Decisions about the operations to be performed usually affect the occupancy of downstream resources such as intensive care units (ICU), recovery rooms or regular patient wards. Since the capacity of e.g. ICUs is severely limited, bottlenecks may occur here, leading to cancellations of planned surgeries. Our research results provide action patterns for hospital decision makers for daily patient scheduling, which are optimized using a novel chance-constraint optimization model in combination with a simulation for the corresponding patient mix, taking into account both operating room capacity and ICUs.

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