Earn MOC for this article: www.wileyhealthlearning.com/aasld.aspx Little is known about the role that transplant centers may play in perpetuating racial disparities after liver transplantation, which are unexplained by patient-level factors. We examined variation in between-center and within-center disparities among 34,114 Black and White liver transplant recipients in the United States from 2010 to 2017 using Scientific Registry of Transplant Recipient (SRTR) data. We used Cox proportional hazards models to calculate transplant center-specific Black-White hazard ratios and hierarchical survival analysis to examine potential effect modification of the race-survival association by transplant center characteristics, including transplant volume, proportion of Black patients, SRTR quality rating, and region. Models were sequentially adjusted for clinical, socioeconomic, and center characteristics. After adjustment, Black patients experienced 1.11 excess deaths after liver transplant per 100 person-years compared with White patients (95% confidence interval [CI], 0.65-1.56), corresponding to a 21% increased mortality risk (95% CI, 1.12-1.31). Although there was substantial variation in this disparity across transplant centers, there was no evidence of effect modification by transplant center volume, proportion of minority patients seen, quality rating, or region. We found significant racial disparities in survival after transplant, with substantial variation in this disparity across transplant centers that was not explained by selected center characteristics. This is the first study to directly evaluate the role transplant centers play in racial disparities in transplant outcomes. Further assessment of the qualitative factors that may drive disparities, such as selection processes and follow-up care, is needed to create effective center-level interventions to address health inequity.

Background Since the introduction of remdesivir and dexamethasone for severe COVID-19 treatment, few large multi-hospital system US studies have described clinical characteristics and outcomes of minority COVID-19 patients who present to the emergency department (ED). Methods This cohort study from the Cerner Real World Database (87 US health systems) from December 1, 2019 to September 30, 2020 included PCR-confirmed COVID-19 patients who self-identified as non-Hispanic Black (Black), Hispanic White (Hispanic), or non-Hispanic White (White). The main outcome was hospitalization among ED patients. Secondary outcomes included mechanical ventilation, intensive care unit care, and in-hospital mortality. Descriptive statistics and Poisson regression compared sociodemographics, comorbidities, receipt of remdesivir, receipt of dexamethasone, and outcomes by racial/ethnic groups and geographic region. Results 94,683 COVID-19 patients presented to the ED. Blacks comprised 26.7% and Hispanics 33.6%. Nearly half (45.1%) of ED patients presented to hospitals in the South. 31.4% (n=29,687) were hospitalized. Lower proportions of Blacks were prescribed dexamethasone (29.4%; n=7,426) compared to Hispanics (40.9%; n=13,021) and Whites (37.5%; n=14,088). Hospitalization risks, compared to Whites, were similar in Blacks (Risk Ratio (RR)=0.94; 95% CI:0.82, 1.08; p=0.4)) and Hispanics RR=0.99 (95% CI:0.81, 1.21; p=0.91), but risk of in-hospital mortality was higher in Blacks, RR=1.18 (95% CI:1.06, 1.31; p=0.002) and Hispanics, RR=1.28 (95% CI: 1.13, 1.44; p < 0.001). Conclusions Minority patients were overrepresented among COVID-19 ED patients, and while they had similar risks of hospitalization as Whites, in-hospital mortality risk was higher. Interventions targeting upstream social determinants of health are needed to reduce racial/ethnic disparities in COVID-19.

BACKGROUND AND AIMS: Data have demonstrated state-wide variability in mortality rates from liver disease (cirrhosis þ hepatocellular carcinoma), but data are lacking at the local level (eg, county) to identify factors associated with variability in liver disease-related mortality and hotspots of liver disease mortality. METHODS: We used Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research data from 2009 to 2018 to calculate county-level, ageadjusted liver disease-related death rates. We fit multivariable linear regression models to adjust for county-level covariates related to demographics (ie, race and ethnicity), medical comorbidities (eg, obesity), access to care (eg, uninsured rate), and geographic (eg, distance to closest liver transplant center) variables. We used optimized hotspot analysis to identify clusters of liver disease mortality hotspots based on the final multivariable models. RESULTS: In multivariable models, 61% of the variability in among-county mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the closest transplant center, and local rates of obesity, diabetes, and alcohol use. Despite adjustment, significant within-state variability in county-level mortality rates was found. Of counties in the top fifth percentile (ie, highest mortality) of fully adjusted mortality, 60% were located in 3 states: Oklahoma, Texas, and New Mexico. Adjusted mortality rates were highly spatially correlated, representing 5 clusters: South Florida; Appalachia and the eastern part of the Midwest; Texas and Oklahoma; New Mexico, Arizona, California, and southern Oregon; and parts of Washington and Montana. CONCLUSIONS: Our data demonstrate significant intrastate differences in liver disease-related mortality, with more than 60% of the variability explained by patient demographics, clinical risk factors for liver disease, and access to specialty liver care.

Background. Monitoring efforts to improve access to transplantation requires a definition of the population attributable to a transplant center. Previously, assessment of variation in transplant care has focused on differences between administrative units—such as states—rather than units derived from observed care patterns. We defined catchment areas (transplant referral regions [TRRs]) from transplant center care patterns for population-based assessment of transplant access. Methods. We used US adult transplant listings (2006–2016) and Dartmouth Atlas catchment areas to assess the optimal method of defining TRRs. We used US Renal Data System and Scientific Registry of Transplant Recipient data to compare waitlist- and population-based kidney transplant rates. Results. We identified 110 kidney, 67 liver, 85 pancreas, 68 heart, and 43 lung TRRs. Most patients were listed in their assigned TRR (kidney: 76%; liver: 75%; pancreas: 75%; heart: 74%; lung: 72%), although the proportion varied by organ (interquartile range for kidney, 65.7%–82.5%; liver, 58.2%–78.8%; pancreas, 58.4%–81.1%; heart, 63.1%–80.9%; lung, 61.6%–76.3%). Patterns of population- and waitlist-based kidney transplant rates differed, most notably in the Northeast and Midwest. Conclusions. Patterns of TRR-based kidney transplant rates differ from waitlist-based rates, indicating that current metrics may not reflect transplant access in the broader population. TRRs define populations served by transplant centers and could enable future studies of how transplant centers can improve access for patients in their communities.