Sociodemographic and geospatial disparities in outcomes for patients with biliary atresia: A comprehensive analysis using national and state datasets

PROJECT SUMMARY / ABSTRACT Biliary atresia (BA) is the leading indication for pediatric liver transplant in United States and the leading indication for any solid organ transplant in a child less than 1 year old. Affected infants are usually born healthy but develop clinical manifestations of liver failure between 2 weeks and 2 months of age. Prompt diagnosis and surgical intervention with the Kasai portoenterostomy procedure, which can restore bile flow and delay liver transplant, are critical to short- and long-term disease outcomes. Unfortunately, factors that influence access to care, including race, ethnicity, and socioeconomics, have been shown to influence age at diagnosis of BA and Kasai procedure. These findings suggest an inadequacy in our current care paradigms and indicate that further work is needed to fully understand how disparities are shaping unequal BA outcomes. Specifically, it is critical to understand whether demographic, socioeconomic, and geographic factors influence disparities at additional time points, such as prior to diagnosis, post- Kasai procedure, and in age at liver transplant. Further clarity as to these outcomes will enable targeting of interventions and resources towards these time points, to enhance equity for this vulnerable population of children. Therefore, we propose a comprehensive analysis of clinically significant BA outcomes, at several time points along the disease continuum, stratified by race/ethnicity, neighborhood- level socioeconomic advantage, and geographic factors. In Aim 1, we will link two national databases to examine disease outcomes from Kasai surgery extending through liver transplant – including survival with native liver at 2, 5, and 10 years; readmissions after Kasai surgery; admissions for cirrhosis-associated conditions prior to transplant; MELD at time of transplant; and overall survival. These outcomes have not been examined with respect to race/ethnicity or socioeconomics. In Aim 2, we will examine a more granular statewide dataset detailing all emergency department and hospital admissions for children in California. We will build a cohort of infants diagnosed with BA across the state and examine outcomes within the first year of life, including age at diagnosis, age at first surgery, cumulative emergency and hospital admissions both prior to and after diagnosis, and survival without transplant at 1 year. The results of our analyses will indicate which sub-populations of children with BA are suffering worse outcomes and where along the disease continuum these differences occur. These findings will guide targeted interventions and policy decisions and will also equip me with specific skills in health equity science, advanced statistics, and geospatial analysis to propel me towards my career goal as a funded surgeon scientist.