100+ datasets found
  1. Leading problems in the U.S. healthcare system 2024

    • statista.com
    Updated Apr 25, 2014
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    Statista (2014). Leading problems in the U.S. healthcare system 2024 [Dataset]. https://www.statista.com/statistics/917159/leading-problems-healthcare-system-us/
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    Dataset updated
    Apr 25, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 26, 2024 - Aug 9, 2024
    Area covered
    United States
    Description

    A 2024 survey found that over half of U.S. individuals indicated the cost of accessing treatment was the biggest problem facing the national healthcare system. This is much higher than the global average of 32 percent and is in line with the high cost of health care in the U.S. compared to other high-income countries. Bureaucracy along with a lack of staff were also considered to be pressing issues. This statistic reveals the share of individuals who said select problems were the biggest facing the health care system in the United States in 2024.

  2. Number of large-scale data breaches in the U.S. healthcare industry...

    • statista.com
    Updated Oct 14, 2024
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    Statista (2024). Number of large-scale data breaches in the U.S. healthcare industry 2009-2024 [Dataset]. https://www.statista.com/statistics/1274594/us-healthcare-data-breaches/
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    Dataset updated
    Oct 14, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Between January and September 2024, healthcare organizations in the United States saw 491 large-scale data breaches, resulting in the loss of over 500 records. This figure has increased significantly in the last decade. To date, the highest number of large-scale data breaches in the U.S. healthcare sector was recorded in 2023, with a reported 745 cases.

  3. U.S. Healthcare Data

    • kaggle.com
    zip
    Updated Dec 22, 2017
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    BuryBuryZymon (2017). U.S. Healthcare Data [Dataset]. https://www.kaggle.com/maheshdadhich/us-healthcare-data
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    zip(37547642 bytes)Available download formats
    Dataset updated
    Dec 22, 2017
    Authors
    BuryBuryZymon
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    Context

    Health care in the United States is provided by many distinct organizations. Health care facilities are largely owned and operated by private sector businesses. 58% of US community hospitals are non-profit, 21% are government owned, and 21% are for-profit. According to the World Health Organization (WHO), the United States spent more on healthcare per capita ($9,403), and more on health care as percentage of its GDP (17.1%), than any other nation in 2014. Many different datasets are needed to portray different aspects of healthcare in US like disease prevalences, pharmaceuticals and drugs, Nutritional data of different food products available in US. Such data is collected by surveys (or otherwise) conducted by Centre of Disease Control and Prevention (CDC), Foods and Drugs Administration, Center of Medicare and Medicaid Services and Agency for Healthcare Research and Quality (AHRQ). These datasets can be used to properly review demographics and diseases, determining start ratings of healthcare providers, different drugs and their compositions as well as package informations for different diseases and for food quality. We often want such information and finding and scraping such data can be a huge hurdle. So, Here an attempt is made to make available all US healthcare data at one place to download from in csv files.

    Content

    • Nhanes Survey (National Health and Nutrition Examination Survey) - The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. NHANES is a major program of the National Center for Health Statistics (NCHS). NCHS is part of the Centers for Disease Control and Prevention (CDC) and has the responsibility for producing vital and health statistics for the Nation. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel. The diseases, medical conditions, and health indicators to be studied include: Anemia, Cardiovascular disease, Diabetes, Environmental exposures, Eye diseases, Hearing loss, Infectious diseases, Kidney disease, Nutrition, Obesity, Oral health, Osteoporosis, Physical fitness and physical functioning, Reproductive history and sexual behavior, Respiratory disease (asthma, chronic bronchitis, emphysema), Sexually transmitted diseases, Vision. 10000 individuals are surveyed to represent US statistics. Five files in this datasets represent current recent Nhanes data -
      Nhanes_2005_2006.csv
      Nhanes_2007_2008.csv
      Nhanes_2009_2010.csv
      Nhanes_2011_2012.csv
      Nhanes_2013_2014.csv
  4. Health Insurance Marketplace

    • kaggle.com
    zip
    Updated May 1, 2017
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    US Department of Health and Human Services (2017). Health Insurance Marketplace [Dataset]. https://www.kaggle.com/datasets/hhs/health-insurance-marketplace
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    zip(868821924 bytes)Available download formats
    Dataset updated
    May 1, 2017
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    US Department of Health and Human Services
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The Health Insurance Marketplace Public Use Files contain data on health and dental plans offered to individuals and small businesses through the US Health Insurance Marketplace.

    median plan premiums

    Exploration Ideas

    To help get you started, here are some data exploration ideas:

    • How do plan rates and benefits vary across states?
    • How do plan benefits relate to plan rates?
    • How do plan rates vary by age?
    • How do plans vary across insurance network providers?

