Abstract
PurposeThis study examines how medical quality indicators and transportation/logistics conditions jointly affect the probability of deceased-donor kidney discard. While previous research has focused on clinical factors, this research quantifies the added impact of distance, airport accessibility and temporal coordination on discard decisions.Design/methodology/approachWe analyzed a retrospective panel dataset of deceased-donor kidneys from UNOS Region 4 (2001-2021) using binary logistic regression and pooled logit models with year fixed effects and time-varying interactions. Medical variables, including kidney donor profile index (KDPI) and cold ischemia time, were combined with logistical variables, including donor-to-transplant center distance, airport category, time of day and day of week. We reported results with log-odds coefficients and average marginal effects for better managerial interpretability. Robustness checks addressed multicollinearity and extreme-value sensitivity.FindingsHigher KDPI and longer cold ischemia time significantly increase the probability of organ discard. Key logistics variables include donor-to-transplant distance and airport accessibility; organs from non-hub and small-hub airports have higher discard rates than those from large-hub airports, even after accounting for medical risk. Temporal controls reflect system-level shifts over the years, whereas time-of-day and weekday effects remain weak. Interaction analyses reveal that logistics burdens disproportionately impact marginal-quality organs.Originality/valueThe study conducts an integrated, multidisciplinary examination of clinical risk and transportation infrastructure for kidney discard within a single empirical framework. By translating coefficients into probability-scale AMEs, the research provides actionable insights for allocation design, transport planning and infrastructure prioritization. Findings extend healthcare supply-chain theory to a high-stakes, perishable-asset context, demonstrating that accessibility and coordination constraints significantly affect medical utilization outcomes.
