TY - JOUR
T1 - Referral and Evaluation for Kidney Transplantation Following Implementation of the 2014 National Kidney Allocation System
AU - Southeastern Kidney Transplant Coalition
AU - Patzer, Rachel E.
AU - Di, Mengyu
AU - Zhang, Rebecca
AU - McPherson, Laura
AU - DuBay, Derek A.
AU - Ellis, Matthew
AU - Wolf, Joshua
AU - Jones, Heather
AU - Zayas, Carlos
AU - Mulloy, Laura
AU - Reeves-Daniel, Amber
AU - Mohan, Sumit
AU - Perez, Aubriana C.
AU - Trivedi, Amal N.
AU - Pastan, Stephen O.
AU - Adler, Joel
AU - Berlin, Alexander
AU - Browne, Teri
AU - Canavan, Kelley
AU - Carter, Rosalyn
AU - Graves, Hannah
AU - Harding, Jessica
AU - Kleman, Mark
AU - Malik, Sana
AU - Mohan, Prince
AU - Moshiri, Rebekah
AU - Muench, Dorothy
AU - Mutell, Rich
AU - Newsome, Jessica
AU - O'Shea, Michael
AU - Plantinga, Laura
AU - Retzloff, Samantha
AU - Rossi, Ana
AU - Sauls, Leighann
AU - Stratta, Robert
AU - Teunis, Larissa
AU - Urbanski, Megan
N1 - Funding Information:
This work was supported by the National Institute on Minority Health and Health Disparities grants R01MD010290 and U01MD010611. The funder did not have a role in study design, data collection, analysis, reporting, or the decision to submit for publication.
Funding Information:
In addition to authors DuBay, Ellis, Jones, Mohan, and Reeves-Daniel, members of the Southeastern Kidney Transplant Coalition include Joel Adler (Brigham and Women's Hospital), Alexander Berlin (Patient Partner), Teri Browne (University of South Carolina), Kelley Canavan (National Kidney Foundation), Rosalyn Carter (Duke University), Hannah Graves (Piedmont Hospital), Jessica Harding (Emory University), Mark Kleman (University of North Carolina), Sana Malik (IPRO ESRD Network), Prince Mohan (Medical University of South Carolina), Rebekah Moshiri (Georgia Transplant Foundation), Dorothy Muench (Wake Forest Health), Rich Mutell (Apex Health Innovations), Jessica Newsome (Fresenius Medical Care), Michael O'Shea (DaVita Kidney Care), Laura Plantinga (Emory University), Samantha Retzloff (Emory University), Ana Rossi (Piedmont Hospital), Leighann Sauls (Alliant Health Solutions), Robert Stratta (Wake Forest Health), Larissa Teunis (Emory University), and Megan Urbanski (Emory University). Rachel E. Patzer, PhD, MPH, Mengyu Di, MPH, Rebecca Zhang, MS, Laura McPherson, MPH, Derek A. DuBay, MD, Matthew Ellis, MD, Joshua Wolf, MD, Heather Jones, MD, Carlos Zayas, MD, Laura Mulloy, DO, Amber Reeves-Daniel, MD, Sumit Mohan, MD, MPH, Aubriana C. Perez, BS, Amal N. Trivedi, MD, MPH, and Stephen O. Pastan, MD. Research idea and study design: REP; data acquisition: DAD, ME, JW, HJ, CZ, LMulloy, ARD, SM; data analysis: REP, MD, RZ, LMcPherson; data interpretation: REP, MD, RZ, LMcPherson, ACP, ANT, SM, SOP; supervision or mentorship: SOP. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. This work was supported by the National Institute on Minority Health and Health Disparities grants R01MD010290 and U01MD010611. The funder did not have a role in study design, data collection, analysis, reporting, or the decision to submit for publication. Dr Mohan is a national faculty chair for the ESRD treatment choices learning collaborative (ETCLC). The other authors declare that they have no relevant financial interests. The data reported here have been supplied in part by the USRDS. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as official policy or interpretation of the US government. Deidentified data can be shared with researchers with appropriate human subjects approvals and data use agreements. Received April 13, 2021. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form January 3, 2022.
Publisher Copyright:
© 2022 National Kidney Foundation, Inc.
