Triage Level Research Articles

Evaluating bias of child maltreatment referrals in encounters for unintentional ingestions

BackgroundUnintentional ingestions commonly result in presentation to the pediatric emergency department (PED). No standardized recommendations exist regarding when to call Child Protective Services (CPS) for unintentional ingestions, which allows for the possibility of biased decision-making. ObjectiveIdentify patient and visit level characteristics associated with CPS referral status in unintentional ingestion encounters. Participants and SettingRetrospective cross-sectional study of children ≤6 years old presenting with unintentional ingestion to a metropolitan PED from 2015 to 2021. MethodsICD-10-CM codes were used to identify unintentional ingestion visits in the electronic health record. CPS referral was determined by manual chart review. Bivariable and multivariable logistic regression models identified patient and visit level characteristics associated with CPS referral. Socioeconomic status (SES) was classified based on zip code, the Child Opportunity Index data, and insurance. ResultsOf 3,836 charts reviewed, 808 met inclusion criteria. CPS referrals were made in 109 (13.5%) visits. Compared to non-Hispanic white patients, non-Hispanic Black patients had 7.37 (95% CI:1.38, 39.26) higher adjusted odds of being referred to CPS after adjusting for triage level, age, and ingestion type. Patients in the Lowest SES group had a 3.01 (95% CI:1.42, 6.40) higher adjusted odds when compared to the Middle/Highest SES group. ConclusionThis study found that CPS referrals in unintentional ingestions occur more often in those identifying as non-Hispanic Black and in those in the Lowest SES group, suggesting clinician bias may impact the decision regarding referrals. To mitigate subjective decision-making, we propose creating standardized, objective CPS referral criteria for unintentional ingestions.

33 Use of CHU Ste. Justine online resources prior to visiting the Emergency Department for less-urgent, acute febrile illness

Abstract Background Over the past 20 years, visits to paediatric emergency departments (EDs) across Canada have steadily increased, with a higher proportion of presentations for lower acuity symptoms. Many paediatric institutions’ websites now provide information and recommendations for caregivers on common illnesses and reasons for seeing healthcare providers or going to the ED. Increasing the use of internet resources may improve health literacy and hopefully decrease ED use for lower acuity presentations like uncomplicated viral illness. Objectives The objective of this study was to assess whether caregivers presenting with children with lower acuity at triage were aware of and using the online resources provided by our paediatric institution to help with at-home management of febrile illnesses and to guide their decision to present to the ED. Design/Methods This was a cross-sectional study in a tertiary care university-affiliated paediatric ED in an urban setting. Participants were a convenience sample of caregivers of children 6 months to 17 years old with a fever 72 hours or less and triaged low acuity (Canadian Triage and Acuity Scale levels 3 to 5). Caregivers of children with underlying significant systemic illness were excluded. Consenting participants completed two questionnaires. The first questionnaire included demographic data, information on baseline internet utilisation, use of general online health information and our institutions’ website specifically, and whether use of those resources influenced their decision to present to the ED. After browsing dedicated web materials developed by our institution (“Before going to the emergency room” and “Fever”), questionnaire 2 asked for feedback on the website. Results From April to July 2023, 100 caregivers participated in the study (response rates questionnaires 1 and 2: 80% and 70%, respectively) (Table 1). Half (49%) of caregivers researched their child’s symptoms prior to coming to the ED (Table 2). Approximately one third (39%) of respondents were aware that our institution provided online information for caregivers about common symptoms and when to present to the ED. Half (51%) of caregivers who completed questionnaire 2 said they would not have come to the ED if they had read these resources prior (Table 3). Many (66%) respondents reported they would be “likely/very likely” to look up their child’s symptoms on the institutional website before going to the ED in the future. Conclusion Half of caregivers presenting to the ED for their child’s lower-acuity febrile illness conducted research on their child’s symptoms prior to visiting the ED and most were influenced in their decision to come to ED by what they found. Most caregivers were not aware that our institution had online resources available. Promotion of the institutional resources available to parents may empower parents to manage common symptoms at home and prevent ED visits for lower-acuity illness.

