In 2023, U.S. national health expenditure as a share of its gross domestic product (GDP) reached 17.6 percent, this was an increase on the previous year. The United States has the highest health spending based on GDP share among developed countries. Both public and private health spending in the U.S. is much higher than other developed countries. Why the U.S. pays so much moreWhile private health spending in Canada stays at around three percent and in Germany under two percent of the gross domestic product, it is nearly nine percent in the United States. Another reason for high costs can be found in physicians’ salaries, which are much higher in the U.S. than in other wealthy countries. A general practitioner in the U.S. earns nearly twice as much as the average physician in other high-income countries. Additionally, medicine spending per capita is also significantly higher in the United States. Finally, inflated health care administration costs are another of the predominant factors which make health care spending in the U.S. out of proportion. It is important to state that Americans do not pay more because they have a higher health care utilization, but mainly because of higher prices. Expected developmentsBy 2031, it is expected that health care spending in the U.S. will reach nearly one fifth of the nation’s gross domestic product. Or in dollar-terms, health care expenditures will accumulate to about seven trillion U.S. dollars in total.

Limit state-purchased health care cost growth to 2% less than the projected national health expenditures average every year through 2019.

Health expenditure in the U.S. has been a hotly debated topic among political parties, especially on the verge of presidential elections. Health expenditures in the U.S. have been increasing over time and are projected to keep increasing. As of 2023, the U.S. spent a total of *** trillion U.S. dollars on healthcare. U.S. health expenditure in comparison The U.S has some of the highest expenditures for health care in the world. With a total health spending of roughly ** percent of the country’s GDP, the U.S. has far surpassed the country with the second highest health expenditure as a share of GDP, Germany. The United States, despite having a mixed method of healthcare financing and insurances, also has one of the highest shares of domestic governmental health expenditures. U.S. health care payers There are several different governmental and non-governmental agencies that are responsible for health care funding and payments in the United States. Currently, private insurance and Medicare are the two largest payers of U.S. health care. Direct health care costs are not the only things that these payers are responsible for. They may also be partly responsible for prescription drug costs. Again, private insurance and Medicare are the two largest payers of prescription drug costs in the U.S. Among all the payers of health care costs in the U.S., Medicare has experienced the highest level of health spending increases in recent years.

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Explore the intricacies of medical costs and healthcare expenses with our meticulously curated Medical Cost Dataset. This dataset offers valuable insights into the factors influencing medical charges, enabling researchers, analysts, and healthcare professionals to gain a deeper understanding of the dynamics within the healthcare industry.

Columns: 1. ID: A unique identifier assigned to each individual record, facilitating efficient data management and analysis. 2. Age: The age of the patient, providing a crucial demographic factor that often correlates with medical expenses. 3. Sex: The gender of the patient, offering insights into potential cost variations based on biological differences. 4. BMI: The Body Mass Index (BMI) of the patient, indicating the relative weight status and its potential impact on healthcare costs. 5. Children: The number of children or dependents covered under the medical insurance, influencing family-related medical expenses. 6. Smoker: A binary indicator of whether the patient is a smoker or not, as smoking habits can significantly impact healthcare costs. 7. Region: The geographic region of the patient, helping to understand regional disparities in healthcare expenditure. 8. Charges: The medical charges incurred by the patient, serving as the target variable for analysis and predictions.

Whether you're aiming to uncover patterns in medical billing, predict future healthcare costs, or explore the relationships between different variables and charges, our Medical Cost Dataset provides a robust foundation for your research. Researchers can utilize this dataset to develop data-driven models that enhance the efficiency of healthcare resource allocation, insurers can refine pricing strategies, and policymakers can make informed decisions to improve the overall healthcare system.

Unlock the potential of healthcare data with our comprehensive Medical Cost Dataset. Gain insights, make informed decisions, and contribute to the advancement of healthcare economics and policy. Start your analysis today and pave the way for a healthier future.

Graph and download economic data for Health Expenditures per Capita (HLTHSCPCHCSA) from 2000 to 2021 about healthcare, health, expenditures, per capita, and USA.

The retirement healthcare cost index compares the estimated cost of healthcare at retirement against expected social security benefits (before taxes) throughout retirement. The retirement healthcare cost index for a healthy 65-year-old- couple retiring in 2023 in the U.S. is estimated to be **** percent in the first year. In the next ten years, it is projected to rise to ** percent, and by the end of their lives, it is most likely to offset their social security payments.

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

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.

Historical chart and dataset showing Switzerland healthcare spending per capita by year from 2000 to 2022.

This dataset identifies health care spending at medical services such as hospitals, physicians, clinics, and nursing homes etc. as well as for medical products such as medicine, prescription glasses and hearing aids. This dataset pertains to personal health care spending in general. Other datasets in this series include Medicaid personal health care spending and Medicare personal health care spending.

