Build Health Equity with Data Science | RTI Tech Talk Webinar
Public health officials at the federal and state levels have called for a better way to measure, predict, and adjust for social 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 concerning community-level social, behavioral, environmental, and economic factors for quality health care?
The Build Health Equity with Data Science webinar discussed how RTI Rarity takes an “artificially intelligent” approach to risk adjustment for local social determinants of health (SDoH). Drawing from a national dataset with over 150 small-area measures, RTI Rarity uses random forest models to understand life expectancy at birth, as well as other health outcomes, at the Census tract, ZIP code, and county levels across the U.S.
During this webinar, Local Social Inequity (LSI) scores—drawing on more than 150 measures across 10 domains of SDoH—were compared to other composite measures of SDoH. We also explained how LSI scores can be used to:
understand the impact of health care innovations, payment models, and interventions on SDoH in high-risk communities;
identify neighborhoods and areas at highest risk of poor outcomes for better targeting of interventions and resources;
account for factors outside of providers’ control for more fair and equitable performance/quality measurement and reimbursement.
Meet the Presenters
Lisa M. Lines, PhD, MPH, has an extensive background in both managing and contributing to successful research projects for both public- and private-sector clients and has more than 20 years of experience in health care research and consulting. She joined RTI in 2009 and has experience with program evaluations, large-scale database analyses (including machine learning and other “big data” methods), and interactive decision-analytic models, as well as literature reviews and policy analyses. Currently, Dr. Lines co-directs the RTI Rarity project, which has developed Local Social Inequity scores—a new approach to risk prediction and adjustment for social factors using artificial intelligence. In addition, she leads the Social Determinants of Health Workgroup for the HEALing Communities Study focused on the opioid epidemic. She is also a task leader for the national implementation of the Home Health CAHPS survey.
Jamie Humphrey, PhD, is a Health Geographer and Research Public Health Analyst in RTI International’s Center for Health Analytics, Media, and Policy. Dr. Humphrey has more than 10 years of experience using interdisciplinary quantitative and geospatial methods to develop, implement, and oversee research at the intersection of geography and public health. With a focus on geographic patterns and inequalities, she studies the social and spatial epidemiology of the built environment and a variety of health outcomes and behaviors. Currently, Dr. Humphrey is an associate project director for several projects that explore place-based inequities including the development of a Local Social Inequity score (RTI Rarity), the spatio-temporal evolution of opioid-related mortality and its relationship with community resources, and the spatial analysis of underage tobacco sales in New York.
Matt Brown is a Research Public Health Analyst in RTI International’s Center for Health Analytics, Media, and Policy. Mr. Brown has more than 10 years of experience building processes for extracting, transforming, validating, aggregating, and analyzing data from a variety of health domains. As RTI Rarity's Data Lead, he designed and coded the core algorithm for producing Rarity's underlying data. Elsewhere at RTI, he has helped build a nationwide database of primary care practices, performs quality checks for ACO quality measures, owns a portion of the Nielsen tobacco data processing workflow, and is working to aggregate all the available data sets within RTI.
Cindy D'Annunzio, MBA, is the Strategic Account Executive who supports the strategy and growth behind RTI’s projects for the Centers for Medicare & Medicaid Services (CMS). RTI's CMS portfolio includes implementing and evaluating CMMI models, quality measurement and reporting, data standardization and analysis, risk adjustment, economic analysis, and national survey programs, including Consumer Assessment of Health Care Providers and Systems. As a Managing Director, Ms. D’Annunzio is responsible for building partnerships, understanding consumers’ needs, and bridging the right solutions for those challenges.