Patient-centric design of long-term care networks

Paul Intrevado (), Vedat Verter () and Lucie Tremblay ()
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Paul Intrevado: University of San Francisco
Vedat Verter: McGill University
Lucie Tremblay: President of the Order of Nurses of Québec

Health Care Management Science, 2019, vol. 22, issue 2, No 11, 376-390

Abstract: Abstract 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.

Keywords: Long-term care; Nursing homes; Multi-period capacity planning; Network design; Mixed integer programming (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10729-018-9445-7

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