Korean Triage And Acuity Scale Research Articles

Triage—clinical reasoning on emergency nursing competency: a multiple linear mediation effect

BackgroundTriage is the first step in providing prompt and appropriate emergency nursing and addressing diagnostic issues. Rapid clinical reasoning skills of emergency nurses are essential for prompt decision-making and emergency care. Nurses experience limitations in emergency nursing that begin with triage. This cross-sectional study explored the mediating effect of perceived triage competency and clinical reasoning skills on the association between Korean Triage and Acuity Scale (KTAS) proficiency and emergency nursing competency.MethodsA web-based survey was conducted with 157 emergency nurses working in 20 hospitals in South Korea between mid-May and mid-July 2022. Data were collected utilizing self-administered questionnaires to measure KTAS proficiency (48 tasks), perceived triage competency (30 items), clinical reasoning skills (26 items), and emergency nursing competency (78 items). Data were analyzed using the PROCESS macro (Model 6).ResultsPerceived triage competency indirectly mediate the relationship between KTAS proficiency and emergency nursing competency. Perceived triage competency and clinical reasoning skills were significant predictors of emergency nursing competency with a multiple linear mediating effect. The model was found have a good fit (F = 8.990, P <.001) with, a statistical power of 15.0% (R² = 0.150).ConclusionsThis study indicates that improving emergency nursing competency requires enhancing triage proficiency as well as perceived triage competency, which should be followed by developing clinical reasoning skills, starting with triage of emergency nurses.

Change of utilization of emergency department in children after lifting mask mandates in a single center in Korea

Purpose: We aimed to investigate changes in visiting patterns after the lifting of mask mandates in a single pediatric emergency medical center in Seoul, Korea.Methods: This retrospective study was based on the data of patients’ (≤ 18 years) visits to the emergency department (ED) of the center from January 1, 2022 through June 30, 2023. Clinical characteristics, Korean Triage and Acuity Scale (KTAS) level, ED outcomes, and length of stay were compared between before (March 20-June 30, 2022) and after (March 20-June 30, 2023) the lifting of mask mandates. The comparisons were iterated in the patients with infectious disease.Results: During the study period, a total of 18,654 children visited the ED. After the lifting of mask mandates, ED visits increased from 7,146 to 11,508 (61.0%; 95% confidence interval, 59.5-62.6; P &lt; 0.001). The increase was more prominent in the age of 2-5 years (82.9%), infectious diseases (175.3%), KTAS level 3 (127.7%), and length of stay shorter than 3 hours (78.8%-92.6%). The number of patients per hour increased by 151.2% for 5 patients or more and over 3,000% for 10 or more. Median length of stay decreased (2.3 hours [interquartile range, 1.2-4.1] to 1.9 hours [1.1-3.5]; P &lt; 0.001). The patients with infectious disease (n = 7,139) showed similar patterns of increase in the age of 2-5 years, KTAS level 3, and length of stay shorter than 3 hours, with an additional increase in the age of 6-18 years.Conclusion: After the lifting of mask mandates, pediatric visits increased by 61%, with the highest increase in children with mild infectious diseases on weekends and at night, and the proportion of more than 10 visits per hour significantly increased. We need urgent and realistic support measures from health authorities.

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

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 coronavirus disease 2019 (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. 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 group) and COVID-19 screening-positive (SP group) groups. We compared the predictability of the KTAS for urgent patients between the two groups. Of 107,480 patients, the SN and SP groups included 62,776 (58.4%) and 44,704 (41.6%) patients, respectively. The odds ratios for severity variables at each KTAS level revealed a more evident discriminatory power of KTAS for severity variables in the SN group (p-value <0.001). The predictability of KTAS for severity variables was higher in the SN group than in the SP group (area under the curve, p-value <0.001). During the pandemic, the KTAS had low accuracy in predicting patients in critical conditions 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.

Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale.

Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings. This study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS). Two hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss' kappa and intra-class correlation coefficient (ICC). The kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802. A substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.

