This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black). Later vintages of this layer have a different age group for children that includes age 18. This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Local, state, tribal, and federal agencies use health insurance coverage data to plan government programs, determine eligibility criteria, and encourage eligible people to participate in health insurance programs. This map shows where those with no health insurance live. Map opens in Houston, TX. Use the bookmarks or search to see other cities. Zoom out to see map render data for counties and states.

6 (%) in 2022. 12.2% (over 5.3 million) of adults with a mental illness remain uninsured. Under the Affordable Care Act (ACA), the US continues to see a decline in Americans who are uninsured. There was a 2.5% reduction from last year’s dataset. 46 states saw a reduction in Adults with AMI who are uninsured. The largest reductions were seen in South Carolina (7.1%), Missouri (6.3%), Arkansas (6.7%), Arizona (5.6%). The state prevalence of uninsured adults with mental illness ranges from 2.2% in Massachusetts to 23.0% in Texas.

Key Table Information.Table Title.Selected Characteristics of the Uninsured in the United States.Table ID.ACSST1Y2024.S2702.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Subject Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cit...

Key Table Information.Table Title.Selected Characteristics of the Uninsured in Puerto Rico.Table ID.ACSST1Y2024.S2702PR.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Subject Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities,...

13 (%) in 2022. 12.2% (over 5.3 million) of adults with a mental illness remain uninsured. Under the Affordable Care Act (ACA), the US continues to see a decline in Americans who are uninsured. There was a 2.5% reduction from last year’s dataset. 46 states saw a reduction in Adults with AMI who are uninsured. The largest reductions were seen in South Carolina (7.1%), Missouri (6.3%), Arkansas (6.7%), Arizona (5.6%). The state prevalence of uninsured adults with mental illness ranges from 2.2% in Massachusetts to 23.0% in Texas.

6 (%) in 2021. 12.2% (over 5.3 million) of adults with a mental illness remain uninsured. Under the Affordable Care Act (ACA), the US continues to see a decline in Americans who are uninsured. There was a 2.5% reduction from last year’s dataset. 46 states saw a reduction in Adults with AMI who are uninsured. The largest reductions were seen in South Carolina (7.1%), Missouri (6.3%), Arkansas (6.7%), Arizona (5.6%). The state prevalence of uninsured adults with mental illness ranges from 2.2% in Massachusetts to 23.0% in Texas.

We are releasing data that compares the HHS Provider Relief Fund and the CMS Accelerated and Advance Payments by State and provider as of May 15, 2020. This data is already available on other websites, but this chart brings the information together into one view for comparison. You can find additional information on the Accelerated and Advance Payments at the following links:

Fact Sheet: https://www.cms.gov/files/document/Accelerated-and-Advanced-Payments-Fact-Sheet.pdf;

Zip file on providers in each state: https://www.cms.gov/files/zip/accelerated-payment-provider-details-state.zip

Medicare Accelerated and Advance Payments State-by-State information and by Provider Type: https://www.cms.gov/files/document/covid-accelerated-and-advance-payments-state.pdf.

This file was assembled by HHS via CMS, HRSA and reviewed by leadership and compares the HHS Provider Relief Fund and the CMS Accelerated and Advance Payments by State and provider as of December 4, 2020.

HHS Provider Relief Fund President Trump is providing support to healthcare providers fighting the coronavirus disease 2019 (COVID-19) pandemic through the bipartisan Coronavirus Aid, Relief, & Economic Security Act and the Paycheck Protection Program and Health Care Enhancement Act, which provide a total of $175 billion for relief funds to hospitals and other healthcare providers on the front lines of the COVID-19 response. This funding supports healthcare-related expenses or lost revenue attributable to COVID-19 and ensures uninsured Americans can get treatment for COVID-19. HHS is distributing this Provider Relief Fund money and these payments do not need to be repaid. The Department allocated $50 billion of the Provider Relief Fund for general distribution to Medicare facilities and providers impacted by COVID-19, based on eligible providers' net reimbursement. It allocated another $22 billion to providers in areas particularly impacted by the COVID-19 outbreak, rural providers, and providers who serve low-income populations and uninsured Americans. HHS will be allocating the remaining funds in the near future.

As part of the Provider Relief Fund distribution, all providers have 45 days to attest that they meet certain criteria to keep the funding they received, including public disclosure. As of May 15, 2020, there has been a total of $34 billion in attested payments. The chart only includes those providers that have attested to the payments by that date. We will continue to update this information and add the additional providers and payments once their attestation is complete.

CMS Accelerated and Advance Payments Program On March 28, 2020, to increase cash flow to providers of services and suppliers impacted by the coronavirus disease 2019 (COVID-19) pandemic, the Centers for Medicare & Medicaid Services (CMS) expanded the Accelerated and Advance Payment Program to a broader group of Medicare Part A providers and Part B suppliers. Beginning on April 26, 2020, CMS stopped accepting new applications for the Advance Payment Program, and CMS began reevaluating all pending and new applications for Accelerated Payments in light of the availability of direct payments made through HHS’s Provider Relief Fund.

Since expanding the AAP program on March 28, 2020, CMS approved over 21,000 applications totaling $59.6 billion in payments to Part A providers, which includes hospitals, through May 18, 2020. For Part B suppliers—including doctors, non-physician practitioners and durable medical equipment suppliers— during the same time period, CMS approved almost 24,000 applications advancing $40.4 billion in payments. The AAP program is not a grant, and providers and suppliers are required to repay the loan.

CMS has published AAP data, as required by the Continuing Appropriations and Other Extensions Act of 2021, on this website: https://www.cms.gov/files/document/covid-medicare-accelerated-and-advance-payments-program-covid-19-public-health-emergency-payment.pdf

HHS is providing support to healthcare providers fighting the coronavirus disease 2019 (COVID-19) pandemic through the bipartisan Coronavirus Aid, Relief, & Economic Security (CARES) Act; the Paycheck Protection Program and Health Care Enhancement Act (PPPHCEA); and the Coronavirus Response and Relief Supplemental Appropriations (CRRSA) Act, which provide a total of $178 billion for relief funds to hospitals and other healthcare providers on the front lines of the COVID-19 response. This funding supports healthcare-related expenses or lost revenue attributable to COVID-19 and ensures uninsured Americans can get treatment for COVID-19. HHS is distributing this Provider Relief Fund (PRF) money and these payments do not need to be repaid.

The Department allocated $50 billion in PRF payments for general distribution to Medicare facilities and providers impacted by COVID-19, based on eligible providers' net reimbursement. HHS has made other PRF distributions to a wide array of health care providers and more information on those distributions can be found here: https://www.hhs.gov/coronavirus/cares-act-provider-relief-fund/data/index.html

This layer shows health insurance coverage by type and by age group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.