Due to the scarcity and perishable nature of blood products, collecting blood in an effective and efficient way is critical. Indeed, the margin between blood needs and transfusable blood component collection has been critically low, and blood shortages have received extensive media attention. Despite the national awareness campaigns and intense media coverage, less than 5% of U.S. citizens who are eligible to donate blood are actually blood donors. Furthermore, the increase in demand outpaces the increase in donations, with donations increasing annually by about 3% while demand growing by 6%.
Blood collection operations are complex processes. Donors provide blood either through automated blood collection (apheresis) or through regular whole blood (WB) donation, with the latter being significantly more common. Once collected, WB can be separated into different components, such as red blood cells, platelets, plasma, and cryoprecipitate.
Among different blood products, the collection for cryoprecipitate (or "cryo'' for short) is most challenging. In particular, to produce cryo, plasma needs to be first separated from red blood cells and then frozen into fresh frozen plasma (FFP). Finally, to acquire cryo, the FFP should be centrifuged and the precipitate should be collected. The collection for cryo is particularly challenging because to be able to produce cryo, the plasma needs to be frozen within 8 hours of collection, while for all other blood products, the time constraint between collection and processing is at least 24 hours. This tight collection-to-processing time constraint for cryo complicates blood collection and production planning and poses managerial challenges and practical ramifications. For example, in order ensure that the 8-hour constraint is satisfied, extra courier services are usually needed for the collected WB to be shipped back to the production facility in time, which makes the collection for cryo more complicated and expensive than other blood products.
Optimizing Cryo Collection Operations
In this study, we describe and analyze a regional level cryo collection problem motivated by our collaboration with the American Red Cross (ARC) Douglasville manufacturing facility, the largest ARC blood manufacturing facility in the US, which serves the ARC Southern Region and covers more than 120 hospitals. More specifically, the problem is to determine when and from which mobile collection sites to collect blood for cryo production, such that collection targets are met and total collection costs are minimized. Regional level cryo collection planning is important and challenging because: i) cryo is made from a significant proportion (approximately 20%) of the blood collected by the ARC; ii) as discussed above, if the blood collected is to be processed into cryo units, it has to be processed within 8 hours after collection, which imposes perishability-related challenges and makes the collection for cryo more expensive than that for other blood products. Furthermore, cryo collection faces other challenges that are common among all other blood products, including i) the collection quantities are uncertain due to no shows, random walk-ins, and random yields in production; and ii) collection schedules need to be made in advance and may be dynamically adjusted depending on the realizations of uncertainties.
The majority of the blood units are collected at mobile collection sites via blood drives at the ARC. In previous practice of the ARC, each collection site was designated as either purely a cryo site or purely a non-cryo site. That is, the type of collection at each site was the same (either cryo or non-cryo) during the entire day. We call this collection model the non-split model, and introduce an alternative model, which suggests splitting the collection window into two intervals and allows collecting blood for cryo either in both intervals or only in the second interval. We call this alternative model the split model. In the split model, instead of designating a collection site as purely a cryo or a non-cryo site, the collection window of each site is split into two intervals, and blood can be collected for either cryo or non-cryo in each of these two intervals. This way, blood can be collected for non-cryo products in the first interval and for cryo in the second interval. Since the split model allows for collecting cryo only during the second interval, some cryo units can be collected without incurring mid-day pickup cost.
Comparison of non-split and split models in an example with 6 blood collection sites.
To formally analyze the value of the split model and to optimize the collection schedules, we formulate a mathematical model for the cryo collection problem, analyze this model structurally, and present a near-optimal solution algorithm. Using real data from the ARC, we show that our proposed collection model and the near-optimal collection schedules can significantly reduce the total collection costs. The size of the estimated cost reduction was deemed very significant by the ARC management team and led to a change in collection operations.
Implementation and Organizational Benefits
To facilitate the implementation of the split collection model and to systematize the cryo collection decision making process, we developed a Microsoft Excel spreadsheet-based decision support tool (DST) using Visual Basic for Applications (VBA) that is currently implemented at the Red Cross. The implementation of the split collection model and the DST has led to several organizational benefits to the American Red Cross. First, the use of the DST led to more constantly meeting the cryo collection targets. In particular, in the Douglasville facility that serves the Red Cross Southern Region, there used to be inconsistent supply of WB units that were eligible for cryo production, and only in about 50% of the time, this facility was able to meet the weekly collection target. After the implementation of the DST, the Douglasville facility was able to hit the collection target 87% of the time, and on those few weeks that the target was missed, the gap has been very small.
Second, the Red Cross has improved cost effectiveness and efficiency of its cryo collection operations, resulting in a significant cost avoidance. At the time of the implementation, the demand for cryo units has increased compared with the pre-implementation stage. During this period, the Red Cross Douglasville facility was able to collect and process about 1000 more units of cryo per month than the pre-implementation stage, and they were able to collect this increased quantity at a slightly lower collection cost, which together led to approximately a 40% reduction in the cost per unit of cryo collected, where a significantly proportion of the cost avoidance came from the switch from a non-split model to a split model.
Finally, due to the successful implementation at the Douglasville facility, the DST has been also rolled out and implemented at the Red Cross St. Louis manufacturing facility which serves the Missouri-Illinois Region. Further, this project has been recently presented at a national Red Cross Conference by the Red Cross co-authors, and plans are in place for rolling out the DST at the 10 remaining Red Cross cryo production facilities in the near future.
Reference
Ayer T, Zhang C, Zeng C, White III CC, Joseph VR (2018) Analysis and improvement of blood collection operations. Manufacturing & Service Operations Management 21(1):29-46. https://doi.org/10.1287/msom.2017.0693
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