Abstract
A general multi-stage queuing system model with patients’ feedback flow is developed to address the behavior of patients’ flow in an Outpatient Department (OD) in a hospital. The whole process includes registration, diagnosis, chemical examination, payment, and medicine-taking. Focusing on nurse resources, the formulas of performance indicators such as patient waiting times and nurse idle times are derived by using the system parameters. A mathematical programming model is developed to determine how many nurses should be allocated to each stage to minimize the total costs of patient waiting times and nurse idle times. The neighborhood search combined Simulated Annealing (NS-SA) is developed to solve the model, which is essentially a natural number decomposition problem. Numerical experiments are conducted to analyze the discipline of nurse allocation and the impact of patient arrival rates and the probability of patient’s feedback flow on the system costs. The research results will be helpful for hospital managers to make decisions on allocation of nurse staff in practice.
Highlights
Over the years, hospital managers continually confront many challenges, such as providing better service quality, with less nurse staff and more patients
A mathematical programming model is developed to determine how many nurses should be allocated to each stage to minimize the total costs of patient waiting times and nurse idle times
We introduce these critical operations in our NS-SAalgorithm in details as followings
Summary
Hospital managers continually confront many challenges, such as providing better service quality, with less nurse staff and more patients. Nurse staff allocation in multi-stage queuing system with patients’ feedback flow for OD is mainly concerned in this paper. According to the performance indicators such as patient waiting times, and the probability of nurse idle times in the multi-severs queuing systems, Abadi(2000)[7] and Balsamo made some analysis[8]. Focusing on the nurse resources, the formula of performance indicators such as patient waiting times, probability of nurse idle times are derived by the system parameters. A mathematical programming model is developed to determine how many nurses are allocated to each stage/ division to minimize the total costs of patient waiting times and nurse idle times.
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