Comparison of validity of Korean triage and acuity scale levels assessed by triage nurse in real-time and by retrospectively applying strict systemic inflammatory response syndrome criteria in patients with fever

The strict application of vital signs has substantial risk of over-triage. Therefore, this study assessed the predictive value of Korean Triage and Acuity Scale (KTAS) level calculated using strict Systemic Inflammatory Response Syndrome (SIRS) criteria versus that evaluated by a verified triage nurse (TN). The study is based on a retrospective observational cohort of a single-center emergency department (ED) from 01 May 2018 to 30 April 2019. Study subjects were patients aged ≥18 years with fever. Intensive care unit admission rate or death in ED (IADE) and general ward admission rate according to two differently defined KTAS levels were compared by receiver operating characteristic curve and logistic regression. A total of 2322 patients were included. In comparing the area under the curves (AUCs) of TN- and SIRS-KTAS, TN-KTAS’ predictive power for IADE (0.802) was higher than that of SIRS-KTAS (0.7440, p = 0.0489). The odds ratio of level 3 for IADE (1.35) was not significantly different from that of level 4 in SIRS-KTAS (p = 0.5429). In KTAS, the severity of illness in patients was more accurately predicted by the triage nurse’s decision based on clinical experience than the strict application of SIRS criteria with only vital signs.

Emergency department utilization in elderly patients: a report from the National Emergency Department Information System (NEDIS) of Korea, 2018-2022.

: With general aging of the population, emergency department (ED) utilization by elderly patients is increasing. In this study, we analyzed data on ED visits of patients aged 65 years and older in Korea. : The study is a retrospective analysis of National Emergency Department Information System (NEDIS) data from 2018-2022, focusing on patients aged 65 years and older who visited EDs across Korea. ED utilization data were analyzed using Korean Triage and Acuity Scale (KTAS) scores. The patients were divided into three age groups, and common chief complaints and diagnoses were identified. Age- and sex-standardized ED visits per 100,000 population and outcomes were also analyzed. : During the study period, there was a total of 9,803,065 elderly patient ED visits. The mean patient age was 76.4±7.6 years, and 47.6% were men. The ED mortality rate and in-hospital mortality rate were 1.8% and 4.6%, respectively. The KTAS scores 1-2 group accounted for 11.0% of patients, KTAS score 3 group for 42.5%, KTAS scores 4-5 group for 37.2%, and KTAS score unknown group for 9.4%. When patients were categorized into three age groups, the oldest group exhibited the highest rates of KTAS score 1, severe illness diagnoses, and mortality. The most frequently reported chief complaint was abdominal pain, and the most common diagnosis was light headedness. When analyzing the data by year, the COVID-19 outbreak had a discernible impact on ED visits and clinical outcomes. : Over the past 5 years, ED visits for elderly patients have averaged 26,050 per 100,000 population per year, with a temporary decline during the COVID-19 pandemic and a subsequent upward trend.

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.

Within the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. However, there is generally limited information about patients that die in the ED. The aim of this study was to develop an artificial intelligence (AI) model to predict trauma mortality and analyze pertinent mortality factors for all patients visiting the ED. We used the Korean National Emergency Department Information System (NEDIS) data set (N=6,536,306), incorporating over 400 hospitals between 2016 and 2019. We included the International Classification of Disease 10th Revision (ICD-10) codes and chose the following input features to predict ED patient mortality: age, sex, intentionality, injury, emergent symptom, Alert/Verbal/Painful/Unresponsive (AVPU) scale, Korean Triage and Acuity Scale (KTAS), and vital signs. We compared three different feature set performances for AI input: all features (n=921), ICD-10 features (n=878), and features excluding ICD-10 codes (n=43). We devised various machine learning models with an ensemble approach via 5-fold cross-validation and compared the performance of each model with that of traditional prediction models. Lastly, we investigated explainable AI feature effects and deployed our final AI model on a public website, providing access to our mortality prediction results among patients visiting the ED. Our proposed AI model with the all-feature set achieved the highest area under the receiver operating characteristic curve (AUROC) of 0.9974 (adaptive boosting [AdaBoost], AdaBoost + light gradient boosting machine [LightGBM]: Ensemble), outperforming other state-of-the-art machine learning and traditional prediction models, including extreme gradient boosting (AUROC=0.9972), LightGBM (AUROC=0.9973), ICD-based injury severity scores (AUC=0.9328 for the inclusive model and AUROC=0.9567 for the exclusive model), and KTAS (AUROC=0.9405). In addition, our proposed AI model outperformed a cutting-edge AI model designed for in-hospital mortality prediction (AUROC=0.7675) for all ED visitors. From the AI model, we also discovered that age and unresponsiveness (coma) were the top two mortality predictors among patients visiting the ED, followed by oxygen saturation, multiple rib fractures (ICD-10 code S224), painful response (stupor, semicoma), and lumbar vertebra fracture (ICD-10 code S320). Our proposed AI model exhibits remarkable accuracy in predicting ED mortality. Including the necessity for external validation, a large nationwide data set would provide a more accurate model and minimize overfitting. We anticipate that our AI-based risk calculator tool will substantially aid health care providers, particularly regarding triage and early diagnosis for trauma patients.

