The blood supply chain, from donor to patient: a call for greater understanding leading to more effective strategies for managing the blood supply
Bibliographic record
Abstract
Over the past 2 years, we witnessed massive disruption and displacement of our nation's base of blood donors, resulting in unprecedented fluctuations in blood donations and blood supply. The two major causes of this disruption were the recent FDA extended blood donor restrictions related to variant CJD (vCJD)1 and the blood donor response after the terrorist attacks of September 11. Although it is difficult to quantify the overall impact of the September 11 attacks on the blood supply, few would argue that, despite the overwhelming initial blood donation response and the outpouring of first-time blood donors, the overall impact on blood donations over the year following September 11 has been negative.2 The public reaction to massive outdating of RBCs and general public lack of understanding of the perishable nature of blood led to months of lower than expected blood donations in many parts of the country. For example, New York area blood donations took almost an entire year to return to the levels seen before September 11 and have yet to return to expected levels. Conversely, there have been reports from other parts of the country where September 11 donors have returned to become repeat donors.3,4 As well, many blood collection programs have found that the overall impact of vCJD guidance has been unexpectedly greater than the 5 to 10 percent loss of blood donors predicted by donor surveys done before guidance. In the wake of vCJD guidance implementation, blood donations over the past summer were well below the donations necessary to support growth of the overall blood supply and contributed to serious regional blood shortages. These events also had a disproportionate impact on specific regions of the United States, such as the New York, Washington and other coastal metropolitan areas. Areas that depend heavily on military collections were also hard hit. As such, they not only tested the limits of elasticity of the blood supply (ability to expand to compensate for sudden contraction), but also tested the limits of fluidity of the supply (ability of centers to move products to areas experiencing either disproportionate reduction in supply or extraordinary demand). The events of the past year occurred in the context of steady and perilous narrowing of the margin between blood collections and blood transfusions in the decade preceding 2000.5 This picture raises serious questions about the stability of the “system” of blood donations and supply; our understanding of the complexity and fragility of the supply chain that connects blood donors to patients; and the potential for blood donations and blood supply to adapt under these kinds of challenges. Three reports in the January issue of TRANSFUSION6-8 deal with aspects of donor suitability and donor motivation, both critical determinants in creating our blood supply. One study from Canada concluded that the incremental risk of changing to a 12-month deferral criterion for male sex with males would be very low (although not zero) while the donations would rise by 1.3 percent.6 Another report indicated that whole-blood donor retention and frequency in general are low, that older donors are more loyal than younger donors, that non-Hispanic white people donate far more blood proportionally than other ethnic or racial groups, and that donations from lapsed blood donors are safer than donations from first-time donors.7 The third report indicated a significant positive impact that results from offering credits and health screening as incentives to donate.8 These studies and the Retrovirus Epidemiology Donor Study (REDS) offer unique and important insights into an increasingly complex and difficult responsibility: how to find the numbers of blood donors and donations necessary for our everyday task of fulfiling the demand for transfusion. They point out an increasingly urgent need to have a much more comprehensive and sophisticated understanding of how blood donors are motivated and how best we can maximize the relationship between blood donors and the organizations that collect and manage their gift of life. Increasingly, it seems that altruism, the cornerstone of the all-volunteer blood supply, is not sufficient to acquire and maintain an adequate number of donations. In this issue of TRANSFUSION, Simon9 argues that it might be time to consider paying donors to solve some of the critical type-specific needs for whole blood and platelets. Also, new FDA clarification on blood donor incentives may have changed the set point that determines the difference between paid and nonpaid donors.10 The perception of looser standards may have precipitated an escalation of offerings to (and competition for) blood donors, such as raffles for larger scale prizes and scholarship programs to high schools. What the REDS data suggests, however, is that some personal return to the donor, such as health screening, might help to tighten the individual donor and blood collector relationship and to make it more lasting and worthwhile. Mutual benefit that is more personal than tangible may promote a closer, more meaningful relationship and therefore more frequent donations. The studies indicate that there is a large reserve of blood donors that could be tapped if we only understood how to maintain their interest and commitment. We are beginning to understand how to integrate some personal health benefit into the blood donation experience. The examples cited by Glynn et al.8 and Rzaza and Gilcher,11 such as cholesterol and prostate-specific antigen screening, are good models. Other studies have shown that iron supplementation for female donors with low Hb levels can increase the donation yield from this population.12 What about blood pressure monitoring and referral for control of hypertension where indicated? Are there other disease-screening techniques such as glycohemoglobin or other blood chemistry tests that could serve to motivate people to donate more frequently? At the New York Blood Center, we have initiated genetic screening for hemochromatosis as a way of identifying blood donors who might benefit medically by more frequent donations.13 Finally, there continue to be reports of cardiovascular benefit from blood donations for still to be