Platelet pool inventory management: theory meets practice

Transfusion. 2011 Nov;51(11):2295-303. doi: 10.1111/j.1537-2995.2011.03190.x. Epub 2011 May 26.

Abstract

Background: The shelf life of platelet concentrates (PCs) is a matter of days. Simultaneously, the demand is highly variable, shortages are not allowed, and producing too many results in outdating. Concurrently, younger PCs, implying an extended time till outdating (TTO), are preferred. Common PC inventory management relies on experience-based order-up-to rules. This study aimed at minimizing outdating and shortages, while extending the TTO through a theoretical approach. It focuses on PCs processed from whole blood donations.

Study design and methods: A combined approach of stochastic dynamic programming and simulation techniques (SDP/S), from the mathematical discipline operations research, has been implemented. This approach included the design of the dedicated software tool thrombocyte inventory management optimizer (TIMO). Based on the 2007 data, an optimal order-up-to rule was calculated. Outdating percentages and TTOs have been collected from August 2005 to July 2010. The resulting order-up-to rule has been applied and adjusted from summer 2007 onward.

Results: Over the study period, the results of the practical implementation showed significant improvements. The median weekly outdating percentage dropped to less than 1% and a gain in TTO of 0.48 day was reached. The results and the additional computer simulations brought confidence to the personnel to apply and adopt the "theoretical" approach and TIMO.

Conclusion: Applying theory may help a blood bank to improve its PC inventory management and may help to identify to what extent practical limits can approach theoretical limits. The application of the theory has led to both a significant improvement and a more structured and less panic-driven PC inventory management.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Banks
  • Blood Platelets*
  • Blood Preservation*
  • Humans
  • Models, Theoretical
  • Stochastic Processes