Leveraging American Community Survey (ACS) Data to Address Social Determinants of Health and Advance Health Equity
In a new issue brief for the Robert Wood Johnson Foundation’s State Health and Value Strategies, SHADAC Senior Researchers Lacey Hartman, MPP, Elizabeth Lukanen, MPH, and Colin Planalp, MPA explain how researchers and policymakers can leverage federal survey data to inform and target interventions that seek to address social determinants of health and advance health equity.
About the Issue Brief
As state Medicaid programs increasingly seek to understand and address social factors that contribute to poor health, they need data in order to identify priority areas of unmet social and economic needs, to execute SDOH initiatives, and to monitor and evaluate the impacts of these programs.
While Medicaid programs can choose to utilize data from a broad array of sources, this brief highlights several advantages to using data from one federal survey, the American Community Survey (ACS), to inform and target interventions that seek to address social determinants of health and advance health equity. The ACS contains a vast range of variables relevant to social determinants of health including but not limited to; food insecurity, unstable housing, and lack of access to social supports, and has a large sample size that supports estimates for smaller subpopulations.
This brief provides an overview of select social determinants of health measures and examples of how the data could be used to address questions and evaluate interventions related to housing, transportation, and nutrition. It also provides examples of states that use SDOH and health equity measures from the ACS, including which measures are used and what they are used for.
Access the new “Leveraging American Community Survey (ACS) Data to Address Social Determinants of Health and Advance Health Equity” brief in full to read more about how researchers can use federal-level SDOH survey data to advance health equity. Readers can also download the brief, along with a companion toolkit that includes a detailed data dictionary.
Support for this project was provided by the Robert Wood Johnson Foundation. The views expressed here do not necessarily reflect the views of the foundation.