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.
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.
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.
The United States has the highest expenditure on health care per capita globally. However, the U.S. has an unique way of paying for their health care where a majority of the expenditure falls upon private insurances. In FY 2024, around one ***** of all health expenditure is paid by private insurance. Public insurance programs Medicare and Medicaid accounted for ** and ** percent, respectively, of health expenditure during that same year. U.S. health care system Globally health spending has been increasing among most countries. However, the U.S. has the highest public and private per capita health expenditure among all countries globally, followed by Switzerland. As of 2020, annual health care costs per capita in the United States totaled to over ** thousand U.S. dollars, a significant amount considering the average U.S. personal income is around ** thousand dollars. Out of pocket costs in the U.S. Aside from overall high health care costs for U.S. residents, the total out-of-pocket costs for health care have been on the rise. In recent years, the average per capita out-of-pocket health care payments have exceeded *** thousand dollars. Physician services, dental services and prescription drugs account for the largest proportion of out-of-pocket expenditures for U.S. residents.
This map service shows the locations of healthcare facilities (hospitals, medical centers, federally qualified health centers, home health services, and nursing homes) in the United States. The data was provided by the U.S. Department of Health Human Services and is current as of 2012.The data is symbolized by facility type:Hospital: an institution providing medical and surgical treatment and nursing care for sick or injured people.Medical Center: a health care facility staffed and equipped to care for many patients and for a large number of various kinds of diseases and dysfunctions, using sophisticated technology.Federally Qualified Health Center: a community-based organization that provides comprehensive primary care and preventative care, including health, oral, and mental health/substance abuse services to persons of all ages, regardless of their ability to pay or health insurance status.Home Health Service: health care or supportive care provided in the patient's home by health care professionals (often referred to as home health care or formal care).Nursing Home: provides a type of residential care. They are a place of residence for people who require constant nursing care and have significant deficiencies with activities of daily living.Other data sources include: Data.gov_Other Health Datapalooza focused content that may interest you: Health Datapalooza Health Datapalooza
The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of reduced access to healthcare for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included questions about unmet care in the last 2 months during the coronavirus pandemic. Unmet needs for health care are often the result of cost-related barriers. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor cost-related health care access problems in the United States. For example, in 2018, 7.3% of persons of all ages reported delaying medical care due to cost and 4.8% reported needing medical care but not getting it due to cost in the past year. However, cost is not the only reason someone might delay or not receive needed medical care. As a result of the coronavirus pandemic, people also may not get needed medical care due to cancelled appointments, cutbacks in transportation options, fear of going to the emergency room, or an altruistic desire to not be a burden on the health care system, among other reasons. The Household Pulse Survey (https://www.cdc.gov/nchs/covid19/pulse/reduced-access-to-care.htm), an online survey conducted in response to the COVID-19 pandemic by the Census Bureau in partnership with other federal agencies including NCHS, also reports estimates of reduced access to care during the pandemic (beginning in Phase 1, which started on April 23, 2020). The Household Pulse Survey reports the percentage of adults who delayed medical care in the last 4 weeks or who needed medical care at any time in the last 4 weeks for something other than coronavirus but did not get it because of the pandemic. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who were unable to receive medical care (including urgent care, surgery, screening tests, ongoing treatment, regular checkups, prescriptions, dental care, vision care, and hearing care) in the last 2 months. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/reduced-access-to-care.htm#limitations
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Graph and download economic data for All Employees, Health Care (CES6562000101) from Jan 1990 to Jun 2025 about health, establishment survey, education, services, employment, and USA.
In 2023, there were more than *** incidents of data compromises in the healthcare sector in the United States. Reaching its all-time highest. This indicates a significant growth since 2005 when the industry saw only ** cases of data compromises in the country.
This data package contains the information of Medicare and Medicaid healthcare spending and healthcare cost and percentages by state.
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Graph and download economic data for Expenditures: Healthcare by Age: Age 65 or over (CXUHEALTHLB0407M) from 1988 to 2023 about 65-years +, healthcare, age, health, expenditures, and USA.
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Artificial Intelligence in healthcare refers to the use of advanced computer algorithms and machine learning techniques to analyze data in the healthcare sector to provide better healthcare services.
AI helps healthcare providers make more accurate and real-time diagnoses, personalize treatment plans, and improve patient safety by identifying health risks earlier.