In the U.S. many employers pay a portion of health care costs for employees. As of 2019, the total annual medical costs for employees was just over 13 thousand U.S. dollars. That cost is expected to increase to 13.7 thousand U.S. dollars by 2020. There have been recent changes to employer-offered health care through the Affordable Care Act that requires employers with over 50 employees to offer affordable health care options to their employees.

U.S. health benefits at work

In the United States, both employers and employees may pay health care costs, depending on the work. In a recent survey U.S. residents were asked what benefits they expected from their employers, a vast majority of them said that they expect health care benefits. Despite the demand from employer-sponsored healthcare coverage, not all companies feel that they would be able to offer health coverage as an employment benefit. Another recent survey has illustrated that employer confidence in offering health insurance can change dramatically from year-to-year.

U.S. sick leave benefits

Another aspect of workplace health and wellness, is annual sick leave. In general, a majority of U.S. workers have access to a fixed number of paid sick days per year. However, a very small proportion of employees had access to paid sick leave as needed. As of 2017, around half of all employees utilized up to 5 days of sick leave per year. Despite that, there was still a large proportion, especially among those aged 18-30 years that went to work even though they were ill.

The rationale for developing the EU HCCD for use in Health Technology Assessment (HTA) across countries is to provide a common dataset of international costs, which can feed into health economic evaluations carried out by transferring economic evaluation analysis and models across countries. Defining a core dataset of costs for use in HTA across countries enables analyses that try to understand the variation in costs within and across countries (taking into account the differences between the healthcare systems and other factors). Additionally, it makes it easier to carry out multi-country studies and to adapt economic evaluation studies from country to country by saving human resources time (and consequently costs) in the task of looking for healthcare costs.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all payers and the uninsured. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in health care data - the lack of nationally representative information on hospital readmissions for all ages. Outcomes of interest include national readmission rates, reasons for returning to the hospital for care, and the hospital costs for discharges with and without readmissions. Unweighted, the NRD contains data from approximately 18 million discharges each year. Weighted, it estimates roughly 35 million discharges. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NRD is drawn from HCUP State Inpatient Databases (SID) containing verified patient linkage numbers that can be used to track a person across hospitals within a State, while adhering to strict privacy guidelines. The NRD is not designed to support regional, State-, or hospital-specific readmission analyses. The NRD contains more than 100 clinical and non-clinical data elements provided in a hospital discharge abstract. Data elements include but are not limited to: diagnoses, procedures, patient demographics (e.g., sex, age), expected source of payer, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge, discharge month, quarter, and year, total charges, length of stay, and data elements essential to readmission analyses. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

Historical chart and dataset showing Lebanon healthcare spending per capita by year from 2000 to 2022.

China Consumption Expenditure per Capita: Health Care and Medical Services data was reported at 2,547.000 RMB in 2024. This records an increase from the previous number of 2,460.000 RMB for 2023. China Consumption Expenditure per Capita: Health Care and Medical Services data is updated yearly, averaging 743.700 RMB from Dec 1998 (Median) to 2024, with 27 observations. The data reached an all-time high of 2,547.000 RMB in 2024 and a record low of 173.200 RMB in 2000. China Consumption Expenditure per Capita: Health Care and Medical Services data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Expenditure per Capita.

The dataset contains a summary of government spending on healthcare, presented as a share of a country's GDP in selected years. Data are presented for the years 1880–2020, in 10-year intervals (i.e. in 1880, 1890, 1900, …, 2010, 2020). The aim of the summary was to present changes in the approach of governments of selected countries in Europe (including Poland), the USA, China andIndia over the 140 years studied.

This dataset contains data for the Healthcare Payments Data (HPD): Medical Out-of-Pocket Costs and Chronic Conditions report. The data covers three measurement categories: annual member count, annual median out-of-pocket count, annual median claim count. The annual member count quantify the number of unique individuals who received at least one medical service in the reporting year. Annual median out-of-pocket measurements quantifies the sum of copay, coinsurance, and deductible incurred by members. Annual median claim count measurements quantifies the number of distinct claims or encounters associated with members. Both 25th and 75th percentiles for out-of-pocket cost and claim count are also included. Measures are grouped by payer types, chronic conditions flag, chronic condition types, and chronic condition numbers.

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.

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These data files contain the highest level of cost report status for cost reports in all reported fiscal years. For example, if the Healthcare Cost Report Information System (HCRIS) department has both an as submitted report and a final settled report for a hospital for a particular year, the data files will only contain the final settled report. If HCRIS has both a final settled report and a reopened report, the data files will only have the reopened report.

These data files contain the highest level of cost report status for cost reports in all reported fiscal years. For example, if the Healthcare Cost Report Information System (HCRIS) department has both an as submitted report and a final settled report for a hospital for a particular year, the data files will only contain the final settled report. If HCRIS has both a final settled report and a reopened report, the data files will only have the reopened report.

Historical chart and dataset showing St. Martin (French part) healthcare spending per capita by year from N/A to N/A.