Quality measures in pre-liver transplant care by the Practice Metrics Committee of the American Association for the Study of Liver Diseases.

The liver transplantation (LT) evaluation and waitlisting process is subject to variations in care that can impede quality. The American Association for the Study of Liver Diseases (AASLD) Practice Metrics Committee (PMC) developed quality measures and patient-reported experience measures along the continuum of pre-LT care to reduce care variation and guide patient-centered care. Following a systematic literature review, candidate pre-LT measures were grouped into 4 phases of care: referral, evaluation and waitlisting, waitlist management, and organ acceptance. A modified Delphi panel with content expertise in hepatology, transplant surgery, psychiatry, transplant infectious disease, palliative care, and social work selected the final set. Candidate patient-reported experience measures spanned domains of cognitive health, emotional health, social well-being, and understanding the LT process. Of the 71 candidate measures, 41 were selected: 9 for referral; 20 for evaluation and waitlisting; 7 for waitlist management; and 5 for organ acceptance. A total of 14 were related to structure, 17 were process measures, and 10 were outcome measures that focused on elements not typically measured in routine care. Among the patient-reported experience measures, candidates of LT rated items from understanding the LT process domain as the most important. The proposed pre-LT measures provide a framework for quality improvement and care standardization among candidates of LT. Select measures apply to various stakeholders such as referring practitioners in the community and LT centers. Clinically meaningful measures that are distinct from those used for regulatory transplant reporting may facilitate local quality improvement initiatives to improve access and quality of care.

The Association between Long-term PM2.5 Exposure and Risk for Pancreatic Cancer: An Application of Social Informatics.

There is a profound need to identify modifiable risk factors to screen and prevent pancreatic cancer. Air pollution, including fine particulate matter (PM2.5), is increasingly recognized as a risk factor for cancer. We conducted a case-control study using data from the electronic health record (EHR) of Duke University Health System, 15-year residential history, NASA satellite fine particulate matter (PM2.5) and neighborhood socioeconomic data. Using deterministic and probabilistic linkage algorithms, we linked residential history and EHR data to quantify long term PM2.5 exposure. Logistic regression models quantified the association between a one interquartile range (IQR) increase in PM2.5 concentration and pancreatic cancer risk. The study included 203 cases and 5027 controls (median age of 59 years, 62% female, 26% Black). Individuals with pancreatic cancer had higher average annual exposure (9.4 µg/m3) as compared to IQR increase in average annual PM2.5 was associated with greater odds of pancreatic cancer (OR=1.20; 95% CI: 1.00-1.44). These findings highlight the link between elevated PM2.5 exposure and increased pancreatic cancer risk. They may inform screening strategies for high-risk populations and guide air pollution policies to mitigate exposure.

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.

Pragmatic strategies to address health disparities along the continuum of care in chronic liver disease.

Racial, ethnic, and socioeconomic disparities exist in the prevalence and natural history of chronic liver disease, access to care, and clinical outcomes. Solutions to improve health equity range widely, from digital health tools to policy changes. The current review outlines the disparities along the chronic liver disease health care continuum from screening and diagnosis to the management of cirrhosis and considerations of pre-liver and post-liver transplantation. Using a health equity research and implementation science framework, we offer pragmatic strategies to address barriers to implementing high-quality equitable care for patients with chronic liver disease.

Geography, inequities, and the social determinants of health in transplantation.

Among the causes of inequity in organ transplantation, geography is oft-cited but rarely defined with precision. Traditionally, geographic inequity has been characterized by variation in distance to transplant centers, availability of deceased organ donors, or the consequences of allocation systems that are inherently geographically based. Recent research has begun to explore the use of measures at various geographic levels to better understand how characteristics of a patient's geographic surroundings contribute to a broad range of transplant inequities. Within, we first explore the relationship between geography, inequities, and the social determinants of health. Next, we review methodologic considerations essential to geographic health research, and critically appraise how these techniques have been applied. Finally, we propose how to use geography to improve access to and outcomes of transplantation.