Predictive indicators for determining red blood cell transfusion strategies in the emergency department.

Appropriate decision-making is critical for transfusions to prevent unnecessary adverse outcomes; however, transfusion in the emergency department (ED) can only be decided based on sparse evidence in a limited time window. This study aimed to identify factors associated with appropriate red blood cell (RBC) transfusion in the ED by analyzing retrospective data of patients who received transfusions at a single center. This study analyzed associations between transfusion appropriateness and sex, age, initial vital signs, an ED triage score [the Korean Triage and Acuity Scale (KTAS)], the length of stay, and the hemoglobin (Hb) concentration. Of 10 490 transfusions, 10 109 were deemed appropriate, and 381 were considered inappropriate. A younger age ( P < 0.001) and a KTAS level of 3-5 ( P = 0.028) were associated with inappropriate transfusions, after adjusting for O 2 saturation and the Hb level. In this single-center retrospective study, younger age and higher ED triage scores were associated with the appropriateness of RBC transfusions.

A combination of the Modified Early Warning Score and the Korean Triage and Acuity Scale as a triage tool in patients with infection.

We evaluated the utility of the Korean Modified Early Warning Score (KMEWS), which combines the Modified Early Warning Score (MEWS) and the Korean Triage and Acuity Scale (KTAS), as a triage tool to screen for infection in patients who visit the emergency department. We retrospectively reviewed data extracted from electronic medical records. Patients aged ≥18 years with an infection who were admitted to the hospital via the emergency department between January 2018 and December 2019 were eligible for inclusion. The KMEWS score was calculated as the sum of the KTAS level and the MEWS score. We generated receiver operating characteristic curves and determined the area under the receiver operating characteristic curve (AUC) for the KMEWS, KTAS, MEWS, and Mortality in Emergency Department Sepsis (MEDS) scales. The primary outcome was septic shock, and secondary outcomes were intensive care unit admission and in-hospital mortality. The AUC values (95% confidence interval) for predicting septic shock were as follows: KMEWS, 0.910 (0.902-0.918); MEWS, 0.896 (0.887-0.904); KTAS score, 0.809 (0.798-0.819); and MEDS, 0.927 (0.919-0.934). The AUC values (95% confidence interval) for predicting in-hospital mortality were as follows: KMEWS, 0.752 (0.740-0.764); MEWS, 0.717 (0.704-0.729); KTAS score, 0.764 (0.752-0.776); and MEDS, 0.844 (0.834-0.854). The AUC values (95% confidence interval) for predicting intensive care unit admission were as follows: KMEWS, 0.826 (0.816-0.837); MEWS, 0.782 (0.770-0.793); KTAS score, 0.821 (0.810-0.831); and MEDS, 0.839 (0.829-0.849). The KMEWS, which is a combination of the MEWS and the KTAS scores, might be a useful triage tool in emergency department patients who present with infection, particularly for predicting septic shock.

Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea.

Physical trauma-related mortality places a heavy burden on society. Estimating the mortality risk in physical trauma patients is crucial to enhance treatment efficiency and reduce this burden. The most popular and accurate model is the Injury Severity Score (ISS), which is based on the Abbreviated Injury Scale (AIS), an anatomical injury severity scoring system. However, the AIS requires specialists to code the injury scale by reviewing a patient's medical record; therefore, applying the model to every hospital is impossible. We aimed to develop an artificial intelligence (AI) model to predict in-hospital mortality in physical trauma patients using the International Classification of Disease 10th Revision (ICD-10), triage scale, procedure codes, and other clinical features. We used the Korean National Emergency Department Information System (NEDIS) data set (N=778,111) compiled from over 400 hospitals between 2016 and 2019. To predict in-hospital mortality, we used the following as input features: ICD-10, patient age, gender, intentionality, injury mechanism, and emergent symptom, Alert/Verbal/Painful/Unresponsive (AVPU) scale, Korean Triage and Acuity Scale (KTAS), and procedure codes. We proposed the ensemble of deep neural networks (EDNN) via 5-fold cross-validation and compared them with other state-of-the-art machine learning models, including traditional prediction models. We further investigated the effect of the features. Our proposed EDNN with all features provided the highest area under the receiver operating characteristic (AUROC) curve of 0.9507, outperforming other state-of-the-art models, including the following traditional prediction models: Adaptive Boosting (AdaBoost; AUROC of 0.9433), Extreme Gradient Boosting (XGBoost; AUROC of 0.9331), ICD-based ISS (AUROC of 0.8699 for an inclusive model and AUROC of 0.8224 for an exclusive model), and KTAS (AUROC of 0.1841). In addition, using all features yielded a higher AUROC than any other partial features, namely, EDNN with the features of ICD-10 only (AUROC of 0.8964) and EDNN with the features excluding ICD-10 (AUROC of 0.9383). Our proposed EDNN with all features outperforms other state-of-the-art models, including the traditional diagnostic code-based prediction model and triage scale.

