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Published on: June 17, 2020
Early Assessment of National Kidney Allocation Policy Change
Vinayak S Rohan1, Nicole Pilch, John McGillicuddy
1From the Division of Transplant Surgery, Department of Surgery, Medical University of South Carolina, College of Medicine, Charleston, SC.
Background:
The new kidney allocation changes with elimination of donor service areas (DSAs) and Organ Procurement and Transplantation Network regions were initiated to improve equity in organ allocation. The aim of this evaluation was to determine the operational, financial, and recipient-related effect of the new allocation system on a large rural transplantation program.
Study Design:
A retrospective, cross-sectional analysis of organ offers, allograft outcomes, and attributed costs in a comparative time cohort, before (December 16, 2020 to March 14, 2021) and after (March 15, 2021 to June 13, 2021) the allocation change was performed. Outcomes were limited to adult, solitary, deceased donor kidney transplantations.
Results:
We received 198,881 organ offers from 3,886 organ donors at our transplantation center from December 16, 2020 to June 31, 2021: 87,643 (1,792 organ donors) before the change and 111,238 (2094 organ donors) after the change, for a difference of +23,595 more offers (+302 organ donors). This resulted in 6.5 more organs transplanted vs a predicted loss of 4.9 per month. Local organ offers dropped from 70% to 23%. There was a statistically significantly increase in donor terminal serum creatinine (1.2 ± 0.86 mg/dL vs 2.2 ± 2.3 mg/dL, p < 0.001), kidney donor profile index (KDPI) (39 ± 20 vs 48 ± 22, p = 0.017), cold ischemia time (16 ± 7 hours vs 21 ± 6 hours, p < 0.001), and delayed graft function rates (23% vs 40%, p = 0.020).
Conclusion:
The new kidney allocation policy has led to an increase in KDPI of donors with longer cold ischemia time, leading to higher delayed graft function rates. This has resulted in increasing logistical and financial burdens on the system. Implementing large-scale changes in allocation based predominantly on predictive modeling needs to be intensely reassessed during a longer follow up.
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