The dataset has information on percentage of uninsured population with respect to different population characteristics, including federal poverty level, education, and language. The data here are for outreach targeting purposes only. The number of people with incomes at varying federal poverty levels is based on data from the Census Bureau’s American Community Survey (ACS) data for 2011.

Decrease the percentage of uninsured individuals from 17% in 2013 to 9.5% by 2019.

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

Uninsured ED Visits - This indicator shows the percentage of persons without health (medical) insurance who seek care through the Emergency Department. People without health insurance are more likely to be in poor health than the insured. Lack of health insurance can result in increased visits to the emergency department and decreased routine care visits with a primary care provider.

This layer shows the percentage of people without health insurance in the U.S. by state and county, from American Community Survey 5-year estimates: 2011-2015 (Table GCT2701). The map switches from state data to county data as the map zooms in. The national average was 13.0%, down from approximately 20% in 2005.A person’s ability to access health services has a profound effect on every aspect of his or her health. Many Americans do not have a primary care provider (PCP) or health center where they can receive regular medical services. People without medical insurance are more likely to lack a usual source of medical care, such as a PCP, and are more likely to skip routine medical care due to costs, increasing their risk for serious and disabling health conditions. When they do access health services, they are often burdened with large medical bills and out-of-pocket expenses. Increasing access to both routine medical care and medical insurance are vital steps in improving the health of all Americans.

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.

This data file indicates the estimated number of uninsured individuals ages 19-25 in each U.S. county. These individuals may be eligible to join their parents health plan if that plan offers dependent coverage. The data is based on the 2007 Small Area Health Insurance Estimates (SAHIE) and March 2008 Current Population Survey Annual Social and Economic Supplement (CPS-ASEC).

This data spotlight uses 2009 to 2011 National Survey on Drug Use and Health (NSDUH) to estimate the number of people without insurance who are likely to use behavioral health services after they become insured under the Affordable Care Act (ACA).

Abstract (en): In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. The Oregon Health Insurance Experiment follows and compares those selected in the lottery (treatment group) with those not selected (control group). The data collected and provided here include data from in-person interviews, three mail surveys, emergency department records, and administrative records on Medicaid enrollment, the initial lottery sign-up list, welfare benefits, and mortality. This data collection has seven data files: Dataset 1 contains administrative data on the lottery from the state of Oregon. These data include demographic characteristics that were recorded when individuals signed up for the lottery, date of lottery draw, and information on who was selected for the lottery, applied for the lotteried Medicaid plan if selected, and whose application for the lotteried plan was approved. Also included are Oregon mortality data for 2008 and 2009. Dataset 2 contains information from the state of Oregon on the individuals' participation in Medicaid, Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance to Needy Families (TANF). Datasets 3-5 contain the data from the initial, six month, and 12 month mail surveys, respectively. Topics covered by the surveys include demographic characteristics; health insurance, access to health care and health care utilization; health care needs, experiences, and costs; overall health status and changes in health; and depression and medical conditions and use of medications to treat them. Dataset 6 contains an analysis subset of the variables from the in-person interviews. Topics covered by the survey questionnaire include overall health, health insurance coverage, health care access, health care utilization, conditions and treatments, health behaviors, medical and dental costs, and demographic characteristics. The interviewers also obtained blood pressure and anthropometric measurements and collected dried blood spots to measure levels of cholesterol, glycated hemoglobin and C-reactive protein. Dataset 7 contains an analysis subset of the variables the study obtained for all emergency department (ED) visits to twelve hospitals in the Portland area during 2007-2009. These variables capture total hospital costs, ED costs, and the number of ED visits categorized by time of the visit (daytime weekday or nighttime and weekends), necessity of the visit (emergent, ED care needed, non-preventable; emergent, ED care needed, preventable; emergent, primary care treatable), ambulatory case sensitive status, whether or not the patient was hospitalized, and the reason for the visit (e.g., injury, abdominal pain, chest pain, headache, and mental disorders). The collection also includes a ZIP archive (Dataset 8) with Stata programs that replicate analyses reported in three articles by the principal investigators and others: Finkelstein, Amy et al "The Oregon Health Insurance Experiment: Evidence from the First Year". The Quarterly Journal of Economics. August 2012. Vol 127(3). Baicker, Katherine et al "The Oregon Experiment - Effects of Medicaid on Clinical Outcomes". New England Journal of Medicine. 2 May 2013. Vol 368(18). Taubman, Sarah et al "Medicaid Increases Emergency Department Use: Evidence from Oregon's Health Insurance Experiment". Science. 2 Jan 2014. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Presence of Common Scales: Patient Health Questionnaire-9 (PHQ-9) Total Severity Score SF-8 Health Survey Physical Component Score SF-8 Health Survey Mental Component Score Framingham Risk Score Response Rates: For the mail surveys, the response rates were 45 percent for the initial survey, 49 percent for the six month survey, and 41 percent for the 12 month survey. For the in-person survey the response rate was 59 percent. The individu...