    See this forum thread for more ideas, and post there if you want to add your own ideas or answer some of the open questions!

    Data Description

    This data was originally prepared and released by the Centers for Medicare & Medicaid Services (CMS). Please read the CMS Disclaimer-User Agreement before using this data.

    Here, we've processed the data to facilitate analytics. This processed version has three components:

    1. Original versions of the data

    The original versions of the 2014, 2015, 2016 data are available in the "raw" directory of the download and "../input/raw" on Kaggle Scripts. Search for "dictionaries" on this page to find the data dictionaries describing the individual raw files.

    2. Combined CSV files that contain

    In the top level directory of the download ("../input" on Kaggle Scripts), there are six CSV files that contain the combined at across all years:

    • BenefitsCostSharing.csv
    • BusinessRules.csv
    • Network.csv
    • PlanAttributes.csv
    • Rate.csv
    • ServiceArea.csv

    Additionally, there are two CSV files that facilitate joining data across years:

    • Crosswalk2015.csv - joining 2014 and 2015 data
    • Crosswalk2016.csv - joining 2015 and 2016 data

    3. SQLite database

    The "database.sqlite" file contains tables corresponding to each of the processed CSV files.

    The code to create the processed version of this data is available on GitHub.

  5. U.S. Americans with health insurance 1990-2024

    • statista.com
    Updated Nov 24, 2025
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    Statista (2025). U.S. Americans with health insurance 1990-2024 [Dataset]. https://www.statista.com/statistics/200946/americans-with-health-insurance/
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    Dataset updated
    Nov 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of 2024, nearly *** million people in the United States had some kind of health insurance, a significant increase from around *** million insured people in 2010. However, as of 2024, there were still approximately ** million people in the United States without any kind of health insurance. Insurance coverage The United States does not have universal health insurance, and so health care cost is mostly covered through different private and public insurance programs. In 2021, almost ** percent of the insured population of the United States were insured through employers, while **** percent of people were insured through Medicaid, and **** percent of people through Medicare. As of 2022, about *** percent of people were uninsured in the U.S., compared to ** percent in 2010. The Affordable Care Act The Affordable Care Act (ACA) significantly reduced the number of uninsured people in the United States, from **** million uninsured people in 2013 to **** million people in 2015. However, since the repeal of the individual mandate the number of people without health insurance has risen. Healthcare reform in the United States remains an ongoing political issue with public opinion on a Medicare-for-all plan consistently divided.

  6. North America Healthcare Analytics Market - Size, Growth, Report & Trends...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Nov 25, 2025
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    Mordor Intelligence (2025). North America Healthcare Analytics Market - Size, Growth, Report & Trends Analysis [Dataset]. https://www.mordorintelligence.com/industry-reports/north-america-healthcare-analytics-market-industry
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Nov 25, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    North America
    Description

    The North America Healthcare Analytics Market Report Segments the Industry Into Technology Type (Predictive Analytics, Prescriptive Analytics, Descriptive Analytics), Application (Clinical Data Analytics, Financial Data Analytics, Administrative Data Analytics), Component (Hardware, Software, Service), Mode of Delivery (On-Premise Model, Cloud- and Web-Based Models), End Users (Healthcare Providers, and More), and Geography.

  7. U

    US Health Information Exchange Industry Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Dec 17, 2024
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    Data Insights Market (2024). US Health Information Exchange Industry Report [Dataset]. https://www.datainsightsmarket.com/reports/us-health-information-exchange-industry-9426
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Dec 17, 2024
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The size of the US Health Information Exchange Industry market was valued at USD 0.66 Million in 2023 and is projected to reach USD 1.47 Million by 2032, with an expected CAGR of 12.12% during the forecast period. Recent developments include: In October 2022, Mpowered Health launched its xChange, the United States consumer-mediated healthcare data exchange. The exchange enables health plans, health systems, and other healthcare organizations to request and obtain medical records from consumers with their consent., In March 2022, mpro5 Inc announced its launch into the United States market with a strategy of enabling the collection and leverage of real-time data to simplify the most complex operational challenges in healthcare and hospitals.. Key drivers for this market are: Increasing Demand for Electronic Health Records Resulting in the Expansion of the Market, Government Support via Various Programs and Incentives; Reduction in Healthcare Cost and Improved Efficacy. Potential restraints include: Huge Initial Infrastructural Investment and Slow Return on Investment, Data Privacy and Security Concerns. Notable trends are: The Decentralized/Federated Model is Expected to Hold a Notable Market Share Over the Forecast Period.

