Brooklyn Digital Community Care Intervention to Address Unmet Social Needs and Optimize Engagement in Maternal Health Care

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Project Abstract Central Brooklyn is the epicenter of the maternal health crisis in New York City. The highest rates of severe maternal morbidity (SMM), considered “near misses” to maternal death, are found in Black immigrant women, who are concentrated in Central Brooklyn. This situation reflects a history of systemic racism and neglect. Women who lack adequate care throughout pregnancy and post-partum are at higher risk of SMM and death. To address this public health crisis, we will test the preliminary efficacy and acceptability of novel intervention prototype called We Care About Brooklyn (WeCAB), which integrates principles of an evidence-based community-centered care model and employs community health workers (CHWs) to connect with and support families while leveraging a digital social determinants of health (SDOH) screening and closed-loop referral system. We hypothesize that comprehensively addressing SDOH (basic survival needs such as food security, decent housing, and childcare) will reduce barriers to healthcare utilization and improve engagement in care throughout pregnancy and the post-partum period. We propose a mixed-methods study design with the following specific aims: 1) tailor the existing digital SDOH screening tool for Central Brooklyn and build clinician, client and community stakeholder fit to inform the CHW intervention training protocol; 2) conduct a pilot RCT of WeCAB in the Central Brooklyn maternal population to measure acceptability and preliminary efficacy of the system; and 3) identify barriers and facilitators to the adoption and integration of our intervention prototype into routine maternal care through key informant interviews and a post-intervention survey. WeCAB has the long-term potential to improve health during and after pregnancy in America’s historically marginalized maternal populations who experience a disproportionate burden of adverse health outcomes.