Surgical Suite Utilization and Capacity Planning: A Minimal Cost Analysis Model
Journal of Medical Systems
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
The Sample Average Approximation Method for Stochastic Discrete Optimization
SIAM Journal on Optimization
Hospital Operating Room Capacity Expansion
Management Science
Managing Patient Service in a Diagnostic Medical Facility
Operations Research
Dynamic Programming and Optimal Control, Vol. II
Dynamic Programming and Optimal Control, Vol. II
Dynamic Multipriority Patient Scheduling for a Diagnostic Resource
Operations Research
A Markov decision process approach to multi-category patient scheduling in a diagnostic facility
Artificial Intelligence in Medicine
Multi-objective operating room scheduling considering desiderata of the surgical team
Decision Support Systems
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This paper addresses a scheduling problem where patients with different priorities are scheduled for elective surgery in a surgical facility, which has a limited capacity. When the capacity is available, patients with a higher priority are selected from the waiting list and put on the schedule. At the beginning of each period, a decision of the number of patients to be scheduled is made based on the trade-offs between the cost for overtime work and the cost for surgery postponement. A stochastic dynamic programming model is formulated to address this problem. A structural analysis of the proposed model is conducted to understand the properties of an optimal schedule policy. Based on the structural analysis, bounds on feasible actions are incorporated into a value iteration algorithm, and a brief computation experiment shows the improvement in computational efficiency. Numerical examples show that the consideration of patient priority results in significant differences in surgery schedules from the schedule that ignores the patient priority.