Optimal admission control under premature discharge decisions for operational effectiveness

Yang, Feifei; Jiang, Yan-Ping; Tang, Zhenpeng

doi:10.1111/itor.13113

Cited by 3 publications

(2 citation statements)

References 46 publications

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“…The myopic policy reflects the status quo and applies in practice. It has been discussed in several papers, such as Yang et al (2023), Samiedaluie et al (2017), andChan et al (2012). Although the myopic policies are easy to implement, they have harmful effects in case of capacity shortages.…”

Section: Performance Evaluation Of Optimal Admission and Queuing Cont...mentioning

confidence: 99%

“…To make additional space for ED admissions, the inpatient nurse managers and physicians may prematurely discharge patients whose health conditions are relatively stable (either to home or to an appropriate lower-level care provider, such as a skilled nursing facility) to obtain additional space for high-acuity ED patients (Chan et al, 2012;Li et al, 2019;Bai et al, 2021). Such a transfer policy to improve bed utility can effectively improve ED indicators and positively impact patients' health (Lange et al, 2018;Yang et al, 2023). Admittedly, it is interesting and challenging to find a suitable balance among reserving the bed, admitting the waiting patients, and prematurely discharging.…”

Section: Introductionmentioning

confidence: 99%

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Optimal admission and queuing control with reneging behavior under premature discharge decisions

Yang

Zhang

et al. 2023

Int Trans Operational Res

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Queues or waiting lines are a common phenomenon in healthcare facilities. The increasing number of admissions to hospital emergency departments (EDs) has resulted in overcrowded EDs and decreased quality of care. Patients may renege with dissatisfaction while waiting, prolonged hospital stays, or the cancelation of surgeries, especially for those with acute diseases. This paper studies patient admission and queuing control policies, considering premature discharge decisions and reneging behavior. First, we formulate this problem as an infinite‐horizon total discounted cost Markov decision process to balance bed utility and experiences of patients waiting for admission to minimize the total expected cost for the hospital. Then, we characterize an optimal admission threshold policy by analyzing the structural properties of the optimal value function. Numerical experiments are employed to discuss how the optimal dynamic policy depends on some key parameters of the system. Finally, the performance of the optimal policy is discussed through comparison with the benchmark: A myopic rule (first come, first served) mimicking the decision‐making in practice under different scenarios. The numerical results show that the reneging behavior can affect the superiority of the optimal policy compared to the benchmark, and the optimal policy can significantly reduce the number of waiting patients without increasing the total expected cost when the system is overloaded.

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Section: Performance Evaluation Of Optimal Admission and Queuing Cont...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal admission and queuing control with reneging behavior under premature discharge decisions

Yang

Zhang

et al. 2023

Int Trans Operational Res

Self Cite

View full text Add to dashboard Cite

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Inventory rationing, admission control, and production capacity allocation in a make‐to‐stock/make‐to‐order manufacturing system

Kim

2024

Int Trans Operational Res

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This paper considers a manufacturing system in which products are produced in both make‐to‐stock (MTS) and make‐to‐order (MTO) modes. Production of MTS and MTO products is done in batches, incurs a setup cost, and is non‐preemptive. The inventory of MTS products fulfills the demand of multiple classes, and each class demand can be satisfied or rejected. Customer orders for MTO production can be accepted or rejected, and their size is the same as the production batch. The primary goal of this paper is to study a policy that coordinates inventory rationing, admission control, and production capacity allocation to maximize the system's profit. We formulate the problem as a Markov decision process model and identify the structure of optimal control policies. We investigate the effect of inventory rationing on the profit by comparing its performance to that of the system with a first‐come‐ first‐serve policy to allocate inventory to multiple demand classes and study the extent to which the benefit of inventory rationing can be affected by system parameter changes. We also propose a heuristic that manages control decisions from linear threshold functions. Our test results from numerical examples show that the average percentage difference between the optimal and heuristic policies is within 1.2%.

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Optimal Decision of Dynamic Bed Allocation and Patient Admission with Buffer Wards during an Epidemic

Wang

Yang

2023

Mathematics

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To effectively prevent patients from nosocomial cross-infection and secondary infections, buffer wards for screening infectious patients who cannot be detected due to the incubation period are established in public hospitals in addition to isolation wards and general wards. In this paper, we consider two control mechanisms for three types of wards and patients: one is the dynamic bed allocation to balance the resource utilization among isolation, buffer, and general wards; the other is to effectively control the admission of arriving patients according to the evolution process of the epidemic to reduce mortality for COVID-19, emergency, and elective patients. Taking the COVID-19 pandemic as an example, we first develop a mixed-integer programming (MIP) model to study the joint optimization problem for dynamic bed allocation and patient admission control. Then, we propose a biogeography-based optimization for dynamic bed and patient admission (BBO-DBPA) algorithm to obtain the optimal decision scheme. Furthermore, some numerical experiments are presented to discuss the optimal decision scheme and provide some sensitivity analysis. Finally, the performance of the proposed optimal policy is discussed in comparison with the other different benchmark policies. The results show that adopting the dynamic bed allocation and admission control policy could significantly reduce the total operating cost during an epidemic. The findings can give some decision support for hospital managers in avoiding nosocomial cross-infection, improving bed utilization, and overall patient survival during an epidemic.

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Optimal admission control under premature discharge decisions for operational effectiveness

Cited by 3 publications

References 46 publications

Optimal admission and queuing control with reneging behavior under premature discharge decisions

Optimal admission and queuing control with reneging behavior under premature discharge decisions

Inventory rationing, admission control, and production capacity allocation in a make‐to‐stock/make‐to‐order manufacturing system

Optimal Decision of Dynamic Bed Allocation and Patient Admission with Buffer Wards during an Epidemic

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