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.

Introduction

AI in Healthcare Statistics: Artificial Intelligence (AI) in healthcare is growing rapidly, helping doctors and healthcare providers improve patient care. AI uses machines and algorithms to analyse data, such as medical records or images, to help diagnose diseases and suggest treatments faster and more accurately. AI technologies like machine learning, natural language processing, and robotic surgery are driving this growth.

AI helps in areas like medical imaging, drug discovery, and personalised treatment, making healthcare more efficient. This technology is transforming healthcare by reducing costs, speeding up diagnoses, and improving the accuracy of treatments, all while supporting healthcare professionals in delivering better care.

This statistic, biennative and censal in nature, allows, from the Free Insurance Entities operating in the C.A. of the Basque Country, to give information on the main magnitudes of insurance in health care (insured persons, premiums and type of insurance)

This page leads to several types of statistics relating to health care and indemnity insurance, grouped by theme. Select the theme that interests you by clicking on it:

• Health care: Statistics on health care providers, cost for health care insurance, patient co-payment, prescriptions, etc.

• Allowances: Statistics on primary work incapacity, invalidity, maternity, birth leave, etc.

• Medical assessment and control: Statistics on the monitoring of health care providers and evaluation of medical practice.

• Administrative control: Statistics on the control of mutual funds and the fight against social fraud.

• Medications: Statistics and specific analyzes on drugs dispensed in public pharmacies: prescription, volume, cost for insurance, etc.

• Frontier workers: Statistics on frontier workers entering and leaving Belgium.

• People affiliated with a health insurance fund: Statistics on the number of people affiliated to a health insurance fund to benefit from healthcare and indemnity insurance in Belgium. Customize your search with our web program.

AI in Healthcare Statistics: AI in healthcare has been a hot topic for the past few years, and the report says that the industry is expected to reach $187.95 billion by the end of 2030. The fact of this platform in 2023 suggests a huge boom in the market size worldwide, with a compound annual increase rate (CAGR) of 40.1% from 2023 to 2030. The worldwide Artificial intelligence in the healthcare marketplace length changed into worth $20.65 billion in 2023 which has increased from last year. These AI in Healthcare Statistics include insights from various aspects and sources that will provide effective light on the importance of AI in the healthcare industry around the world in recent times. In 2023, the Market share records the gradual adoption of AI which is advancing the sector, and has been observed that 85% of organizations have already implemented AI. Additionally, 1/2 of the executives claimed that AI is indicating a tremendous shift inside and outside the industry. Aid of AI-based healthcare companies used solutions like telemedicine and remote tools and sensors backed by means of large information that can reduce healthcare charges improve access, and promote better outcomes, and performance. Key Takeaways According to AI in Healthcare Statistics, the platform when implemented Artificial Intelligence has experienced a huge increase, with a CAGR of 40.1% from 2023 to 2030 and a global market size expected to attain $187.95 billion by 2030. Around the world, approximately 40% of healthcare industries are regularly using AI and Machine Language in the sector. In 2023, Healthcare executives are increasingly adopting AI in their techniques, and nearly 1/2 of the executives surveyed are already using it. This is being adopted globally, with answers like telemedicine and faraway tools and sensors backed through huge information that could lessen healthcare charges and equitably improve admission to, results, and performance.

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

Introduction

Home Healthcare Statistics: Home healthcare has become essential to the healthcare system, highlighting a notable shift towards patient-focused and cost-efficient care delivery models. This sector includes diverse medical and support services provided directly in patients' homes to enhance health outcomes while ensuring greater comfort and convenience.

Key drivers such as the aging global population, rising incidence of chronic illnesses, and advancements in remote patient monitoring technologies have significantly fueled the expansion of home healthcare demand worldwide. Examining relevant statistics in this field offers crucial insights into market size, demographic changes, service usage, and spending patterns.

Information is vital for healthcare providers, policymakers, and investors seeking to make well-informed decisions. This introduction paves the way for an in-depth analysis of current data and emerging trends that define the evolving home healthcare market.

The amount of global healthcare data is expected to increase dramatically by the year 2020. Early estimates from 2013 suggest that there were about 153 exabytes of healthcare data generated in that year. However, projections indicate that there could be as much as 2,314 exabytes of new data generated in 2020.

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.

The Health Statistics and Health Research Database is Estonian largest set of health-related statistics and survey results administrated by National Institute for Health Development. Use of the database is free of charge.

The database consists of eight main areas divided into sub-areas. The data tables included in the sub-areas are assigned unique codes. The data tables presented in the database can be both viewed in the Internet environment, and downloaded using different file formats (.px, .xlsx, .csv, .json). You can download the detailed database user manual here (.pdf).

The database is constantly updated with new data. Dates of updating the existing data tables and adding new data are provided in the release calendar. The date of the last update to each table is provided after the title of the table in the list of data tables.