Association between the Korean Triage and Acuity Scale level and severity of children with dyspnea in the emergency department

Purpose: Triage tools play a vital role in classifying the severity of children in emergency departments (EDs). We investigated the association between the Korean Triage and Acuity Scale (KTAS) and severity of dyspnea in the ED.Methods: We conducted a retrospective study of children aged 3-14 years with dyspnea who visited the ED from January 2015 through December 2021. They were divided into severe (KTAS level 1-3) and non-severe (KTAS level 4-5) groups. Between the groups, we compared the clinical characteristics, including age, sex, associated symptoms, vital signs, route of visit, treatment at ED, and outcomes. Results: Among a total of 468 children with dyspnea, 267 and 201 were assigned to the severe and non-severe groups, respectively. The severe group had higher frequencies of fever (21.7% vs. 13.9%; P = 0.031), cough (53.2% vs. 43.3%; P = 0.034), systemic steroids (42.3% vs. 25.9%; P &lt; 0.001), intravenous fluids (47.6% vs. 25.4%; P &lt; 0.001), oxygen therapy (16.5% vs. 6.5%; P = 0.001), inotropics (4.1% vs. 1.0%; P = 0.042), and hospitalization (24.7% vs. 11.9%; P = 0.002). The severe group also showed a higher mean heart rate, respiratory rate, and temperature, and lower mean oxygen saturation (all Ps &lt; 0.001). Among these findings, fever, heart rate, respiratory rate, temperature, intravenous fluids, oxygen therapy, inotropics, and hospitalization remained significantly different between the groups after defining the severe group as a KTAS level 1-2.Conclusion: This study shows the association between KTAS and severity of dyspnea in the ED. Therefore, KTAS may reflect not only the initial clinical conditions but also emergency measures and outcomes in children with dyspnea who visit EDs.

The Effect of Competency-Based Triage Education Application on Emergency Nurses' Triage Competency and Performance.

The Korean Triage and Acuity Scale (KTAS) is used to determine emergency patient priority. The purpose of this study was to develop the Competency-Based Triage Education Application (CTEA) using KTAS and evaluate its effectiveness on emergency nurses’ triage competency and performance. The developed CTEA mobile application comprised 4 lectures, 12 text-based cases, and 8 video-based triage scenarios. A quasi-experimental pre-post design with a comparison group (CG) was used to evaluate the effectiveness of the CTEA. Thirty-one participants were assigned to an intervention group (IG) and used the application for at least 100 min over one week. Thirty-five participants were assigned to a CG and underwent book-based learning, which covered the same content as the CTEA. Triage competency (t = 2.55, p = 0.013) and performance (t = 2.11, p = 0.039) were significantly improved in the IG. The IG’s undertriage error was significantly reduced compared to that of the CG (t = 2.08, p = 0.041). These results indicated that the CTEA was effective in improving the emergency nurses’ triage competency and performance. This application will be useful as a program for providing repeated and continuous triage education.

Development and Validation of Simple Age-Adjusted Objectified Korean Triage and Acuity Scale for Adult Patients Visiting the Emergency Department.