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Column Name | Description |
---|---|
city_name | The name of the city where healthcare providers are located. |
result_count | The count of healthcare providers in the city. |
results | Details of healthcare providers in the city. |
created_epoch | The epoch timestamp when the provider's information was created. |
enumeration_type | The type of enumeration for the provider (e.g., NPI-1, NPI-2). |
last_updated_epoch | The epoch timestamp when the provider's information was last updated. |
number | The unique identifier for the healthcare provider. |
addresses | Information about the provider's addresses, including mailing and location addresses. |
country_code | The country code for the provider's address (e.g., US for the United States). |
country_name | The country name for the provider's address. |
address_purpose | The purpose of the address (e.g., MAILING, LOCATION). |
address_type | The type of address (e.g., DOM - Domestic). |
address_1 | The first line of the provider's address. |
address_2 | The second line of the provider's address. |
city | The city where the provider is located. |
state | The state where the provider is located. |
postal_code | The postal code or ZIP code for the provider's location. |
telephone_number | The telephone number for the provider's contact. |
practiceLocations | Details about the provider's practice locations. |
basic | Basic information about the provider, including their name, credentials, and gender. |
first_name | The first name of the healthcare provider. |
last_name | The last name of the healthcare provider. |
middle_name | The middle name of the healthcare provider. |
credential | The credential of the healthcare provider (e.g., PT, DPT). |
sole_proprietor | Indicates whether the provider is a sole proprietor (e.g., YES, NO). |
gender | The gender of the healthcare provider (e.g., M, F). |
enumeration_date | The date when the provider's enumeration was recorded. |
last_updated | The date when the provider's information was last updated. |
taxonomies | Information about the provider's taxonomies, including code, description, state, license, and primary designation. |
identifiers | Additional identifiers for the healthcare provider. |
endpoints | Information about communication endpoints for the provider. |
other_names | Any other names associated with the healthcare provider. |
1. Healthcare Provider Analysis: This dataset can be used to perform in-depth analyses of healthcare providers across various cities. You can extract insights into the distribution of different types of healthcare professionals, their practice locations, and their specialties. This information is valuable for healthcare workforce planning and resource allocation.
2. Geospatial Mapping: Utilize the city names and addresses in the dataset to create geospatial visualizations. You can map the locations of healthcare providers in each city, helping stakeholders identify areas with potential shortages or surpluses of healthcare services.
3. Provider Directory Development: The dataset provides detailed information about healthcare providers, including their names, contact details, and credentials. You can use this data to build a comprehensive healthcare provider directory or search tool, helping patients and healthcare organizations find and connect with the right providers in their area.
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US Healthcare NPI Data is a comprehensive resource offering detailed information on health providers registered in the United States.
Dataset Highlights:
Taxonomy Data:
Data Updates:
Use Cases:
Data Quality and Reliability:
Access and Integration: - CSV Format: The dataset is provided in CSV format, making it easy to integrate with various data analysis tools and platforms. - Ease of Use: The structured format of the data ensures that it can be easily imported, analyzed, and utilized for various applications without extensive preprocessing.
Ideal for:
Why Choose This Dataset?
By leveraging the US Healthcare NPI & Taxonomy Data, users can gain valuable insights into the healthcare landscape, enhance their outreach efforts, and conduct detailed research with confidence in the accuracy and comprehensiveness of the data.
Summary:
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:
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:
Why Choose Our Dataset?
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.
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Global Big Data in Healthcare Market size is expected to be worth around USD 145.8 Billion by 2033 from USD 42.2 Billion in 2023, growing at a CAGR of 13.2% during the forecast period from 2024 to 2033.
Big data in healthcare encompasses vast amounts of diverse, unstructured data sourced from medical journals, biometric sensors, electronic medical records (EMRs), Internet of Medical Things (IoMT), social media platforms, payer records, omics research, and data repositories. Integrating this unstructured data into traditional systems presents considerable challenges, primarily in data structuring and standardization. Effective data structuring is essential for ensuring compatibility across systems and enabling robust analytical processes.
However, advancements in big data analytics, artificial intelligence, and machine learning have significantly enhanced the ability to convert complex healthcare data into actionable insights. These advancements have transformed healthcare, driving informed decision-making, enabling early and accurate diagnostics, facilitating precision medicine, and enhancing patient engagement through digital self-service platforms, including online portals, mobile applications, and wearable health devices.
The role of big data in pharmaceutical R&D has become increasingly central, as analytics tools streamline drug discovery, accelerate clinical trial processes, and identify potential therapeutic targets more efficiently. The demand for business intelligence solutions within healthcare is rising, fueled by the surge of unstructured data and the focus on developing tailored treatment protocols. As a result, the global market for big data in healthcare is projected to grow steadily during the forecast period.
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Graph and download economic data for Output per Worker for Health Care and Social Assistance: Diagnostic Imaging Centers (NAICS 621512) in the United States (IPURN621512W001000000) from 1995 to 2022 about diagnostic imaging, healthcare, social assistance, output, health, NAICS, IP, employment, and USA.
The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.
