PURPOSE: Health policy simulation models incorporate disease processes but often ignore social processes that influence health outcomes, potentially leading to suboptimal policy recommendations. To address this gap, we developed a novel decision-analytic modeling framework to integrate social processes. METHODS: We evaluated a simplified decision problem using two models: a standard decision-analytic model and a model incorporating our social factors framework. The standard model simulated individuals transitioning through three disease natural history states-healthy, sick, and dead-without accounting for differential health system utilization. Our social factors framework incorporated heterogeneous health insurance coverage, which influenced disease progression and health system utilization. We assessed the impact of a new treatment on a cohort of 100,000 healthy, non-Hispanic Black and non-Hispanic white 40-year-old adults. Main outcomes included life expectancy, cumulative incidence and duration of sickness, and health system utilization over the lifetime. Secondary outcomes included costs, quality-adjusted life years, and incremental cost-effectiveness ratios. RESULTS: In the standard model, the new treatment increased life expectancy by 2.7 years for both non-Hispanic Black and non-Hispanic white adults, without affecting racial/ethnic gaps in life expectancy. However, incorporating known racial/ethnic disparities in health insurance coverage with the social factors framework led to smaller life expectancy gains for non-Hispanic Black adults (2.0 years) compared to non-Hispanic white adults (2.2 years), increasing racial/ethnic disparities in life expectancy. LIMITATIONS: The availability of social factors and complexity of causal pathways between factors may pose challenges in applying our social factors framework. CONCLUSIONS: Excluding social processes from health policy modeling can result in unrealistic projections and biased policy recommendations. Incorporating a social factors framework enhances simulation models' effectiveness in evaluating interventions with health equity implications.