Dominant strategies to reduce patient waiting time under multiple constrained resources

Waiting times for elective procedures are a major health policy concern in many European countries. Initiatives to control waiting times involve supply-side policies that encompass raising public capacity, and demand-side policies with a prioritization of patients according to need for a better management of waiting lists. On a microeconomic level, complementary approaches to tackle the issue of waiting times include the use of Operational Research techniques. The present paper is in line with these approaches and provides strategies to reduce the waiting time for elective surgery in any speciality requiring multiple constrained resources. In the medium run, the objective is to determine the best admission policy at the tactical level. The resulting tactical plan which is based on a fixed number of patients derived from historical data of arrivals can be adjusted to patients in the queue to provide an operational plan. Several strategies to translate a tactical plan into an operational plan are considered and assessed in terms of hospital performance and patient satisfaction. We propose a new strategy that allows for substantial decrease in waiting time while keeping a high hospital performance. The hospital performance is measured by a weighted sum of several criteria such as additional and cancelled operations, plan changes and deviations of resource consumptions compared to their target levels. Weights in the hospital performance indicator are drawn at random in selected intervals to portray a wide spread of managers' assessments. Simulation results show that several strategies are dominant whatever the assessment profile. We also identify the best strategies to reach a limited waiting time.