Who Is Next: Patient Prioritization Under Emergency Department Blocking

Upon arrival at emergency departments (EDs), patients are classified into different triage levels indicating their urgency. Using data from a large hospital in Canada, we find that, within the same triage level, the average waiting time (time from triage to initial assessment by a physician) of patients who are discharged is shorter than that of patients who are admitted for middle- and low-acuity patients, suggesting that the order in which patients are served deviates from first-come, first-served, and to a certain extent, discharged patients are prioritized over admitted patients. This observation is intriguing as, among patients of the same triage level, admitted patients—who need further care in the hospital—should be deemed no less urgent than discharged patients who only need treatment at the ED. To understand how ED decision makers choose the next patient for treatment, we estimate a discrete-choice model and find that ED decision makers apply urgency-specific delay-dependent prioritization. Moreover, we find that, when the ED blocking level is sufficiently low, admitted patients are prioritized over discharged patients for high-acuity patients, whereas disposition does not affect the prioritization of middle- and low-acuity patients. When the ED blocking level becomes sufficiently high, decision makers start to prioritize discharged patients in an effort to avoid further blocking the ED. We then analyze a stylized model to explain the rationale behind the change in decision makers’ prioritization behavior as the ED blocking level increases. Using a simulation study, we demonstrate how policies inspired by our findings improve ED operations by reducing the average patient waiting time and length of stay, resulting in significant cost savings for hospitals. We also show how to leverage our findings to improve the accuracy of ED waiting time predictions. By testing and highlighting the central role of decision makers’ patient prioritization behavior, this paper advances our understanding of ED operations and patient flow.