Geographic and Racial Disparities in Mortality of Dialysis Patients
AdvisorCalhoun, Elizabeth A.
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PublisherThe University of Arizona.
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EmbargoRelease after 01/13/2021
AbstractBACKGROUND: The incidence rate and hospitalization rate for patients with End Stage Renal Disease (ESRD) vary across different counties in the U.S. Little information is available on how geography can impact patient mortality through county health status and gaps in supply and demand for hemodialysis services. METHODS: This is a retrospective cohort study where adult patients who initiated in-center hemodialysis between 2007 and 2016 and recorded in the United States Renal Data System (USRDS) were assessed for survival time and mortality rate. The primary exposure variable in Aim 1 was the overall county health status (Most Healthy vs Least Healthy) based on the health factor ranks published by County Health Rankings & Roadmap (CHR&R). The primary exposure variable for Aim 2 was the supply-demand gap for hemodialysis services as measured by the patient-station ratio for each county. The primary exposure variable for Aim 3 was the change in the number of dialysis stations between 2011 and 2016 for each county. Kaplan-Meier estimate used to compute the median survival time and Cox regression analysis was used to compute the hazard rate (HR) for mortality after adjusting for various confounders. RESULTS: Most Healthy counties in the U.S. are likely to be larger urban counties with predominantly white and older patients. On the contrary, Least Healthy counties are comparatively more rural and smaller counties with a higher percentage of African American population, more unemployed and Medicaid patients. Patients residing in Most Healthy counties (HR = 0.899, 95% CI 0.825,0.979) had a lower hazard rate (HR) for mortality compared to patients living in Least Healthy Counties (p value = 0.0143). In Aim 2, counties in Category 1 (counties with no hemodialysis stations), Category 2.1 (underutilized HD stations with population <50,000) and Category 2.2 (underutilized HD stations with population 50,000) had higher HR compared to the reference Category 3. However, when stratified by age and race, the HR was statistically significant for Blacks only for Category 2.2 for all age groups (HR = 1.11, 95% CI 1.06,1.16) and for Whites for Category 1 (aged 40 – 79; HR=1.1) and Category 2.2 (aged 65 – 79; HR=1.11). In Aim 3, counties with No Change had a marginally higher hazard rate (HR=1.04, 95% CI 1.02, 1.07) compared to counties with an increase in dialysis stations. Race was a significant confounder but not an effect modifier to this association (p-value 0.2942). CONCLUSION: County health status and lack of hemodialysis facilities affects survival of ESRD patients. Additionally, patients residing in some suburban counties or smaller metros had a higher hazard rate for mortality despite excess supply of dialysis stations. It is important for care providers and local health officials to understand the health factor profile and spatial distribution of dialysis stations in their county to help ESRD patients navigate barriers to care, reduce rates of dialysis withdrawal, and improve mortality outcomes.
Degree ProgramGraduate College