Factors that predict emergency department length of stay in analysis of national data

Minha Kim; Sujeong Lee; Minyoung Choi; Doyeop Kim; Junsang Yoo; Tae Gun Shin; Jin-Hee Lee; Seongjung Kim; Hansol Chang; Eunsil Ko

doi:10.15441/ceem.24.309

Clin Exp Emerg Med > Accepted Articles

Original Article

doi: https://doi.org/10.15441/ceem.24.309 [Accepted]

Factors that predict emergency department length of stay in analysis of national data

Minha Kim^1,2

, Sujeong Lee³, Minyoung Choi², Doyeop Kim^1,4

¹Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
²Department of Medical Sciences, Graduate School of Kangwon National University, Chuncheon, Korea
³Department of Health Sciences and Technology, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
⁴Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
⁵National Emergency Medical Center, National Medical Center, Seoul, Korea
⁶Department of Emergency Medicine, Chosun University Hospital, Gwangju, Korea

Correspondence Hansol Chang Email: briquet90@naver.com, Eunsil Ko Email: eunsil0802@nmc.or.kr

Received: September 4, 2024. Revised: September 26, 2024. Accepted: October 8, 2024. Published online: October 16, 2024.

ABSTRACT

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.
Result
s: 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.

Keywords: Emergency departments; Emergency medicine; Length of stay; Emergency medical service communication systems; Health information systems