PY - 2022/12
Y1 - 2022/12
N2 - Rationale & Objective: The national kidney allocation system (KAS) implemented in December 2014 in the United States redefined the start of waiting time from the time of waitlisting to the time of kidney failure. Waitlisting has declined post-KAS, but it is unknown if this is due to transplant center practices or changes in dialysis facility referral and evaluation. The purpose of this study was to assess the impact of the 2014 KAS policy change on referral and evaluation for transplantation among a population of incident and prevalent patients with kidney failure. Study Design: Cohort study. Setting & Participants: 37,676 incident (2012-2016) patients in Georgia, North Carolina, and South Carolina identified within the US Renal Data System at 9 transplant centers and followed through December 2017. A prevalent population of 6,079 patients from the same centers receiving maintenance dialysis in 2012 but not referred for transplantation in 2012. Exposure: KAS era (pre-KAS vs post-KAS). Outcome: Referral for transplantation, start of transplant evaluation, and waitlisting. Analytical Approach: Multivariable time-dependent Cox models for the incident and prevalent population. Results: Among incident patients, KAS was associated with increased referrals (adjusted HR, 1.16 [95% CI, 1.12-1.20]) and evaluation starts among those referred (adjusted HR, 1.16 [95% CI, 1.10-1.21]), decreased overall waitlisting (adjusted HR, 0.70 [95% CI, 0.65-0.76]), and lower rates of active waitlisting among those evaluated compared to the pre-KAS era (adjusted HR, 0.81 [95% CI, 0.74-0.90]). Among the prevalent population, KAS was associated with increases in overall waitlisting (adjusted HR, 1.74 [95% CI, 1.15-2.63]) and active waitlisting among those evaluated (adjusted HR, 2.01 [95% CI, 1.16-3.49]), but had no significant impact on referral or evaluation starts among those referred. Limitations: Limited to 3 states, residual confounding. Conclusions: In the southeastern United States, the impact of KAS on steps to transplantation was different among incident and prevalent patients with kidney failure. Dialysis facilities referred more incident patients and transplant centers evaluated more incident patients after implementation of KAS, but fewer evaluated patients were placed onto the waitlist. Changes in dialysis facility and transplant center behaviors after KAS implementation may have influenced the observed changes in access to transplantation.
AB - Rationale & Objective: The national kidney allocation system (KAS) implemented in December 2014 in the United States redefined the start of waiting time from the time of waitlisting to the time of kidney failure. Waitlisting has declined post-KAS, but it is unknown if this is due to transplant center practices or changes in dialysis facility referral and evaluation. The purpose of this study was to assess the impact of the 2014 KAS policy change on referral and evaluation for transplantation among a population of incident and prevalent patients with kidney failure. Study Design: Cohort study. Setting & Participants: 37,676 incident (2012-2016) patients in Georgia, North Carolina, and South Carolina identified within the US Renal Data System at 9 transplant centers and followed through December 2017. A prevalent population of 6,079 patients from the same centers receiving maintenance dialysis in 2012 but not referred for transplantation in 2012. Exposure: KAS era (pre-KAS vs post-KAS). Outcome: Referral for transplantation, start of transplant evaluation, and waitlisting. Analytical Approach: Multivariable time-dependent Cox models for the incident and prevalent population. Results: Among incident patients, KAS was associated with increased referrals (adjusted HR, 1.16 [95% CI, 1.12-1.20]) and evaluation starts among those referred (adjusted HR, 1.16 [95% CI, 1.10-1.21]), decreased overall waitlisting (adjusted HR, 0.70 [95% CI, 0.65-0.76]), and lower rates of active waitlisting among those evaluated compared to the pre-KAS era (adjusted HR, 0.81 [95% CI, 0.74-0.90]). Among the prevalent population, KAS was associated with increases in overall waitlisting (adjusted HR, 1.74 [95% CI, 1.15-2.63]) and active waitlisting among those evaluated (adjusted HR, 2.01 [95% CI, 1.16-3.49]), but had no significant impact on referral or evaluation starts among those referred. Limitations: Limited to 3 states, residual confounding. Conclusions: In the southeastern United States, the impact of KAS on steps to transplantation was different among incident and prevalent patients with kidney failure. Dialysis facilities referred more incident patients and transplant centers evaluated more incident patients after implementation of KAS, but fewer evaluated patients were placed onto the waitlist. Changes in dialysis facility and transplant center behaviors after KAS implementation may have influenced the observed changes in access to transplantation.
KW - Allocation time
KW - health care access
KW - health care policy
KW - kidney allocation policy (KAS)
KW - kidney failure
KW - kidney transplantation
KW - transplant referral
KW - waitlisting
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UR - http://www.scopus.com/inward/citedby.url?scp=85132668825&partnerID=8YFLogxK
U2 - 10.1053/j.ajkd.2022.01.423
DO - 10.1053/j.ajkd.2022.01.423
M3 - Article
C2 - 35301050
AN - SCOPUS:85132668825
SN - 0272-6386
VL - 80
SP - 707
EP - 717
JO - American Journal of Kidney Diseases
JF - American Journal of Kidney Diseases
IS - 6
ER -