About

Our PopSim models, like some other mathematical simulations in healthcare, are important for understanding which public health strategies are expected to have the greatest value in terms of health outcomes and cost. In addition, our models provide insight into how these findings may vary by location or subgroup. For example, is insurance expansion expected to differentially benefit people who have historically been underserved, such as people of color or rural-dwelling people, in terms of cancer-related outcomes?

Our PopSim models are intended to be used as a “virtual world” in which to simulate population-level health and cost outcomes associated with alternate assumptions about population demographics, disease determinants, effects of clinical interventions or policies on health, and costs of healthcare use over time. This information is needed to provide state-level, system-level, and community-level data to decision-makers who are in positions to invest in public health interventions and policies to reduce cancer-related morbidity, mortality, and disparities. In particular, decision-makers can use this information to determine which strategies are most optimal and value-added depending on the target region and/or subgroup of interest.