Improving Health Equity in Living Donor Kidney Transplant: Application of an Implementation Science Framework.

BACKGROUND: Interventions to improve racial equity in access to living donor kidney transplants (LDKT) have focused primarily on patients, ignoring the contributions of clinicians, transplant centers, and health system factors. Obtaining access to LDKT is a complex, multi-step process involving patients, their families, clinicians, and health system functions. An implementation science framework can help elucidate multi-level barriers to achieving racial equity in LDKT and guide the implementation of interventions targeted at all levels. METHODS: We adopted the Pragmatic Robust Implementation and Sustainability Model (PRISM), an implementation science framework for racial equity in LDKT. The purpose was to provide a guide for assessment, inform intervention design, and support planning for the implementation of interventions. RESULTS: We applied 4 main PRISM domains to racial equity in LDKT: Organizational Characteristics, Program Components, External Environment, and Patient Characteristics. We specified elements within each domain that consider perspectives of the health system, transplant center, clinical staff, and patients. CONCLUSION: The applied PRISM framework provides a foundation for the examination of multi-level influences across the entirety of LDKT care. Researchers, quality improvement staff, and clinicians can use the applied PRISM framework to guide the assessment of inequities, support collaborative intervention development, monitor intervention implementation, and inform resource allocation to improve equity in access to LDKT.

Racial Equity in Living Donor Kidney Transplant Centers, 2008-2018.

Importance: It is unclear whether center-level factors are associated with racial equity in living donor kidney transplant (LDKT). Objective: To evaluate center-level factors and racial equity in LDKT during an 11-year time period. Design, Setting, and Participants: A retrospective cohort longitudinal study was completed in February 2023, of US transplant centers with at least 12 annual LDKTs from January 1, 2008, to December 31, 2018, identified in the Health Resources Services Administration database and linked to the US Renal Data System and the Scientific Registry of Transplant Recipients. Main Outcomes and Measures: Observed and model-based estimated Black-White mean LDKT rate ratios (RRs), where an RR of 1 indicates racial equity and values less than 1 indicate a lower rate of LDKT of Black patients compared with White patients. Estimated yearly best-case center-specific LDKT RRs between Black and White individuals, where modifiable center characteristics were set to values that would facilitate access to LDKT. Results: The final cohorts of patients included 394 625 waitlisted adults, of whom 33.1% were Black and 66.9% were White, and 57 222 adult LDKT recipients, of whom 14.1% were Black and 85.9% were White. Among 89 transplant centers, estimated yearly center-level RRs between Black and White individuals accounting for center and population characteristics ranged from 0.0557 in 2008 to 0.771 in 2018. The yearly median RRs ranged from 0.216 in 2016 to 0.285 in 2010. Model-based estimations for the hypothetical best-case scenario resulted in little change in the minimum RR (from 0.0557 to 0.0549), but a greater positive shift in the maximum RR from 0.771 to 0.895. Relative to the observed 582 LDKT in Black patients and 3837 in White patients, the 2018 hypothetical model estimated an increase of 423 (a 72.7% increase) LDKTs for Black patients and of 1838 (a 47.9% increase) LDKTs for White patients. Conclusions and Relevance: In this cohort study of patients with kidney failure, no substantial improvement occurred over time either in the observed or the covariate-adjusted estimated RRs. Under the best-case hypothetical estimations, modifying centers' participation in the paired exchange and voucher programs and increased access to public insurance may contribute to improved racial equity in LDKT. Additional work is needed to identify center-level and program-specific strategies to improve racial equity in access to LDKT.

Redressing the Harms of Race-Based Kidney Function Estimation.

This Viewpoint emphasizes the urgency of abolishing race-based medical practices and explains how they have unjustly contributed to racial inequities in clinical care and health outcomes.

Association of Acute Kidney Injury and Cardiovascular Disease Following Percutaneous Coronary Intervention: Assessment of Interactions by Race, Diabetes, and Kidney Function.

