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The allocation of surgeries to operating rooms (ORs) is a challenging combinatorial optimization problem. There is also significant uncertainty in the duration of surgical procedures, which further complicates assignment decisions. In this article, we present stochastic optimization models for the assignment of surgeries to ORs on a given day of surgery.(More)
O perating room (OR) scheduling is an important operational problem for most hospitals. In this study, we present a novel two-stage stochastic mixed-integer programming model to minimize total expected operating cost given that scheduling decisions are made before the resolution of uncertainty in surgery durations. We use this model to quantify the benefit(More)
Creation of an Outpatient Procedure Center (OPC) is a complicated endeavor, requiring a detailed understanding of the resources available and the procedures to be performed. Miscalculation of resource allocation or patient flow through the area can result in the waste of expensive resources, patient dissatisfaction, and health care provider inefficiency.(More)
Surgical services require the coordination of many activities, including patient check-in and surgical preparation, surgery, and recovery after surgery. Each of these activities requires the availability of resources including staff, operating rooms, and intake and recovery beds. Furthermore, each of these activities has substantial uncertainty in their(More)
At Mayo Clinic, care teams are being evaluated as a means to improve health care staff productivity and patient service. Traditional care in outpatient practices has health care staff working independently of each other with little coordination. Initial feedback by participating practices support the value of care teams. Our research focuses on a(More)
Patient appointment booking, sequencing, and scheduling decisions are challenging for outpatient procedure centers due to uncertainty in procedure times and patient attendance. We formulate a model based on a two-stage stochastic mixed integer program for optimizing booking and appointment times in the presence of uncertainty. The objective is to maximize(More)
Increasing healthcare costs are driving the need for optimizing care delivery processes. Due to the complexity associated with healthcare processes, discrete event simulation is the most popularly used decision support tool in assessing trade-offs between multiple objectives of healthcare systems. However in situations where there is little or no structure(More)
Perioperative services have a high impact on a hospital's financial success. In order to increase patients' privacy and satisfaction, while restraining cost, a redesign of the existing Post-Anesthesia Care Unit (PACU) was suggested at the Mayo Clinic. A simulation model was created to determine the number of beds required in the redesign of the PACU to(More)
In this paper we use simulation to evaluate the effect of shorter red cell shelf life on blood supplies at the Mayo Clinic and compare these results to previous work. Results show that a reduced maximum shelf life of 28 days is supportable under current conditions but that a maximum shelf life of 21 days or less will likely result in unacceptably high(More)
An outpatient clinic faces frequent appointment requests and visits from different classes of patients each day. Although the patients arriving to the outpatient clinic may not be in a critical condition, it is still very important for the clinic to have adequate appointments to serve patients without significant delay in order to not lose patients and(More)