This report looks at SAMHSA Block Grants that serve as a safety net for individuals without health insurance or other resources who seek specialty substance use treatment and prevention services. Under the Affordable Care Act, some of the treatment options that were covered by the SAMHSA Block Grants are likely to be covered by the expansion in Medicaid. Despite the expected increase in Medicaid enrollment, this short report finds that the Substance Abuse Prevention and Treatment Block Grant (SAPT) will still be important in paying for specialty substance abuse treatment for uninsured, low-income individuals.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). This indicator includes adults who reported it is somewhat or very difficult to obtain needed medical care.The vast majority of adults and children in Los Angeles County have health insurance, in large part due to outreach efforts and local insurance availability for children and the expansion of insurance coverage following the passage of the federal Affordable Care Act in 2012. Despite this progress, rates of uninsured remain high in some communities. Even among people who have health insurance, many continue to experience difficulties accessing needed healthcare. Cities and community organizations can play an important role in advocating for needed services and in providing information on free or low-cost services in their communities. Hospitals can also provide medical and dental services through their community benefit programs and other community services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

In order to facilitate public review and access, enrollment data published on the Open Data Portal is provided as promptly as possible after the end of each month or year, as applicable to the data set. Due to eligibility policies and operational processes, enrollment can vary slightly after publication. Please be aware of the point-in-time nature of the published data when comparing to other data published or shared by the Department of Social Services, as this data may vary slightly. As a general practice, for monthly data sets published on the Open Data Portal, DSS will continue to refresh the monthly enrollment data for three months, after which time it will remain static. For example, when March data is published the data in January and February will be refreshed. When April data is published, February and March data will be refreshed, but January will not change. This allows the Department to account for the most common enrollment variations in published data while also ensuring that data remains as stable as possible over time. In the event of a significant change in enrollment data, the Department may republish reports and will notate such republication dates and reasons accordingly. In March 2020, Connecticut opted to add a new Medicaid coverage group: the COVID-19 Testing Coverage for the Uninsured. Enrollment data on this limited-benefit Medicaid coverage group is being incorporated into Medicaid data effective January 1, 2021. Enrollment data for this coverage group prior to January 1, 2021, was listed under State Funded Medical. Effective January 1, 2021, this coverage group have been separated: (1) the COVID-19 Testing Coverage for the Uninsured is now G06-I and is now listed as a limited benefit plan that rolls up into “Program Name” of Medicaid and “Medical Benefit Plan” of HUSKY Limited Benefit; (2) the emergency medical coverage has been separated into G06-II as a limited benefit plan that rolls up into “Program Name” of Emergency Medical and “Medical Benefit Plan” of Other Medical. An historical accounting of enrollment of the specific coverage group starting in calendar year 2020 will also be published separately. The data represents number of active recipients who received benefits from a type of assistance (TOA) in that calendar year and month. A recipient may have received benefits from multiple TOAs in the same month; if so that recipient will be included in multiple categories in this dataset (counted more than once.) For privacy considerations, a count of zero is used for counts less than five. The methodology for determining the address of the recipients changed: 1. The address of a recipient in the ImpaCT system is now correctly determined specific to that month instead of using the address of the most recent month. This resulted in some shuffling of the recipients among townships starting in October 2016. 2. If, in a given month, a recipient has benefit records in both the HIX system and in the ImpaCT system, the address of the recipient is now calculated as follows to resolve conflicts: Use the residential address in ImpaCT if it exists, else use the mailing address in ImpaCT if it exists, else use the address in HIX. This resulted in a reduction in counts for most townships starting in March 2017 because a single address is now used instead of two when the systems do not agree.

This data set provides de-identified population data for Hypertension and Hyperlipidemia comorbidity prevalence. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 and 2016 calendar years.

Disclaimer: Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

The COVID-19 Claims Reimbursement to Health Care Providers and Facilities for Testing, Treatment, and Vaccine Administration for the Uninsured Program provides reimbursements on a rolling basis directly to eligible health care entities for claims that are attributed to the testing, treatment, and or vaccine administration of COVID-19 for uninsured individuals. The program funding information is as follow:

TESTING The American Rescue Plan Act (ARP) which provided $4.8 billion to reimburse providers for testing the uninsured; the Families First Coronavirus Response Act (FFCRA) Relief Fund, which includes funds received from the Public Health and Social Services Emergency Fund, as appropriated in the FFCRCA (P.L. 116-127) and the Paycheck Protection Program and Health Care Enhancement Act (P.L. 116-139) (PPPHCEA), which each appropriated $1 billion to reimburse health care entities for conducting COVID-19 testing for the uninsured.