  8. F

    Employment for Health Care and Social Assistance: Ambulatory Health Care...

    • fred.stlouisfed.org
    json
    Updated Apr 24, 2025
    + more versions
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    (2025). Employment for Health Care and Social Assistance: Ambulatory Health Care Services (NAICS 621) in the United States [Dataset]. https://fred.stlouisfed.org/series/IPURN621W201000000
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Employment for Health Care and Social Assistance: Ambulatory Health Care Services (NAICS 621) in the United States (IPURN621W201000000) from 1988 to 2024 about ambulatory, healthcare, social assistance, health, NAICS, IP, services, employment, and USA.

  9. d

    Dataplex: United Healthcare Transparency in Coverage | 76,000+ US Employers...

    • datarade.ai
    .json
    Updated Jan 1, 2025
    + more versions
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    Dataplex (2025). Dataplex: United Healthcare Transparency in Coverage | 76,000+ US Employers | Insurance Data | Ideal for Healthcare Cost Analysis [Dataset]. https://datarade.ai/data-products/dataplex-united-healthcare-transparency-in-coverage-76-000-dataplex
    Explore at:
    .jsonAvailable download formats
    Dataset updated
    Jan 1, 2025
    Dataset authored and provided by
    Dataplex
    Area covered
    United States of America
    Description

    United Healthcare Transparency in Coverage Dataset

    Unlock the power of healthcare pricing transparency with our comprehensive United Healthcare Transparency in Coverage dataset. This invaluable resource provides unparalleled insights into healthcare costs, enabling data-driven decision-making for insurers, employers, researchers, and policymakers.

    Key Features:

    • Extensive Coverage: Access detailed pricing information for a wide range of medical procedures and services across the United States, covering approximately 76,000 employers.
    • Granular Data: Analyze costs at the provider, plan, and employer levels, allowing for in-depth comparisons and trend analysis.
    • Massive Scale: Over 400TB of data generated monthly, providing a wealth of information for comprehensive analysis.
    • Historical Perspective: Track pricing changes over time to identify patterns and forecast future trends.
    • Regular Updates: Stay current with the latest pricing information, ensuring your analyses are always based on the most recent data.

    Detailed Data Points:

    For each of the 76,000 employers, the dataset includes: 1. In-network negotiated rates for covered items and services 2. Historical out-of-network allowed amounts and billed charges 3. Cost-sharing information for specific items and services 4. Pricing data for medical procedures and services across providers, plans, and employers

    Use Cases

    For Insurers: - Benchmark your rates against competitors - Optimize network design and provider contracting - Develop more competitive and cost-effective insurance products

    For Employers: - Make informed decisions about health plan offerings - Negotiate better rates with insurers and providers - Implement cost-saving strategies for employee healthcare

    For Researchers: - Conduct in-depth studies on healthcare pricing variations - Analyze the impact of policy changes on healthcare costs - Investigate regional differences in healthcare pricing

    For Policymakers: - Develop evidence-based healthcare policies - Monitor the effectiveness of price transparency initiatives - Identify areas for potential cost-saving interventions

    Data Delivery

    Our flexible data delivery options ensure you receive the information you need in the most convenient format:

    • Custom Extracts: We can provide targeted datasets focusing on specific regions, procedures, or time periods.
    • Regular Reports: Receive scheduled updates tailored to your specific requirements.

    Why Choose Our Dataset?

    1. Expertise: Our team has extensive experience in healthcare data retrieval and analysis, ensuring high-quality, reliable data.
    2. Customization: We can tailor the dataset to meet your specific needs, whether you're interested in particular companies, regions, or procedures.
    3. Scalability: Our infrastructure is designed to handle the massive scale of this dataset (400TB+ monthly), allowing us to provide comprehensive coverage without compromise.
    4. Support: Our dedicated team is available to assist with data interpretation and technical support.

