Analysis of the Impact of the Coronavirus Disease Epidemic on the Emergency Medical System in South Korea Using the Korean Triage and Acuity Scale.
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ABSTRACT: Purpose
Severe 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 methods
This 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.Results
Severe 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)].Conclusion
During 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.
SUBMITTER: Kim SJ
PROVIDER: S-EPMC8236346 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundArtificial 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.ObjectiveThis study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS).MethodsTwo 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).ResultsThe 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.ConclusionsA 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.
| S-EPMC10798071 | biostudies-literature
Project description:PURPOSE:To identify emergency department triage accuracy using the Korean Triage and Acuity Scale (KTAS) and evaluate the causes of mistriage. METHODS:This cross-sectional retrospective study was based on 1267 systematically selected records of adult patients admitted to two emergency departments between October 2016 and September 2017. Twenty-four variables were assessed, including chief complaints, vital signs according to the initial nursing records, and clinical outcomes. Three triage experts, a certified emergency nurse, a KTAS provider and instructor, and a nurse recommended based on excellent emergency department experience and competence determined the true KTAS. Triage accuracy was evaluated by inter-rater agreement between the expert and emergency nurse KTAS scores. The comments of the experts were analyzed to evaluate the cause of triage error. An independent sample t-test was conducted to compare the number of patient visits per hour in terms of the accuracy and inaccuracy of triage. RESULTS:Inter-rater reliability between the emergency nurse and the true KTAS score was weighted kappa = .83 and Pearson's r = .88 (p < .001). Of 1267 records, 186 (14.7%) showed some disagreement (under triage = 131, over triage = 55). Causes of mistriage included: error applying the numerical rating scale (n = 64) and misjudgment of the physical symptoms associated with the chief complaint (n = 47). There was no statistically significant difference in the number of patient visits per hour for accurate and inaccurate triage (t = -0.77, p = .442). CONCLUSION:There was highly agreement between the KTAS scores determined by emergency nurses and those determined by experts. The main cause of mistriage was misapplication of the pain scale to the KTAS algorithm.
| S-EPMC6730846 | biostudies-literature
Project description:This study aimed to develop and implement an educational simulation program based on the Korean Triage and Acuity Scale (KTAS) for nurses in emergency medical centers who completed the KTAS training, and assess its effects. We examined the educational effects of the program by evaluating clinical decision-making ability, job satisfaction, and customer orientation among the participants, namely 27 nurses in the emergency center of a general hospital. Data were collected from 3 to 24 May 2017, and analyzed using SPSS 22.0. There was a significant difference in nurses' mean scores on clinical decision-making ability, job satisfaction, and customer orientation before and after the simulation-based education. In other words, after completing the KTAS-based simulation education program, the emergency nurses showed improved clinical decision-making ability, job satisfaction, and customer orientation. Based on the results of this study, it is expected that this educational program can be effectively used for KTAS education, and it was confirmed that simulation-based education is a useful learning method for triage nurses in emergency medical centers.
| S-EPMC7730408 | biostudies-literature
Project description:BackgroundThe Korean Triage and Acuity Scale (KTAS) was developed based on the Canadian Emergency Department Triage and Acuity Scale. In patients with pain, to determine the KTAS level, the pain scale is considered; however, since the degree of pain is subjective, this may affect the accuracy of KTAS. The purpose of this study was to evaluate the accuracy of KTAS in predicting patient's severity with the degree of pain used as a modifier.MethodA retrospective observational cohort study was conducted in an urban tertiary hospital emergency department (ED). We investigated patients over 16 years old from January to June 2016. The patients were divided into the pain and non-pain groups according to whether the degree of pain was used as a modifier or not. We compared the predictive power of KTAS on the urgency of patients between the two groups. Acute area registration in the ED, emergency procedure, emergency operation, hospitalization, intensive care unit admission, and 7-day mortality were used as markers to determine urgent patients.ResultsOverall, 24,253 patients were included in the study, with 9,175 (37.8%) in the pain group. The proportions of patients with KTAS 1-3 were 61.4% in the pain and 75.6% in the non-pain groups. Among patients with KTAS 2-3, the proportion of urgent patients was higher in the non-pain group than the pain group (p<0.001). The odds ratios for urgent patients at each KTAS level revealed a more evident discriminatory power of KTAS for urgent patients in the non-pain group. The predictability of KTAS for urgent patients was higher in the non-pain group than the pain group (area under the curve; 0.736 vs. 0.765, p-value <0.001).ConclusionsConsidering the degree of pain with KTAS led to overestimation of patient severity and had a negative impact on the predictability of KTAS for urgent patients.
