Abstract
In a hospital, operating rooms produces a large part of the costs, on the one hand, and a large part of the income, on the other hand. One of the most impressive ways to increase the operating rooms efficiency is using effective ways for programming and scheduling. While this department has a close relation with other departments in the hospital, improving its efficiency will raise patients satisfaction and the whole hospital efficiency and performance. In this paper, a stochastic integer programming model has been developed for operating rooms programming and scheduling, with the aim of minimizing the cost of underutilization and overcapacity in downstream units, including intensive care unit and wards. The model aims to provide a cyclic master surgery scheduling at the tactical level based on hospital strategic decisions. First, it allocates blocks to specialties based on block scheduling strategy, and secondly determines each surgeon’s surgery schedule. In addition, to improve the efficiency and reduce the complexity of the model for the large scale cases, the convolution stochastic distribution parts of the model have been exchanged with the expected values and variances of the capacities needed for different days of the week in a corresponding integer goal programming model. Then, different case studies have been generated by changing some of the parameters to show the objective function sensitivity to the changes. Innovation of this research compared to the previous studies is providing the schedules for the surgeons rather than the specialties. This saves time, expenses, and computational operations. Also, positive half variance of the number of patients in downstream units in each day of the week has been used directly rather than the variance of the number of patients in these units.
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