Capacity planning for a network of community health services

• Published in: European journal of operational research Vol. 275; no. 1; pp. 266 - 279
• Main Authors: Mohammadi Bidhandi, Hadi, Patrick, Jonathan, Noghani, Pedram, Varshoei, Peyman
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 16.05.2019
• Subjects: Metaheuristics; OR in health services; Queueing network; Simulation; Simulation; Queueing network; Metaheuristics; OR in health services
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2018.11.008

•Developed queuing model to predict blocking at each stage of a generalized network.•Coupled queuing model with an Non-Linear Integer Program to optimize capacity.•Developed an innovated simulated annealing method to solve Integer program.•Tested approach on a network of 6 stages using data provided by health authority.•Developed two simulation models to validate our capacity planning approach. Community care services are becoming increasingly important to health delivery as patients live longer but with chronic disease. In this research, we propose a queuing network approach to capacity planning for a network of services. We take advantage of existing heuristics that calculate the probability of blocking for a given capacity plan and utilize the output of these heuristics to run a simulated annealing approach to optimize capacity allocation across the network subject to a performance guarantee related to the sum of the blocking probabilities. We apply this model to a local health region with a network of six services – acute care, long term care, assisted living, home care, rehabilitation and chronic care. We test the results of the optimization model through a simulation that incorporates more realism than is possible in the queuing model and that also allows us to determine the transient behaviour of the system as it transitions from current capacity levels to the those proposed by the optimization model.