Study on the centralization strategy of the blood allocation among different departments within a hospital

Duan, Jingnan; Su, Qiang; Yu, Zhu; Lu, Yanxia

doi:10.1109/icsssm.2017.7996266

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…The same probability distribution is assumed to model demand and supply in Duan et al. (2018), who define an optimal inventory setting within different departments in a hospital. Under the same assumption regarding the demand, Najafi et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, Haijema et al (2007) and Van Dijk et al (2009) apply dynamic techniques to determine an optimum ordering policy for platelet with a Poisson distribution. The same probability distribution is assumed to model demand and supply in Duan et al (2018), who define an optimal inventory setting within different departments in a hospital. Under the same assumption regarding the demand, Najafi et al (2017) formulate a multi-objective integer programming model to manage inventory in HBB.…”

Section: Literature Reviewmentioning

confidence: 99%

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Blood inventory management: Ordering policies for hospital blood banks under uncertainty

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Barbosa‐Póvoa

2021

Int Trans Operational Res

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The blood supply chain faces several challenges, such as stochastic demand and supply, the relation between the various stages of the chain, and the intrinsic nature of the product. Blood is a perishable, scarce, and (in most cases) voluntarily supplied product used to perform vital transfusions in patients which increases the pressure of managing its supply chain as efficiently and effectively as possible. For these reasons, it is crucial to have optimized inventory management that allows the availability of the right type of blood product, in the right place, at the right time, and in the right amount while avoiding wastage, especially in hospital blood banks that are the direct link to patients. This work aims to address these challenges with a new twostage stochastic programming model for defining optimal ordering policies for blood products, considering demand uncertainty. This model minimizes wastage, shortages, and total costs related to blood inventory management, including ABO-substitutions. The model supports hospitals' tactical-operational decisions of when and how much blood products to order. A case study of a Portuguese hospital is used to validate and show the applicability of the model. By comparing several ordering policies, we show that it is possible to contemplate the decision maker's goals whilst obtaining substantial reductions in terms of wastage and costs. These results allow the definition of an important set of managerial insights.

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Section: Literature Reviewmentioning

confidence: 99%