How large language model-powered conversational agents influence decision making in domestic medical triage contexts

IntroductionEffective delivery of healthcare depends on timely and accurate triage decisions, directing patients to appropriate care pathways and reducing unnecessary visits. Artificial Intelligence (AI) solutions, particularly those based on Large Language Models (LLMs), may enable non-experts to make better triage decisions at home, thus easing the healthcare system's load. We investigate how LLM-powered conversational agents influence non-experts in making triage decisions, further studying different persona profiles embedded via prompting.MethodsWe designed a randomized experiment where participants first assessed patient symptom vignettes independently, then consulted one of the two agent profiles—rational or empathic—for advice, and finally revised their triage ratings. We used linear models to quantify the effect of the agent profile and confidence on the weight of advice. We examined changes in confidence and accuracy of triage decisions, along with participants' perceptions of the agents.ResultsIn a study with 49 layperson participants, we found that persona profiles can be differentiated in LLM-powered conversational agents. However, these profiles did not significantly affect the weight of advice. Notably, less confident participants were more influenced by LLM advice, leading to larger adjustments to initial decisions. AI guidance improved alignment with correct triage levels and boosted confidence in participants' decisions.DiscussionWhile LLM advice improves triage recommendations accuracy, confidence plays an important role in its adoption. Our findings raise design considerations for human-AI interfaces, highlighting two key aspects: encouraging appropriate alignment with LLMs' advice and ensuring that people are not easily swayed in situations of uncertainty.

Association between peripheral venous catheter failure and care complexity factors in emergency department: a cross-sectional study

ObjectiveThe objective was to determine the prevalence of peripheral venous catheter (PVC) failure and its association with care complexity individual factors (CCIFs) in emergency department (ED) patients.DesignA cross-sectional, descriptive-correlational study...

The Effectiveness of Media Disc Triage Assessment on Clinical Reasoning Skills of Australasian Triage Scale (ATS) in Nursing Students

Australasian Triage Scale (ATS) is a tool used by emergency department nurses to assess a patient's health status and prioritise services based on the severity of the patient's condition. Clinical Reasoning skills are cognitive processes in the form of theoretical applications and clinical abilities of a nurse in evaluating, diagnosing, and providing nursing care for patients based on information and condition. Objective: This study aims to evaluate the effectiveness of using learning tools by using media Disc Triage Assessment to improve clinical reasoning skills using ATS triage. Method: The research method used was quasi-experimental without control group design. A total of 193 nursing diploma students who passed the Emergency Nursing course were selected using purposive sampling. Therefore, the sample is 35 students. Data analysis was performed using Wilcoxon test. Result: The results were significant improvements across five domains of Nurses Clinical Reasoning Skills (NCRS): Assessment, Diagnosis, Intervention, Implementation, and Evaluation, all with p-values < 0.05. Conclusions: This has a significant positive effect on improving students' clinical reasoning skills in determining triage ATS. This shows can be effective in improving the ability of students to determine triage levels and make informed clinical decisions.

Relationship of Emergency Ambulance Response Time to Australasian Triage Scale (ATS) Level in Non-Trauma Case Patients

Emergency ambulance is an emergency service carried out outside the hospital, both trauma and non-trauma, which is carried out to prevent death and further disability. This service is carried out by increasing the ambulance response time. Emergency ambulance response time in pre-hospital emergency services can impact the assessment of patient triage levels in the development of modern triage, one of which is the Australasian Triage Scale (ATS). This study aims to determine the relationship between emergency ambulance response time and the Australasian Triage Scale (ATS) triage level in non-trauma case patients in Samarinda. The design of this study used a quantitative method, namely descriptive correlation, using a cross-sectional research design. The population in this study was 78 patients. Sampling used the total sampling technique. The instruments used in this study were observation sheets, stopwatches (response time), and the Australasian Triage Scale (ATS). This study was conducted for 3 months from March to May in Public Hospital Samarinda in 2024. Meanwhile, the person correlation test results found a p-value of 0.000<0.05, which means there is a relationship between the emergency ambulance response time to ATS Triage and an r-value of 0.767 where the strength of the relationship is high/strong. With a positive correlation result, the direction of the relationship is in the same direction. This means that the faster the emergency ambulance response time, the better (lower) the emergency condition of non-trauma patients based on the ATS triage level.

