Advertisement

Modelling the Need for New Blood Donors Following a Change in Deferral Period

  • John T. BlakeEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 280)

Abstract

Blood donation is considered a safe procedure. Injuries are not common during blood donation and are most frequently fainting or minor bruising. Blood donation does, however, lower iron stores. Recently, Canadian Blood Services announced plans to increase the deferral period for females from 56 to 84 days between consecutive donations to avoid the risk of anemia. The change will reduce the number of collections that can be obtained from women. Lost donations have both a permanent component in terms of fewer donations, as well as a transient effect, due to the timing of the last donation by female donors prior to the implementation of the deferral change. In this paper, we present a forecasting model and optimization routine to identify donor requirements following the change in deferral durations. Model results suggest that the deferral change should be phased-in as female donors book new appointments. Phasing in the policy change reduces the need for newly recruited donors by 5–10%. Nevertheless, a substantial recruiting effort will be required for the first five weeks following the deferral change. Results also show that 32,000 to 35,000 additional donations will be required to during that period. These results were subsequently adopted by CBS, as donation targets following the change in deferral policy and the figure of 35,000 additional donations has been widely quoted in the press.

Keywords

Blood collections Donor recruiting Linear programming 

References

  1. 1.
    Eder, A., Hillyer, C., Dy, B., Notari, E., Benjamin, R.: Adverse reactions to allogeneic whole blood donation by 16- and 17-year olds. JAMA 299(19), 2279–2286 (2008)CrossRefGoogle Scholar
  2. 2.
    Goldman, M., Uzicanin, S., Scalia, V., O’Brien, S.: Iron deficiency in Canadian blood donors. Transfusion 54(3 Pt 2), 775–779 (2014)CrossRefGoogle Scholar
  3. 3.
    Blake, J., Shimla, S.: Determining staffing requirements for blood donor clinics: the Canadian Blood Services experience. Transfusion 54(3), 814–820 (2014)CrossRefGoogle Scholar
  4. 4.
    Mansur, A., Vanany, I.A.N.: Challenge and research opportunity in blood supply chain management: A literature review. 154, 1092–1098 (2018)Google Scholar
  5. 5.
    Osorio, A., Brailsford, S., Smith, H.: A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making. Int. J. Prod. Res. 53(24), 7191–7212 (2015)CrossRefGoogle Scholar
  6. 6.
    Pratt, M., Grindon, A.: Computer simulation analysis of blood donor queuing problems. Transfusion 22(3), 234–237 (1982)CrossRefGoogle Scholar
  7. 7.
    Brennan, J., Golden, B., Rappaport, H.: Go with the flow: Improving Red Cross bloodmobiles using simulation analysis. Interfaces 22(5), 1–13 (1992)CrossRefGoogle Scholar
  8. 8.
    Blake, J., Lipton, C., Sangster, S.: An OR based tool to optimize donor flow in blood clinics. In: Xie, X., Lorca, F., Marcon, E., (eds.) Proceedings of the 33rd International Conference on Operational Research Applied to Health Services, Saint-Etienne. pp. 73–88 (2017)Google Scholar
  9. 9.
    Alfonso, E., Xie, X., Augusto, V., Garraud, O.: Modelling and simulation of blood collection systems: improvement of human resources allocation for better cost-effectiveness and reduction of candidate donor abandonment. Vox Sang. 104(3), 225–233 (2013)CrossRefGoogle Scholar
  10. 10.
    van Brummelen, S.: Bloody Fast Blood Collection. University of Twente, Enschede (2017)CrossRefGoogle Scholar
  11. 11.
    Lowalekar, H., Ravichandran, N.: Model for blood collections management. Transfusion 50(12 pt 2):2778–2784CrossRefGoogle Scholar
  12. 12.
    Alfonso, E., Augusto, V., Xie, X.: Mathematical programming models for annual and weekly bloodmobile collection planning. IEEE Trans. Autom. Sci. Eng. 12(1), 96–105 (2015)CrossRefGoogle Scholar
  13. 13.
    Custer, B., Johnson, E., Sullivan, S., Hazlet, T., Ramsey, S., Hirschler, N., Murphy, E., Busch, M.: Quantifying losses to the donated blood supply due to donor deferral and miscollection. Transfusion. 44(10), 1417–1426 (2004)CrossRefGoogle Scholar
  14. 14.
    Madden, E., Murphy, E., Custer, B.: Modeling red cell procurement with both double-red-cell and whole-blood collection and the impact of European travel deferral on units available for transfusion. Transfusion 47(11), 2025–2037 (2007)CrossRefGoogle Scholar
  15. 15.
    Law, A.: Simulation modeling and analysis, 4th edn. McGraw-Hill, New York (2006)Google Scholar
  16. 16.
    Graveland, W.: Canadian Blood Services struggling for donors after new iron guidelines. [Internet]. 2017 [cited 2018 Mar 07]. Available from: www.huffingtonpost.ca/2017/02/09/canadian-blood-services-iron_n_14655624.html
  17. 17.
    Nguyen, D., DeVita, D., Hirshler, N., Murphy, E.: Blood donor satisfaction and intention of future donation. Transfusion 48(4), 742–748 (2008)CrossRefGoogle Scholar
  18. 18.
    Jackson, B.: Canadian CIOs react to Gartner’s digital platform vision. [Internet]. 2016 [cited 2018 April 24]. Available from: https://www.itworldcanada.com/article/canadian-cios-react-to-gartners-digital-platform-vision/387689
  19. 19.
    Canadian Blood Services. Canadian Blood Services launches new tool to engage young donors. [Internet]. 2017 [cited 2018 April 24]. Available from: https://blood.ca/en/media/canadian-blood-services-launches-new-tool-engage-young-donors

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Industrial EngineeringDalhousie UniversityHalifaxCanada
  2. 2.Canadian Blood ServicesCentre for InnovationOttawaCanada

Personalised recommendations