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3259 Identifying the barriers and disparities for referral to kidney transplantation faced by HIV-infected patients with End Stage Renal Disease.

Published online by Cambridge University Press:  26 March 2019

Ruth Adekunle
Affiliation:
Emory University
Aneesh Mehta
Affiliation:
Emory University
Rachel Patzer
Affiliation:
Emory University
Wendy Armstrong
Affiliation:
Emory University
Ashley Burroughs
Affiliation:
Emory University
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Abstract

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OBJECTIVES/SPECIFIC AIMS: Our study aims to create a novel state level HIV-ESRD dataset and compare patient-level characteristics on rates of transplant referral, evaluation, waitlisting, and transplantation for HIV-positive versus HIV-negative patients. Our main hypothesis is that HIV-positive patients in Georgia are less likely to be referred to kidney transplant compared with HIV-negative patients. METHODS/STUDY POPULATION: Three datasets will be merged in order to create the HIV-ESRD dataset. The datasets are United States Renal Data System (USRDS), a southeast Transplant Referral Dataset and patient-level Georgia Department of Public Health HIV Incidence Database. The resulting study population will include patients that are older than 18, but less than 70, are HIV-positive and are on dialysis in Georgia. This dataset will also identify those patients who have been referred to transplantation, have been waitlisted, and have received kidney transplants between January 2012 and December 2017. If within a 1-year period, the prevalence of HIV-positive patients referred to transplant was lower than the 1-year period prevalence of HIV-negative patients for 3 consecutive years, the dialysis facility will be classified as having a within-facility disparity. We will then characterize patient level and dialysis facility-level factors that may contribute to observed findings. Patient characteristics will include demographic, clinical data, proxies of socioeconomic status, and geospatial relationships to transplant centers and rural vs urban neighborhoods. Facility-level characteristics includes profit status (profit vs. nonprofit), total number of staff (including full-time and part-time employees), aggregate demographic and clinical facility characteristics, and total number of treated patients. RESULTS/ANTICIPATED RESULTS:. We anticipate the successful creation of the proposed dataset that will allow for accurate identification of HIV-positive patients on dialysis in Georgia.. This dataset will provide the ability to determine referral, waitlisting, and transplantation rates.. We predict the overall rate of referral, waitlisting, and kidney transplantation in HIV patients will be relatively low, and that dialysis facilities with a higher proportion of HIV-positive will have lower referral rates compared to dialysis facilities treating a higher proportion of HIV-negative patients. It is foreseen that among patient-level characteristics, the strongest predictor for decreased referral rates will be HIV serostatus and among dialysis facility factors, profit status will be associated with decreased referral rates. DISCUSSION/SIGNIFICANCE OF IMPACT: This pilot study offers the creation of the first regional dataset of HIV-ESRD patients that will include patient-level characteristic of HIV-positive patients and provide a model for other states to adopt. We will contribute improved state-level description of incidence data of HIV-positive patients on dialysis, current rates of transplant referral, waitlisting, and transplantation, and offer potential associated factors that influence these processes. This knowledge will be used to determine the next steps in improving access to care; conducting qualitative research to understand dialysis facility views on transplant in HIV patients, understanding HIV patient’s position on transplantation, providing education on the value of kidney transplant referral, and expanding the approach of combining patient level HIV data to the southeast.

Type
Health Equity & Community Engagement
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Association for Clinical and Translational Science 2019