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The percent without health insurance of Los Angeles County, CA was 21.50% for 18 to 64, all races, both sexes and all income levels in 2014.

Percent Uninsured

Percent Uninsured by Income Level

Percent Uninsured by Race

The Small Area Health Insurance Estimate (SAHIE) estimates health insurance coverage from the American Community Survey (ACS).

Above charts are based on data from the Small Area Health Insurance Estimate | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Health and Health Insurance Datasets Involving Los Angeles County, CA

  • API

    City Employee Payroll (Current)

    controllerdata.lacity.org | Last Updated 2024-05-10T12:08:48.000Z

    Payroll information for all Los Angeles City Employees including the City's three proprietary departments: Water and Power, Airports and Harbor. Data is updated bi-weekly by the Los Angeles City Controller's Office. Payroll information for employees of the Department of Water and Power is updated every three months.

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    City Employee Payroll (2013-2018)

    controllerdata.lacity.org | Last Updated 2021-02-09T23:34:48.000Z

    Note this dataset is no longer being updated. Please use the updated payroll dataset with current pay year information: https://controllerdata.lacity.org/Payroll/City-Employee-Payroll-Current-/g9h8-fvhu. Payroll information for all Los Angeles City Employees including the City's three proprietary departments: Water and Power, Airports and Harbor. Data is updated on a quarterly basis by the Los Angeles City Controller's Office. Payroll information for employees of the Department of Water and Power is provided by the Department.

  • API

    MCG Group Health Plan Rates

    data.montgomerycountymd.gov | Last Updated 2023-04-04T00:00:46.000Z

    Montgomery County offers medical, prescription, vision and dental plans for our employees, their families and their partners. Employees can choose between two Point-of-Service (POS) plans with CareFirst Blue Cross and Blue Shield (BCBS) and two Health Maintenance Organizations (HMO’s) with United HealthCare and Kaiser; two prescription plans with Caremark; National Vision Administrators (NVA) plan and two PPO and DHMO dental plans with United Concordia. The dataset contains all available plan rates, provider websites and contact numbers. In addition, this information is also available on the Office of Human Resources (OHR) website at https://www.montgomerycountymd.gov/HR/Benefits/EmployeeMedical.html#1 Update Frequency : Annually

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    Education, Health, And Transportation Demographics

    data.orcities.org | Last Updated 2017-01-06T16:41:02.000Z

    Data from the American Community Survey 2014 on all LOC member cities. This dataset includes select information for education, health and transportation statistics.

  • API

    Taxes by County and Industry in Colorado

    data.colorado.gov | Last Updated 2024-05-14T11:00:30.000Z

    Sales Tax information is summarized monthly at the county level by industry. Net Tax for the monthly filing period are summarized by county and industry in this report including tax totals. Contains fields like agriculture, clothing, food & beverage, etc. This data set is provided by the Department of Revenue (CDOR).

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    Vital Signs: Migration - Bay Area

    data.bayareametro.gov | Last Updated 2019-10-25T20:40:04.000Z

    VITAL SIGNS INDICATOR Migration (EQ4) FULL MEASURE NAME Migration flows LAST UPDATED December 2018 DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables. DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration. Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23) One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

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    VEHSS Composite Prevalence Estimates

