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Cost-effective practices in the blood service sector

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  • Katsaliaki, Korina

Abstract

Objectives The objective of this study is to recommend alternative policies, which are tested on a computer simulation model, towards a more cost-effective management of the blood supply chain in the UK.Methods With the use of primary and secondary data from the National Blood Service (NBS) and the supplied hospitals, statistical analysis is conducted and a detailed discrete event simulation model of a vertical part of the UK supply chain of blood products is developed to test and identify good ordering, inventory and distribution practices.Results Fewer outdates, group substitutions, shortages and deliveries could be achieved by blood banks: holding stock of rare blood groups of red blood cells (RBC), having a second routine delivery per weekday, exercising a more insensitive ordering point for RBC, reducing the total crossmatch release period to less than 1.5 days, increasing the transfusion-to-crossmatch ratio to 70%, adhering to an age-based issuing of orders, holding RBC stock of a weighted average of approximately 4 days.Conclusions The blood supply simulation model can offer useful pieces of advice to the stakeholders of the examined system which leads to cost reductions and increased safety. Moreover, it provides a great range of experimental capabilities in a risk-free environment.

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  • Katsaliaki, Korina, 2008. "Cost-effective practices in the blood service sector," Health Policy, Elsevier, vol. 86(2-3), pages 276-287, May.
    • Handle: RePEc:eee:hepoli:v:86:y:2008:i:2-3:p:276-287
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    2. Puranam, Kartikeya & Novak, David C. & Lucas, Marilyn T. & Fung, Mark, 2017. "Managing blood inventory with multiple independent sources of supply," European Journal of Operational Research, Elsevier, vol. 259(2), pages 500-511.
    3. Liu, Wenqian & Ke, Ginger Y. & Chen, Jian & Zhang, Lianmin, 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    4. Gunpinar, Serkan & Centeno, Grisselle, 2016. "An integer programming approach to the bloodmobile routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 94-115.
    5. Gilani Larimi, Niloofar & Azhdari, Abolghasem & Ghousi, Rouzbeh & Du, Bo, 2022. "Integrating GIS in reorganizing blood supply network in a robust-stochastic approach by combating disruption damages," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    6. Tirkolaee, Erfan Babaee & Golpîra, Hêriş & Javanmardan, Ahvan & Maihami, Reza, 2023. "A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    7. Beliën, Jeroen & Forcé, Hein, 2012. "Supply chain management of blood products: A literature review," European Journal of Operational Research, Elsevier, vol. 217(1), pages 1-16.

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