Predictive validity of resource-adjusted Korean Triage and Acuity Scale in pediatric gastrointestinal tract foreign body patients

Although paediatric patients with gastrointestinal (GI) foreign bodies require multiple resources, they often present with few or no discernible symptoms and are typically assigned a low acuity level during triage. We compared the predictive accuracy of the revised Korean Triage and Acuity Scale (rKTAS), which elevates acuity by one step in relation to anticipated resource utilization, with that of the conventional KTAS for clinical outcomes. This was a retrospective study of National Emergency Department Information System data. Data on patient and ED characteristics, resources used, and clinical outcomes were collected from January 2018 to December 2021 for patients with GI foreign bodies aged under 19. The primary outcome was rKTAS accuracy in predicting hospitalization, ICU admission, operating room (OR) use, and ED length of stay (EDLOS). The AUROC was used to evaluate the performance via of the KTAS and rKTAS. In total, 25,324 paediatric patients visited the ED for GI tract foreign bodies. The mean age was 3.8 years, and 51% (12,923) were between 1 and 4 year old. Although most (23,658; 93.4%) were discharged, 4.9% required hospitalization. Two or more resources were utilized in 2514 (9.9%) cases, and 3,514 individuals had their triage levels increased by one step. Compared with those of the KTAS, the AUROCs of the rKTAS for predicting overall hospitalization (p < 0.05), admission to general wards (p < 0.05), ICU admission (p = 0.01), and admission via the OR (p < 0.05)were higher than KTAS. Compared with that with the KTAS, the EDLOS with the rKTAS was longer at levels 1, 2, and 3. The adjusted rKTAS is a better predictor of clinical outcomes for paediatric patients with GI tract foreign bodies than the KTAS.

Exploring Hospital Overcrowding with an Explainable Time-to-Event Machine Learning Approach.

Emergency department (ED) overcrowding is a complex problem that is intricately linked with the operations of other hospital departments. Leveraging ED real-world production data provides a unique opportunity to comprehend this multifaceted problem holistically. This paper introduces a novel approach to analyse healthcare production data, treating the length of stay of patients, and the follow up decision regarding discharge or admission to the hospital as a time-to-event analysis problem. Our methodology employs traditional survival estimators and machine learning models, and Shapley additive explanations values to interpret the model outcomes. The most relevant features influencing length of stay were whether the patient received a scan at the ED, emergency room urgent visit, age, triage level, and the medical alarm unit category. The clinical insights derived from the explanation of the models holds promise for increase understanding of the overcrowding from the data. Our work demonstrates that a time-to-event approach to the over- crowding serves as a valuable initial to uncover crucial insights for further investigation and policy design.

The COVID-19 Pandemic and Emergencies in Otolaryngology-Head and Neck Surgery: An Analysis of Patients Presenting to Emergency Rooms in South-West Germany: A Bi-Center Study.

This study was designed to examine the changes in emergency room visits in otolaryngology, head and neck surgery, during the COVID-19 pandemic. The study included 11,277 patients who presented to a tertiary care hospital (ER) and an emergency practice (EP) during on-call hours in the first half of 2018, 2019, and 2020. The epidemiologic parameters, diagnoses, and level of urgency were recorded using a four-step scale. A comparison was made between the pre-pandemic years and 2020. The findings revealed a significant decrease in the frequency of ER visits in the second quarter of 2020 compared to 2019 (ER: 30.8%, EP: 37.8%), mainly due to the fact that there were significantly fewer patients, with low levels of urgency. Certain diagnoses, such as epistaxis (-3.0%) and globus sensation (-3.2%), were made at similar frequencies to 2019, while inflammatory diseases like skin infections (-51.2%), tonsillitis (-55.6%), sinusitis (-59%), and otitis media (-70.4%) showed a significant reduction. The study concludes that patients with a low triage level were less likely to visit the ER during the early stages of the pandemic, but some diagnoses were still observed at comparable rates. This suggests a disparity in perception between patients and ER staff regarding urgency. Many of the issues discussed were also emphasized in the 2024 proposal by the German Ministry of Health to reform emergency care in Germany.

Added predictive value of prehospital measurement of point-of-care lactate in an adult general EMS population in Sweden: a multi-centre observational study