| S-EPMC6508716 | biostudies-literature
Project description:BackgroundRapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed of a speech recognition model and natural language processing-based classification.MethodsWe simulated 762 triage cases that consisted of 18 classes with six types of the main symptom (chest pain, dyspnea, fever, stroke, abdominal pain, and headache) and three levels of KTAS. In addition, we recorded conversations between emergency patients and clinicians during the simulation. We used speech recognition models to transcribe the conversation. Bidirectional Encoder Representation from Transformers (BERT), support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) were used for KTAS and symptom classification. Additionally, we evaluated the Shapley Additive exPlanations (SHAP) values of features to interpret the classifiers.ResultsThe character error rate of the speech recognition model was reduced to 25.21% through transfer learning. With auto-transcribed scripts, support vector machine (area under the receiver operating characteristic curve [AUROC], 0.86; 95% confidence interval [CI], 0.81-0.9), KNN (AUROC, 0.89; 95% CI, 0.85-0.93), RF (AUROC, 0.86; 95% CI, 0.82-0.9) and BERT (AUROC, 0.82; 95% CI, 0.75-0.87) achieved excellent classification performance. Based on SHAP, we found "stress", "pain score point", "fever", "breath", "head" and "chest" were the important vocabularies for determining KTAS and symptoms.ConclusionWe demonstrated the potential of an automatic KTAS classification system using speech recognition models, machine learning and BERT-based classifiers.
| S-EPMC8275459 | biostudies-literature
Project description:BackgroundThe 5-level triage tool, the Korean Triage and Acuity Scale (KTAS), was developed based on the Canadian Triage and Acuity Scale and has been used for triage in all emergency medical institutions in Korea since 2016. This study evaluated the association between the decrease in level number and the change in its relative importance for disposition in the emergency department (ED).MethodsUsing the registry of the National Emergency Department Information System (NEDIS) ver. 3.1, data regarding consecutive emergency patients from March 2017 to October 2017 were reviewed retrospectively. Reconfiguring KTAS levels, a total of 15 multinomial logistic regression models (KTAS_0 to KTAS_14), including the KTAS, its variants, and covariates were constructed to determine significant factors affecting ED disposition. The relative importance of each model was obtained using a dominance analysis.ResultsA total of 79,771 patients were included in the analysis. In the model KTAS_0, the KTAS and 8 covariates were found to be significantly related to ED disposition. The KTAS and the decision maker of each ED visit, whether it was the physician or others, had the largest relative importance, 34.8% and 31.4%, respectively (P < 0.001). In other models of KTAS variants, including 4-level, 3-level and 2-level, the rates of the KTAS decreased to 31.8% (interquartile range [IQR], 28.9-34.2), 26.4% (IQR, 23.2-31.0), and 18.7% (IQR, 7.5-24.9), respectively (P = 0.016). On the other hand, the rates for covariates tended to be larger for smaller triage levels and so there was a significant interaction effect between the KTAS and the covariates according to the triage level (P < 0.001).ConclusionThe 5-level triage tool, the KTAS, had the largest relative importance among the predictors affecting ED disposition only at its original level. Therefore, it is recommended that no attempt should be made to reduce the number of levels in the triage tool.
| S-EPMC6460112 | biostudies-literature
Project description:BackgroundEarly in the coronavirus disease 2019 (COVID-19) pandemic, there was a concern over possible increase in antibiotic use due to coinfections among COVID-19 patients in the community. Here, we evaluate the changes in nationwide use of broad-spectrum antibiotics during the COVID-19 epidemic in South Korea.MethodsWe obtained national reimbursement data on the prescription of antibiotics, including penicillin with β-lactamase inhibitors, cephalosporins, fluoroquinolones, and macrolides. We examined the number of antibiotic prescriptions compared with the previous 3 years in the same period from August to July. To quantify the impact of the COVID-19 epidemic on antibiotic use, we developed a regression model adjusting for changes of viral acute respiratory tract infections (ARTIs), which are an important factor driving antibiotic use.ResultsDuring the COVID-19 epidemic in South Korea, the broad-spectrum antibiotic use dropped by 15%-55% compared to the previous 3 years. Overall reduction in antibiotic use adjusting for ARTIs was estimated to be 14%-30%, with a larger impact in children.ConclusionsOur study found that broad-spectrum antibiotic use was substantially reduced during the COVID-19 epidemic in South Korea. This reduction can be in part due to reduced ARTIs as a result of stringent public health interventions including social distancing measures.
