Neonatal-Perinatal Medicine Fellow Stanford University School of Medicine Sunnyvale, California, United States
Background: Regionalization of care improves neonatal outcomes. Previous research demonstrates racial/ethnic differences in acute neonatal transports, suggesting differences in which infants are born in a risk-appropriate hospital, which may contribute to disparities in neonatal outcomes. Prior studies aggregate Asian American, Native Hawaiian, and Pacific Islander (AANHPI) infants, despite their heterogeneity in maternal characteristics and healthcare behaviors. This aggregation may obscure disparities in transfer patterns. Objective: To compare acute transport patterns in disaggregated and aggregated AANHPI infants born between 2012-2018. Design/Methods: This is a retrospective cohort study of infants born from 2012-2018 in California with a recorded maternal self-reported race/ethnicity using a dataset linking California birth records with the California Perinatal Quality Care Collaborative database to identify births and acute transfers. We will exclude infants who were born in hospitals with less than five births or who died within 24 hours of life. We will quantify patterns of delivery hospital use and acute infant transport and interactions between race/ethnicity subgroups using adjacency tests. Any reaggregation of disaggregated AANHPI groups will be based on the proportion of co-localization at delivery hospital. We will construct a network representation of the transfers, treating hospitals as “nodes,” and number of acute transfers making up the “edges,” enabling quantitative measures of network shape and structure to describe these networks. Network characteristics and infant/maternal variables will be included in a mixed-effects logistic regression model to identify differences in likelihood of infant acute transfer between infant race/ethnicity and to identify risk factors. This study has been approved by the Institutional Review Board. We have already constructed the linked dataset, and data analysis will be completed by February 2024.
