• Sean Boley, Abbey Sidebottom, Marc Vacquier, David Watson, Jeremy Olsen, Kelsey Echols, and Sara Friedman.
• Emergency Care Consultants, Minneapolis, MN, United States. Electronic address: Sean.boley@eccemergency.com.
• Am J Emerg Med. 2022 Oct 1; 60: 657265-72.

ObjectivesRacial disparities in emergency medical care are abundant, and processes aimed to increase throughput, such as a rapid triage fast-track (FT) systems, may exacerbate these inequities. A FT strategy may be more susceptible to implicit bias as subjective information is obtained quickly. We aim to determine whether a FT model was associated with greater disparities between Black and White emergency department (ED) patients.MethodsTriage-related outcomes were compared across race using a cohort selected from encounters in an ED that uses a FT model. White and Black patient encounters were exact-matched on potential confounders including sex; presence of abnormal vital signs; ED arrival time; insurance type; age category; and chief complaint. The primary triage-related outcome was use of the FT area (versus the main ED), and the secondary outcomes were wait time and assigned encounter acuity.ResultsEncounters for 5151 Black patients were exact-matched with 7179 encounters for White patients. Weights were applied to address differential numbers of encounters from each group. Within this matched cohort, Black patients were more likely to be triaged to FT than White patients (odds ratio = 1.28, 95% CI: 1.12; 1.46) and less likely to be given a high acuity score (odds ratio = 0.73, 95% CI: 0.66, 0.81). Among the high-acuity patients, Black patients were 40% more likely to be triaged to the FT area.ConclusionsThese results suggest that, after controlling for potential confounders, racial disparities may have been exacerbated in a FT ED triage process. In a FT model utilizing physicians and midlevel providers, this may create tiered levels of care between Black and White patients - an unacceptable side-effect of an effort to increase ED throughput.Published by Elsevier Inc.

10 keywords...

hide…