PurposeThe study aimed to develop an objectified Korean Triage and Acuity Scale (OTAS) that can objectively and quickly classify severity, as well as a simple age-adjusted OTAS (S-OTAS) that reflects age and evaluate its usefulness.Materials and MethodsA retrospective analysis was performed of all adult patients who had visited the emergency department at three teaching hospitals. Sex, systolic blood pressure, diastolic blood pressure, pulse rate, respiratory rate, body temperature, O2 saturation, and consciousness level were collected from medical records. The OTAS was developed with objective criterion and minimal OTAS level, and S-OTAS was developed by adding the age variable. For usefulness evaluation, the 30-day mortality, the rates of computed tomography scan and emergency procedures were compared between Korean Triage and Acuity Scale (KTAS) and OTAS.ResultsA total of 44402 patients were analyzed. For 30-day mortality, S-OTAS showed a higher area under the curve (AUC) compared to KTAS (0.751 vs. 0.812 for KTAS and S-OTAS, respectively, p<0.001). Regarding the rates of emergency procedures, AUC was significantly higher in S-OTAS, compared to KTAS (0.807 vs. 0.830, for KTAS and S-OTAS, respectively, p=0.013).ConclusionS-OTAS showed comparative usefulness for adult patients visiting the emergency department as a triage tool compared to KTAS.

Changes in the pattern of suicide attempters visiting the emergency room after COVID-19 pandemic: an observational cross sectional study

BackgroundThis study aimed to find out the change in the rate and pattern of suicide attempts during severe acute respiratory syndrome COVID-19 pandemic period.MethodsThis study was a retrospective analysis of data collected as a part of an emergency room-based post-suicide management program. The data were collected through interviews and from medical records of suicide attempts, maintained in the emergency room, from January 19 to October 31, 2020, during the “COVID-19 period,” and those who attempted suicide from January 19 to October 31, 2019 “pre-COVID-19 period.” We extracted educational background, marital status, occupation, presence of domestic partner, history of mental illness, alcohol consumption, history of previous suicide attempts; suicide attempt method and location (i.e., at home or a place other than home) at the time of attempt, and whether the attempt was a mass suicide. In addition, we compared patient severity between “COVID-19 period” and “pre-COVID-19 period” using the initial KTAS (South Korean triage and acuity scale) level, consciousness level, and systolic blood pressure. In 2012, KTAS was developed through the Ministry of Health and Welfare’s research project to establish triage system in South Korea.ResultsThe analysis of the number of suicide attempts during “pre-COVID-19 period” and “ COVID-19 period” showed that the number of suicide attempts during “COVID-19 period” (n = 440) increased compared to the “pre-COVID-19 period” (n = 400). Moreover, the method of suicide attempts during “COVID-19 period” included overdose of drugs such as hypnotics, antipsychotics, and pesticides that were already possessed by the patient increased compared to the “pre-COVID-19 period” (P < 0.05). At the time of the visit to the emergency room, high KTAS level, low level of consciousness, and low systolic blood pressure, were observed, which were significantly different between “COVID-19 period” and “pre-COVID-19 period” (P < 0.05).ConclusionWith the worldwide COVID-19 virus spread, suicide rate and suicide attempts at home have significantly increased. In addition, patient severity was higher in the “COVID-19 period” than that in the “pre-COVID-19 period.” The increasing suicide attempt rate should be controlled by cooperation between the emergency room and regional organizations.

Point-of-care lactate: a predictor of emergency medicine resource use and outcomes in infants with diarrhea

Purpose: Fluid therapy for diarrhea-induced dehydration inadvertently increases emergency department length of stay (EDLOS). To prevent this delay, we investigated the usefulness of triage using point-of-care (POC) lactate in infants with diarrhea.Methods: This study was performed on infants with diarrhea who visited the emergency department from January 2019 through December 2020. According to the POC lactate concentration and the Korean Triage and Acuity Scale (KTAS) level, the infants were separately divided into the low (&lt; 2 mmol/L), moderate (2-3.9), and high (≥ 4) lactate groups and the mild (KTAS 4-5) and severe (1-3) groups, respectively. Using these 2 group designations, we compared variables regarding the emergency medicine resource use and outcomes. To predict the prolonged EDLOS (≥ median value) we performed logistic regression and receiver operating characteristic analyses.Results: A total of 540 infants were included. The median of EDLOS was 169 minutes (interquartile range, 103-220). Fluid therapy was more frequently performed in the high lactate group than in the low-moderate lactate groups (85.0% vs. 60.4%-73.6%; P = 0.025). The high lactate and severe groups respectively showed higher rates of hospitalization (40.0% vs. 3.8%-7.6% [P &lt; 0.001] and 10.9% vs. 1.4% [P = 0.015]), and longer median EDLOS (259 minutes vs. 147-178 [P &lt; 0.001] and 185 vs. 131 [P = 0.001]) compared to the low-moderate lactate and mild groups. Compared to the KTAS, lactate is more strongly associated with the prolonged EDLOS (lactate, adjusted odds ratio, 4.80 [95% confidence interval, 1.87-15.34] vs. KTAS, 3.52 [1.90-6.54]). The areas under curve for lactate and for the KTAS were 0.66 (0.60-0.73) and 0.62 (0.55-0.69), respectively (P = 0.058).Conclusion: In infants with diarrhea, POC lactate can be a predictor of emergency medicine resource use and outcomes.

