Voluntary Priority Program for Older Kidneys Could Add 900 Transplants a Year

More than 100,000 people currently sit on the national transplant waiting list in the United States, waiting an average of five years for a kidney that may arrive too late. At the same time, thousands of donated kidneys are discarded every year, often simply because they come from older donors and are expected to provide fewer remaining years of function. A study led by researchers at Virginia Tech suggests that a carefully engineered redesign of how these organs are matched could recover a substantial share of that lost supply, projecting more than 900 additional kidney transplants each year and the prevention of more than 190 deaths annually. The findings, published in the journal Management Science, combine rigorous mathematical modeling of patient behavior with a machine-learning-driven simulation of the entire U.S. kidney allocation system.

The proposed intervention is known as a targeted priority mechanism, and its intellectual ancestor already operates in Europe. The Eurotransplant Senior Program demonstrated that kidneys from older donors, which younger recipients and transplant centers often decline, can produce excellent outcomes when directed to older recipients whose expected remaining lifespan better matches the organ’s expected functional years. The American version studied by the Virginia Tech team would be voluntary rather than mandatory. Waitlisted candidates aged 65 or older could choose to enroll, agreeing in advance to accept so-called marginal kidneys, such as those from older adults, in exchange for priority. Enrollment moves a patient to the front of the queue for that specific pool of harder-to-place organs, while the patient gives up access to kidneys outside the group. The trade is explicit, transparent, and entirely in the hands of the patient.

Sait Tunc, assistant professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech, who led the multi-institutional research team, emphasized that the mechanism works through incentives rather than coercion. According to Tunc, the design encourages more efficient matching without forcing patients to accept organ offers or requiring a complete overhaul of the existing allocation infrastructure. In his characterization, the program benefits not only those who enroll but also younger patients who remain outside it, because higher-quality organs can then be better matched to the recipients with the greatest post-transplant life expectancy. He described the outcome as close to a win-win situation, a rare property in allocation problems where prioritizing one group typically comes at another group’s expense.

The scale of inefficiency in the current system is striking. Roughly 20 percent of donated kidneys never find a recipient at all. The mismatch arises at several points in the pipeline: organs are paired poorly with patients, transplant centers decline offers that could have been used, and individual providers apply acceptance heuristics shaped by their own clinical experience, including assumptions and biases that may or may not reflect the underlying data. Matthew J. Ellis, medical director of the Kidney and Pancreas Transplant Programs at Duke University School of Medicine and a co-author of the study, explained that providers making acceptance decisions often rely on rules of thumb grounded partly in concrete evidence and partly in institution-specific judgment. The consequence, he noted, is that many usable kidneys are never transplanted, deepening the supply-and-demand misalignment that defines American organ transplantation.

Why does this misalignment happen in the first place? A donated kidney is not a standardized commodity. Its expected years of remaining function vary with donor age, medical history, and retrieval circumstances, and the value of any given kidney depends critically on who receives it. A kidney projected to function for ten years offers modest benefit to an 80-year-old candidate but potentially decades of dialysis-free life to a 40-year-old. Conversely, a kidney projected to function for seven years may be entirely adequate for an older recipient who would otherwise spend those years on dialysis, where five-year survival remains dramatically worse than after transplantation. When allocation ignores these complementarities, the result is a double failure: marginal kidneys are declined for younger patients and never rerouted to older ones, while younger patients wait longer for organs whose longevity they cannot fully exploit.

The technical core of the new study is a hybrid modeling framework. The researchers first built mathematical descriptions of patient choices, capturing how waitlisted candidates weigh the trade-off between waiting time and organ quality when deciding whether to enroll in a priority program. These choice models were then embedded in a sophisticated computer simulation of the U.S. kidney allocation system, trained with machine learning and predictive models on historical transplantation data. The simulation does not merely track organs through queues; it predicts how offer acceptance behavior and program participation would shift under the new rules, allowing the team to test policy variants before any real-world pilot. By iterating over enrollment scenarios and priority structures, the researchers could estimate equilibrium outcomes, in which patients’ enrollment decisions and centers’ acceptance behavior settle into a stable pattern that the simple static projections of earlier studies could not capture.

The projected impact on individual patients is dramatic. Under the simulated program, older participants who currently face a multiyear wait could receive a transplant within a few months or less. Earlier transplantation matters because time on dialysis is itself a health hazard: each additional waiting year is associated with accumulating frailty, cardiovascular damage, and reduced post-transplant survival. Moving elderly candidates off dialysis faster, even with organs of moderate expected longevity, compounds into a meaningful mortality reduction at the population level, which is how the team arrived at its estimate of more than 190 deaths prevented annually. Just as importantly, the simulation showed no detectable harm to non-participants. Because enrolled older patients absorb the marginal organs that would otherwise be discarded, kidneys with longer expected function become available to younger and healthier candidates, improving their match quality as well.

This result challenges a long-standing intuition in organ policy, namely that priority for one group must necessarily disadvantage others. When the scarce resources in question are heterogeneous and preferences are correlated with recipient characteristics, properly designed priority rules can reallocate organs toward the recipients who value them most, expanding the effective supply rather than merely redistributing it. The flexibility of the mechanism is central to this outcome. Unlike top-down mandates, which transplant centers might resist or game, the voluntary structure lets patients self-select based on their own risk tolerance and life circumstances, and lets the program rules be tuned so that the incentive gradient, the reward for accepting a marginal kidney, is strong enough to shift behavior without distorting clinical judgment.

The research was supported by Tunc’s 2024 National Science Foundation CAREER Award, one of the foundation’s most competitive grants for early-career faculty. Beyond Tunc, the author team spans industrial engineering, clinical transplant medicine, and operations management: Ruochen Wang, a former Virginia Tech doctoral student now a postdoctoral fellow at the Queen’s University Smith School of Business; Matthew J. Ellis of Duke; Bekir Tanriover, chief of the Division of Nephrology and professor of medicine at the University of Arizona College of Medicine in Tucson; and Burhan Sandikci, dean and professor in the Faculty of Management at Istanbul Technical University. That composition reflects the study’s dual identity as an operations research contribution and a clinically grounded policy proposal, a balance the authors regard as essential for moving from simulation to implementation.

The team is candid that publication in Management Science is a beginning rather than an endpoint. Tunc noted that the article serves to bring discussions into the community and establish that the work is theoretically rigorous, but that the next step is to carry it to the transplant community itself. A second phase of the research will focus on initial policy conversations with transplant professionals and on practical program designs that clinicians and patients can evaluate in concrete terms. The ultimate pathway to clinical practice runs through clinically oriented journals and working groups within the United Network for Organ Sharing, the nonprofit organization that administers the U.S. organ transplantation system. If those discussions succeed, the study’s central promise, that hundreds of discarded kidneys and hundreds of lives could be reclaimed each year through smarter incentives rather than new supply, may move from simulation to surgical suites within the decade.

Subject of Research: Kidney transplant allocation redesign using a voluntary targeted priority mechanism for older donor organs and recipients

Article Title: A new approach to kidney matching could save lives

Article References: A new approach to kidney matching could save lives. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: kidney transplantation, organ allocation, targeted priority mechanism, Eurotransplant Senior Program, Management Science, Virginia Tech, machine learning simulation, donor organ shortage, transplant waiting list, older donor kidneys, health policy, operations research