Gathering deep insights into communities from advanced data science methods and geospatial analytics

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. The RTI Rarity project takes an “artificially intelligent” approach to inform decisions concerning community-level social, behavioral, environmental, and economic factors for quality health care. By curating a national database of more than 200 area-level social determinants of health (SDoH) measures within ten domains at the Census tract, ZIP code, and county levels across the U.S., the RTI Rarity tool provides high-resolution insights into factors that strongly influence health outcomes.

The RTI Rarity tool uses supervised machine learning, including random forests and other state-of-the-art predictive methods, to create local social inequity (LSI) scores drawing on the SDoH measures. The health equity analysis tool and its underlying data allow for the development of both within-state and cross-state summary scores and ten domain-specific sub scores informed by our conceptual framework. The scores yield meaningful insights into the neighborhood-level factors driving local health outcomes.

Download the RTI Rarity Overview

View the RTI Rarity conceptual framework and learn more about the health data used in the RTI Rarity tool that come from 38 different publicly available federal, state, and nonprofit/academic resources, including the American Community Survey, USDA’s Food Environment Atlas, CDC’s Wide-ranging ONline Data for Epidemiologic Research (WONDER), HUD, Child Opportunity Index, Opportunity Atlas, and more.

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The Impact of LSI Scores on Health Equity

The RTI Rarity LSI scores have been benchmarked against three existing area-based composite measures related to SDoH: the Area Deprivation Index (ADI), the Social Deprivation Index (SDI), and the Social Vulnerability Index (SVI). In terms of life expectancy at birth, the LSI leads in explaining 67% of the variance across the US, whereas the SVI only explains 26%, the SDI explains 29%, and the ADI explains 43%. In other words, the LSI measure accounts for substantially more of the disparity between the neighborhoods with the highest and lowest life expectancies across the U.S.

The RTI Rarity LSI scores can also be linked with individual-level data to improve predictions of individual outcomes. In population-based analyses, these 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.

Rochester is one of the most racially segregated mid-size cities in New York state and the fifth poorest in the country. Poverty rates, average home values, and unemployment rates within the highest LSI Census tract are all substantially different compared to that of the low LSI tract.

Improving Health Equity and Outcomes via RTI Rarity LSI Scores

With the data LSI scores provide, organizations can draw insights to inform factors that can strongly influence and improve health outcomes. The RTI Rarity project merges AI and data science in a risk adjustment framework with high-resolution SDoH data, all through a health equity lens. We aim to provide the local context that will enable researchers, policy makers, and health care systems to better account for, and address, SDoH across the life course.    

The Child and Family Wellbeing Dashboard

The Child and Family Wellbeing Dashboard brings together publicly available and restricted-access geospatial data into one interactive tool to visualize how risk and protective factors influence child welfare outcomes. It provides a comprehensive picture of the geographic risk and protective factors for child wellbeing, safety, and permanency—accounting for both social and environmental factors—to enable strategic resource planning.

View the dashboard about The Child and Family Wellbeing Dashboard

ASTHO Podcast Interview: Ep 209: New Tool Predicts PH Risks, featuring Dr. Lisa Lines

Dr. Lisa Lines joins the Association of State and Territorial Health Officials (ASTHO) Public Health Review Morning Edition podcast to discuss how the RTI Rarity tool can help public health leaders measure, predict, and respond to social factors that impact population health.

Listen now about ASTHO Podcast Interview: Ep 209: New Tool Predicts PH Risks, featuring Dr. Lisa Lines

Health Equity goRED Talk, featuring Dr. Stephanie Hawkins

The American Heart Association's goRED Talks help educate, entertain, and inspire women to take action and prioritize their heart health. View Dr. Stephanie Hawkins' presentation during the Health Equity goRED Talk, where she uses RTI Rarity data to understand and visualize her personal experience with health equity.

Watch the recording about Health Equity goRED Talk, featuring Dr. Stephanie Hawkins

Learn more about RTI's Health Equity work and our commitment to advancing equity through TRUE: RTI's Transformative Research Unit for Equity.

Contact us using the form below to learn more about the RTI Rarity tool and how you can access insights to improve health equity.

Disclaimer: This piece was written by Lisa M. Lines (Senior Health Services Researcher) to share perspectives on a topic of interest. Expression of opinions within are those of the author or authors.