Prediction of Critical Care Outcome for Adult Patients Presenting to Emergency Department Using Initial Triage Information: An XGBoost Algorithm Analysis.

BackgroundThe emergency department (ED) triage system to classify and prioritize patients from high risk to less urgent continues to be a challenge.ObjectiveThis study, comprising 80,433 patients, aims to develop a machine learning algorithm prediction model of critical care outcomes for adult patients using information collected during ED triage and compare the performance with that of the baseline model using the Korean Triage and Acuity Scale (KTAS).MethodsTo predict the need for critical care, we used 13 predictors from triage information: age, gender, mode of ED arrival, the time interval between onset and ED arrival, reason of ED visit, chief complaints, systolic blood pressure, diastolic blood pressure, pulse rate, respiratory rate, body temperature, oxygen saturation, and level of consciousness. The baseline model with KTAS was developed using logistic regression, and the machine learning model with 13 variables was generated using extreme gradient boosting (XGB) and deep neural network (DNN) algorithms. The discrimination was measured by the area under the receiver operating characteristic (AUROC) curve. The ability of calibration with Hosmer–Lemeshow test and reclassification with net reclassification index were evaluated. The calibration plot and partial dependence plot were used in the analysis.ResultsThe AUROC of the model with the full set of variables (0.833-0.861) was better than that of the baseline model (0.796). The XGB model of AUROC 0.861 (95% CI 0.848-0.874) showed a higher discriminative performance than the DNN model of 0.833 (95% CI 0.819-0.848). The XGB and DNN models proved better reclassification than the baseline model with a positive net reclassification index. The XGB models were well-calibrated (Hosmer-Lemeshow test; P>.05); however, the DNN showed poor calibration power (Hosmer-Lemeshow test; P<.001). We further interpreted the nonlinear association between variables and critical care prediction.ConclusionsOur study demonstrated that the performance of the XGB model using initial information at ED triage for predicting patients in need of critical care outperformed the conventional model with KTAS.

Facilitators and Barriers of the Triage Process based on Emergency Nurses’ Experience with the Korean Triage and Acuity Scale: A Qualitative Content Analysis

Since 2016, the Korean Triage and Acuity Scale (KTAS) algorithm has been applied to the triage process in the emergency departments (EDs) of Korea. This study aimed to investigate the facilitators of and barriers to a well-run triage function based on how Korean emergency nurses perceived the triage process and their experiences with it. Data were collected using focus group interviews from June 2018 to January 2019. Twenty emergency nurses were divided into two junior and four senior groups based on their level of clinical experience. All interviews were recorded as they were spoken and transcribed. Data were analyzed using qualitative content analysis. The participants recognized the need for the KTAS algorithm to efficiently classify emergency patientsand were working on it properly. According to the data, we extracted 4 themes and 20 subthemes. Four themes were as follows: (1) awareness about the necessity of triage, (2) facilitators to triage process, (3) barriers to triage process, and (4) suggestions for the establishment and development of triage. From the findings of this study, various vulnerabilities of the triage process were identified, and solutions were suggested from the emergency nurses' perspective. Educational, staffing, financial support, and periodic updates of the KTAS are needed to promote the triage process in the future.

Modification and Validation of a Complaint-Oriented Emergency Department Triage System: A Multicenter Observational Study.