BackgroundEmergency medical services (EMS) personnel must rapidly assess and transport patients with time-sensitive conditions to optimise patient outcomes. Serum lactate, a valuable in-hospital biomarker, has become more accessible in EMS settings through point-of-care (POC) testing. Although POC lactate levels are valuable in specific patient groups, its broader application in EMS remains unclear. This study assessed the additional predictive value of POC lactate levels in a general adult EMS population.MethodsThis prospective observational study (March 2018 to September 2019) involved two EMS organisations in Västra Götaland, Sweden. Patients were triaged using the Rapid Triage and Treatment System (RETTS). POC lactate levels were measured using StatStrip Xpress devices. Non-consecutive patients who received EMS and were aged 18 years and above were available for inclusion if triaged into RETTS levels: red, orange, yellow, or green if respiratory rate of ≥ 22 breaths/min. Outcomes were adverse outcomes, including a time-sensitive diagnosis, sequential organ failure assessment (SOFA) score ≥ 2, and 30-day mortality. Statistical analyses included descriptive statistics, imputation, and regression models to assess the impact of the addition of POC lactate levels to a base model (comprising patient age, sex, presence of past medical conditions, vital signs, pain, EMS response time, assessed triage condition, and triage level) and a RETTS triage model.ResultsOf 4,546 patients (median age 75 [57, 84] years; 49% male), 32.4% had time-sensitive conditions, 12.5% met the SOFA criteria, and 7.4% experienced 30-day mortality. The median POC lactate level was 1.7 (1.2, 2.5) mmol/L. Patients with time-sensitive conditions had higher lactate levels (1.9 mmol/L) than those with non-time-sensitive conditions (1.6 mmol/L). The probability of a time-sensitive condition increased with increasing lactate level. The addition of POC lactate marginally enhanced the predictive models, with a 1.5% and 4% increase for the base and RETTS triage models, respectively. POC lactate level as a sole predictor showed chance-only level predictive performance.ConclusionsPrehospital POC lactate assessment provided limited additional predictive value in a general adult EMS population. However, it may be beneficial in specific patient subgroups, emphasizing the need for its judicious use in prehospital settings.

Software symptomcheckR: an R package for analyzing and visualizing symptom checker triage performance

BackgroundA major stream of research on symptom checkers aims at evaluating the technology’s predictive accuracy, but apart from general trends, the results are marked by high variability. Several authors suggest that this variability might in part be due to different assessment methods and a lack of standardization. To improve the reliability of symptom checker evaluation studies, several approaches have been suggested, including standardizing input procedures, the generation of test vignettes, and the assignment of gold standard solutions for these vignettes. Recently, we suggested a third approach––test-theoretic metrics for standardized performance reporting–– to allow systematic and comprehensive comparisons of symptom checker performance. However, calculating these metrics is time-consuming and error prone, which could hamper the use and effectiveness of these metrics.ResultsWe developed the R package symptomcheckR as an open-source software to assist researchers in calculating standard metrics to evaluate symptom checker performance individually and comparatively and produce publication-ready figures. These metrics include accuracy (by triage level), safety of advice (i.e., rate of correctly or overtriaged cases), comprehensiveness (i.e., how many cases could be entered or were assessed), inclination to overtriage (i.e., how risk-averse a symptom checker is) and a capability comparison score (i.e., a score correcting for case difficulty and comprehensiveness that enables a fair and reliable comparison of different symptom checkers). Each metric can be obtained using a single command and visualized with another command. For the analysis of individual or the comparison of multiple symptom checkers, single commands can be used to produce a comprehensive performance profile that complements the standard focus on accuracy with additional metrics that reveal strengths and weaknesses of symptom checkers.ConclusionsOur package supports ongoing efforts to improve the quality of vignette-based symptom checker evaluation studies by means of standardized methods. Specifically, with our package, adhering to reporting standards and metrics becomes easier, simple, and time efficient. Ultimately, this may help users gain a more systematic understanding of the strengths and limitations of symptom checkers for different use cases (e.g., all-purpose symptom checkers for general medicine versus symptom checkers that aim at improving triage in emergency departments), which can improve patient safety and resource allocation.

Activity, triage levels and impact of the pandemic on hospital emergency departments: A multicentre cross-sectional study.

