Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds. THE IMPACT OF HOURLY DISCHARGE RATES AND PRIORITIZATION ON TIMELY ACCESS TO INPATIENT BEDS Asli Ozen Patricia Samra Hari Balasubramanian Mike Ehresman Haiping Li Todd Fairman Joan Roche University of Massachusetts, Amherst Baystate Medical Center 160 Governors Drive 759 Chestnut Street Amherst, MA 01002, USA Springfield, MA 01199, USA ABSTRACT We develop an empirically calibrated hospital-wide simulation model to represent a time-varying, multiserver queuing network with multiple patient classes. The focus is on quantifying the impact of discharge profiles to alleviate inpatient bed congestions. A discharge profile is defined by (a) discharge window, which specifies hours of the day discharges are allowed; and (b) the maximum capacity for discharges in each hour of the window. Results of our simulation model show that a more responsive policy that prioritizes discharges in units with longer admission queues can significantly reduce waiting times (40% reduction in queues). In comparison, an early in the day discharge policy has a lower impact on improving bed congestions; we also find that early in the day discharges are very hard to realize in practice. Further, expanding the discharge windows by only 2 hours in the evening (7-9 PM) creates the same benefit, and is more realistic. 1 INTRODUCTION Inability to satisfy bed requests in a timely manner causes hospital wide congestions. These effects include but are not limited to: patients waiting long hours in the ED or a surgical area for an inpatient bed; patients not being placed in their primary unit (i.e. off-service placement); urgent patients bumping less critically sick patients from ICUs to “step-down units”; and refusing transfers from other hospitals. In this paper, we use an empirically calibrated hospital-wide simulation model to quantify the impact of discharge profiles on timely access to inpatient beds. We define a discharge profile by (a) discharge window, which specifies the hours of the day discharges are allowed; and (b) maximum discharges a hospital can manage in each hour of the window. The discharge process is typically complex and involves many moving parts; it requires the timing of physician rounds; availability of nurses, case managers and social workers; and coordination with families and post-hospitalization facilities to all come together. Rather than considering these individual aspects, which are quite difficult to estimate, we instead use discharge profiles to model the hospital’s aggregate hourly capacity. Timely access in our model is measured by the average number of patients waiting for an inpatient bed (average queue length) in any hour. This queue size includes all patients waiting in the Emergency Department (ED), Post-Acute Care Unit (PACU) or other locations after the physician has made a request for an inpatient bed. 1210 978-1-4799-7486-3/14/$31.00 ©2014 IEEE