determined biological reasons.14 Overall, given that people are interested in their health, it appears that blood donation could be a reasonable way to efficiently monitor the health status of donors and in some cases contribute to a healthier life. Whether it is health benefit or some other benefit, we must find new ways to foster closer and more productive bonds with the individuals who donate blood. While learning more of the specifics of donor motivation, it is also critical that we also step back and understand the total landscape of donor awareness, suitability, demographics, and accessibility. All of these factors, and more, contribute to the magnitude of the donor base and should be considered as a whole. The “social science” of blood donation must become much more sophisticated. The conventional assumptions about the blood donor base need evaluation. For example, there is no current estimate of the size of our national blood donor base. Accepted community lore asserts that up to 60 percent of the population is eligible to donate blood, but only 5 percent donate at present.15 This estimate, based on historic US demographics, leaves the impression that there is essentially an unlimited reserve of blood donors and donations to meet our nation's transfusion needs. However, the recent experiences cited earlier suggest that this blood donor reserve is either increasingly difficult to recruit, smaller than we thought, or both. In this issue, Simon9 also speculates that large numbers of actual and potential donors have been lost because of donor center service issues, confusion over regulations and deferrals, and under-investment in donor recruitment due to poor blood center finances. When considering the blood supply we must consider the actual and the potential magnitude of the blood donor base and also the entire blood supply chain in order to get accurate estimates of blood supply potential. This chain begins with donor motivation, donor access, and eligibility. It then proceeds through collections, testing, storage, and distribution, and ultimately results in transfusion of a product into a patient. All links (events) in this chain are definable and have a measurable impact on the total supply. The supply chain is linear and complex and what seems not to be appreciated is the additive impact of the links of the chain on the available donor pool and ultimately on the supply of blood products for transfusion. Laudably motivated by blood safety and efficacy, technology and regulation have taken a measurable toll on this chain and the number of donations contributing to our national blood supply. Each regulatory or technologic link or action applies to one or more points along the chain of blood production. As we conceptualize the supply chain and make assumptions about the donor pool, it is possible that by understanding the impact of each link or action we could more accurately estimate the actual size of the potential donor base, the total impact of processing, storage and distribution, and thus the potential blood supply under various circumstances. Given the persistent and worsening state of blood shortages, it seems prudent to investigate this supply chain in a more comprehensive way in order to estimate the true magnitude of the nation's blood donor pool and thus the upper limit of the US blood supply available for transfusion. Such a study would look at each segment of the supply chain and calculate the amounts removed from the total resulting supply from each intervention: sociologic, regulatory, or technologic. For example, donor deferrals remove a calculable percentage of the eligible donors, depending on the criteria. There are also donors lost because they perceive they fall into ineligible categories and do not present to donate—a more difficult estimate. Other examples include those who are either deferred or whose donations are discarded because they test positive for a viral marker. There are also donors and donations that are lost due to false positives or indeterminate results. Manufacturing into components, data management, and inventory management also take some toll on supply. There are also effects of the technology applied directly to blood products, such as the loss of RBCs produced by WBC filtration,16 and the impact of future pathogen reduction technology.17 The site of transfusion also is an important link in the chain. As products are distributed to hospitals for transfusion, there are losses due to inventory management, transfusion practices, and outdating. Each of these steps has some potential for improvement and increase of overall yield if understood and managed in a more comprehensive manner. The impacts of each link in the supply chain could be quantified, collated, and analyzed via a meta-analysis. The sources of data for such a study are numerous. In addition to published studies, there are many numerous unpublished donor market research studies and operational assessments that have been performed by most of the large blood care organizations. With the cooperation and sharing of information from all interested parties (America's Blood Center members, American Red Cross, AABB, etc.) these data could be aggregated and much could be learned without major investments of new resources. Such a study has recently been proposed at the national level and a diverse group of individuals familiar with various parts of the supply chain and representing all the major blood care organizations have gathered to consider this undertaking. The goals of the study would be to examine all interventions in total to determine an estimate of the true size of the US blood donor base and an estimate of the upper limits of a volunteer blood supply as currently structured in the US, as well as to identify opportunities for better management of donations and supply in order to optimize our total yield. Hence, the background of increasing demand for transfusion versus blood collections plus the tests of the past year on the elasticity and fluidity of the overall supply call for a new and comprehensive understanding of all the events that impact on the blood supply. We will reach this understanding much more quickly and effectively if we act in the aggregate, nonselfishly and with a commitment to finding new and improved ways to manage this precious resource—the gift of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".