Originally Aired - Tuesday, March 12 • 3:00 PM - 4:00 PM Eastern Time (US & Canada)
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Location: W206A
Type: General Education
Session ID: 51
Title: How AI-Driven SDOH Analytics Drives Improved Care for Vulnerable Populations
Description: Racial disparities in care and social determinants of health (SDOH) disproportionately impact people of color in the United States. In 2021, New Jersey’s Hackensack Meridian Health, which comprises two of the top 10 hospitals in New Jersey, partnered with a leader in predictive analytics to not only identify patients with high need of support based on their underlying health risks and/or SDoH needs, but also leverage artificial intelligence to eliminate selection bias. Known as the Healthy Connections Community Health Workers Initiative, this program achieved a nearly 5:1 return on investment, with a statistically significant increase in use of primary and specialty care and reduced ED visits and length of stay among program participants within just three months. In this presentation, Nicole Harris-Hollingsworth, vice president, Social Determinants of Health for Hackensack Meridian Health, and Jean-Claude Saghbini, CTO, Lumeris, will discuss ways to leverage AI—from predictive analytics to machine learning to generative AI—to avoid bias and improve health outcomes for vulnerable populations. They will also explain the importance of embedding nontraditional healthcare data and analytics in initiatives designed to improve health in high-needs populations.
Level: Intermediate
Format: 60-Minute Lecture
Learning Objective #1: Assess the potential for bias in AI-based models for addressing SDOH and why organizations must proactively address the potential for bias
Learning Objective #2: Explain how an AI-driven approach to addressing SDOH and reducing inequities in care decreases healthcare costs and utilization in vulnerable populations
Learning Objective #3: Discuss how a New Jersey program influenced about 10,000 participants to increase their use of primary and specialty care and decrease reliance on emergency department care
Learning Objective #4: Demonstrate the impressive results this program achieves in reducing healthcare costs and improving health outcomes via adjustments in utilization patterns
Learning Objective #5: Evaluate how AI initiatives can be leveraged to further improve healthcare outcomes in high-risk populations