A contact person for each sub-area is provided under the "Definitions and Methodology" link of each sub-area, so you can ask additional information about the data published in the database. Contact this person for any further questions and data requests.

Read more about publication of health statistics by National Institute for Health Development in Health Statistics Dissemination Principles.

Graph and download economic data for All Employees, Health Care (CES6562000101) from Jan 1990 to Aug 2025 about health, education, establishment survey, services, employment, and USA.

Graph and download economic data for Expenditures: Healthcare by Region: Residence in the Northeast Census Region (CXUHEALTHLB1102M) from 1984 to 2023 about Northeast Census Region, healthcare, health, expenditures, residents, and USA.

Introduction

Cybersecurity in Healthcare Statistics: As the healthcare sector increasingly integrates digital technologies, the need for robust cybersecurity measures has become more critical than ever. Adopting electronic health records (EHRs), telemedicine, and connected medical devices has significantly enhanced patient care and operational efficiency.

However, this digital shift has also exposed healthcare organizations to a rising tide of cyber threats, including data breaches, ransomware attacks, and hacks of medical devices. The sensitive nature of the data fuels these threats, such as personal health information (PHI) and payment records, making healthcare one of the most targeted cyberattack industries.

In response to these growing risks, healthcare providers must prioritize implementing stringent cybersecurity policies and embrace cutting-edge technologies like encryption, artificial intelligence, and multi-factor authentication. The sector is grappling with challenges such as outdated security systems, inadequate staff training, and the complexities of safeguarding networks of interconnected devices.

As cyberattacks become more frequent and sophisticated, understanding cybersecurity statistics within healthcare is essential for identifying vulnerabilities, assessing risks, and strengthening defenses to protect sensitive patient data and maintain trust within the industry.

Graph and download economic data for Expenditures: Healthcare by Age: Age 65 or over (CXUHEALTHLB0407M) from 1988 to 2023 about 65-years +, age, healthcare, health, expenditures, and USA.

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.

Healthcare Cost and Utilization Project (HCUP) Fast Stats provides easy access to the latest HCUP-based statistics for health care information topics. HCUP Fast Stats uses visual statistical displays in stand-alone graphs, trend figures, or simple tables to convey complex information at a glance. Fast Stats is updated regularly for timely, topic-specific national and State-level statistics. Fast Stats topics and graphics on hospital stays and emergency department visits, including information at the national, and state levels, trends over time, and selected priority topics such as: State Trends in Hospital User by Payer National Hospital Utilization and Costs Hurricane Impact on Hospital Use Opioids & Neonatal Abstinence Syndrome Severe Maternal Morbidity

This is an overview document covering the Healthcare Workforce as at March 2019 and refers to numbers of staff in three areas: i) Those directly employed by the NHS in Hospital and Community Health Services (HCHS) ii) GPs and their staff iii) A proportion of the staff working in Independent Healthcare Providers (see key facts below). More information on all of these areas are available within the accompanying documents and also via the 'Related Links' section below. This includes a link to the Independent Healthcare Provider Workforce report. We are now reviewing the content, format and purpose of this publication and welcome your feedback. In particular we are considering whether it would be useful to provide something more like a data hub to help guide users around the workforce publications including interactive visualisations rather than continuing with the current publication. Please email us with your comments and suggestions, clearly stating Healthcare Workforce Statistics as the subject heading, via enquiries@nhsdigital.nhs.uk

Introduction

AI in Healthcare Statistics: Artificial intelligence (AI) is swiftly reshaping the healthcare sector, transforming areas such as diagnostics, treatment planning, patient management, and drug development. By analyzing large volumes of data and delivering precise insights, AI is boosting clinical decision-making, enhancing patient outcomes, and optimizing healthcare operations.

Key advancements in machine learning, natural language processing, and other AI technologies are propelling this shift, with healthcare systems worldwide increasingly adopting these innovations to improve efficiency and offer more personalized care. The ongoing potential of AI to refine healthcare delivery is reshaping the industry's future.

AI in healthcare is accelerating transformation, from diagnosing illnesses faster to streamlining hospital workflows. Impact spans advanced diagnostics to drug development and patient documentation. For example, AI is cutting drug development timelines by over 50% in some cases, and ambient‑AI scribes are already easing burnout for clinicians. Explore the stats...

Introduction

EHR Industry Statistics: Electronic Health Records (EHRs) are digital versions of patient paper charts, revolutionizing healthcare by providing instant, secure access to comprehensive medical information.

They include details like medical history, diagnoses, medications, and test results, consolidating data from various sources into one accessible record.

EHRs enhance patient care by supporting better coordination among healthcare providers, improving efficiency through reduced paperwork, and enabling patient engagement via access to their records.

Challenges include high implementation costs, interoperability issues between different systems, and concerns about data privacy.

Looking ahead, advancements aim to improve interoperability, enhance data analytics, and integrate with telemedicine for more efficient and personalized healthcare delivery.