Analysis and Improvement of Blood Collection Operations

Manufacturing & Service Operations Management, Forthcoming

33 Pages Posted: 10 Oct 2017

See all articles by Turgay Ayer

Turgay Ayer

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Can Zhang

Duke University - Fuqua School of Business

Chenxi Zeng

Georgia Institute of Technology

Chelsea C White

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

V. Roshan Joseph

Georgia Institute of Technology

Date Written: October 9, 2017

Abstract

Due to the importance, limited supply and perishable nature of blood products, effective management of blood collection is critical for high quality healthcare delivery. In this paper, working closely with the American Red Cross (ARC), we study a blood collection problem focusing on whole blood that is to be processed into cryoprecipitate (cryo), a critical blood product for controlling massive hemorrhaging. In particular, we aim to determine when and from which mobile collection sites to collect blood for cryo production, such that the weekly collection target is met while the collection costs are minimized. The cryo collection problem imposes a unique challenge: if blood collected is to be processed into cryo units, it has to be processed within 8 hours after collection, while this time limit is 24 hours for most other blood products.

To analyze the cryo collection problem, we first develop a mathematical program to represent and compare two different blood collection business models, namely the status quo non-split model and an alternative model we propose, which splits each collection window into two intervals and allows different types of collections in the two intervals. Then, we establish several structural properties of the proposed mathematical program and develop a near-optimal solution algorithm to determine the cryo collection schedules under each collection model. Our extensive computational analyses based on real data indicated that, compared with the status quo, our proposed collection model can significantly reduce total collection costs. Based on this significant potential impact, our proposed collection model has been implemented by the ARC Douglasville manufacturing facility, the largest ARC blood manufacturing facility supplying blood to about 120 hospitals in the Southern US. Field data from post-implementation indicated that our proposed solution has resulted in i) reducing inconsistencies in supply of cryo collections, and ii) an approximately 40 percent reduction in the per unit collection cost for cryo. Due to this success, the ARC is now at the stage of rolling out our proposed solution approach to other regions in the nation.

Suggested Citation

Ayer, Turgay and Zhang, Can and Zeng, Chenxi and White, Chelsea C and Joseph, V. Roshan, Analysis and Improvement of Blood Collection Operations (October 9, 2017). Manufacturing & Service Operations Management, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3050171

Turgay Ayer (Contact Author)

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

Can Zhang

Duke University - Fuqua School of Business ( email )

100 Fuqua Dr
Durham, NC North Carolina 27708
United States

Chenxi Zeng

Georgia Institute of Technology ( email )

Atlanta, GA 30332
United States

Chelsea C White

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

V. Roshan Joseph

Georgia Institute of Technology ( email )

Atlanta, GA 30332
United States

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