ABSTRACT Maternal mortality and severe maternal morbidity (SMM) continue to rise in the United States, and women from low-income communities, minoritized racial/ethnic groups, and those with Medicaid or who are uninsured face increased risk. Hospital care at the time of delivery, and prenatal care during pregnancy, both occur late in the progression of conditions that are important to maternal outcomes. Therefore, expanding access to preconception care is a promising approach to improving maternal health and outcomes. Evidence-based preconception interventions include counseling patients on healthy behaviors (e.g. taking folic acid), managing chronic health conditions, and providing contraceptive care to plan timing of pregnancy. For many low-income women, a major barrier to receiving preconception care has been lack of health insurance coverage. The Affordable Care Act (ACA) reduced the uninsured rate among reproductive age women, giving women greater access to preconception care. Some states began implementing the ACA’s Medicaid coverage expansion in 2014, and women’s report of receiving counseling on preconception health increased significantly in Medicaid expansion states compared to non-expansion states. Prior research has identified an association between preconception care and decreased risk of SMM, particularly among women with a chronic disease. However, further research is needed to establish a causal effect. This study will harness the study team’s access to nationwide Medicaid claims data and leverage Medicaid expansion as a natural experiment to estimate the causal effect of preconception care on SMM for women insured by Medicaid. Analyzing existing Medicaid claims data will allow us to describe change in preconception care and SMM rates in expansion and non- expansion states (Aim 1). We will then use quasi-experimental design enabled by variation in state policy (i.e. timing of adopting Medicaid expansion) to estimate the causal effect of preconception care on risk of SMM, both in the Medicaid population overall and in sub-groups at highest risk based on medical history (e.g. chronic disease or history of prior SMM) or sociodemographic characteristics (Aim 2). We will also gain the nuanced perspectives of patients at high risk for SMM and clinicians who care for them, using qualitative focus groups and key informant interviews (Aim 3). By combining quantitative Medicaid claims and qualitative analyses, we will identify preconception interventions and approaches with high likelihood of reducing SMM, particularly for women at highest risk. We will translate these findings to develop a novel preconception care model that will be tested in future work.