Simulation-based evaluation of operating room management policies

被引:21
作者
Schoenfelder, Jan [1 ,2 ]
Kohl, Sebastian [1 ,2 ]
Glaser, Manuel [1 ,2 ]
McRae, Sebastian [1 ,2 ]
Brunner, Jens O. [1 ,2 ]
Koperna, Thomas [3 ,4 ]
机构
[1] Univ Augsburg, Fac Business & Econ, Chair Hlth Care Operat Hlth Informat Management, Univ Str 16, D-86159 Augsburg, Germany
[2] Klinikum Augsburg UNIKA T, Univ Ctr Hlth Sci, Neusasser Str 47, D-86156 Augsburg, Germany
[3] Univ Hosp Augsburg, Surg, Stenglinstr 2, D-86156 Augsburg, Germany
[4] Univ Hosp Augsburg, OR Management, Stenglinstr 2, D-86156 Augsburg, Germany
关键词
Operating room management; Patient scheduling; Patient flow; Capacity management; Simulation;
D O I
10.1186/s12913-021-06234-5
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg. Methods Based on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries. Results We identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators. Conclusions Our simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner.
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页数:13
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