PROJECT SUMMARY Social drivers of health (SDoH) are the largest factors affecting our health and wellbeing but are difficult for healthcare systems to address. The lack of healthy food, inadequate housing, and sparse social supports disproportionately affect individuals burdened by health disparities, both exacerbating chronic conditions and preventing people from receiving the care they need. The nearly 90 million Medicaid recipients are at particularly high risk with overrepresentation of individuals vulnerable to health disparities, including those with low or no income, racial or ethnic minorities, children, the elderly, or individuals with disabilities. Health systems face two problems when reaching beyond clinical care to improve patient health outcomes. The first problem is one of identification; providers undercode social needs in existing schemas and ancillary data collection methods such as social screens are not common, standardized, or easily shared. The second problem is a lack of engagement between individuals and social services, which is especially frustrating since there are many evidence-based practices that community-based organizations (CBOs) use to address social needs. Our project will apply a precision medicine approach to the identification of, and engagement with, Medicaid recipients with social needs. We will enhance the health information infrastructure of a managed care organization that coordinates benefits for over 250,000 Maryland Medicaid members by: ● Developing and deploying a set of machine learning models that use multiple individual- and community-level data sources to predict which members use the emergency department to fulfill social or non-urgent needs as opposed to treatment for urgent medical conditions. ● Developing and deploying an engagement support system that identifies and displays the characteristics of members that are predicted to prevent them from engaging with a CBO. ● Implementing a continuous qualitative and quantitative improvement process that identifies recurring themes and disengagement points in cases where members did not complete their social intervention. The study team is well positioned to develop a social needs intervention protocol and will include rigorous evaluations to assess the effects of our intervention on the health and social outcomes of participating members by their demographic and geographic characteristics. Together, our Aims will help identify and address social needs and shrink disparities in health outcomes across a large, high-risk population.

PROJECT NARRATIVE Existing healthcare data systems lack relevant information to support social interventions: it is difficult to identify individuals with social needs and difficult to facilitate their engagement with social service providers. This project will apply a precision medicine approach to the identification of, and engagement with, Medicaid recipients with social needs. We will help identify and address social needs and shrink disparities in health outcomes across a large, high-risk population while informing the next generation of value-based care paradigms.