Describe the activity of hospital emergency departments (EDs) and the sociodemographic profile of patients in the eight public hospitals in Spain, according to the different triage levels, and to analyse the impact of the SARS-CoV-2 pandemic on patient flow. An observational, descriptive, cross-sectional and retrospective study was carried out. Three high-tech public hospitals and five low-tech hospitals consecutively included 2,332,654 adult patients seen in hospital EDs from January 2018 to December 2021. Hospitals belonging to the Catalan Institute of Health. The main variable was triage level, classified according to a standard for the Spanish structured triage system known as Sistema Español de Triaje. For each of the five triage levels, a negative binomial regression model adjusted for year and hospital was performed. The analysis was performed with the R 4.2.2 software. The mean age was 55.4 years. 51.4% were women. The distribution of patients according to the five triage levels was: level 1, 0.41% (n = 9565); level 2, 6.10% (n = 142,187); level 3, 40.2% (n = 938,203); level 4, 42.6% (n = 994,281); level 5, 10.6% (n = 248,418). The sociodemographic profile was similar in terms of gender and age: as the level of severity decreased, the number of women, mostly young, increased. In the period 2020-2021, the emergency rate increased for levels 1, 2 and 3, but levels 4 and 5 remained stable. More than half of the patients attended in high-technology hospital EDs were of low severity. The profile of these patients was that of a young, middle-aged population, mostly female. The SARS-CoV2 pandemic did not change this pattern, but an increase in the level of severity was observed. What problem did the study address? There is overcrowding in hospital EDs. What were the main findings? This study found that more than half of the patients attended in high-technology hospital EDs in Spain have low or very low levels of severity. Young, middle-aged women were more likely to visit EDs with low levels of severity. The SARS-CoV2 pandemic did not change this pattern, but an increase in severity was observed. Where and on whom will the research have an impact? The research will have an impact on the functioning of hospital EDs and their staff. Not applicable.

Evaluation of compliance of emergency severity index triage levels and demographic characteristics with the outcome of patients referred to the emergency department: A retrospective study

This research sought to examine the relationship between emergency severity index (ESI) triage levels, demographic factors, and patient outcomes. A total of 350 patient cases were analyzed from the emergency department (ED) of Khoy University of Medical Sciences and Health Services Hospital, where ESI triage was systematically implemented. A simple random sampling method was employed for selection. The study identified key variables including age, gender, outcomes, and triage levels, categorizing levels 1 and 2 as high-priority triage and levels 3, 4, and 5 as low priority. Data were retrospectively gathered from the medical records of all patients involved. The outcomes assessed included hospitalization, discharge from the hospital, patient satisfaction, and mortality. Statistical analysis was conducted using SPSS software version 20, employing non-parametric chi-square tests, analysis of variance (ANOVA), and multiple regression, with a significance threshold set at 0.05. The findings revealed a statistically significant correlation between ESI triage levels, demographic characteristics, and the outcomes of patients presenting to the ED (P&lt;0.0001). The results indicate that the ESI triage system demonstrates high accuracy in prioritizing patients and effectively predicting outcomes, thereby serving as a valuable tool in hospital triage processes.

Predicting sepsis at emergency department triage: Implementing clinical and laboratory markers within the first nursing assessment to enhance diagnostic accuracy.

Early identification of sepsis in the emergency department (ED) triage is both valuable and challenging. Numerous studies have endeavored to pinpoint clinical and biochemical criteria to assist clinicians in the prompt diagnosis of sepsis, but few studies have assessed the efficacy of these criteria in the ED triage setting. The aim of the study was to explore the accuracy of clinical and laboratory markers evaluated at the triage level in identifying patients with sepsis. A prospective study was conducted in a large academic urban hospital, implementing a triage protocol aimed at early identification of septic patients based on clinical and laboratory markers. A multidisciplinary panel of experts reviewed cases to ensure accurate identification of septic patients. Variables analyzed included: Charlson comorbidity index, mean arterial pressure (MAP), partial pressure of carbon dioxide (PetCO2), white cell count, eosinophil count, C-reactive protein to albumin ratio, procalcitonin, and lactate. A total of 235 patients were included. Multivariable analysis identified procalcitonin ≥1 ng/mL (OR 5.2; p < 0.001); CRP-to-albumin ratio ≥32 (OR 6.6; p < 0.001); PetCO2 ≤ 28 mmHg (OR 2.7; p = 0.031), and MAP <85 mmHg (OR 7.5; p < 0.001) as independent predictors for sepsis. MAP ≥85 mmHg, CRP/albumin ratio <32, and procalcitonin <1 ng/mL demonstrated negative predictive values for sepsis of 90%, 89%, and 88%, respectively. Our study underscores the significance of procalcitonin and mean arterial pressure, while introducing CRP/albumin ratio and PetCO2 as important variables to consider in the very initial assessment of patients with suspected sepsis in the ED. Early identification of sepsis since the emergency department (ED) triage is challenging Implementing the ED triage protocol with simple clinical and laboratory markers allows to recognize patients with sepsis with a very good discriminatory power (AUC 0.88).

