Roger Thorpe and Bianca Garcia Stellisano explored how organizations can use health data more meaningfully to design benefits and wellness programs. They emphasized moving beyond traditional claims data to include behavioral and early indicators like sleep, stress, diet, and burnout risk. By analyzing both lagging and leading indicators, organizations can better forecast costs, identify emerging trends, and take proactive action—whether adjusting reimbursement levels, supporting chronic conditions, or launching awareness campaigns like annual physicals.
They also discussed common barriers to data collection, such as privacy concerns and resource limitations, and encouraged starting with simple tools like annual surveys. Bianca noted that targeted wellness programs based on real employee data (e.g., fatigue or mental health challenges) are more impactful than general benchmarking. Roger concluded that data-informed plan design—focused on specific challenges like elder care or substance use—will differentiate progressive organizations that prioritize employee health and well-being.