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A stock-and-flow simulation model of the US blood supply

Authors

  • Arianna Simonetti,

    Corresponding author
    1. Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, Rockville, Maryland
    • Address reprint requests to: Arianna Simonetti, PhD, Risk Assessment, Office of Biostatistics & Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, 1401 Rockville Pike HFM-210 WOC I, Suite 316N, Rockville, MD 20852; e-mail: Arianna.Simonetti@fda.hhs.gov.

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  • Richard A. Forshee,

    1. Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, Rockville, Maryland
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  • Steven A. Anderson,

    1. Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, Rockville, Maryland
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  • Mark Walderhaug

    1. Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, Rockville, Maryland
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  • This research was supported in the form of Grant 224-08-1088 from HHS/BARDA. This project was supported in part by the Research Participation Program at the Center for Biologics Evaluation and Research administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and the US Food and Drug Administration.

Abstract

Background

Lack of reporting requirements for the amount of blood stored in blood banks and hospitals poses challenges to effectively monitor the US blood supply. Effective strategies to minimize collection and donation disruptions in the supply require an understanding of the daily amount of blood available in the system.

Study Design and Methods

A stock-and-flow simulation model of the US blood supply was developed to obtain estimates of the daily on-hand availability of blood, with uncertainty and by ABO/Rh type. The model simulated potential impact on supply of using different blood management practices for transfusion: first in-first out (FIFO), using the oldest stored red blood cell units first; non-FIFO likely oldest, preferentially selecting older blood; and non-FIFO likely newest, preferentially selecting younger blood.

Results

Simulation results showed higher estimates of the steady-state of the blood supply level for FIFO (1,630,000 units, 95% prediction interval [PI] 1,610,000-1,650,000) than non-FIFO scenarios (likely oldest, 1,530,000 units, 95% PI 1,500,000-1,550,000; and likely newest, 1,190,000 units, 95% PI 1,160,000-1,220,000), either for overall blood or by blood types.

Conclusion

To our knowledge, this model represents a first attempt to evaluate the impact of different blood management practices on daily availability and distribution of blood in the US blood supply. The average storage time before blood is being issued was influenced by blood management practices, for preferences of blood that is younger and also that use specific blood types. The model also suggests which practice could best approximate the current blood management system and may serve as useful tool for blood management.

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