    Harness the power of healthcare pricing transparency to drive your business forward. Contact us today to discuss how our United Healthcare Transparency in Coverage dataset can meet your specific needs and unlock valuable insights for your organization.

  10. F

    All Employees, Home Health Care Services

    • fred.stlouisfed.org
    json
    Updated Nov 20, 2025
    + more versions
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    (2025). All Employees, Home Health Care Services [Dataset]. https://fred.stlouisfed.org/series/CEU6562160001
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 20, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for All Employees, Home Health Care Services (CEU6562160001) from Jan 1985 to Sep 2025 about health, establishment survey, education, services, employment, and USA.

  11. F

    Labor Productivity for Health Care and Social Assistance: Medical and...

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    + more versions
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    (2025). Labor Productivity for Health Care and Social Assistance: Medical and Diagnostic Laboratories (NAICS 62151) in the United States [Dataset]. https://fred.stlouisfed.org/series/IPURN62151L000000000
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Labor Productivity for Health Care and Social Assistance: Medical and Diagnostic Laboratories (NAICS 62151) in the United States (IPURN62151L000000000) from 1994 to 2024 about diagnostic labs, healthcare, medical, social assistance, productivity, health, NAICS, IP, labor, and USA.

  12. F

    Unit Labor Costs for Health Care and Social Assistance: Medical and...

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    + more versions
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    (2025). Unit Labor Costs for Health Care and Social Assistance: Medical and Diagnostic Laboratories (NAICS 6215) in the United States [Dataset]. https://fred.stlouisfed.org/series/IPURN6215U100000000
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Unit Labor Costs for Health Care and Social Assistance: Medical and Diagnostic Laboratories (NAICS 6215) in the United States (IPURN6215U100000000) from 1994 to 2024 about diagnostic labs, healthcare, unit labor cost, medical, social assistance, health, NAICS, IP, and USA.

  13. d

    Health Care Satellite Account

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Jul 15, 2022
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    Bureau of Economic Analysis (2022). Health Care Satellite Account [Dataset]. https://catalog.data.gov/dataset/health-care-satellite-account
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    Dataset updated
    Jul 15, 2022
    Dataset provided by
    Bureau of Economic Analysis
    Description

    The Health Care Satellite Account measures U.S. health care spending to treat diseases, like cancer or diabetes, rather than by place of service, like a hospital or doctor's office, offering a new way of analyzing the health care sector.

  14. Satisfaction with cost of healthcare in the U.S. 2002-2023

    • statista.com
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    Statista, Satisfaction with cost of healthcare in the U.S. 2002-2023 [Dataset]. https://www.statista.com/statistics/1290021/satisfaction-with-healthcare-cost-in-the-us/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2002 - 2023
    Area covered
    United States
    Description

    As of 2023, around 19 percent of U.S. adults were satisfied with the total healthcare cost in the United States, a significant decrease from the previous year. Also, this is much lower than the share of U.S. adults satisfied with their own cost for healthcare. This statistic illustrates the satisfaction and dissatisfaction of U.S. adults with the total cost of healthcare in the United States from 2002 to 2023.

  15. d

    US Consumer Prescription Medicine Leads | Consumer Medical Data | Healthcare...

    • datarade.ai
    .csv
    Updated Nov 1, 2022
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    Data Scout Inc. (2022). US Consumer Prescription Medicine Leads | Consumer Medical Data | Healthcare Consumer Database [Dataset]. https://datarade.ai/data-products/us-consumer-prescription-medicine-leads-consumer-medical-da-data-scout-inc
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Nov 1, 2022
    Dataset authored and provided by
    Data Scout Inc.
    Area covered
    United States of America
    Description

    Our highly-targeted consumer healthcare database includes:

    🗸 Name 🗸 Postal Address, Email Address, Telephone Number 🗸 Age, Gender 🗸 Most likely to ask a Doctor About an Advertised Prescription Medicine 🗸 Most likely looked for Medical Information on the Web 🗸 Most Likely to Prefer Brand Name Medicines 🗸 Most Likely to Buy Prescriptions through the Mail

