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Storing Crossmatched Blood: A Perishable Inventory Model with Prior Allocation

Author

Listed:
  • Raj Jagannathan

    (College of Business Administration, The University of Iowa, Iowa City, Iowa 52242)

  • Tarun Sen

    (The R. B. Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061)

Abstract

The process of testing a sample of a patient's blood against units of blood from inventory to ensure compatibility is called crossmatching. When a physician orders blood, it is crossmatched and then held for a patient. As a precautionary measure, physicians tend to order blood in excess of the amount that is transfused (used by the patient). Consequently, a large proportion of blood held for a patient (often higher than 50 percent) is eventually not transfused. This leads to increased outdates. The effects of crossmatching on outdates are widely acknowledged, but have seldom been included in blood inventory control models. In this paper, we develop a model for determining outdates and shortages for crossmatched blood using generally accepted parameters, such as proportion of crossmatched blood that is actually transfused, and the number of days after which crossmatched blood is released if not transfused. This model can be used as a decision support system that allows the blood bank administrator to do sensitivity analyses related to controllable blood inventory parameters.

Suggested Citation

  • Raj Jagannathan & Tarun Sen, 1991. "Storing Crossmatched Blood: A Perishable Inventory Model with Prior Allocation," Management Science, INFORMS, vol. 37(3), pages 251-266, March.
    • Handle: RePEc:inm:ormnsc:v:37:y:1991:i:3:p:251-266
    DOI: 10.1287/mnsc.37.3.251
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    Citations

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    Cited by:

    1. Duan, Qinglin & Liao, T. Warren, 2014. "Optimization of blood supply chain with shortened shelf lives and ABO compatibility," International Journal of Production Economics, Elsevier, vol. 153(C), pages 113-129.
    2. Ramezanian, Reza & Behboodi, Zahra, 2017. "Blood supply chain network design under uncertainties in supply and demand considering social aspects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 69-82.
    3. 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.
    4. Osorio, Andres F. & Brailsford, Sally C. & Smith, Honora K., 2018. "Whole blood or apheresis donations? A multi-objective stochastic optimization approach," European Journal of Operational Research, Elsevier, vol. 266(1), pages 193-204.
    5. 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.
    6. 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.
    7. K Katsaliaki & S C Brailsford, 2007. "Using simulation to improve the blood supply chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 219-227, February.

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