Abstract Rates of pregnancy-associated and related morbidity and mortality (PRAMM) are far higher in the U.S. than in any other high-income country. Technology has clear potential for reduction of PRAMM by providing screening, tailored digital content, and connection to live assistance. Digital approaches also provide tremendous scalability and potential for long-term optimization. Finally, technology that is sufficiently flexible and easy to use—as is the platform used in this project—can also support deep community input through direct content creation. The proposed study builds upon an existing app (the Pregnancy Checkup) developed by project PI Ondersma, already integrated with antenatal services throughout Michigan, that provides universal digital screening for health risks, a brief motivational intervention, and referral to services. The proposed project will create the Pregnancy Checkup- PRAMM (PC-PRAMM) by extending the Pregnancy Checkup in two ways: (1) adding elements to address key determinants of PRAMM risks at four distinct levels (individual, support system, provider, and community), with further optimization to address the needs of women disproportionately affected; and (2) providing pregnant participants with immediate and secure “live chat” text access to a Community Health Worker who can facilitate warm handoffs to local services. Development of PC-PRAMM will use an innovative community partnered approach to co-creating app content. The PC-PRAMM will target known preventable determinants of PRAMM at four levels throughout pregnancy and the first year postpartum. Our first specific aim is to collaborate with pregnant and postpartum women, healthcare providers, family members, and researchers to develop the PC-PRAMM, including a manual for CHWs providing live chat assistance and facilitating engagement in services. Our second specific aim is to evaluate PC-PRAMM effects using a cluster randomized design in 10 antenatal care clinics throughout Michigan (N = 500 participants receiving Medicaid and enrolled at less than 20 weeks gestation). We will measure change on an index of PRAMM risk factors directly targeted by the PC-PRAMM (e.g., substance use, treatment-seeking, partner violence, early warning sign awareness, mental health); total PRAMM among trial participants through 1 year postpartum as measured using a pre-existing linked dataset of Medicaid claims, deaths, birth records, and primary care program data, and disparities in both measures. This innovative community-engaged trial will translate key findings from PRAMM research into a technology-driven intervention with strong potential for cost-effective dissemination. If supported, this approach could provide a highly scalable approach to PRAMM reduction. Further, the novel open-source platform on which the PC-PRAMM is built would allow long-term optimization and adaptation based on new findings, quality improvement, and regional needs.