    The dataset is available for purchase by US region: 🗸 New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont) 🗸 Middle Atlantic (New Jersey, New York, and Pennsylvania) 🗸 East North Central (Illinois, Indiana, Michigan, Ohio, and Wisconsin) 🗸 West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota) 🗸 South Atlantic (Delaware; Florida; Georgia; Maryland; North Carolina; South Carolina; Virginia; Washington, D.C. and West Virginia) 🗸 East South Central (Alabama, Kentucky, Mississippi, and Tennessee) 🗸 West South Central (Arkansas, Louisiana, Oklahoma, and Texas) 🗸 Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming) 🗸 Pacific (Alaska, California, Hawaii, Oregon, and Washington)

  16. y

    US Health Care and Social Assistance Sector Total Revenue

    • ycharts.com
    html
    Updated Sep 12, 2025
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    Census Bureau (2025). US Health Care and Social Assistance Sector Total Revenue [Dataset]. https://ycharts.com/indicators/us_health_care_and_social_assistance_sector_total_revenue
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    htmlAvailable download formats
    Dataset updated
    Sep 12, 2025
    Dataset provided by
    YCharts
    Authors
    Census Bureau
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Mar 31, 2009 - Jun 30, 2025
    Area covered
    United States
    Variables measured
    US Health Care and Social Assistance Sector Total Revenue
    Description

    View quarterly updates and historical trends for US Health Care and Social Assistance Sector Total Revenue. from United States. Source: Census Bureau. Tra…

  17. Mental Health Care in the Last 4 Weeks

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Mental Health Care in the Last 4 Weeks [Dataset]. https://catalog.data.gov/dataset/mental-health-care-in-the-last-4-weeks
    Explore at:
    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  18. i

    Grant Giving Statistics for Jordanian American Healthcare Association Jaha

    • instrumentl.com
    Updated May 27, 2024
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    (2024). Grant Giving Statistics for Jordanian American Healthcare Association Jaha [Dataset]. https://www.instrumentl.com/990-report/jordanian-american-healthcare-association-jaha
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    Dataset updated
    May 27, 2024
    Area covered
    Jordan
    Description

    Financial overview and grant giving statistics of Jordanian American Healthcare Association Jaha

  19. a

    Medical Service Study Areas

    • hub.arcgis.com
    • data.ca.gov
    • +5more
    Updated Sep 5, 2024
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    CA Department of Health Care Access and Information (2024). Medical Service Study Areas [Dataset]. https://hub.arcgis.com/datasets/dce6f4b66f4e4ec888227eda905ed8fd
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    Dataset updated
    Sep 5, 2024
    Dataset authored and provided by
    CA Department of Health Care Access and Information
    Area covered
    Description

