One of the impacts of the rising demand for community health services, primarily used by seniors, is that hospitals are often faced with the challenge of having patients finish the acute phase of their treatment and yet are unable to discharge them due to the lack of a bed in a more appropriate community care setting. The frequency of this challenge has led to the designation of “alternative level of care” (ALC) being ascribed to patients who remain in the hospitals due to insufficient capacity downstream. The thesis focuses on a model that seeks to address patient flow through the community care network (CCN) and finding capacity allocation policies for the different facilities that resolves the ALC challenge using scenario analysis. A queuing network model with general routings and nodes’ blocking has been developed and a heuristic approximation method has been employed for solving the model. Blocking probabilities and the number of blocked patients are derived as performance metrics of the CCN. We test the accuracy of the queuing model through a simulation model and the behaviours of the system in different scenarios are investigated in the simulation model and our policy insights and conclusions are provided.

One of the impacts of the rising demand for community health services, primarily used by seniors, is that hospitals are often faced with the challenge of having patients finish the acute phase of their treatment and yet are unable to discharge them due to the lack of a bed in a more appropriate community care setting. The frequency of this challenge has led to the designation of “alternative level of care” (ALC) being ascribed to patients who remain in the hospitals due to insufficient capacity downstream. The thesis focuses on a model that seeks to address patient flow through the community care network (CCN) and finding capacity allocation policies for the different facilities that resolves the ALC challenge using scenario analysis. A queuing network model with general routings and nodes’ blocking has been developed and a heuristic approximation method has been employed for solving the model. Blocking probabilities and the number of blocked patients are derived as performance metrics of the CCN. We test the accuracy of the queuing model through a simulation model and the behaviours of the system in different scenarios are investigated in the simulation model and our policy insights and conclusions are provided.