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    Optimizing operating room scheduling considering instrument sterilization processing
    (Montana State University - Bozeman, College of Engineering, 2019) Harris, Sean Paul; Chairperson, Graduate Committee: David Claudio
    The United States healthcare system represents approximately 18% of the nation's GDP and its numerous challenges continue to receive significant attention from researchers. Within healthcare, operating rooms (ORs) often represent the largest source of revenue and costs in a hospital. Consequently, OR surgical scheduling strategies have been thoroughly examined from a wide variety of performance measures such as overtime, patient waiting time, and utilization rates. ORs are a complex system, and researchers have begun to consider the upstream and downstream resources involved in the surgical process such as the Post Anesthesia Care Unit, Intensive Care Unit, and bed availability. However, two factors that have only begun to be examined are the sterilization process of OR instrumentation and the assignment of instruments into trays and preference cards, either by surgical procedure or individual surgeon preference. Using both collected and historical data, this research 1) examined and improved how the block schedule of an OR suite affected the Sterilization Processing Department (SPD) and 2) examined and improved preference cards for surgical cases. A series of mathematical models optimized surgical block schedules while considering the impact on the SPD and a goal programming model was developed for the tray optimization problem. A comprehensive simulation model of the OR suite and SPD tested the output of the mathematical models. The simulation results confirmed block scheduling does affect SPD performance. A linear goal programming formulation that smoothed SPD workload across block times was the most effective type of model to optimize block scheduling. A goal programming tray optimization model improved expected instrument utilization rates. For practical applications, this research suggests reducing SPD staff turnover is a more effective method for improving SPD performance than rearranging the OR block schedule. This research is among the first of its kind to consider SPD workload as an objective in OR block scheduling models, to consider expected instrument non-usage rates in the tray optimization problem, and to develop a comprehensive simulation model of an OR suite and its SPD to test the results of mathematical models.
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    Standard work procedures and compliance in the OR : a study on the effect of standard work in all surgery types
    (Montana State University - Bozeman, College of Engineering, 2013) Cosgriff, Virginia Evelyn; Chairperson, Graduate Committee: David Claudio
    The operating room (OR) department is one of the most expensive area to run in a hospital. The cost per minute to run the OR is $33/minute, so decreasing the time will save the hospital a significant amount, even if it is a minute per turnover. This research looks at to reducing the turnover time (non-operative time) and variation in the OR by using standardization. Data collection consisted of observation and interviews of the circulating nurses, surgical techs, and aides to identify causes of delays and long turnovers. It was determined that the turnover could be divided into two stages: cleaning of the room and setting up for the next surgery. With this in mind, the research team met with the cleaning staff (aides) to create a standard operating procedure. Preliminary tests with the cleaning procedure proved to be promising, and a full-scale implementation in all ORs and surgery types was carried out. Along with a cleaning procedure, standardization of tasks for the three staff types helped to decrease the time of cleaning the OR, setup of a room, and the overall time. The overall turnover time decreased by two minutes and standard deviation decreased by almost two minutes for all surgery types throughout the OR department. The decrease in time will allow the OR to hire more staff to increase the efficiency of setup for the turnovers. A decrease in standard deviation signifies more consistent turnovers which create more predicable times for scheduling in the future.
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