A comparison of deprivation indices and application to transplant populations.

The choice of deprivation index can influence conclusions drawn regarding the extent of deprivation within a community and the identification of the most deprived communities in the United States. This study aimed to determine the degree of correlation among deprivation indices commonly used to characterize transplant populations. We used a retrospective cohort consisting of adults listed for liver or kidney transplants between 2008 and 2018 to compare 4 deprivation indices: neighborhood deprivation index, social deprivation index (SDI), area deprivation index, and social vulnerability index. Pairwise correlation between deprivation indices by transplant referral regions was measured using Spearman correlations of population-weighted medians and upper quartiles. In total, 52 individual variables were used among the 4 deprivation indices with 25% overlap. For both organs, the correlation between the population-weighted 75th percentile of the deprivation indices by transplant referral region was highest between SDI and social vulnerability index (liver and kidney, 0.93) and lowest between area deprivation index and SDI (liver, 0.19 and kidney, 0.15). The choice of deprivation index affects the applicability of research findings across studies examining the relationship between social risk and clinical outcomes. Appropriate application of these measures to transplant populations requires careful index selection based on the intended use and included variable relevance.

Characterization of social determinants of health of a liver transplant referral population.

Disparities exist in referral and access to the liver transplant (LT) waitlist, and social determinants of health (SDOH) are increasingly recognized as important factors driving health inequities, including in LT. The SDOH of potential transplant candidates is therefore important to characterize when designing targeted interventions to promote equity in access to LT. Yet, it is uncertain how a transplant center should approach this issue, characterize SDOH, identify disparities, and use these data to inform interventions. We performed a retrospective study of referrals for first-time, single-organ LT to our center from 2016 to 2020. Addresses were geoprocessed and mapped to the corresponding county, census tract, and census block group to assess their geospatial distribution, identify potential disparities in referrals, and characterize their communities across multiple domains of SDOH to identify potential barriers to evaluation and selection. We identified variability in referral patterns and areas with disproportionately low referrals, including counties in the highest quartile of liver disease mortality (9%) and neighborhoods in the highest quintile of socioeconomic deprivation (17%) and quartile of poverty (21%). Black individuals were also under-represented compared with expected state demographics (12% vs. 18%). Among the referral population, several potential barriers to evaluation and selection for LT were identified, including poverty, educational attainment, access to healthy food, and access to technology. This approach to the characterization of a transplant center's referral population by geographic location and associated SDOH demonstrates a model for identifying disparities in a referral population and potential barriers to evaluation that can be used to inform targeted interventions for disparities in LT access.

Social determinants of health data in solid organ transplantation: National data sources and future directions.

Health equity research in transplantation has largely relied on national data sources, yet the availability of social determinants of health (SDOH) data varies widely among these sources. We sought to characterize the extent to which national data sources contain SDOH data applicable to end-stage organ disease (ESOD) and transplant patients. We reviewed 10 active national data sources based in the United States. For each data source, we examined patient inclusion criteria and explored strengths and limitations regarding SDOH data, using the National Institutes of Health PhenX toolkit of SDOH as a data collection instrument. Of the 28 SDOH variables reviewed, eight-core demographic variables were included in ≥80% of the data sources, and seven variables that described elements of social status ranged between 30 and 60% inclusion. Variables regarding identity, healthcare access, and social need were poorly represented (≤20%) across the data sources, and five of these variables were included in none of the data sources. The results of our review highlight the need for improved SDOH data collection systems in ESOD and transplant patients via: enhanced inter-registry collaboration, incorporation of standardized SDOH variables into existing data sources, and transplant center and consortium-based investigation and innovation.