TREATMENT & VACCINATION The Provider Relief Fund, which includes funds received from the Public Health and Social Services Emergency Fund, as appropriated in the Coronavirus Aid, Relief, and Economic Security (CARES) Act (P.L. 116-136), provided $100 billion in relief funds. The PPPHCEA appropriated an additional $75 billion in relief funds and the Coronavirus Response and Relief Supplemental Appropriations (CRRSA) Act (P.L. 116-260) appropriated another $3 billion. Within the Provider Relief Fund, a portion of the funding from these sources will be used to support healthcare-related expenses attributable to the treatment of uninsured individuals with COVID-19 and vaccination of uninsured individuals. To learn more about the program, visit: https://www.hrsa.gov/CovidUninsuredClaim

This dataset represents the list of health care entities who have agreed to the Terms and Conditions and received claims reimbursement for COVID-19 testing of uninsured individuals, vaccine administration and treatment for uninsured individuals with a COVID-19 diagnosis.

For Provider Relief Fund Data - https://data.cdc.gov/Administrative/HHS-Provider-Relief-Fund/kh8y-3es6

Between September and November 1998, California HealthCare Foundation commissioned a survey from the Field Research Corporation to gain insight into the reasons that some people purchase individual (nongroup) health insurance while others remain uninsured. This study compares a sample from each group -- uninsured and individually insured -- meeting the same minimum household income definition of at least 200 percent above the federal poverty level. Telephone interviews were conducted with 1,009 nonpoor uninsured individuals between the ages of 19 and 64 regarding current utilization of and expenditures for medical care, satisfaction with current sources of care, attitudes toward health insurance, perception of the cost of health insurance, willingness to pay, experiences with health insurance, and reasons for not purchasing health insurance. Interviews were also conducted with 802 individuals between the ages of 19 and 64 who had purchased individual (nongroup) health insurance. The questionnaire for the insured group was identical to the questionnaire for the uninsured group, with two exceptions: it did not include perceptions of the cost of health insurance or willingness to pay, and added questions regarding type and cost of health insurance purchased. In all, 1,811 interviews were conducted: 1,782 in English and 29 in Spanish. Demographic variables for both groups include age, gender, employment, and education.

These datasets provide de-identified insurance data for diabetes. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 and calendar years. Disclaimer: Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.

This table shows the number of uninsured people against health costs on a reference date, broken down by GGD region (Municipal Health Service), age and gender. With effect from 2006, the number of uninsured people has been defined as the number of people who are registered in the GBA (Municipal Personal Records Database) and who are obliged to take out insurance under the Health Insurance Act, but who have not taken out health insurance as referred to in that law. The limitation to the number of uninsured persons in the GBA means that uninsured persons among illegal immigrants, cross-border workers who live abroad and work in the Netherlands and Dutch nationals who live abroad (for example the so-called pensioners) are not taken into account. Data available: 2006-2010 Status of the figures: The figures in the table for 2006 up to and including 2009 are final figures. The figures for 2010 are provisional figures. Changes as of June 6, 2012: This table has been discontinued. When will new numbers come out? This table has been discontinued. For further information see Statistics Netherlands starts new series Uninsured against health insurance.

These datasets provide de-identified insurance data for hypertension hyperlipidemia. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 and 2016 calendar years.

Disclaimer: Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

These datasets provide de-identified insurance data for hyperlipidemia. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 and 2016 calendar years.

Disclaimer: Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

The mission of the Bay Area Health Task Force (BAHTF) was to address the issues and problems of the growing number of people who were uninsured for health care. With the support of the Robert Wood Johnson Foundation, BAHTF established the Health Insurance Helpline, which provided health insurance information and referrals for small businesses. This data collection was produced in order to evaluate this Helpline. The data collection consists of four sets of data, one from each year that the Helpline service was offered (1989 through 1992). The unit of analysis is calls received by the Helpline, which were categorized by the type of caller (business, individual, other) and type of service received (broker referral, guidebook only, other). Callers were generally categorized as insured businesses, uninsured businesses, insured individuals, or uninsured individuals. (The category "other" was left for callers who could not be clearly classified as business or individual callers.) A follow-up was conducted for over a quarter of the callers to obtain feedback about the program. Callers provided information concerning their reason for calling, the number of employees they had working full-time, the nature of their business firm, whether the business firm offered health insurance, and which plan they offered.

These Census Tract-level datasets described here provide de-identified diagnosis data for customers of three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) that have filed a claim for anxiety medications in 2015 and 2016. The data also includes the number of enrolled members in the three participating managed care organizations in 2015 and 2016.

Disclaimer: Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.