Using emergency physicians' abilities to predict patient admission to decrease admission delay time

Emerg Med J. 2020 Jul;37(7):417-422. doi: 10.1136/emermed-2019-208859. Epub 2020 Mar 5.


Background: In many EDs, emergency physicians (EPs) do not have admitting privileges and must wait for consultants to further assess and admit patients. This delays bed requests and increases ED crowding. We measured EPs' abilities to predict patient admission prior to consultation and estimated the potential ED stretcher time saved if EPs requested a bed with consultation.

Methods: We conducted a prospective cohort study in an academic centre in Canada between October 2017 and February 2018 using a convenience sample of ED patient encounters requiring consultation. We excluded patients under 18 years or those clearly likely to be admitted (traumas, strokes, S-T elevation myocardial infarctions and Canadian Triage and Acuity Scale of 1). EPs predicted patient admission just before consultation. Potential ED stretcher time saved was estimated for correctly predicted admissions assuming bed requests were initiated with consultation and a constant time to inpatient bed.

Results: Characteristics of 454 patients were: mean age 60.1 years, 48.5% male, 46.9% evening presentation, 69.4% admitted and median time to bed request of 3.5 hours (IQR 2.0-5.3 hours). Overall, EPs prediction sensitivity, specificity, positive predictive value and negative predictive value were 90.5% (95% CI 86.7% to 93.5%), 84.2% (95% CI 77.0% to 89.8%), 92.8% (95% CI 89.8% to 95.0%) and 79.6% (95% CI 73.4% to 84.7%). Approximately 922.1 hours of ED stretcher time could have been saved during the 5-month study period if EPs initiated a bed request with consultation.

Conclusion: Crowding is a reality for EDs worldwide, and many systems could benefit from EP-initiated hospital admissions to decrease the amount of time admitted patients wait in the ED.

Keywords: admission avoidance; emergency department; hospitalisations.

MeSH terms

  • Adult
  • Aged
  • Clinical Competence*
  • Crowding
  • Emergency Service, Hospital / organization & administration*
  • Female
  • Hospitalization / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Ontario
  • Predictive Value of Tests
  • Process Assessment, Health Care*
  • Prospective Studies
  • Referral and Consultation*
  • Time Factors