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.
Objective This study aimed to develop and validate MEDIVAL (Medical Documentation Validation), a progressive chain-of-thought (CoT) evaluation framework for automated assessment of large language model (LLM)-generated emergency department documentation, designed to align with expert clinical judgment in acute care settings. Methods We designed a three-tier evaluation framework incorporating persona-based, error-enhanced, and insight-integrated strategies. The framework was tested across four LLMs (GPT-4o, GPT-4.1, Claude-3.5, Claude-3.7) on 33 emergency department records reviewed by four expert emergency physicians. Each model applied the three CoT strategies across five criteria: appropriateness, accuracy, structure/format, conciseness, and clinical validity. Model outputs were compared with expert ratings using Spearman correlation coefficients. Differences were analyzed with the Friedman test and Wilcoxon signed rank test with Bonferroni correction. Reproducibility was assessed through intraclass correlation coefficient (ICC) analysis. Results All models demonstrated stronger alignment with expert ratings as CoT complexity increased, with Claude-3.7 (r=0.712, P<0.001) and GPT-4o (r=0.702, P<0.001) showing the highest correlations under the insight-integrated strategy. GPT-4.1 showed the greatest relative improvement (43.3% increase, r=0.457 to r=0.655, P<0.001). Significant overall differences were observed across strategies (χ2 (2)=48.39, P<0.001), though the error-enhanced and insight-integrated approaches differed only modestly yet significantly (P=0.002). High reproducibility was confirmed (ICC >0.919), with Claude-3.5 achieving the most consistent results (ICC, 0.997–0.998). Conclusion MEDIVAL demonstrates that progressive CoT strategies systematically improve automated evaluation of emergency department documentation while maintaining excellent reproducibility. This framework offers a viable prescreening tool to reduce expert workload and support reliable artificial intelligence integration into emergency medicine workflows.
Performance Evaluation of the 2020 European Society of Cardiology 0-hour/1-hour Algorithm Using High-sensitivity Cardiac Troponin I for Non-ST-segment Elevation Acute Coronary Syndrome and Mortality Assessment Based on 1-year Real-world Data Changhee Ha, Yeon Jae Lee, Jong Do Seo, Hanah Kim, Hee-Won Moon, Mina Hur, Young Hwan Lee, Sang O Park, Kyeong Ryong Lee, Hyun-Joong Kim, Yeo-Min Yun Annals of Laboratory Medicine.2026; 46(1): 52. CrossRef
Association between emergency department crowding and mortality: a nationwide analysis stratified by emergency department levels: a retrospective cohort study Minha Kim, Jin-Hee Lee, Minyoung Choi, Doyeop Kim, Hanseok Chang, Sejin Heo, Seung Jin Maeng, Tae Gun Shin, Eunsil Ko, Hansol Chang BMC Emergency Medicine.2026;[Epub] CrossRef
Brecha entre demanda asistencial y disponibilidad médica en servicio de Urgencias Hugo Ariel Cabrera Britez Revista Científica de Salud "Ciensa".2026; : 1. CrossRef
Pediatric emergency care: Determinants and systematic barriers Pankaj Soni, Amit Agrawal World Journal of Clinical Pediatrics.2025;[Epub] CrossRef
Beyond Annual Averages: Rethinking Metrics For Emergency Department Crowding And Capacity Planning JeongWook Lim, Jisun Lee, Song-Hee Kim, Taehui Kim, Hyo Jin Kim, Mi Gyeong Yoo, Chun Song Youn, Yun-Suk Pak The Journal of Emergency Medicine.2025; 79: 591. CrossRef
Enhancing patient participation in emergency department through patient-friendly clinical notes generated by large language models Sung-In Kim, Joonyoung Park, Taewan Kim, Woosuk Seo, Taerim Kim, Won Chul Cha, Hwajung Hong Scientific Reports.2025;[Epub] CrossRef
Objective This study used a nationwide database to identify and analyze factors that influence emergency department (ED) length of stay (LOS) and improve the efficiency of emergency care. Methods This retrospective study analyzed data from the National Emergency Department Information System (NEDIS) database in Korea: 25,578,263 ED visits from 2018 to 2022. Patient demographics, clinical characteristics, and ED operational variables were examined. Univariate and multivariate logistic regression analyses were used to assess the associations between the variables and prolonged ED LOS, defined as 6 hours or more. Results Among the 25,578,263 patients, the median ED LOS was 2.1 hours (interquartile range, 1.050–3.830 hours), with 12.6% experiencing a prolonged ED LOS. Elderly patients (aged ≥65 years) were significantly more likely than younger patients to experience prolonged ED LOS (adjusted odds ratio [aOR], 1.415; 95% confidence interval [CI]: 1.411–1.419). Patients transferred from other hospitals (aOR, 1.469; 95% CI, 1.463–1.474) and those arriving by emergency medical services (aOR, 1.093; 95% CI, 1.077–1.108) also had high odds of prolonged LOS. Conversely, pediatric patients had a low likelihood of extended stay (aOR, 0.682; 95% CI, 0.678–0.686). Severe illness, including sepsis (aOR, 1.324; 95% CI, 1.311–1.340) and COVID-19 infection (aOR, 1.413; 95% CI, 1.399–1.427), was strongly associated with prolonged LOS. Conclusion Prolonged ED LOS is influenced by a combination of patient demographics, clinical severity, and systemic factors. Targeted interventions for older adults, severe illness, and operational inefficiencies such as hospital transfers are essential for reducing ED LOS and improving overall emergency care delivery.
Citations
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