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• W4205161874 abstract "Abstract The shortage of inpatient beds causes surgery cancellations, treatment delays, and inappropriate ward arrangements. That is why studying how to make admission decisions on the wards of crowded units under premature discharge decisions is essential. In this study, we set up an infinite‐horizon total discounted cost Markov decision process model to minimize the total expected cost to the hospital. By analyzing the structural properties of the optimal value function, we find that there is an optimal admission control policy of the threshold type for low‐acuity emergency patients (type‐2). Numerical experiments are done to examine how optimal dynamic policy depends on key system parameters. Furthermore, we evaluate the performance of the optimal dynamic policy with a benchmark policy without premature discharge decisions. The results indicate that the optimal admission control policy helps hospitals in maintaining low costs and enables patients with high‐acuity diseases to enter primary wards more quickly." @default.
• W4205161874 created "2022-01-26" @default.
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• W4205161874 date "2022-01-11" @default.
• W4205161874 modified "2023-09-26" @default.
• W4205161874 title "Optimal admission control under premature discharge decisions for operational effectiveness" @default.
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• W4205161874 doi "https://doi.org/10.1111/itor.13113" @default.
• W4205161874 hasPublicationYear "2022" @default.
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