Triage nurse prediction of hospital admission

J Emerg Nurs. 2012 May;38(3):306-10. doi: 10.1016/j.jen.2011.10.003. Epub 2012 Mar 29.


Introduction: Numerous factors affect patient flow in the emergency department. One important factor that has a negative impact on flow is ED patients waiting for an inpatient bed. It currently takes approximately 5 hours from triage to a request for an inpatient bed in our emergency department. Knowledge of patients requiring admission early in their ED evaluation could speed up the process of securing a bed. The objective of this study was to determine if an ED triage nurse (TRN) can determine at triage if a patient will be admitted to an inpatient unit. A secondary objective was to measure the confidence of the TRN prediction.

Methods: A prospective, non-consecutive study was conducted during an 18-day period in 2010 in a community hospital emergency department treating 76,000 patients. Experienced TRNs were trained in the evaluation tool. Immediately after the initial TRN evaluation, a determination was made in writing by the TRN regarding the likelihood of hospital admission and level of confidence in this decision. Patients who did not enter the emergency department through triage (ambulance) or were younger than 18 years were excluded.

Results: A total of 3514 patients approached triage. Of these patients, 1866 were eligible for the study and 1164 (62%) were enrolled. We excluded 25 subjects because of missing data, resulting in 1139 subjects. Missed subjects had the same baseline characteristics. A total of 287 (25.2%) hospital admissions occurred. TRN predicted 217 admissions, with a sensitivity of 75.6% (95% confidence interval [CI] 71.3-79.5) and a specificity of 84.5% (95% CI 83.1-85.8). The TRN reported being extremely confident in the prediction 50.1% of the time. In these cases, the TRN demonstrated an admission sensitivity of 81.6% (95% CI 76.5-85.8) and specificity of 93.1% (95% CI 91.8-94.3).

Conclusions: The TRN demonstrated a high sensitivity and specificity in admission prediction at triage and could potentially save many hours in requesting an inpatient bed. This increased efficiency could result in a more rapid ED throughput and decreased ED boarding.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Chi-Square Distribution
  • Crowding
  • Data Collection / instrumentation
  • Emergency Nursing*
  • Emergency Service, Hospital / organization & administration*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Patient Admission / standards*
  • Predictive Value of Tests
  • Prospective Studies
  • Sensitivity and Specificity
  • Triage*
  • Waiting Lists