Donghyun Kim, Junsang Yoo, Ye Rim Lee, Ji Sim Yoon, Seung Jin Maeng, Minha Kim, Sejin Heo, Jong Eun Park, Gun Tak Lee, Se Uk Lee, Taerim Kim, Sung Yeon Hwang, Hee Yoon, Won Chul Cha, Hansol Chang
In Press, Received September 23, 2025 Accepted December 29, 2025 Available online February 27, 2026
Objective Emergency department (ED) physicians face substantial cognitive and physical demands, yet workload data applicable to real-world staffing and operational decisions remain limited. This study aimed to quantify perceived workload across diverse ED tasks using the NASA Task Load Index (NASA-TLX) and to determine how workload varies by physician experience, patient acuity, and clinical context. A secondary aim was to generate practical insights that may inform resource allocation and experience-based task distribution in the ED.
Methods We conducted an observational survey of interns, residents, and specialists working in the ED of a tertiary hospital between June and July 2022. NASA-TLX questionnaires were administered to assess workload across common procedures and patient-care tasks. Analyses were stratified by physician experience, Korean Triage and Acuity Scale (KTAS) level, and chief complaint. Nonparametric methods were used to evaluate differences in workload patterns.
Results Sixty physicians participated (30 interns, 30 residents/specialists). Procedures with high technical complexity, such as thoracentesis and lumbar puncture, showed the highest workload among interns. Among residents, workload decreased from postgraduate year 1 to 3 but rose again in year 4, reflecting increased supervisory responsibilities. Higher patient acuity (KTAS 1–2) and neurological chief complaints were consistently associated with elevated workload across all experience levels.
Conclusion Perceived workload in the ED varies significantly by task type, experience level, and patient acuity. These findings provide actionable data that may support evidence-based staffing decisions, workload redistribution, and training strategies to optimize physician performance and mitigate cognitive overload in resource-limited emergency departments.
Objective Trauma is one of the leading causes of obstetric morbidity and mortality, and incorrect seat belt use is a major determinant of adverse outcomes. This study evaluated the impact of structured education on proper seat belt use during pregnancy and examined preferences for future interventions.
Methods This prospective pilot study was conducted at a single center in Korea, over an 8-week period. Pregnant women between 20 and 37 weeks of gestation who visited the outpatient obstetrics and gynecology department were enrolled. A pre-education survey assessed baseline seat belt practices. Participants then received structured education, and a post-education survey 1 month later evaluated changes in awareness and behavior.
Results Sixty participants were included in the final analysis. Most reported obtaining seat belt information from unverified sources, particularly online communities. Many indicated a preference for structured education delivered by obstetricians, especially early in pregnancy. After the intervention, knowledge of proper seat belt use increased from 21.7% to 85.0% (P<0.001), and correct seat belt usage rose from 16.7% to 88.3% (P<0.001). Seat belt use while driving also improved markedly, increasing from 19.5% to 78.0% (P<0.001), demonstrating the program’s effectiveness in enhancing awareness and behavior.
Conclusion Education on seat belt use during pregnancy significantly improved both knowledge and correct usage among pregnant women. Routine, formal educational programs are recommended to promote maternal and fetal safety.
Da Seul Kim, Jong Eun Park, Sung Yeon Hwang, Daun Jeong, Gun Tak Lee, Taerim Kim, Se Uk Lee, Hee Yoon, Won Chul Cha, Min Seob Sim, Ik Joon Jo, Tae Gun Shin
Clin Exp Emerg Med 2022;9(3):176-186. Published online September 30, 2022
Objective We evaluated the performance of diastolic shock index (DSI) and lactate in predicting vasopressor requirement among hypotensive patients with suspected infection in an emergency department.
Methods This was a single-center, retrospective observational study for adult patients with suspected infection and hypotension in the emergency department from 2018 to 2019. The study population was split into derivation and validation cohorts (70/30). We derived a simple risk score to predict vasopressor requirement using DSI and lactate cutoff values determined by Youden index. We tested the score by the area under the receiver operating characteristic curve (AUC). We performed a multivariable regression analysis to evaluate the association between the timing of vasopressor treatment and 28-day mortality.