RATIONALE & OBJECTIVE: Black patients and those with diabetes or reduced kidney function experience a disproportionate burden of acute kidney injury (AKI) and cardiovascular events. However, whether these factors modify the association between AKI and cardiovascular events after percutaneous coronary intervention (PCI) is unknown and was the focus of this study. STUDY DESIGN: Observational cohort. SETTING & PARTICIPANTS: Patients who underwent PCI at Duke between January 1, 2003, and December 31, 2013, with data available in the Duke Databank for Cardiovascular Disease. EXPOSURE: AKI, defined as ≥1.5-fold relative elevation in serum creatinine within 7 days from a reference value ascertained 30 days before PCI, or a 0.3 mg/dL increase from the reference value within 48 hours. OUTCOME: A composite of all-cause death, myocardial infarction, stroke, or revascularization during the first year after PCI. ANALYTICAL APPROACH: Cox regression models adjusted for potential confounders and with interaction terms between AKI and race, diabetes, or baseline estimated glomerular filtration rate (eGFR). RESULTS: Among 9,422 patients, 9% (n = 865) developed AKI, and the primary composite outcome occurred in 21% (n = 2,017). AKI was associated with a nearly 2-fold higher risk of the primary outcome (adjusted HR, 1.94 [95% CI, 1.71-2.20]). The association between AKI and cardiovascular risk did not significantly differ by race (P interaction, 0.4), diabetes, (P interaction, 0.06), or eGFR (P interaction, 0.2). However, Black race and severely reduced eGFR, but not diabetes, each had a cumulative impact with AKI on risk for the primary outcome. Compared with White patients with no AKI as the reference, the risk for the outcome was highest in Black patients with AKI (HR, 2.27 [95% CI, 1.83-2.82]), followed by White patients with AKI (HR, 1.87 [95% CI, 1.58-2.21]), and was least in patients of other races with AKI (HR, 1.48 [95% CI, 0.88-2.48]). LIMITATIONS: Residual confounding, including the impact of clinical care following PCI on cardiovascular outcomes of AKI. CONCLUSIONS: Neither race, diabetes, nor reduced eGFR potentiated the association of AKI with cardiovascular risk, but Black patients with AKI had a qualitatively greater risk than White patients with AKI or patients of other races with AKI. PLAIN-LANGUAGE SUMMARY: This study examined differences by race, diabetes, or kidney function in the well-known association of AKI with increased risk for cardiovascular outcomes among patients undergoing percutaneous coronary intervention. The authors found that AKI was associated with a greater risk for cardiovascular outcomes, but this risk did not differ by patients' race, diabetes status, or level of kidney function before the procedure. That said, the risk for cardiovascular outcomes was numerically highest among Black patients compared with White patients or those of other races. These study findings suggest that future efforts to prevent AKI among patients undergoing the procedure could reduce racial disparities in risk for unfavorable cardiovascular outcomes afterward.

Association of the Affordable Care Act on Access to and Outcomes After Kidney or Liver Transplant: A Transplant Registry Study.

