RTI Sponsor Session
Building Health Equity with Data Science
Public health officials have called for a better way to measure, predict, and adjust for social, behavioral, environmental, and economic factors in health care and population health. How can we employ data science to improve health equity? How can data from numerous sources be curated and used to inform decisions for quality health care and policy? RTI Rarity™ takes an “artificially intelligent” approach to risk adjustment for local social determinants of health (SDoH). By curating a national database of more than 200 area-level SDoH measures within ten domains at the Census tract, ZIP code, and county levels across the U.S., RTI Rarity provides high-resolution insights into factors that strongly influence health outcomes. Learn more about how these Local Social Inequity (LSI) scores compare to other composite measures of SDOH and how they can be used to understand the impact of health care innovations, payment models, and interventions on SDoH in high-risk communities, and more.
Learn more about RTI Rarity.
View the full agenda.