PurposeThe objective of this study was to modify and validate an emergency department (ED) triage system with improved prediction performance on hospital outcomes by modifying the Korean Triage and Acuity Scale (KTAS).Materials and MethodsWe performed a retrospective observational study at three academic universities in South Korea. The KTAS code, determined by the chief complaint and the selected modifier of a patient, was used to derive the Modified KTAS (MKTAS). We calculated the area under the receiver operating characteristics curve (AUC) and the test characteristics to evaluate the performance of MKTAS to predict hospital mortality, critical outcome, and admission.ResultsA total of 272402 and 128831 ED visits were used for the derivation and validation of MKTAS, respectively. Compared to KTAS, MKTAS had significantly higher AUC values for the prediction of hospital mortality [MKTAS 0.826 (0.818–0.835) vs. KTAS 0.794 (0.784–0.803)], critical outcome [MKTAS 0.836 (0.830–0.841) vs. 0.798 (0.792–0.804)], and admission [MKTAS 0.725 (0.723–0.728) vs. KTAS 0.685 (0.682–0.688)]. The sensitivity for predicting hospital mortality and critical outcome, as well as the specificity for predicting admission, were significantly improved.ConclusionMKTAS was derived by modifying the KTAS, and then validated. Compared with KTAS, MKTAS showed better discriminating ability to predict hospital outcomes. Continuous efforts to evaluate and modify widely used triage systems are required to improve their performance.

Analysis of the Impact of the Coronavirus Disease Epidemic on the Emergency Medical System in South Korea Using the Korean Triage and Acuity Scale.

PurposeSevere acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19), has spread worldwide. Global health systems, including emergency medical systems, are suffering from a lack of medical resources. Using a method for classifying patients visiting the emergency department (ED), we aimed to investigate trends in emergency medical system usage during the COVID-19 epidemic in Korea.Materials and MethodsThis retrospective observational study included patients who visited emergency medical institutions registered with the National Emergency Department Information System database from January 1, 2017 to May 31, 2020. The primary outcome was identification of changes in the distribution of patients visiting the ED according to the type of emergency medical institution. The secondary outcome was a detailed comparison of Korean Triage and Acuity Scale (KTAS) levels and patient distributions before and during the infectious disaster crisis period.ResultsSevere patients visited regional emergency centers (RECs) and local emergency centers (LECs) more frequently during the COVID-19 period, and disposition status warranting admission to the intensive care unit or resulting in death was more common in RECs and LECs during the COVID-19 period [RECs, before COVID-19: 300686 (6.3%), during COVID-19: 33548 (8.0%) (p<0.001); LECs, before COVID-19: 373593 (3.7%), during COVID-19: 38873 (4.5%) (p<0.001)].ConclusionDuring the COVID-19 period, severe patients were shifted to advanced emergency medical institutions, and the KTAS better reflected severe patients. Patient distribution according to the stage of emergency medical institution improved, and validation of the KTAS triage increased more in RECs.

Surge Capacity and Mass Casualty Incidents Preparedness of Emergency Departments in a Metropolitan City: a Regional Survey Study.

BackgroundEmergency departments (EDs) generally receive many casualties in disaster or mass casualty incidents (MCI). Some studies have conceptually suggested the surge capacity that ED should have; however, only few studies have investigated measurable numbers in one community. This study investigated the surge capacity of the specific number of accommodatable patients and overall preparedness at EDs in a metropolitan city.MethodsThis cross-sectional study officially surveyed surge capacity and disaster preparedness for all regional and local emergency medical centers (EMC) in Seoul with the Seoul Metropolitan Government's public health division. This study developed survey items on space, staff, stuff, and systems, which are essential elements of surge capacity. The number of patients acceptable for each ED was investigated by triage level in ordinary and crisis situations. Multivariate linear regression analysis was performed on hospital resource variables related to surge capacity.ResultsIn the second half of 2018, a survey was conducted targeting 31 EMC directors in Seoul. It was found that all regional and local EMCs in Seoul can accommodate 848 emergency patients and 537 non-emergency patients in crisis conditions. In ordinary situations, one EMC could accommodate an average of 1.3 patients with Korean Triage and Acuity Scale (KTAS) level 1, 3.1 patients with KTAS level 2, and 5.7 patients with KTAS level 3. In situations of crisis, this number increased to 3.4, 7.8, and 16.2, respectively. There are significant differences in surge capacity between ordinary and crisis conditions. The difference in surge capacity between regional and local EMC was not significant. In both ordinary and crisis conditions, only the total number of hospital beds were significantly associated with surge capacity.ConclusionIf the hospital's emergency transport system is ideally accomplished, patients arising from average MCI can be accommodated in Seoul. However, in a huge disaster, it may be challenging to handle the current surge capacity. More detailed follow-up studies are needed to prepare a surge capacity protocol in the community.