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Leveraging American Community Survey (ACS) data to address social determinants of health and advance health equity
Leveraging American Community Survey (ACS) data to address social determinants of health and advance health equity
- Collection:
- Health Policy and Services Research
- Alternate Title(s):
- Leveraging ACS data to address social determinants of health and advance health equity
- Contributor(s):
- Woodrow Wilson School of Public and International Affairs. State Health and Value Strategies, issuing body.
Robert Wood Johnson Foundation, issuing body.
State Health Access Data Assistance Center, University of Minnesota, issuing body. - Publication:
- [Minneapolis, Minnesota] : State Health Access Data Assistance Center, University of Minnesota, February 2020
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Health Equity
Health Surveys
Social Determinants of Health
United States - Genre(s):
- Technical Report
- Abstract:
- State Medicaid programs are increasingly seeking to understand and address social factors that contribute to poor health--such as food insecurity, unstable housing, and a lack of access to social supports--in order to lower costs, improve outcomes for their members, and advance health equity. Health equity can be defined as when "everyone has a fair and just opportunity to be as healthy as possible. This requires removing obstacles to health such as poverty, discrimination, and their consequences, including powerlessness and lack of access to good jobs with fair pay, quality education and housing, safe environments, and health care." To inform this work of addressing the social determinants of health (SDOH) and advancing health equity, states and Medicaid officials need data in order to identify priority areas of unmet social and economic needs, execute SDOH initiatives, and monitor and evaluate the impacts of these programs. Increasingly, states are leveraging a broad array of data sources to support efforts to address health equity (see Table 1). While those sources closest to the Medicaid program are the most widely used, each has advantages and disadvantages. Data from providers are extremely rich but can be challenging to collect and extract information in a uniform way. Similarly, while data from other state agencies have great depth (e.g., incarceration history, housing history, information on food security), using them may require lengthy data use agreement (DUA) negotiations, and matching individuals across agencies can be complex. Commercial data can provide insights on comparison populations (e.g., those with employer-sponsored insurance) or fill other data gaps (e.g., information on patient or consumer preferences), but it can be expensive to obtain and analyze. Federal survey data also have important advantages and disadvantages. For example, survey data cannot provide direct information about the service use of people enrolled in Medicaid; however, the data are broad in scope, easy to access, and able to support population-level analysis. In addition, while obtaining complete information on race, ethnicity, and language (also known as "REL" data) continues to be challenging for providers and insurers, federal surveys have adapted a variety of techniques (such as detailed probes and imputations) to improve the reliability and consistency of this information.3 This makes federal survey data particularly valuable for understanding and developing strategies that address health equity. When used as part of a broader data strategy, federal survey data can be a powerful additional tool for Medicaid programs seeking to measure social determinants of health in ways that can guide efforts to address health equity. In this brief, we focus on how Medicaid programs can use 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. We focus on the ACS because it contains content relevant to a range of social determinants of health, such as housing, income, and food supports, and has a large sample size that supports estimates for smaller subpopulations and geographic areas. This brief also highlights relevant examples from states that use SDOH and health equity measures from the ACS, including which measures and what they are used for.
- Copyright:
- Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY-NC-ND license. (More information)
- Extent:
- 1 online resource (1 PDF file (8 pages))
- NLM Unique ID:
- 101772119 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/101772119