Patient characteristics associated with longer emergency department stay: a rapid review

Emerg Med J. 2016 Mar;33(3):194-9. doi: 10.1136/emermed-2015-204913. Epub 2015 Sep 4.


Background: Prolonged emergency department (ED) stays make a disproportionate contribution to ED overcrowding, but the factors associated with longer stays have not been systematically reviewed.

Objective: To identify the patient characteristics associated with ED length of stay (LOS) and ascertain whether a predictive model existed.

Methods: This rapid systematic review included published, English-language studies that assessed at least one patient-level predictor of ED LOS (defined as a continuous or dichotomous variable) in an adult or mixed adult/paediatric population within an Organization for Economic Cooperation and Development country. Findings were synthesised narratively.

Results: We identified 35 relevant studies; most included multiple predictors, but none developed a predictive model. The factors most commonly associated with long ED LOS were need for admission (10 of 10 studies) and older age (which may be a proxy for age-related differences in health condition and severity; 9 of 10), receipt of diagnostic tests or consults (8 of 8) and ambulance arrival (4 of 5). Acuity often showed a bell-shaped relationship with LOS (ie, patients with moderate acuity stayed longest).

Limitations: Methodological choices made in the interests of rapidity limited the review's comprehensiveness and depth.

Conclusions: Despite a sizeable body of literature, the available information is insufficiently precise to inform clinical or service-planning decisions; there is a need for a predictive model, including specific patient complaints. Deeper understanding of the determinants of ED LOS could help to identify patients and/or populations who require special intervention or resources to prevent a protracted stay.

Keywords: crowding; emergency care systems, emergency departments.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Age Factors
  • Crowding
  • Diagnostic Tests, Routine / statistics & numerical data
  • Emergency Service, Hospital / statistics & numerical data*
  • Health Status
  • Hospitalization / statistics & numerical data
  • Humans
  • Length of Stay / statistics & numerical data*
  • Patient Acuity
  • Risk Factors
  • Severity of Illness Index
  • Time Factors