PROJECT SUMMARY AND ABSTRACT Few interventions successfully address racial disparities in maternal health outcomes. Social conditions—or social and structural determinants of health—are the major causes of persistent racial disparities in the US. Integrated models of care that offer home visiting and care coordination can support maternal health and have the potential to meaningfully reduce disparities. Prenatal care coordination (PNCC) is a fee-for-service Medicaid benefit, available in several states including Wisconsin. Its goal is to reduce rates of adverse birth outcomes including low birthweight and premature birth among mothers and infants at high risk. PNCC services include health education, care coordination, social support, and facilitating access to medical care and social services during pregnancy and up to 60 days following delivery for Medicaid-covered mothers. The long-term aim of this research is to improve the health outcomes of high-risk mothers and reduce disparities between racial and ethnic groups by strengthening the PNCC benefit’s implementation and impact. Specifically, this study aims to: 1: Describe the association of receiving PNCC services with five distinct maternal health outcomes among mothers who delivered in WI between 2011 and 2019. Leveraging a large, multisource data set, which links all Wisconsin birth records from 2011-2019 to Medicaid claims and other administrative data sources, we will develop regression models for each of five target outcomes: 1) adequate prenatal care, 2) a 6-week postpartum visit, 3) utilization of needed behavioral health services, 4) occurrence of severe maternal morbidity, and 5) emergency department visits, accounting for mother’s race and geographic location. 2: Evaluate the treatment effect of using a structured model of care to guide PNCC on the 5 target outcomes among mothers who received PNCC services between 2011 and 2019, (a) accounting for interactions with PNCC provider type and site type, and (b) additionally accounting for mother’s race and geographic location. Data will be analyzed using two-level logistic regression models with PNCC site type (public health department, clinical setting, community-based agency) at level 2 and provider type (nurse, community health worker, social worker) as a covariate, and individuals nested within those sites at level 1. 3: Qualitatively describe diverse PNCC providers’ perspectives on the relative advantage of using a structured model to guide PNCC services, implementation processes that impact PNCC, and target outcomes of PNCC. Using a deductive qualitative approach, we will conduct semi-structured interviews and focus groups at five PNCC sites across the state that vary by provider type and setting, and who serve clients from racially and ethnically diverse communities including Black and Native American mothers. Analyses will be framed by the Consolidated Framework for Implementation Science (CFIR), which describes factors that can ...