BACKGROUND: To evaluate the effect of the Affordable Care Act (ACA) Medicaid expansion on payor mix among patients on the kidney and liver transplant waiting list as well as waiting list and post-transplant outcomes. DESIGN: Using the Scientific Registry of Transplant Recipients, we performed a secondary data analysis of all patients on the kidney and liver transplant waiting list from 2007 to 2018. We described changes in payor mix by timing of state Medicaid expansion. We used competing risks models to estimate cause-specific hazard ratios for the effects of insurance and era on death/delisting and transplant. We used a Poisson regression model to estimate the effect of insurance and era on incidence rate ratio of inactivations on the waiting list. We used Cox proportional hazards models to estimate the effect of insurance and era on graft and patient survival. RESULTS: A decade after implementation of the ACA, the prevalence of Medicaid beneficiaries listed for transplant increased by 2.5% (from 7.4% to 9.9%) for kidney and by 2.6% (15.3% to 17.9%) for liver. Expansion states had greater increases than nonexpansion states (kidney 3.8% vs 0.6%, liver 5.3% vs -1.8%). Among wait-listed patients, the magnitude of association of Medicaid insurance vs private insurance with transplant decreased over time for kidney candidates (era 1 subdistribution hazard ratio (SHR), 0.62 [95% CI, 0.60-0.64] vs era 3 SHR, 0.77 [95% CI, 0.74-0.70]) but increased for liver candidates (era 1 SHR, 0.85 [95% CI, 0.83-0.90] vs era 3 SHR 0.79 [95% CI, 0.77-0.82]). Medicaid-insured kidney and liver recipients had greater hazards of graft failure; this did not change over time (kidney: HR, 1.23 [95% CI, 1.06-1.44] liver: HR, 1.05 [95% CI, 0.94-1.17]). CONCLUSIONS: For the millions of patients with chronic kidney and liver diseases, implementation of the ACA has resulted in only modest increases in access to transplant for the publicly insured vs the privately insured.

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.

Use of Race in Kidney Function Estimation: Lessons Learned and the Path Toward Health Justice.

In 2020, the nephrology community formally interrogated long-standing race-based clinical algorithms used in the field, including the kidney function estimation equations. A comprehensive understanding of the history of kidney function estimation and racial essentialism is necessary to understand underpinnings of the incorporation of a Black race coefficient into prior equations. We provide a review of this history, as well as the considerations used to develop race-free equations that are a guidepost for a more equity-oriented, scientifically rigorous future for kidney function estimation and other clinical algorithms and processes in which race may be embedded as a variable.

Association between Gentrification and Health and Healthcare Utilization.

There is tremendous interest in understanding how neighborhoods impact health by linking extant social and environmental drivers of health (SDOH) data with electronic health record (EHR) data. Studies quantifying such associations often use static neighborhood measures. Little research examines the impact of gentrification-a measure of neighborhood change-on the health of long-term neighborhood residents using EHR data, which may have a more generalizable population than traditional approaches. We quantified associations between gentrification and health and healthcare utilization by linking longitudinal socioeconomic data from the American Community Survey with EHR data across two health systems accessed by long-term residents of Durham County, NC, from 2007 to 2017. Census block group-level neighborhoods were eligible to be gentrified if they had low socioeconomic status relative to the county average. Gentrification was defined using socioeconomic data from 2006 to 2010 and 2011-2015, with the Steinmetz-Wood definition. Multivariable logistic and Poisson regression models estimated associations between gentrification and development of health indicators (cardiovascular disease, hypertension, diabetes, obesity, asthma, depression) or healthcare encounters (emergency department [ED], inpatient, or outpatient). Sensitivity analyses examined two alternative gentrification measures. Of the 99 block groups within the city of Durham, 28 were eligible (N = 10,807; median age = 42; 83% Black; 55% female) and 5 gentrified. Individuals in gentrifying neighborhoods had lower odds of obesity (odds ratio [OR] = 0.89; 95% confidence interval [CI]: 0.81-0.99), higher odds of an ED encounter (OR = 1.10; 95% CI: 1.01-1.20), and lower risk for outpatient encounters (incidence rate ratio = 0.93; 95% CI: 0.87-1.00) compared with non-gentrifying neighborhoods. The association between gentrification and health and healthcare utilization was sensitive to gentrification definition.

Observability and its impact on differential bias for clinical prediction models.