Results A total of 1,917 patients were included. We developed a score, assigning 1 point each for the high DSI (≥2.0) and high lactate (≥2.5 mmol/L) criteria. The AUCs of the score were 0.741 (95% confidence interval [CI], 0.715–0.768) at hypotension and 0.736 (95% CI, 0.708–0.763) after initial fluid challenge in the derivation cohort and 0.676 (95% CI, 0.631–0.719) at hypotension and 0.688 (95% CI, 0.642–0.733) after initial fluid challenge in the validation cohort, respectively. In patients with scores of 2 points, early vasopressor therapy initiation was significantly associated with decreased 28-day mortality (adjusted odds ratio, 0.37; 95% CI, 0.14–0.94).
Conclusion A prediction model with DSI and lactate levels might be useful to identify patients who are more likely to need vasopressor administration among hypotensive patients with suspected infection.
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Objective Coronavirus disease 2019 (COVID-19) has notably altered the emergency department isolation protocol, imposing stricter requirements on probable infectious disease patients that enter the department. This has caused adverse effects, such as an increased rate of leave without being seen (LWBS). This study describes the effect of fever/respiratory symptoms as the main cause of isolation regarding LWBS after the COVID-19 pandemic.
Methods We retrospectively analyzed emergency department visits before (March to July 2019) and after (March to July 2020) the COVID-19 pandemic. Patients were grouped based on existing fever or respiratory symptoms, with the LWBS rate as the primary outcome. Logistic regression analysis was used to identify the risk factors of LWBS. Logistic regression was performed using interaction terminology (fever/respiratory symptom patient [FRP]×post–COVID-19) to determine the interaction between patients with FRPs and the COVID-19 pandemic period.
Results A total of 60,290 patients were included (34,492 in the pre–COVID-19, and 25,298 in the post–COVID-19 group). The proportion of FRPs decreased significantly after the pandemic (P<0.001), while the LWBS rate in FRPs significantly increased from 2.8% to 19.2% (P<0.001). Both FRPs (odds ratio, 1.76; 95% confidence interval, 1.59–1.84 (P<0.001) and the COVID-19 period (odds ratio, 2.29; 95% confidence interval, 2.15–2.44; P<0.001) were significantly associated with increased LWBS. Additionally, there was a significant interaction between the incidence of LWBS in FRPs and the COVID-19 pandemic period (P<0.001).
Conclusion The LWBS rate has increased in FRPs after the COVID-19 pandemic; additionally, the effect observed was disproportionate compared with that of nonfever/respiratory symptom patients.
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Objective This study aimed to confirm the accuracy of a machine-learning-based model in predicting the 30-day mortality of patients with pneumonia and evaluating whether they were required to be admitted to the intensive care unit (ICU).
Methods The study conducted a retrospective analysis of pneumonia patients at an emergency department (ED) in Seoul, Korea, from January 1, 2016 to December 31, 2017. Patients aged 18 years or older with a pneumonia registry designation on their electronic medical record were enrolled. We collected their demographic information, mental status, and laboratory findings. Three models were used: the pre-existing CURB-65 model, and the CURB-RF and Extensive CURB-RF models, which were machine-learning models that used a random forest algorithm. The primary outcomes were ICU admission from the ED or 30-day mortality. Receiver operating characteristic curves were constructed for the models, and the areas under these curves were compared.
Results Out of the 1,974 pneumonia patients, 1,732 patients were eligible to be included in the study; from these, 473 patients died within 30 days or were initially admitted to the ICU from the ED. The area under receiver operating characteristic curves of CURB-65, CURB-RF, and extensive-CURB-RF were 0.615 (0.614–0.616), 0.701 (0.700–0.702), and 0.844 (0.843–0.845), respectively.
Conclusion The proposed machine-learning models could predict the mortality of patients with pneumonia more accurately than the pre-existing CURB-65 model and can help decide whether the patient should be admitted to the ICU.
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Methods The clinical outcomes of 607 OHCA patients registered in CAPTURES (Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance), a nationwide multicenter registry performed in 27 hospitals, were analyzed. Early CAG was defined as CAG performed within 24 hours of emergency department admission. The primary outcome was survival to discharge, with neurologically favorable status defined by cerebral performance category scores ≤2.
