Patient-centric design of long-term care networks

Paul Intrevado, Vedat Verter, Lucie Tremblay

Long-term care networks may soon buckle under the weight of overwhelming demand. We present two dynamic, large-scale mixed-integer programs for long-term care network design that execute jointly strategic and tactical facility location, modular capacity acquisition, and patient-assignment decisions. The first model is an adaptive network-design model whose focus is more strategic in nature, whereas the second model focuses exclusively on the expansion of an existing long-term care network and incorporates additional tactical decisions such as patient backlogs. Working directly with the president of the Order of Québec Nurses-the provincial organization representing over 75,000 nurses-we incorporate facets such as assignment permanence, as well as develop and measure patient-centric quality-of-life proxies such as geographic mis-assignment and un-assigned patients, the latter of which is quantified via parametric optimization. Various network-design and patient-assignment policies are explored. We conclude that the use of home care as an alternative to long-term care facilities is cost prohibitive under specific conditions. Employing a bisection algorithm, we identify the implicit cost placed on keeping medically stable elderly patients in a hospital ward, concluding no cost savings are generated from such a policy. The model is analyzed and validated using empirical data from the long-term care network in Montréal, Canada.