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Abstract: SA-PO830

Comparing Measures for Evaluating Dialysis Facilities by Their Kidney Transplant Referral Rates

Session Information

Category: Transplantation

  • 2002 Transplantation: Clinical


  • Wilk, Adam S., Emory University School of Public Health, Atlanta, Georgia, United States
  • Di, Mengyu, Emory University School of Medicine, Atlanta, Georgia, United States
  • Plantinga, Laura, Emory University School of Medicine, Atlanta, Georgia, United States
  • Paul, Sudeshna, Emory University School of Nursing, Atlanta, Georgia, United States
  • Pastan, Stephen O., Emory University School of Medicine, Atlanta, Georgia, United States
  • Patzer, Rachel E., Emory University School of Medicine, Atlanta, Georgia, United States

Among the >560,000 U.S. patients receiving dialysis, many would benefit from transplantation, yet many transplant-eligible dialysis patients are never referred to a transplant center for evaluation. Policymakers are considering including referral rate measures in dialysis facility performance measurement programs. It is unknown to what extent alternative referral rate measures, which are materially different in their sample exclusion criteria and risk adjustment approaches, may be differentially correlated with waitlisting rates downstream.


We compared three measures that can be used to assess dialysis facilities’ referral rates: raw referral rate (percent of patients referred), Paul et al.’s (2018) Standardized Transplantation Referral Ratio (STReR), and the Kidney Care Quality Alliance’s (KCQA) percent referred measure. Using 2014-2020 registry data for incident dialysis patients referred to all nine established transplant centers across Georgia, North Carolina, and South Carolina (referral dates) linked to United States Renal Data System data (denominators, waitlisting dates), we compared the referral measures’ unadjusted distributions and used linear regression to test associations with facility waitlisting rates, overall and among referred patients.


Distributions for the raw referral rate (35,627 patients, 815 facilities), STReR (24,241 patients, 718 facilities), and KCQA measure (8,687 patients, 746 facilities), were similarly right-skewed. Pairwise Pearson correlations among the measures were positive but varied (range 0.34-0.57). Each measure was positively associated with overall waitlisting (estimated change in waitlisting [percentage points] per 1 SD increase in measure: raw referral rate β=5.2; STReR β=1.3; KCQA β=2.7; all p<0.001). None of these measures was statistically associated with waitlisting among referred patients (all p>0.2).


The impact of alternative dialysis facility referral rate measures on subsequent waitlisting may be inconsistent, in part because the measures have different facility exclusion criteria—and so represent different patient and facility populations—and risk adjustment approaches. Programs using these measures should be monitored to ensure they are effective in maximizing transplant access for U.S. patients receiving dialysis.


  • NIDDK Support