Results Compared to patients without CAG (n=469), patients who underwent early CAG (n=138) were younger, more likely to be male, and more likely to have received bystander cardiopulmonary resuscitation, pre-hospital defibrillation, and revascularization (P<0.01 for all). Analysis of 115 propensity score-matched pairs showed that early CAG is associated with a 2.3-fold increase in survival to discharge with neurologically favorable status (P<0.001, all). Survival to discharge increased consistently according to the time interval between emergency department visit and CAG (P<0.05).
Conclusion Early CAG of OHCA patients was associated with better survival and favorable neurologic outcomes at discharge. However, there was no clear time threshold for CAG that predicted survival to discharge.
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Objective We aimed to evaluate the knowledge and attitudes of emergency medical service (EMS) personnel pertaining to sepsis. We also compared EMS personnel’s knowledge of sepsis and their intention to engage in prehospital sepsis management.
Methods The survey was conducted during education conferences for EMS personnel in December 2013 and January 2015 in Seoul, Korea. The questionnaire composed of 10 questions relevant to sepsis, was distributed on-scene, and was retrieved by investigators after the conference. We classified subjects into active and passive groups based on intent to participate in prehospital sepsis care.
Results A total of 271 questionnaires were distributed; 255 EMS personnel (94%) completed the survey, 126 (49%) of whom were first-degree emergency medical technicians (EMTs). Less than 75% of subjects provided clinically relevant responses to questions about the definitions of sepsis, tachycardia, tachypnea, hypotension, hypothermia, fluid resuscitation, and vasopressor. Only 15% of participants had suspected that a patient had sepsis, and 9% reported that they could identify patients with sepsis during transportation. Overall, first-degree EMTs showed higher levels of knowledge and a positive attitude to sepsis compared with non-first-degree EMTs. Sixty percent of the participants reported that they were actively involved in prehospital sepsis care. The active group showed significantly higher levels of knowledge and more positive responses to the clinical impact of prehospital sepsis care.
Conclusion Our study showed that is a substantial portion of EMS personnel lacks appropriate level of knowledge on sepsis care. We also found that the intention to engage in sepsis management was associated with appropriate knowledge of sepsis.
Citations
Citations to this article as recorded by
Knowledge, attitudes, and practices of pre-hospital emergency medical care practitioners regarding sepsis recognition: a cross-sectional study in Qatar Michael Steven Paul Lewis, Paula J. W. Smith, Ian Lucas Howard, Hassan Farhat, Guillaume Alinier BMC Emergency Medicine.2026;[Epub] CrossRef
Barriers and facilitators to optimal sepsis care – a systematized review of healthcare professionals’ perspectives Lea Draeger, Carolin Fleischmann-Struzek, Sabine Gehrke-Beck, Christoph Heintze, Daniel O. Thomas-Rueddel, Konrad Schmidt BMC Health Services Research.2025;[Epub] CrossRef
Prehospital fluid therapy in patients with suspected infection: a survey of ambulance personnel’s practice Marie Egebjerg Jensen, Arne Sylvester Jensen, Carsten Meilandt, Kristian Winther Jørgensen, Ulla Væggemose, Allan Bach, Hans Kirkegaard, Marie Kristine Jessen Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine.2022;[Epub] CrossRef
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The Knowledge of Nursing Internship Program Students about Early Detection of Sepsis Stefani Stefani, Yanny Trisyani, Anita Setyawati Open Access Macedonian Journal of Medical Sciences.2021; 9(T6): 116. CrossRef
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Prehospital sepsis alert notification decreases time to initiation of CMS sepsis core measures Christopher L. Hunter, Salvatore Silvestri, Amanda Stone, Anne Shaughnessy, Stacie Miller, Alexa Rodriguez, Linda Papa The American Journal of Emergency Medicine.2019; 37(1): 114. CrossRef
Emergency medical service providers' knowledge and perception of sepsis at Makkah Saudi Red Crescent Authority BassamHassan Basaffar, NasserSafar Aloitibi, RashedMohammad Alzahrani, OmarOsama Felimban, KhalidSafir Algethami, AbdullahHamdan Alshehri Saudi Critical Care Journal.2019; 3(2): 85. CrossRef
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