Patient stratification based on the risk of severe illness in emergency departments through collaborative machine learning models

ObjectivesEmergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily rely on the judgment of the triage staff could fail to detect subtle symptoms in critical patients, thus leading to delayed treatment. Unlike previous rivalry-focused approaches, our study aimed to establish a collaborative machine learning (ML) model that renders risk scores for severe illness, which may assist the triage staff to provide a better patient stratification for timely critical cares. MethodsThis retrospective study was conducted at a tertiary teaching hospital. Data were collected from January 2015 to October 2022. Demographic and clinical information were collected at triage. The study focused on severe illness as the outcome. We developed artificial neural network (ANN) models, with or without utilizing the Taiwan Triage and Acuity Scale (TTAS) score as one of the predictors. The model using the TTAS score is termed a machine-human collaborative model (ANN-MH), while the model without it is referred to as a machine-only model (ANN-MO). The predictive power of these models was assessed using the area under the receiver-operating-characteristic (AUROC) and the precision-recall curves (AUPRC); their sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score were compared. ResultsThe study analyzed 668,602 ED visits from 2015 to 2022. Among them, 278,724 visits from 2015 to 2018 were used for model training and validation, while 320,201 visits from 2019 to 2022 were for testing model performance. Approximately 2.6% of visits were by severely ill patients, whose TTAS scores ranged from 1 to 5. The ANN-MH model achieved a testing AUROC of 0.918 and AUPRC of 0.369, while for the ANN-MO model the AUROC and AUPRC were 0.909 and 0.339, respectively. Based on these metrics, the ANN-MH model outperformed the ANN-MO model, and both surpassed human triage classification. Subgroup analyses further highlighted the models' capability to identify higher-risk patients within the same triage level. ConclusionsThe traditional 5-level triage system often falls short, leading to under-triage of critical patients. Our models include a score-based differentiation within a triage level to offer advanced risk stratification, thereby promoting patient safety.

Prioritizing complex health levels beyond autism triage using fuzzy multi-criteria decision-making

This study delves into the complex prioritization process for Autism Spectrum Disorder (ASD), focusing on triaged patients at three urgency levels. Establishing a dynamic prioritization solution is challenging for resolving conflicts or trade-offs among ASD criteria. This research employs fuzzy multi-criteria decision making (MCDM) theory across four methodological phases. In the first phase, the study identifies a triaged ASD dataset, considering 19 critical medical and sociodemographic criteria for the three ASD levels. The second phase introduces a new Decision Matrix (DM) designed to manage the prioritization process effectively. The third phase focuses on the new extension of Fuzzy-Weighted Zero-Inconsistency (FWZIC) to construct the criteria weights using Single-Valued Neutrosophic 2-tuple Linguistic (SVN2TL). The fourth phase formulates the Multi-Attributive Border Approximation Area Comparison (MABAC) method to rank patients within each urgency level. Results from the SVN2TL-FWZIC weights offer significant insights, including the higher criteria values "C12 = Laughing for no reason" and "C16 = Notice the sound of the bell" with 0.097358 and 0.083832, indicating their significance in identifying potential ASD symptoms. The SVN2TL-FWZIC weights offer the base for prioritizing the three triage levels using MABAC, encompassing medical and behavioral dimensions. The methodology undergoes rigorous evaluation through sensitivity analysis scenarios, confirming the consistency of the prioritization results with critical analysis points. The methodology compares with three benchmark studies, using four distinct points, and achieves a remarkable 100% congruence with these prior investigations. The implications of this study are far-reaching, offering a valuable guide for clinical psychologists in prioritizing complex cases of ASD patients.

Clinical characteristics of SARS-CoV-2 Omicron BA.2 infection and its impact on pediatric emergency care in northern Taiwan

