Providers of mental healthcare have been struggling with capacity problems for
many years, in many cases leading to excessive waiting times for the patient-in-need.
This has raised the need for ways to make better use of the available capacity. To this
end, it is crucial to develop models and tools to gain insight into the capacity
bottlenecks, and to answer ‘what-if’ scenarios on the consequences and effectiveness
of capacity decisions. Motivated by this, in this paper we address this problem by
developing a data-driven Decision Support System (DSS) for a specific clinic of a
Dutch mental health care provider. The DSS allows the management team to better
understand (1) the characteristics and performance of their admission process, and
(2) the consequences of capacity decisions in terms of service level and the
occupancy rate of the clinics.
|Doina Leca, Bryan van Ingen, Rebekka Arntzen, Dennis Moeke, Rob van der Mei||Vrije Universiteit Amsterdam, Department of Mathematics, Amsterdam, Centre for Mathematics and Computer Science, Stochastics group, HAN University of Applied Sciences, Research Group Logistics and Alliances, Arnhem||2022|