A Framework for an Intelligent Social Engagement Support System: Identifying and Addressing Challenges at Multiple...

Increasingly managed care organizations (MCOs) - health plans that offer covered health services through networks of healthcare providers and hospitals - are recognizing the role of social drivers of health on both health outcomes and unnecessary healthcare utilization (e.g., emergency department visits) and are taking actions. They are employing social care navigators (SCNs) and screening for social needs such as food, housing, and transportation. However, individuals with social needs can experience barriers to completing the screening and to receiving social care when referred. Additionally, the volume of people with social needs means that SCNs have high caseloads. Without guidance on how to prioritize their efforts, the people who have the highest social needs may not be identified or receive SCN support. To address the many problems, we developed a framework for an intelligent social engagement support system. This framework builds on the Health Care System domain of the National Institutes on Minority Health and Health Disparities' Health Disparities Research Framework as a foundation, leverages learning health system and community-engaged approaches, and incorporates machine learning at key points to create an adaptable, multi-level framework that is intended to have numerous positive outcomes, including reducing health disparities in socially-driven health outcomes. We discuss how we are using this framework and how we envision it could be adapted to different MCO contexts.