVIEW METHODS

Reviewers identified studies, extracted data and assessed the quality of the evidence independently and in duplicate. The Quality Assessment of studies of Diagnostic Accuracy included in Systematic Reviews -2 checklist was used to assess risk of bias. Raw data were extracted to create 2×2 tables and calculate sensitivity and specificity. ED patient volume and casemix severity of illness were investigated as determinants of triage systems' performance.

RESULTS

Sixty-six eligible studies evaluated 33 different triage systems. Comparisons were restricted to the three triage systems that had at least multiple evaluations using the same reference standard (Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System). Overall, validity of each triage system to identify high and low-urgency patients was moderate to good, but performance was highly variable. In a subgroup analysis, no clear association was found between ED patient volume or casemix severity of illness and triage systems' performance.

CONCLUSIONS

Established triage systems show a reasonable validity for the triage of patients at the ED, but performance varies considerably. Important research questions that remain are what determinants influence triage systems' performance and how the performance of existing triage systems can be improved.

[Evaluation of Validity of the Korean Triage and Acuity Scale]

PURPOSE

The aim of this study was to identify the predictive validity of the Korean Triage and Acuity Scale (KTAS).

METHODS

This methodological study used data from National Emergency Department Information System for 2016. The KTAS disposition and emergency treatment results for emergency patients aged 15 years and older were analyzed to evaluate its predictive validity through its sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

In case of death in the emergency department, or where the intensive care unit admission was considered an emergency, the sensitivity, specificity, positive predictive value, and negative predictive value of the KTAS were 0.916, 0.581, 0.097, and 0.993, respectively. In case of death in the emergency department, or where the intensive or non-intensive care unit admission was considered an emergency, the sensitivity, specificity, and positive predictive value, and negative predictive value were 0.700, 0.642, 0.391, and 0.867, respectively.

CONCLUSION

The results of this study showed that the KTAS had high sensitivity but low specificity. It is necessary to constantly review and revise the KTAS level classification because it still results in a few errors of under and over-triage. Nevertheless, this study is meaningful in that it was an evaluation of the KTAS for the total cases of adult patients who sought help at regional and local emergency medical centers in 2016.

Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

IMPORTANCE

While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.

OBJECTIVES

To examine the performance of machine learning approaches to predict clinical outcomes and disposition in children in the ED and to compare their performance with conventional triage approaches.

DESIGN, SETTING, AND PARTICIPANTS

Prognostic study of ED data from the National Hospital Ambulatory Medical Care Survey from January 1, 2007, through December 31, 2015. A nationally representative sample of 52 037 children aged 18 years or younger who presented to the ED were included. Data analysis was performed in August 2018.

MAIN OUTCOMES AND MEASURES

The outcomes were critical care (admission to an intensive care unit and/or in-hospital death) and hospitalization (direct hospital admission or transfer). In the training set (70% random sample), using routinely available triage data as predictors (eg, demographic characteristics and vital signs), we derived 4 machine learning-based models: lasso regression, random forest, gradient-boosted decision tree, and deep neural network. In the test set (the remaining 30% of the sample), we measured the models' prediction performance by computing C statistics, prospective prediction results, and decision curves. These machine learning models were built for each outcome and compared with the reference model using the conventional triage classification information.

RESULTS

Of 52 037 eligible ED visits by children (median [interquartile range] age, 6 [2-14] years; 24 929 [48.0%] female), 163 (0.3%) had the critical care outcome and 2352 (4.5%) had the hospitalization outcome. For the critical care prediction, all machine learning approaches had higher discriminative ability compared with the reference model, although the difference was not statistically significant (eg, C statistics of 0.85 [95% CI, 0.78-0.92] for the deep neural network vs 0.78 [95% CI, 0.71-0.85] for the reference; P = .16), and lower number of undertriaged critically ill children in the conventional triage levels 3 to 5 (urgent to nonurgent). For the hospitalization prediction, all machine learning approaches had significantly higher discrimination ability (eg, C statistic, 0.80 [95% CI, 0.78-0.81] for the deep neural network vs 0.73 [95% CI, 0.71-0.75] for the reference; P < .001) and fewer overtriaged children who did not require inpatient management in the conventional triage levels 1 to 3 (immediate to urgent). The decision curve analysis demonstrated a greater net benefit of machine learning models over ranges of clinical thresholds.

CONCLUSIONS AND RELEVANCE

Machine learning-based triage had better discrimination ability to predict clinical outcomes and disposition, with reduction in undertriaging critically ill children and overtriaging children who are less ill.

Validity and Reliability of the Emergency Severity Index and Australasian Triage System in Pediatric Emergency Care of Mofid Children's Hospital in Iran

Objective:

To evaluate the validity, reliability, sensitivity, and specificity of the Emergency Severity Index (ESI) and Australasian Triage System (ATS) for children visiting admitted to the emergency department (ED).

Methods:

This was a prospective study occurred in the Mofid children's Hospital in Iran from August 2017 to November 2018 and children had aged ≤14 years and presented at the ED with a medical symptom were considered eligible for participation. This study was divided into two phases: in the first phase, we determined the inter-rater reliability of ESI version 4 and ATS by triage nurses and pediatric residents. In the second phase, to analyze the validity, sensitivity, and specificity of each triage system. Reliability and agreement rates were measured using kappa statistics.

Results:

ESI showed inter-rater reliability with kappa of 0.65–0.92 (P<0.001) and ATS showed inter-rater reliability with kappa of 0.51–0.87 ESI had sensitivity ranged from 81% to 95% and specificity ranged from 73% to 86%. In addition, sensitivity ranged of the ATS were 80% to 95% and specificity ranged from 74% to 87%. Under triage and over triage occurred in 12% and 15% of patients respectively in ESI and 13% and 15% of patients respectively in ATS.

Conclusion:

The ESI and ATS both valid to triage children in the ED section of Mofid children's Hospital paediatric. Reliability of the ESI is good, moderate to good for the ATS.