    This is the current Medical Service Study Area. California Medical Service Study Areas are created by the California Department of Health Care Access and Information (HCAI).Check the Data Dictionary for field descriptions.Search for the Medical Service Study Area data on the CHHS Open Data Portal.Checkout the California Healthcare Atlas for more Medical Service Study Area information.This is an update to the MSSA geometries and demographics to reflect the new 2020 Census tract data. The Medical Service Study Area (MSSA) polygon layer represents the best fit mapping of all new 2020 California census tract boundaries to the original 2010 census tract boundaries used in the construction of the original 2010 MSSA file. Each of the state's new 9,129 census tracts was assigned to one of the previously established medical service study areas (excluding tracts with no land area), as identified in this data layer. The MSSA Census tract data is aggregated by HCAI, to create this MSSA data layer. This represents the final re-mapping of 2020 Census tracts to the original 2010 MSSA geometries. The 2010 MSSA were based on U.S. Census 2010 data and public meetings held throughout California.Source of update: American Community Survey 5-year 2006-2010 data for poverty. For source tables refer to InfoUSA update procedural documentation. The 2010 MSSA Detail layer was developed to update fields affected by population change. The American Community Survey 5-year 2006-2010 population data pertaining to total, in households, race, ethnicity, age, and poverty was used in the update. The 2010 MSSA Census Tract Detail map layer was developed to support geographic information systems (GIS) applications, representing 2010 census tract geography that is the foundation of 2010 medical service study area (MSSA) boundaries. ***This version is the finalized MSSA reconfiguration boundaries based on the US Census Bureau 2010 Census. In 1976 Garamendi Rural Health Services Act, required the development of a geographic framework for determining which parts of the state were rural and which were urban, and for determining which parts of counties and cities had adequate health care resources and which were "medically underserved". Thus, sub-city and sub-county geographic units called "medical service study areas [MSSAs]" were developed, using combinations of census-defined geographic units, established following General Rules promulgated by a statutory commission. After each subsequent census the MSSAs were revised. In the scheduled revisions that followed the 1990 census, community meetings of stakeholders (including county officials, and representatives of hospitals and community health centers) were held in larger metropolitan areas. The meetings were designed to develop consensus as how to draw the sub-city units so as to best display health care disparities. The importance of involving stakeholders was heightened in 1992 when the United States Department of Health and Human Services' Health and Resources Administration entered a formal agreement to recognize the state-determined MSSAs as "rational service areas" for federal recognition of "health professional shortage areas" and "medically underserved areas". After the 2000 census, two innovations transformed the process, and set the stage for GIS to emerge as a major factor in health care resource planning in California. First, the Office of Statewide Health Planning and Development [OSHPD], which organizes the community stakeholder meetings and provides the staff to administer the MSSAs, entered into an Enterprise GIS contract. Second, OSHPD authorized at least one community meeting to be held in each of the 58 counties, a significant number of which were wholly rural or frontier counties. For populous Los Angeles County, 11 community meetings were held. As a result, health resource data in California are collected and organized by 541 geographic units. The boundaries of these units were established by community healthcare experts, with the objective of maximizing their usefulness for needs assessment purposes. The most dramatic consequence was introducing a data simultaneously displayed in a GIS format. A two-person team, incorporating healthcare policy and GIS expertise, conducted the series of meetings, and supervised the development of the 2000-census configuration of the MSSAs.MSSA Configuration Guidelines (General Rules):- Each MSSA is composed of one or more complete census tracts.- As a general rule, MSSAs are deemed to be "rational service areas [RSAs]" for purposes of designating health professional shortage areas [HPSAs], medically underserved areas [MUAs] or medically underserved populations [MUPs].- MSSAs will not cross county lines.- To the extent practicable, all census-defined places within the MSSA are within 30 minutes travel time to the largest population center within the MSSA, except in those circumstances where meeting this criterion would require splitting a census tract.- To the extent practicable, areas that, standing alone, would meet both the definition of an MSSA and a Rural MSSA, should not be a part of an Urban MSSA.- Any Urban MSSA whose population exceeds 200,000 shall be divided into two or more Urban MSSA Subdivisions.- Urban MSSA Subdivisions should be within a population range of 75,000 to 125,000, but may not be smaller than five square miles in area. If removing any census tract on the perimeter of the Urban MSSA Subdivision would cause the area to fall below five square miles in area, then the population of the Urban MSSA may exceed 125,000. - To the extent practicable, Urban MSSA Subdivisions should reflect recognized community and neighborhood boundaries and take into account such demographic information as income level and ethnicity. Rural Definitions: A rural MSSA is an MSSA adopted by the Commission, which has a population density of less than 250 persons per square mile, and which has no census defined place within the area with a population in excess of 50,000. Only the population that is located within the MSSA is counted in determining the population of the census defined place. A frontier MSSA is a rural MSSA adopted by the Commission which has a population density of less than 11 persons per square mile. Any MSSA which is not a rural or frontier MSSA is an urban MSSA. Last updated December 6th 2024.

  20. US Healthcare Visits Statistics

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    Updated Jan 20, 2021
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    John Snow Labs (2021). US Healthcare Visits Statistics [Dataset]. https://www.johnsnowlabs.com/marketplace/us-healthcare-visits-statistics/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Area covered
    United States
    Description

    The US Healthcare Visits Statistics dataset includes data about the frequency of healthcare visits to doctor offices, emergency departments, and home visits within the past 12 months in the United States by age, race, Hispanic origin, poverty level, health insurance status, geographic region and other characteristics between 1997 and 2016.

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Statista (2014). Leading problems in the U.S. healthcare system 2024 [Dataset]. https://www.statista.com/statistics/917159/leading-problems-healthcare-system-us/
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Leading problems in the U.S. healthcare system 2024

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Dataset updated
Apr 25, 2014
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Jul 26, 2024 - Aug 9, 2024
Area covered
United States
Description

A 2024 survey found that over half of U.S. individuals indicated the cost of accessing treatment was the biggest problem facing the national healthcare system. This is much higher than the global average of 32 percent and is in line with the high cost of health care in the U.S. compared to other high-income countries. Bureaucracy along with a lack of staff were also considered to be pressing issues. This statistic reveals the share of individuals who said select problems were the biggest facing the health care system in the United States in 2024.

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