BackgroundThe SARS-CoV-2 Omicron BA.2 outbreak started in Taiwan in April 2022. The pandemic posed a challenge to pediatric emergency departments (PEDs) because of increased PED visits and diverse clinical presentations. MethodsWe analyzed the clinical characteristics and impact of the Omicron BA.2 pandemic in patients who visited our PED from April 2022 to July 2022. The data from the Alpha variant pandemic during the same period in 2021 were compared with these findings. ResultsOverall, 10,878 children were enrolled, and 7047 (64.8%) children were positive for SARS-CoV-2 infection. They had a mean ± SD age of 5.3 ± 4.1 years. The rates of patients with Pediatric Taiwan Triage and Acuity Scale (Ped-TTAS) level 1 (most urgent) (12.3%) and level 2 (27.6%) increased. More children were triaged as most urgent during the Omicron BA.2 pandemic than during the Alpha variant pandemic (p < 0.001). Patients with SARS-CoV-2 infection were likely to present with high fever, croup, dyspnea, febrile seizures, headache, dizziness, and myalgia (all p < 0.001). Four hundred and eleven (5.8%) patients were admitted; 25 (0.4%) patients needed intensive care, including 11 (44.0%) with encephalopathy or encephalitis. Three (0.04%) patients died due to fulminant encephalitis, encephalitis with septic shock, and respiratory failure. ConclusionsThe number of PED visits and the Ped-TTAS level of disease severity significantly increased during the SARS-CoV-2 Omicron BA.2 outbreak. The most common symptom was fever, and high fever was more common in patients with SARS-CoV-2 Omicron BA.2 infection. The rates of patients with croup and febrile seizures also increased.

Empowering Community Clinical Triage through Innovative Data-Driven Machine Learning

Efficient triaging and referral assessments are critical in ensuring prompt medical intervention in the community healthcare (CHC) system. However, the existing triaging systems in many community health services are an intensive, time-consuming process and often lack accuracy, particularly for various symptoms which might represent heart failure or other health-threatening conditions. There is a noticeable limit of research papers describing AI technologies for triaging patients. This paper proposes a novel quantitative data-driven approach using machine learning (ML) modelling to improve the community clinical triaging process. Furthermore, this study aims to employ the feature selection process and machine learning power to reduce the triaging process’s waiting time and increase accuracy in clinical decision making. The model was trained on medical records from a dataset of patients with “Heart Failure”, which included demographics, past medical history, vital signs, medications, and clinical symptoms. A comparative study was conducted using a variety of machine learning algorithms, where XGBoost demonstrated the best performance among the other ML models. The triage levels of 2,35,982 patients achieved an accuracy of 99.94%, a precision of 0.9986, a recall of 0.9958, and an F1-score of 0.9972. The proposed diagnostic model can be implemented for the CHC decision system and be developed further for other medical conditions.

Use of Reverse Shock Index Multiplied by Simplified Motor Score in a Five-Level Triage System: Identifying Trauma in Adult Patients at a High Risk of Mortality.

Background and Objectives: The Taiwan Triage and Acuity Scale (TTAS) is reliable for triaging patients in emergency departments in Taiwan; however, most triage decisions are still based on chief complaints. The reverse-shock index (SI) multiplied by the simplified motor score (rSI-sMS) is a more comprehensive approach to triage that combines the SI and a modified consciousness assessment. We investigated the combination of the TTAS and rSI-sMS for triage compared with either parameter alone as well as the SI and modified SI. Materials and Methods: We analyzed 13,144 patients with trauma from the Taipei Tzu Chi Trauma Database. We investigated the prioritization performance of the TTAS, rSI-sMS, and their combination. A subgroup analysis was performed to evaluate the trends in all clinical outcomes for different rSI-sMS values. The sensitivity and specificity of rSI-sMS were investigated at a cutoff value of 4 (based on previous study and the highest score of the Youden Index) in predicting injury severity clinical outcomes under the TTAS system were also investigated. Results: Compared with patients in triage level III, those in triage levels I and II had higher odds ratios for major injury (as indicated by revised trauma score < 7 and injury severity score [ISS] ≥ 16), intensive care unit (ICU) admission, prolonged ICU stay (≥14 days), prolonged hospital stay (≥30 days), and mortality. In all three triage levels, the rSI-sMS < 4 group had severe injury and worse outcomes than the rSI-sMS ≥ 4 group. The TTAS and rSI-sMS had higher area under the receiver operating characteristic curves (AUROCs) for mortality, ICU admission, prolonged ICU stay, and prolonged hospital stay than the SI and modified SI. The combination of the TTAS and rSI-sMS had the highest AUROC for all clinical outcomes. The prediction performance of rSI-sMS < 4 for major injury (ISS ≥ 16) exhibited 81.49% specificity in triage levels I and II and 87.6% specificity in triage level III. The specificity for mortality was 79.2% in triage levels I and II and 87.4% in triage level III. Conclusions: The combination of rSI-sMS and the TTAS yielded superior prioritization performance to TTAS alone. The integration of rSI-sMS and TTAS effectively enhances the efficiency and accuracy of identifying trauma patients at a high risk of mortality.

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.