Strategies for Using AI to Drive Population Health and Address SDOH

Health plans and providers recognize that challenges such as food insecurity or inadequate housing hinder optimal health outcomes without additional support extending beyond clinical care. Therefore, healthcare organizations must implement effective strategies to gather SDOH data and apply targeted interventions to improve population health outcomes. By adopting the right approaches, organizations can address SDOH and ensure patients receive the care they need, while simultaneously reducing costs, emergency services utilization, and employee burnout.To build effective SDOH strategies, payers and providers must leverage technology such as artificial intelligence (predictive and GenAI) to integrate diverse data from both public and private sources, including assessments, surveys, and social media. It is important to collect community-level SDOH information from publicly available databases, mapped to the census tract level, and combine it with experiential claims data and personal assessments to create comprehensive digital member profiles. These profiles are critical for machine learning (ML) and predictive next steps.