Dataset Overview:
118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.
25.8 Billion Rows of Data:
Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.
Monthly Updates:
Data Sourced from CMS:
Use Cases:
Market Analysis:
Healthcare Research:
Performance Tracking:
Compliance and Regulatory Reporting:
Data Quality and Reliability:
The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.
Integration and Usability:
Ease of Integration:
Success.ai’s Healthcare Industry Leads Data and B2B Contact Data for US Healthcare Professionals offers an extensive and verified database tailored to connect businesses with key executives and administrators in the healthcare industry across the United States. With over 170M verified profiles, including work emails and direct phone numbers, this dataset enables precise targeting of decision-makers in hospitals, clinics, and healthcare organizations.
Backed by AI-driven validation technology for unmatched accuracy and reliability, this contact data empowers your marketing, sales, and recruitment strategies. Designed for industry professionals, our continuously updated profiles provide the actionable insights you need to grow your business in the competitive healthcare sector.
Key Features of Success.ai’s US Healthcare Contact Data:
Hospital Executives: CEOs, CFOs, and COOs managing top-tier facilities. Healthcare Administrators: Decision-makers driving operational excellence. Medical Professionals: Physicians, specialists, and nurse practitioners. Clinic Managers: Leaders in small and mid-sized healthcare organizations.
AI-Validated Accuracy and Updates
99% Verified Accuracy: Our advanced AI technology ensures data reliability for optimal engagement. Real-Time Updates: Profiles are continuously refreshed to maintain relevance and accuracy. Minimized Bounce Rates: Save time and resources by reaching verified contacts.
Customizable Delivery Options Choose how you access the data to match your business requirements:
API Integration: Connect our data directly to your CRM or sales platform. Flat File Delivery: Receive customized datasets in formats suited to your needs.
Why Choose Success.ai for Healthcare Data?
Best Price Guarantee We ensure competitive pricing for our verified contact data, offering the most comprehensive and cost-effective solution in the market.
Compliance-Driven and Ethical Data Our data collection adheres to strict global standards, including HIPAA, GDPR, and CCPA compliance, ensuring secure and ethical usage.
Strategic Benefits for Your Business Success.ai’s US healthcare professional data unlocks numerous business opportunities:
Targeted Marketing: Develop tailored campaigns aimed at healthcare executives and decision-makers. Efficient Sales Outreach: Engage with key contacts to accelerate your sales process. Recruitment Optimization: Access verified profiles to identify and recruit top talent in the healthcare industry. Market Intelligence: Use detailed firmographic and demographic insights to guide strategic decisions. Partnership Development: Build valuable relationships within the healthcare ecosystem.
Key APIs for Advanced Functionality
Enrichment API Enhance your existing contact data with real-time updates, ensuring accuracy and relevance for your outreach initiatives.
Lead Generation API Drive high-quality lead generation efforts by utilizing verified contact information, including work emails and direct phone numbers, for up to 860,000 API calls per day.
Use Cases
Healthcare Marketing Campaigns Target verified executives and administrators to deliver personalized and impactful marketing campaigns.
Sales Enablement Connect with key decision-makers in healthcare organizations, ensuring higher conversion rates and shorter sales cycles.
Talent Acquisition Source and engage healthcare professionals and administrators with accurate, up-to-date contact information.
Strategic Partnerships Foster collaborations with healthcare institutions and professionals to expand your business network.
Industry Analysis Leverage enriched contact data to gain insights into the US healthcare market, helping you refine your strategies.
Verified Accuracy: AI-driven technology ensures 99% reliability for all contact details. Comprehensive Reach: Covering healthcare professionals from large hospital systems to smaller clinics nationwide. Flexible Access: Customizable data delivery methods tailored to your business needs. Ethical Standards: Fully compliant with healthcare and data protection regulations.
Success.ai’s B2B Contact Data for US Healthcare Professionals is the ultimate solution for connecting with industry leaders, driving impactful marketing campaigns, and optimizing your recruitment strategies. Our commitment to quality, accuracy, and affordability ensures you achieve exceptional results while adhering to ethical and legal standards.
No one beats us on price. Period.
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Percent of population 18-64 years of age with no health insurance coverage by race/ethnicity in New Orleans and the United States
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United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 0.781 % in 2013. This records a decrease from the previous number of 0.856 % for 2012. United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 0.880 % from Dec 1995 (Median) to 2013, with 18 observations. The data reached an all-time high of 1.078 % in 2000 and a record low of 0.724 % in 2008. United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Poverty. Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure, expressed as a percentage of a total population of a country; ; Wagstaff et al. Progress on catastrophic health spending: results for 133 countries. A retrospective observational study, Lancet Global Health 2017.; Weighted Average;
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.