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Li N, Zeller MP, Shih AW, Heddle NM, St John M, Bégin P, Callum J, Arnold DM, Akbari-Moghaddam M, Down DG, Jamula E, Devine DV, Tinmouth A. A data-informed system to manage scarce blood product allocation in a randomized controlled trial of convalescent plasma. Transfusion 2022; 62:2525-2538. [PMID: 36285763 DOI: 10.1111/trf.17151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/19/2022] [Accepted: 09/26/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Equitable allocation of scarce blood products needed for a randomized controlled trial (RCT) is a complex decision-making process within the blood supply chain. Strategies to improve resource allocation in this setting are lacking. METHODS We designed a custom-made, computerized system to manage the inventory and allocation of COVID-19 convalescent plasma (CCP) in a multi-site RCT, CONCOR-1. A hub-and-spoke distribution model enabled real-time inventory monitoring and assignment for randomization. A live CCP inventory system using REDCap was programmed for spoke sites to reserve, assign, and order CCP from hospital hubs. A data-driven mixed-integer programming model with supply and demand forecasting was developed to guide the equitable allocation of CCP at hubs across Canada (excluding Québec). RESULTS 18/38 hospital study sites were hubs with a median of 2 spoke sites per hub. A total of 394.5 500-ml doses of CCP were distributed; 349.5 (88.6%) doses were transfused; 9.5 (2.4%) were wasted due to mechanical damage sustained to the blood bags; 35.5 (9.0%) were unused at the end of the trial. Due to supply shortages, 53/394.5 (13.4%) doses were imported from Héma-Québec to Canadian Blood Services (CBS), and 125 (31.7%) were transferred between CBS regional distribution centers to meet demand. 137/349.5 (39.2%) and 212.5 (60.8%) doses were transfused at hubs and spoke sites, respectively. The mean percentages of total unmet demand were similar across the hubs, indicating equitable allocation, using our model. CONCLUSION Computerized tools can provide efficient and immediate solutions for equitable allocation decisions of scarce blood products in RCTs.
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Affiliation(s)
- Na Li
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.,McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Department of Computing and Software, McMaster University, Hamilton, Ontario, Canada
| | - Michelle P Zeller
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.,Canadian Blood Services, Ottawa, Ontario, Canada
| | - Andrew W Shih
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology and Laboratory Medicine, Vancouver Coastal Health Authority, Vancouver, British Columbia, Canada.,Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nancy M Heddle
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Canadian Blood Services, Ottawa, Ontario, Canada
| | - Melanie St John
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Philippe Bégin
- Section of Allergy, Immunology and Rheumatology, Department of Pediatrics, CHU Sainte-Justine, Montréal, Québec, Canada.,Department of Medicine, Centre Hospitalier de l'Université de Montréal, Montréal, Québec, Canada
| | - Jeannie Callum
- Department of Pathology and Molecular Medicine, Kingston Health Sciences Centre and Queen's University, Kingston, Ontario, Canada.,Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Donald M Arnold
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.,Canadian Blood Services, Ottawa, Ontario, Canada
| | - Maryam Akbari-Moghaddam
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Douglas G Down
- Department of Computing and Software, McMaster University, Hamilton, Ontario, Canada
| | - Erin Jamula
- McMaster Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Dana V Devine
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Canadian Blood Services, Vancouver, British Columbia, Canada
| | - Alan Tinmouth
- Canadian Blood Services, Ottawa, Ontario, Canada.,Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
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