Evaluation of optimal scheduling policy for accommodating elective and non-elective surgery via simulation

Abstract

There are two main types of surgeries within an operating room (OR) suite, namely elective (or scheduled) and non-elective (or non-scheduled) surgeries. Non-elective surgeries count for a considerable proportion of surgery demand and often have a priority for begin served in a timely manner. Accommodating this type of surgery can be a challenging task on the day of surgery. This is mainly a result of the uncertain demand for non-elective surgeries, which discourages hospitals from reserving sufficient capacity for these surgeries. Using simulation, we evaluate an optimal policy for accommodating elective and non-elective surgeries that minimizes waiting time of patients, overtime, and number of patients turned away. We carry out the analysis on a stylized, two-room study where one room is dedicated to non-elective cases and the other room contains elective cases but can accept a non-elective case if necessary. The optimal policy is originally found by using a Markov decision process (MDP). However, since Markov modeling has an exponential arrival rate and steady state assumptions, which may not always be true in a surgical environment, the evaluation through simulation allows these assumptions to be relaxed.