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.

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.

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
  
  • Data fields' description -
    • Nhanes_2005_2006.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2007_2008.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2009_2010.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2011_2012.csv - Demographic, Dietary, [Examinations](http://https://wwwn.cdc.gov/nchs/nhanes/search/variab...

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.

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.

Health, United States is the report on the health status of the country. Every year, the report presents an overview of national health trends organized around four subject areas: health status and determinants, utilization of health resources, health care resources, and health care expenditures and payers.

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.

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.

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.

For 2023, the health costs (combined medical and pharmacy benefit expenses) of U.S. employers for employees after plan and contribution changes are forecasted to increase by 6 percent. This survey represents US company's health care cost trends from 1999 to 2023.

Personal healthcare spending in the United States. Data are from Health, United States. Source: Centers for Medicare & Medicaid Services, Office of the Actuary, National Health Statistics Group, National Health Expenditure Accounts, National health expenditures.
Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

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

United States Health Insurance: Premium Per Member Per Month data was reported at 364.000 USD in Sep 2024. This stayed constant from the previous number of 364.000 USD for Jun 2024. United States Health Insurance: Premium Per Member Per Month data is updated quarterly, averaging 262.000 USD from Mar 2012 (Median) to Sep 2024, with 51 observations. The data reached an all-time high of 364.000 USD in Sep 2024 and a record low of 178.000 USD in Sep 2013. United States Health Insurance: Premium Per Member Per Month data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG017: Health Insurance: Industry Financial Snapshots.

As of 2023, 46 percent of U.S. adults rated the quality of healthcare as excellent or good in the United States. In comparison, nearly a third rated the country's health care coverage as excellent or good. This statistic presents the ratings for U.S. healthcare quality and coverage among adults in the United States from 2001 to 2023.

The HCUP Summary Trend Tables include monthly information on hospital utilization derived from the HCUP State Inpatient Databases (SID) and HCUP State Emergency Department Databases (SEDD). Information on emergency department (ED) utilization is dependent on availability of HCUP data; not all HCUP Partners participate in the SEDD. The HCUP Summary Trend Tables include downloadable Microsoft® Excel tables with information on the following topics: Overview of monthly trends in inpatient and emergency department utilization All inpatient encounter types Inpatient stays by priority conditions -COVID-19 -Influenza -Other acute or viral respiratory infection Inpatient encounter type -Normal newborns -Deliveries -Non-elective inpatient stays, admitted through the ED -Non-elective inpatient stays, not admitted through the ED -Elective inpatient stays Inpatient service line -Maternal and neonatal conditions -Mental health and substance use disorders -Injuries -Surgeries -Other medical conditions Emergency department treat-and-release visits Emergency department treat-and-release visits by priority conditions -COVID-19 -Influenza -Other acute or viral respiratory infection Description of the data source, methodology, and clinical criteria

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.

Introduction

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.

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

Graph and download economic data for Expenditures: Healthcare by Quintiles of Income Before Taxes: Highest 20 Percent (81st to 100th Percentile) (CXUHEALTHLB0106M) from 1984 to 2023 about healthcare, health, percentile, tax, expenditures, income, and USA.

United States Health Insurance: Enrollment data was reported at 271.000 USD mn in Sep 2024. This records an increase from the previous number of 269.000 USD mn for Jun 2024. United States Health Insurance: Enrollment data is updated quarterly, averaging 225.000 USD mn from Mar 2012 (Median) to Sep 2024, with 51 observations. The data reached an all-time high of 278.000 USD mn in Jun 2023 and a record low of 174.000 USD mn in Jun 2012. United States Health Insurance: Enrollment data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG017: Health Insurance: Industry Financial Snapshots.

This dataset contains the first part of the National Practitioner Data Bank (NPDB) Public Use Data File, which contains reports from 1990 to 2014 of sequence number 1 to 1357832. The NPDB, according to the Health Care Quality Improvement Act of 1986 collects and discloses de-identified professional competence and conduct of professionals reports about practitioners, providers, suppliers and entities figuring malpractice payments, adverse reactions and other actions or decisions.