OBJECTIVE: Electronic health records have incomplete capture of patient outcomes. We consider the case when observability is differential across a predictor. Including such a predictor (sensitive variable) can lead to algorithmic bias, potentially exacerbating health inequities. MATERIALS AND METHODS: We define bias for a clinical prediction model (CPM) as the difference between the true and estimated risk, and differential bias as bias that differs across a sensitive variable. We illustrate the genesis of differential bias via a 2-stage process, where conditional on having the outcome of interest, the outcome is differentially observed. We use simulations and a real-data example to demonstrate the possible impact of including a sensitive variable in a CPM. RESULTS: If there is differential observability based on a sensitive variable, including it in a CPM can induce differential bias. However, if the sensitive variable impacts the outcome but not observability, it is better to include it. When a sensitive variable impacts both observability and the outcome no simple recommendation can be provided. We show that one cannot use observed data to detect differential bias. DISCUSSION: Our study furthers the literature on observability, showing that differential observability can lead to algorithmic bias. This highlights the importance of considering whether to include sensitive variables in CPMs. CONCLUSION: Including a sensitive variable in a CPM depends on whether it truly affects the outcome or just the observability of the outcome. Since this cannot be distinguished with observed data, observability is an implicit assumption of CPMs.

A scoping review of inequities in access to organ transplant in the United States.

BACKGROUND: Organ transplant is the preferred treatment for end-stage organ disease, yet the majority of patients with end-stage organ disease are never placed on the transplant waiting list. Limited access to the transplant waiting list combined with the scarcity of the organ pool result in over 100,000 deaths annually in the United States. Patients face unique barriers to referral and acceptance for organ transplant based on social determinants of health, and patients from disenfranchised groups suffer from disproportionately lower rates of transplantation. Our objective was to review the literature describing disparities in access to organ transplantation based on social determinants of health to integrate the existing knowledge and guide future research. METHODS: We conducted a scoping review of the literature reporting disparities in access to heart, lung, liver, pancreas and kidney transplantation based on social determinants of health (race, income, education, geography, insurance status, health literacy and engagement). Included studies were categorized based on steps along the transplant care continuum: referral for transplant, transplant evaluation and selection, living donor identification/evaluation, and waitlist outcomes. RESULTS: Our search generated 16,643 studies, of which 227 were included in our final review. Of these, 34 focused on disparities in referral for transplantation among patients with chronic organ disease, 82 on transplant selection processes, 50 on living donors, and 61 on waitlist management. In total, 15 studies involved the thoracic organs (heart, lung), 209 involved the abdominal organs (kidney, liver, pancreas), and three involved multiple organs. Racial and ethnic minorities, women, and patients in lower socioeconomic status groups were less likely to be referred, evaluated, and added to the waiting list for organ transplant. The quality of the data describing these disparities across the transplant literature was variable and overwhelmingly focused on kidney transplant. CONCLUSIONS: This review contextualizes the quality of the data, identifies seminal work by organ, and reports gaps in the literature where future research on disparities in organ transplantation should focus. Future work should investigate the association of social determinants of health with access to the organ transplant waiting list, with a focus on prospective analyses that assess interventions to improve health equity.

Health inequities and the inappropriate use of race in nephrology.

Chronic kidney disease is an important clinical condition beset with racial and ethnic disparities that are associated with social inequities. Many medical schools and health centres across the USA have raised concerns about the use of race - a socio-political construct that mediates the effect of structural racism - as a fixed, measurable biological variable in the assessment of kidney disease. We discuss the role of race and racism in medicine and outline many of the concerns that have been raised by the medical and social justice communities regarding the use of race in estimated glomerular filtration rate equations, including its relationship with structural racism and racial inequities. Although race can be used to identify populations who experience racism and subsequent differential treatment, ignoring the biological and social heterogeneity within any racial group and inferring innate individual-level attributes is methodologically flawed. Therefore, although more accurate measures for estimating kidney function are under investigation, we support the use of biomarkers for determining estimated glomerular filtration rate without adjustments for race. Clinicians have a duty to recognize and elucidate the nuances of racism and its effects on health and disease. Otherwise, we risk perpetuating historical racist concepts in medicine that exacerbate health inequities and impact marginalized patient populations.