Kokangul Ali
Department of Industrial Engineering, Cukurova University, 01330 Adana, Turkey.
Comput Methods Programs Biomed. 2008 Apr;90(1):56-65. doi: 10.1016/j.cmpb.2008.01.001. Epub 2008 Feb 15.
Random number of arrivals and random length of stays make the number of patients in a hospital unit behave as a stochastic process. This makes the determination of the optimum size of the bed capacity more difficult. The number of admissions per day, service level and occupancy level are key control parameters that affect the optimum size of the required bed capacity. In this study a new stochastic approximation is developed and applied to a unit of a teaching hospital. Data between 2000 and 2004 was used to obtain the necessary probability distribution functions. Mathematical relationships between the control parameters and size of the bed capacity are obtained using generated data from a constructed simulation model. Nonlinear mathematical models are then used to determine the optimum size of the required bed capacity based on target levels of the control parameters, and a profit and loss analysis is performed.
随机的入院人数和随机的住院时长使得医院科室的患者数量呈现为一个随机过程。这使得确定最佳床位容量变得更加困难。每日入院人数、服务水平和占用率是影响所需最佳床位容量的关键控制参数。在本研究中，开发了一种新的随机近似方法并将其应用于一家教学医院的一个科室。使用2000年至2004年的数据来获取必要的概率分布函数。利用从构建的模拟模型生成的数据，得出控制参数与床位容量大小之间的数学关系。然后使用非线性数学模型根据控制参数的目标水平确定所需的最佳床位容量，并进行盈亏分析。
