Maternal health expert feedback on the attributes of a predictive analytics tool to improve pregnancy-related cardiovascular and mental health outcomes in the United States

Abstract

ABSTRACT Identify pregnancy-related challenges and opportunities to improve maternal health care in the United States and understand the potential role of predictive analytics tool(s) in bridging the existing gaps, specifically, in CVD (cardiovascular disease) and depression. Experts in maternal health care, research, patient advocacy, CVD, psychiatry, and technology were interviewed during February and March of 2020. Additionally, published literature was reviewed to assess existing data, insights, and best practices that might help develop effective predictive analytics tool(s). The majority (78%) of the 18 experts interviewed were women. The feedback revealed several insights, including multiple barriers to diagnosis and treatment of pregnancy-related CVD and depression. In experts’ collective opinion, predictive analytics could play an important role in maternal health care and in limiting pregnancy-related CVD and depression, but it must be grounded in quality data and integrate with existing health management systems. A holistic approach to maternal health that factors in racial-ethnic, regional, and socioeconomic disparities is needed that starts with preconception counseling and continues through 1 year postpartum. Predictive analytics tool(s) that are based on diverse and high-quality data could bridge some of the existing gaps in maternal health care and potentially help limit pregnancy-related CVD and depression.