Improving patient transportation in hospitals using a mixed-integer programming model

This paper investigates the current patient transportation between care units in a large hospital to determine possible solutions to reduce total completion times of demands. The goal is to avoid major changes in the current staff schedules. Historical data of the service calls is available and an in-depth analysis is conducted to identify popular routes and current assignment of demands to patient transport employees. We present a mixed-integer model to determine the best distribution of the employees throughout the most popular routes of the hospital to minimize costs. Experiments are conducted on real data from CHU de Québec-Université Laval, HEJ, in the province of Québec, Canada. Results obtained from assigning specific employees to routes instead of the current method, which consists at assigning employees to all of the hospital are compared and show that there is a gain in doing so.