| S-EPMC8083342 | biostudies-literature
Project description:BACKGROUND:Triage plays a crucial role in the emergency department (ED) management of mass casualty incidents (MCIs) when resources are limited. This study aimed to compare the performance of simple triage and rapid treatment (START) with that of the Taiwan Triage and Acuity Scale (TTAS) for the ED triage of victims following an earthquake-related MCI. METHODS:We retrospectively reviewed the records of victims presenting at our ED with earthquake-related injuries within 24?h of a large-scale earthquake. TTAS was initially used at our ED for this event, and START was performed by retrospectively reviewing the patient records in a blinded manner. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of START and TTAS were determined for predicting ED discharge. RESULTS:We enrolled 105 patients (predominantly women, 60.0%; median age, 45.0?years) in this study; most of them presented with traumatic injuries and were initially triaged as TTAS level III (78.1%), followed by TTAS level II (11.4%). Although the majority of the victims (81.0%) were discharged, four deaths occurred. A moderate agreement in differentiating emergency from nonemergency patients was observed between START and TTAS. Furthermore, both the triage systems showed similar predictions for ED disposition (START AUC/sensitivity/specificity: 0.709/82.35%/55.00%; TTAS AUC/sensitivity/specificity: 0.709/90.59%/45.00%). CONCLUSIONS:The present study demonstrated that START and TTAS have similar triage accuracy and ability to predict ED disposition. Our findings demonstrate that START may be used as an alternative to TTAS for the ED triage of victims following earthquake-related MCIs.
| S-EPMC7065314 | biostudies-literature
Project description:IntroductionA proposed Diagnostic AI System for Robot-Assisted Triage ("DAISY") is under development to support Emergency Department ("ED") triage following increasing reports of overcrowding and shortage of staff in ED care experienced within National Health Service, England ("NHS") but also globally. DAISY aims to reduce ED patient wait times and medical practitioner overload. The objective of this study was to explore NHS health practitioners' perspectives and attitudes towards the future use of AI-supported technologies in ED triage.MethodsBetween July and August 2022 a qualitative-exploratory research study was conducted to collect and capture the perceptions and attitudes of nine NHS healthcare practitioners to better understand the challenges and benefits of a DAISY deployment. The study was based on a thematic analysis of semi-structured interviews. The study involved qualitative data analysis of the interviewees' responses. Audio-recordings were transcribed verbatim, and notes included into data documents. The transcripts were coded line-by-line, and data were organised into themes and sub-themes. Both inductive and deductive approaches to thematic analysis were used to analyse such data.ResultsBased on a qualitative analysis of coded interviews with the practitioners, responses were categorised into broad main thematic-types, namely: trust; current practice; social, legal, ethical, and cultural concerns; and empathetic practice. Sub-themes were identified for each main theme. Further quantitative analyses explored the vocabulary and sentiments of the participants when talking generally about NHS ED practices compared to discussing DAISY. Limitations include a small sample size and the requirement that research participants imagine a prototype AI-supported system still under development. The expectation is that such a system would work alongside the practitioner. Findings can be generalisable to other healthcare AI-supported systems and to other domains.DiscussionThis study highlights the benefits and challenges for an AI-supported triage healthcare solution. The study shows that most NHS ED practitioners interviewed were positive about such adoption. Benefits cited were a reduction in patient wait times in the ED, assistance in the streamlining of the triage process, support in calling for appropriate diagnostics and for further patient examination, and identification of those very unwell and requiring more immediate and urgent attention. Words used to describe the system were that DAISY is a "good idea", "help", helpful, "easier", "value", and "accurate". Our study demonstrates that trust in the system is a significant driver of use and a potential barrier to adoption. Participants emphasised social, legal, ethical, and cultural considerations and barriers to DAISY adoption and the importance of empathy and non-verbal cues in patient interactions. Findings demonstrate how DAISY might support and augment human medical performance in ED care, and provide an understanding of attitudinal barriers and considerations for the development and implementation of future triage AI-supported systems.
| S-EPMC10731272 | biostudies-literature
Project description:Patients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission.Prospective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures. We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons for discharge delays, patient's satisfaction with care, overall hospital costs and patients care needs after returning home.Using a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient's outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.ClinicalTrials.gov Identifier, NCT01768494.
| S-EPMC3723418 | biostudies-literature