A queueing network approach to health care planning with an application to burn care in New York State

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Abstract

Treatment of severe thermal burns is a medical care problem which has not previously received the support and attention required on both the national and state level. With the advent of the Health Systems Agencies and the Systems Perspective to Health Care Planning, there will be a need for analytical planning and evaluation models which produce results with respect to controlling health care costs.

A descriptive planning model has been developed based on the theory of finite capacity multiserver queues and continuous-time Markov chains, which can be used to describe the operations of a system of burn care facilities linked together by a referral policy to accommodate patient overflow. This model has been combined with a heuristic optimization procedure to answer the relevant questions for burn care in New York State.

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    Modeling of stochastic systems using continuous-time Markov chains (CTMCs) (Bhattacharya & Waymire, 2009; Norris, 1998) is useful in a wide variety of fields. They are used as analysis tool in queueing theory, which is applied in the fields of telecommunications (László Lakatos et al., 2019), production, healthcare (Blair & Lawrence, 1981), and more. A specific type of CTMCs, the Stochastic Reaction Networks (SRNs) (Wiuf & Xu, 2020; Xu et al., 2019), is extensively used in the field of biochemistry (Anderson & Kurtz, 2011; Cinquemani, 2019; Murphy et al., 2018).

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