UCLA

A simulation model is developed for scheduling elective patients to a hospital facility based on resource availability. The approach takes into account two different types of patients, emergency in which admission occurs randomly, and elective in which demand is random, but patients are only admitted if they have been scheduled. The simulation aims to maximize the hospital's rewards from treating patients, in the presence of penalties for overbooking the facility. Few different heuristics for admission policies are compared and results analyzed. Simulation was performed on data from the Neurosurgery department at the UCLA Ronald Reagan Hospital. Even though the simulation is based on data from a neurosurgery department it can be used when admitting patients to other medical departments as well.