Reducing workload fluctuations through causal forecasting : a case study in the plaster room of Sint Maartenskliniek

The employees and management of the plaster room in Sint Maartenskliniek in Nijmegen, The Netherlands, perceive high fluctuations of workload over the days resulting in overstaffed and understaffed days. The objective of this research is to minimize workload fluctuations over the days by creating a planning method that incorporates patient demand while maintaining patient service levels. We develop a planning method that improves the match between capacity and demand by incorporating walk-in patient demand. This research provides a step-by-step guide to generate, select and validate causal forecasting models that can support outpatient clinic planning staff in making scheduling decisions. The experimental interventions show to outperform the realized situation by a reduction of overstaffed days of 50%. We achieve a decrease in average capacity shortage of approximately 35%. This research shows that the method to predict walk-in demand can increase the match between capacity and demand in the plaster room and minimizes workload fluctuations over the days. The methodology results in a model that can continuously create walk-in demand predictions and is implemented in the plaster room in the summer of 2018.