Inefficient management of emergent surgeries in hospitals can, in part, be attributed to a lack of rigorous analysis appropriate to capturing the underlying uncertainties inherent to this process and a pricing mechanism to ensure its financial viability. We develop a non-preemptive multi-priority queueing model that optimally manages emergent surgeries and supports the resource allocation decision-making process. Specifically, we utilize queueing and discrete event simulation to develop empirical models for determining the required number of emergent operating rooms for a hospital surgical department. We also present algorithms that estimate the appropriate pricing for patient surgeries differentiated by priority level given the patient demand and the resources reserved to meet this demand.