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.

Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART).

Objective: This study aims to introduce key concepts and methods that inform the design of studies that seek to quantify the causal effect of social determinants of health (SDOH) on access to and outcomes following organ transplant. Background: The causal pathways between SDOH and transplant outcomes are poorly understood. This is partially due to the unstandardized and incomplete capture of the complex interactions between patients, their neighborhood environments, the tertiary care system, and structural factors that impact access and outcomes. Designing studies to quantify the causal impact of these factors on transplant access and outcomes requires an understanding of the fundamental concepts of causal inference. Methods: We present an overview of fundamental concepts in causal inference, including the potential outcomes framework and direct acyclic graphs. We discuss how to conceptualize SDOH in a causal framework and provide applied examples to illustrate how bias is introduced. Results: There is a need for direct measures of SDOH, increased measurement of latent and mediating variables, and multi-level frameworks for research that examine health inequities across multiple health systems to generalize results. We illustrate that biases can arise due to socioeconomic status, race/ethnicity, and incongruencies in language between the patient and clinician. Conclusions: Progress towards an equitable transplant system requires establishing causal pathways between psychosocial risk factors, access, and outcomes. This is predicated on accurate and precise quantification of social risk, best facilitated by improved organization of health system data and multicenter efforts to collect and learn from it in ways relevant to specialties and service lines.

Residential Structural Racism and Prevalence of Chronic Health Conditions.

Importance: Studies elucidating determinants of residential neighborhood-level health inequities are needed. Objective: To quantify associations of structural racism indicators with neighborhood prevalence of chronic kidney disease (CKD), diabetes, and hypertension. Design, Setting, and Participants: This cross-sectional study used public data (2012-2018) and deidentified electronic health records (2017-2018) to describe the burden of structural racism and the prevalence of CKD, diabetes, and hypertension in 150 residential neighborhoods in Durham County, North Carolina, from US census block groups and quantified their associations using bayesian models accounting for spatial correlations and residents' age. Data were analyzed from January 2021 to May 2023. Exposures: Global (neighborhood percentage of White residents, economic-racial segregation, and area deprivation) and discrete (neighborhood child care centers, bus stops, tree cover, reported violent crime, impervious areas, evictions, election participation, income, poverty, education, unemployment, health insurance coverage, and police shootings) indicators of structural racism. Main Outcomes and Measures: Outcomes of interest were neighborhood prevalence of CKD, diabetes, and hypertension. Results: A total of 150 neighborhoods with a median (IQR) of 1708 (1109-2489) residents; median (IQR) of 2% (0%-6%) Asian residents, 30% (16%-56%) Black residents, 10% (4%-20%) Hispanic or Latino residents, 0% (0%-1%) Indigenous residents, and 44% (18%-70%) White residents; and median (IQR) residential income of $54 531 ($37 729.25-$78 895.25) were included in analyses. In models evaluating global indicators, greater burden of structural racism was associated with greater prevalence of CKD, diabetes, and hypertension (eg, per 1-SD decrease in neighborhood White population percentage: CKD prevalence ratio [PR], 1.27; 95% highest density interval [HDI], 1.18-1.35; diabetes PR, 1.43; 95% HDI, 1.37-1.52; hypertension PR, 1.19; 95% HDI, 1.14-1.25). Similarly in models evaluating discrete indicators, greater burden of structural racism was associated with greater neighborhood prevalence of CKD, diabetes, and hypertension (eg, per 1-SD increase in reported violent crime: CKD PR, 1.15; 95% HDI, 1.07-1.23; diabetes PR, 1.20; 95% HDI, 1.13-1.28; hypertension PR, 1.08; 95% HDI, 1.02-1.14). Conclusions and Relevance: This cross-sectional study found several global and discrete structural racism indicators associated with increased prevalence of health conditions in residential neighborhoods. Although inferences from this cross-sectional and ecological study warrant caution, they may help guide the development of future community health interventions.