    data.cdc.gov | Last Updated 2023-09-21T15:47:32.000Z

    VEHSS Composite Prevalence Estimates 2017, 2019, 2021. This dataset contains estimates of the prevalence of visual acuity loss and major eye diseases generated using a Bayesian meta-analytic modeling approach that combines information from multiple data sources to produce comprehensive estimates of prevalence by age, race, and gender at the national, state and county levels. These composite prevalence estimates are the primary surveillance measures developed by the Centers for Disease Control and Prevention’s Vision & Eye Health Surveillance System (VEHSS). For more information about these estimates including summary tables and maps, methods, and links to related publications visit https://www.cdc.gov/visionhealth/vehss/estimates/index.html To view this data in the VEHSS interactive data visualization application, visit https://ddt-vehss.cdc.gov/ and search for “VEHSS Composite Prevalence Estimate”. Visual Acuity Loss: Visual acuity loss prevalence estimates represent best-corrected visual acuity in the better-seeing eye and are included in rows where Category=’Measured Visual Acuity’. Rows with Subgroup = ‘Any vision loss' represents any impairment or blindness of 20/40 or worse; rows with Subgroup = 'US-defined blindness' refers to the subset of vision loss that is 20/200 or worse. Age Related Macular Degeneration: The age-related macular degeneration (AMD) estimates represent AMD as measured with retinal imaging examination, and are included in rows where Category = ‘Age Related Macular Degeneration’. The Subgroup ‘Vision threatening AMD’ includes patients with geographic atrophy, wet-form AMD, or choroidal neovascularization in either eye. The Subgroup ‘Non-vision threatening AMD’ includes patients with early or intermediate dry-form AMD defined as retinal pigment epithelium abnormalities or drusen ≥125 µm in the worse-affected eye, and do not have vision threatening AMD. Diabetic Retinopathy: The diabetic retinopathy (DR) estimates represent DR as measured with retinal imaging examination, and are included in rows where Category=’Diabetic Eye Diseases’. The Subgroup ‘Vision threatening DR’ includes patients with severe non-proliferative DR, proliferative DR, and diabetic macular edema. The Subgroup ‘Non-vision threatening DR’ is defined as patients with mild-moderate non-proliferative DR or unspecified DR, and do not have vision threatening DR. Glaucoma: VEHSS Composite Prevalence Estimates for glaucoma are forthcoming. Age Groups: The VEHSS Composite Prevalence Estimates are available by major age groups (All ages, ages 0-17, 18-39, 40-64, 65-84, 85+) and detailed (5-year) age groups, which are indicated by the text “by detailed age groups” in the ‘Indicator’ field. Prevalence Data Type: These estimates are also available as crude (Data_Value_Type = ‘Crude Prevalence’) or adjusted data (Data_Value_Type=’Adjusted Prevalence). Crude Prevalence is the estimate of the actual number and percentage of people living with each condition. Adjusted Prevalence estimates are adjusted to match the national population by age, race/ethnicity, and gender. Adjusted prevalence estimates can be used to help identify disparities in prevalence between geographic areas that are not explained by differences in demographic characteristics. Data Sources: Data sources for VEHSS Composite Prevalence Estimates include the National Health and Nutrition Examination Survey (NHANES), the American Community Survey (ACS), the National Survey of Children’s Health (NSCH), the Behavioral Risk Factor Surveillance System (BRFSS), Medicare Fee-For-Service claims, the Transformed Medicaid Statistical Information System, MarketScan commercial insurance claims, the Health Resources & Service Administration’s Area Resources File, and published examination study results from the Baltimore Pediatric Eye Disease Study (BPEDS), the Chinese American Eye Study (CHES), the Eye Diseases Prevalence Research Group (EDPRG), the Los Angeles Latino E

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    State Of The Cities 2017

    data.orcities.org | Last Updated 2019-02-15T20:08:13.000Z

    This is the survey responses for the 2017 State of the Cities Report. This data has been coded based on survey response choices. Please consult the attached copy of the survey for more information.

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    Census County Subdivisions in Colorado 2012

    data.colorado.gov | Last Updated 2024-05-14T11:04:13.000Z

    American Community Survey Census data includes demographics, education level, commute information, and more subset to Colorado by the Department of Local Affairs (DOLA).

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    Census Core Based Statistical Area in Colorado 2012

    data.colorado.gov | Last Updated 2024-05-14T11:04:25.000Z

    American Community Survey Census data includes demographics, education level, commute information, and more subset to Colorado by the Department of Local Affairs (DOLA).