ADAPTIVE MULTI-OBJECTIVE OPERATING ROOM PLANNING WITH STOCHASTIC DEMAND AND CASE TIMES

The operating room (OR) is accountable for most hospital admissions and is one of the most cost and work intensive areas in the hospital. From recent trends, we discover an unexpected parallel increase in expenditure and waiting time. Therefore, improving OR planning has become obligatory, particularly regarding utilization, and service level. Significant challenges in OR planning are the high variations in demand, processing times of surgical specialties, the trade-off between the objectives, and control of OR performance in long-term. Our model provides OR configurations at a strategical level of OR planning to minimize the tradeoff between the utilization and service level accounting for variation in both demand and processing times of surgical specialties. An adaptive control scheme is proposed to aid OR managers to maintain the OR performance within the prescribed controllable limits. Our model is validated using a simulation of demand and processing time data of surgical services at University of Kentucky Health Care

Maximizing Operating Room Performance Using Portfolio Selection

The operating room (OR) is responsible for most hospital admissions and is one of the most cost and work intensive areas in the hospital. From recent trends, we observe an ironic parallel increase among expenditure and waiting time. Therefore, improving OR scheduling has become obligatory, particularly in terms of patient flow and benefit. Most of the hospitals rely on average patient arrivals and processing times in OR planning. But in practice, variations in arrivals and processing times causes high instability in OR performance. Our model of optimization provides OR schedules maximizing patient flow and benefit at a fixed level of risk using portfolio selection. The simulation results show that the performance of the OR has a direct relationship with the risk