Developing an adaptive policy for long-term care capacity planning.

This paper describes a refined methodology for determining long-term care (LTC) capacity levels over a multi-year planning horizon based on a previous study. The problem is to find a capacity level in each year during the planning horizon to meet a wait time service level criterion. Instead of a static policy for capacity planning, we proposal an adaptive policy, where the capacity level required in this year depends on the achieved service level in the last year as the state of the LTC system. We aggregate service levels into a few groups for tractability. Our methodology integrates a discrete event simulation for describing the LTC system and an optimization algorithm to find required capacity levels. We illustrate this methodology through a case study. The results show that the refined methodology overcomes the problems observed in the previous study. It also improves resource utilization greatly. To execute this adaptive policy in practice requires availability of surge or temporary capacity.