Machine-learning (ML) prediction models are increasingly used in epidemiology to identify high-risk patients from electronic health records (EHRs), but equity and interpretability improve when clinical data are paired with social context and service-use information. Maternity Outcomes, Metrics and Evidence for periNaTal Services (MOMENTS) is a board-governed South Dakota (SD) maternal–infant database that integrates individual-level EHR data with individual- and community-level social determinants of health (SDoH) and public/health-service utilization data.  MOMENTS includes pregnant people receiving perinatal care at Avera Health-an integrated rural system spanning 72,000 sq. miles-and their infants (>26,000 dyads; >70% rural) from one year pre-pregnancy through one year postpartum. The database includes demographic, clinical, health services use, and social variables at the individual, household and community levels (e.g. Area Deprivation Index, SNAP/WIC participation). Key strengths include linkage of health-system records with state administrative data, longitudinal time-varying measures, referral services received, high data quality, and governed access under a formal policy structure. An example use case is a project recently funded by NIH focused on developing a trimester-specific ‘whole-person’ obstetric risk scores to reduce maternal morbidity. Outcomes include clinical and social sub-scores and an ensemble “whole-person” score using explainable statistical and machine learning models (e.g. XGBoost with SHAP-based variable ranking), internal training/validation, and performance metrics. Two stages of qualitative interviews will be conducted to help understand strategies to support the reach, effectiveness, adoption, implementation, and maintenance of the risk score. MOMENTS provides an opportunity to accelerate equitable use of ML research, while acknowledging its limitations of generalizability, data missingness, and misclassification related to EHR data, and small-area re-identification risk related to the inclusion of rural/frontier areas. This presentation will 1) describe MOMENTS development and governance, 2) highlight a use case, and 3) share lessons learned for other states or single-payer systems.