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Assessing emergency department physician workload: A NASA-TLX analysis by experience and care type
Donghyun Kim1, Junsang Yoo2, Ye Rim Lee2
1Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 115 Irwon-ro Gangnam-gu, Seoul 06355, Republic of Korea.
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.
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