Assessing the impact of patient prioritization on operating room schedules

This paper proposes an integrated approach to merge patient prioritization and patient scheduling to improve access to services in an elective (i.e., non-urgent) context. In particular, we assume that patients are included on a waiting list for a given surgery, and that every patient on the list has received a “utility score”, which is a proxy for the relative urgency with regards to the other patients on the list. A mathematical model is formulated to solve the patient scheduling problem, i.e., the simultaneous assignment of surgery sessions to surgeons and patients to surgeons, in such a way that the total utility is maximized along with other practical requirements. The model has been applied to a testbed of randomly generated instances, inspired by the context of the Urology Department at a University Hospital in Quebec City. Experiments have been conducted to analyze both the short- and medium-term behaviors of the proposed approach. The numerical results confirm that the use of an objective function designed to maximize utility does not deteriorate the efficiency of the resulting schedules in terms of the number of surgeries performed. They also show that, as expected, higher utility patients are scheduled first, and their waiting time before surgery are shorter than those of lower utility. However, this approach may lead to longer, and even unacceptable waiting times for low utility patients. To mitigate such an undesirable effect, a dynamic utility updating approach is proposed to progressively increase the utility of patients according to their time spent on the waiting list. This approach seems to adequately balance the advantages of scheduling patients based on their utility and the risk of causing too much delay for low priority patients.