Nurse-administered early warning score system can be used for emergency department triage

Dan Med Bull. 2011 Jun;58(6):A4221.


Introduction: Studies have shown that early warning score systems can identify in-patients at high risk of catastrophic deterioration and this may possibly be used for an emergency department (ED) triage. Bispebjerg Hospital has introduced a multidisciplinary team (MT) in the ED activated by the Bispebjerg Early Warning Score (BEWS). The BEWS is calculated on the basis of respiratory frequency, pulse, systolic blood pressure, temperature and level of consciousness. The aim of this study is to evaluate the ability of the BEWS to identify critically ill patients in the ED and to examine the feasibility of using the BEWS to activate an MT response.

Material and methods: This study is based on an evaluation of retrospective data from a random sample of 300 emergency patients. On the basis of documented vital signs, a BEWS was calculated retrospectively. The primary end points were admission to an intensive care unit (ICU) and death within 48 hours of arrival at the ED. This study was registered at (NCT01243021).

Results: A BEWS ≥ 5 is associated with a significantly increased risk of ICU admission within 48 hours of arrival (relative risk (RR) 4.1; 95% confidence interval (CI) 1.5-10.9) and death within 48 hours of arrival (RR 20.3; 95% CI 6.9-60.1). The sensitivity of the BEWS in identifying patients who were admitted to the ICU or who died within 48 hours of arrival was 63%. The positive predictive value of the BEWS was 16% and the negative predictive value 98% for identification of patients who were admitted to the ICU or who died within 48 hours of arrival.

Conclusion: The BEWS is a simple scoring system based on readily available vital signs. It is a sensitive tool for detecting critically ill patients and may be used for ED triage and activation of an MT response.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Child
  • Child, Preschool
  • Confidence Intervals
  • Critical Illness*
  • Decision Support Systems, Clinical
  • Early Diagnosis*
  • Emergencies
  • Emergency Service, Hospital*
  • Feasibility Studies
  • Female
  • Humans
  • Intensive Care Units / organization & administration*
  • Male
  • Middle Aged
  • Monitoring, Physiologic
  • Nursing Staff, Hospital / organization & administration*
  • Predictive Value of Tests
  • Retrospective Studies
  • Risk
  • Risk Assessment / methods
  • Sensitivity and Specificity
  • Time Factors
  • Triage / methods*
  • Young Adult

Associated data