Optimizing inpatient bed capacity to improve care delivery

We consider the problem of partitioning clinical services in hospitals into groups with the goal of efficiently allocating existing inpatient beds. At the strategic level, there are two major possibilities: pooling versus focusing. Pooling the bed capacity allows one to achieve an overall high occupancy level for a fixed number of beds. On the other hand, focusing by dividing the capacity into groups with restricted access may offer increased efficiency and better resource utilization. We derive a two-stage schema to address the 3-fold problem: 1) how many groups of services to form; 2) how many beds to allocate to each group; and 3) how to partition services among the groups. Stage 1 uses cluster analysis utilizing the similarity principle for possible advantages of economies of scale, coupled with queueing-based optimization models to obtain a set of candidate groups. Stage 2 incorporates utility/benefit functions to optimize the partitions and allocation of beds. Three full-scale examples demonstrate the flexibility and diverse application of our framework with managerial insights for different utility optimization goals and queueing systems.