Measuring Neonatal Regionalization

Care and outcomes for the 60,000 very low-birth-weight (VLBW; 290,000 VLBW infants (>50% of all VLBW infants in the United States) in ~520 NICUs using linked vital records and patient discharge data from 17 states. This study is designed to achieve 3 specific aims: 1) Quantify regionalization and structure of transfer networks for VLBW infants across the United States; 2) Test the association of network structure with clinical quality of care and outcomes; and 3) Model optimized structure of perinatal transfers networks. Our analyses will employ network analysis as an innovative tool to measure care regionalization focusing on a high impact primary outcome (survival without major morbidity), as a substantive departure from prior work. Machine learning will be used to provide information on optimal network structures in terms of effectiveness, equity and efficiency. These models will reveal how networks would need to be modified to satisfy optimization goals and reveal potential trade-offs. We have a long track record of impactful research funded by the National Institute of Health using this data. We also have an opportunity to investigate more granular questions in California (140 NICUs), which has unique existing linkages to maternal and infant clinical and transport data. We expect our research to have an immediate positive impact because it is designed to result in actionable information for policy makers, administrators and clinicians to improve perinatal care delivery and equity.