Designing the blood supply chain: how much, how and where?. Issue 8 (4th September 2018)

• Record Type: Journal Article
• Authors: Osorio, Andres F.; Brailsford, Sally C.; Smith, Honora K.; Blake, John
• Is Part Of: Vox sanguinis. Volume 113:Issue 8(2018)
• Page Start: 760
• Page End: 769
• Publication Date: 2018-09-04
• Subjects: blood supply chain -- network design -- optimization; Blood -- Periodicals; Blood -- Transfusion -- Periodicals; Immunohematology -- Periodicals; Immunopathology -- Periodicals; 615.39
• DOI: 10.1111/vox.12706
• Languages: English
• ISSNs: 0042-9007

Abstract

Abstract : Background: The topology of the blood supply chain network can take different forms in different settings, depending on geography, politics, costs, etc. Many developed countries are moving towards centralized networks. The goal for all blood distribution networks, regardless of topology, remains the same: to satisfy demand at minimal cost and minimal wastage. Study Design and Methods: Mathematically, the blood supply system design can be viewed as a location‐allocation problem, where the aim is to find the optimal location of collection and production facilities and to assign hospitals to them to minimize total system cost. However, most location‐allocation models in the blood supply chain literature omit several important aspects of the problem, such as selecting amongst differing methods of collection and production. In this paper, we present a location‐allocation model that takes these factors into account to support strategic decision‐making at different levels of centralization. Results: Our approach is illustrated by a case study (Colombia) to redesign the national blood supply chain under a range of realistic travel time limitations. For each scenario, an optimal supply chain configuration is obtained, together with optimal collection and production strategies. We show that the total costs for the most centralized scenario are around 40% of the costs for the least centralized scenario. Conclusion: Centralized systems are more efficient than decentralized systems. However, the latter may be preferred for political or geographical reasons. Our model allows decision‐makers to redesign the supply network per local circumstances and determine optimal collection and production strategies that minimize total costs.