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The percent without health insurance of Adams County, PA was 11.50% for 18 to 64, all races, both sexes and all income levels in 2014. The percent without health insurance of Berkeley County, WV was 13.70% 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 Adams County, PA or Berkeley County, WV

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    Drug and Alcohol Treatment Facilities May 2018 County Drug and Alcohol Programs

    data.pa.gov | Last Updated 2022-10-17T19:15:44.000Z

    This dataset reports the name, street address, city, county, zip code, telephone number, latitude, and longitude of Pennsylvania Department of Drug and Alcohol Programs (DDAP) drug and alcohol treatment facilities in Pennsylvania as of May 2018. The primary difference between the three types of treatment facilities is their funding. Centers of Excellence (COEs) were grant funded by the Department of Human Services, PacMATs were grant funded by the Department of Health, and all other facilities are funded by either billing insurance or billing the county in the case of uninsured clients. Programmatically, COEs differ from the other types because they are designed to serve as “health homes” for individuals with Opioid Use Disorder (OUD). This means that the care coordination staff at the COE is charged with coordinating all kinds of health care (physical and behavioral health) as well as recovery support services. They do this by developing hub-and-spoke networks with other healthcare providers and other sources for recovery supports, such as housing, transportation, education and training, etc. All COEs are required to accept Medicaid. PacMATs also operate in a hub-and-spoke model, but it is different from COEs. PacMATs endeavor to coordinate the provision of Medication Assisted Treatment (MAT) by identifying a core hub of physicians in a health system that work with other providers in the health system (spokes) to train them about the safe and effective provision of MAT so that there are more providers in a health system that are able to confidently prescribe various forms of MAT. I do not know whether all PacMATs are required to accept Medicaid as a term of their receipt of the grant, but I do know that all currently designated PacMATs are health systems that do accept Medicaid. PacMAT services have been advertised as being available to all people regardless of insurance type, so I assume this means they are required to serve Medicaid clients, commercially insured clients, and uninsured clients. In the PacMAT program the Hub is supported right now by grant funding (in the future funding such as a per patient/per month capitated rate) and the spokes bill insurance (both Medicaid and Commercial) DDAP facilities may also be designated as COEs and/or PacMATs. If they are, it means they applied for a specific grant fund and have committed to carrying out the activities of the grant described above. To be clear, DDAP does not run any treatment facilities; they license them. These can be MAT providers such as methadone clinics, providers of outpatient levels of care (i.e., more traditional drug and alcohol counseling services) or inpatient levels of care, such as residential rehabilitation programs. Every facility is different in terms of the menu of services it provides. Every facility also gets to decide what forms of payment they will accept. Many accept Medicaid, but not all do. Some only accept private commercial insurance. Some accept payment from the county on behalf of uninsured clients. And some charge their clients cash for services.

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    Find Naloxone at a Pharmacy Near Me Current Statewide Department of State and Health

    data.pa.gov | Last Updated 2022-10-18T16:13:27.000Z

    Naloxone is a life-saving medication that can reverse an overdose that is caused by an opioid drug (i.e. prescription pain medication or heroin). Naloxone may be obtained at a pharmacy using the statewide standing order (https://www.health.pa.gov/topics/Documents/Opioids/General%20Public%20Standing%20Order.pdf) signed by Secretary of Health, Dr. Rachel Levine. Naloxone may be covered by insurance and consumers are encouraged to check with their insurers to understand their insurance coverage for naloxone. Individuals covered by Medicaid can obtain naloxone without a copay. A video demonstrating how to administer nasal spray naloxone may be found here - https://www.youtube.com/watch?v=v26cDao4AcI&feature=youtu.be <br> More information about how naloxone works as a medication and frequently asked questions about obtaining and using naloxone may be found on the Department of Health’s Naloxone webpage (https://www.health.pa.gov/topics/disease/Opioids/Pages/Naloxone.aspx) <br> *This is a comprehensive listing of all pharmacies registered with the Department of State in Pennsylvania and does not guarantee that the pharmacy listed will have naloxone in stock.

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    Number Of People Without Health Insurance All States 2005-2012

    opendata.utah.gov | Last Updated 2019-04-19T06:44:33.000Z

    Number Of People Without Health Insurance All States 2005-2012

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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.

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    Drug and Alcohol Treatment Get Help Now Intake Hotline November 2016 - Current Statewide Drug and Alcohol Programs

    data.pa.gov | Last Updated 2023-09-19T14:35:29.000Z

    This dataset reports statewide and county numbers of calls and intakes by individuals seeking treatment from hotline staff since the inception of Pennsylvania’s Get Help Now Hotline, text line, and chat line in November 2016. When a field is blank the information is not available; these data were not collected at the time of the phone call.

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    Uninsured Population Census Data 5-year estimates for release years 2017-Current County Human Services and Insurance

    data.pa.gov | Last Updated 2022-02-21T19:25:39.000Z

    The American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty. An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015). In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period. Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.

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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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    Uninsured Population Census Data CY 2009-2014 Human Services

    data.pa.gov | Last Updated 2022-10-18T14:19:11.000Z

    This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.