In 2023, single coverage health insurance for employees cost more than ***** U.S. dollars for the year. this figure has increase every year since 2000, with the average annual cost of health insurance for singles being ***** in 2000.

In the United States, the annual price of health insurance declined by 33.6 percent in the last 12 months which ended in August 2023 after rising by 24.3 percent in the previous year. Over the provided time interval, health insurance prices increased at an average inflation rate of approximately five percent. This statistic shows the annual inflation rate of health insurance prices in the U.S. from 2007 to 2023.

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.

This dataset contains medical insurance cost information for 1338 individuals. It includes demographic and health-related variables such as age, sex, BMI, number of children, smoking status, and residential region in the US. The target variable is charges, which represents the medical insurance cost billed to the individual.

The dataset is commonly used for:

Regression modeling

Health economics research

Insurance pricing analysis

Machine learning education and tutorials

Columns

age: Age of primary beneficiary (int)

sex: Gender of beneficiary (male, female)

bmi: Body Mass Index, a measure of body fat based on height and weight (float)

children: Number of children covered by health insurance (int)

smoker: Smoking status of the beneficiary (yes, no)

region: Residential region in the US (northeast, northwest, southeast, southwest)

charges: Medical insurance cost billed to the beneficiary (float)

Potential Uses

Build predictive models for medical costs Explore how smoking and BMI impact charges Teach students about regression and feature engineering Analyze healthcare affordability trends

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.

Graph and download economic data for Producer Price Index by Industry: Direct Health and Medical Insurance Carriers: Indemnity Health Insurance Plans (PCU5241145241142) from Dec 2002 to Sep 2025 about medical, health, insurance, PPI, industry, inflation, price index, indexes, price, and USA.

In 2023, the total value of direct premiums written by private health insurance companies amounted to approximately *** trillion U.S. dollars. This is more than double the ****** billion U.S. dollars recorded ten years prior in 2013, and over *** billion U.S. dollars higher than the value recorded in 2022. Note these totals include direct premiums written under the Medicare and Medicaid programs, both of which are (largely) public funded.

In 2023, family coverage insurance for fully insured employees cost on average ****** U.S. dollars, whereas employees who funded their own health insurance paid ****** U.S. dollars. Both these figures have increased every year since 2000, with the values being ***** and ***** U.S. dollars respectively in 2000.

This dataset provides a realistic look at how important lifestyle and human characteristics are used to calculate health insurance rates. It presents a wide range of people, each characterized by their age, gender, BMI, number of dependents, smoking status, and geographic location, as well as the associated insurance bills they received.

We can find important patterns by examining this dataset, like: Why smokers pay noticeably higher premiums How age and BMI affect medical expenses Whether insurance costs are higher in some areas The connection between charges and family size

US Health Insurance

Exploring Rates, Benefits, and Providers

By Data Society [source]

About this dataset

This fascinating dataset from the Centers for Medicare & Medicaid Services provides an in-depth analysis of health insurance plans offered throughout the United States. Exploring this data, you can gain insights into how plan rates and benefits vary across states, explore how plan benefits relate to plan rates, and investigate how plans vary across insurance network providers.

The top-level directory includes six CSV files which contain information about: BenefitsCostSharing.csv; BusinessRules.csv; Network.csv; PlanAttributes.csv; Rate.csv; and ServiceArea.csv - as well as two additional CSV files which facilitate joining data across years: Crosswalk2015.csv (joining 2014 and 2015 data) and Crosswalk2016

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For more datasets, click here.

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How to use the dataset

This Kaggle dataset contains comprehensive data on US health insurance Marketplace plans. The data was obtained from the Centers for Medicare & Medicaid Services and contains information such as plan rates and benefits, metal levels, dental coverage, and child/adult-only coverages.

In order to use this dataset effectively, it is important to understand the different columns/variables that make up the dataset. The columns are state, dental plan, multistate plan (2015 and 2016), metal level (2014-2016), child/adult-only coverage (2014-2016), FIPS code (Federal Information Processing Standard code for the particular state), zipcode, crosswalk level (level of crosswalk between 2014-2016 data sets), reason for crosswalk parameter.

Using this dataset can help you answer interesting questions about US health insurance Marketplace plans across different variables such as state or rate information. It may also be interesting to compare certain variables over time with respect to how they affect certain types of people or how they differ across states or regions. Additionally, an analysis of the different price points associated with various kinds of coverage could provide insights into which kinds of plans are most attractive in various marketplaces based on cost savings alone

Once you have a good understanding of your data by studying individual parameters in depth across multiple states or regions you can begin looking at correlations between different parameters You can identify patterns that emerge around common characteristics or trends within areas or across markets over time when you have gathered sufficient historical data:

• Does higher out of pocket limits tend to come with higher premiums?
• Are there more multi-state markets in some states than others?
• What type of metal levels does each region prefer?

Research Ideas

• Examining the impacts of age, metal levels and plan benefits on insurance rates in different states.
• Analyzing how dental plans vary across different states/regions and examining whether there are correlations between affordability and quality of care among plans with dental coverage options.
• Investigating how the Crosswalk level affects insurance rates by comparing insurance premiums from different metals level across states with varying Crosswalk Levels (e.g., how does a Bronze plan differ in cost for two states with differing Crosswalk Level 1 vs 2)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Crosswalk2016.csv | Column name | Description | |:------------------------------|:------------------------------------------------------------------------------------------------------------------------------| | State | The state in which...

The graph presents the number of people with health insurance in the United States from 2013 to 2023. The x-axis represents the years, ranging from 2013 to 2023, while the y-axis shows the number of insured individuals in millions. Throughout this period, the number of people with health insurance rose from approximately 271.6 million in 2013 to 305 million in 2023, marking the lowest value in 2013 and the highest in 2023. The data exhibits a steady upward trend in health insurance coverage over the ten-year span. This information is depicted in a line graph, effectively highlighting the annual increase in the insured population.

Total insurance premium income statistics for health insurance in the property and casualty insurance market in the last five years (Insurance Regulatory and Development Authority of India)

Graph and download economic data for Producer Price Index by Industry: Direct Health and Medical Insurance Carriers: Dental Service Plans (PCU52411452411410301) from Dec 2000 to Aug 2025 about dental, medical, health, insurance, services, PPI, industry, inflation, price index, indexes, price, and USA.

The data is formatted as a spreadsheet, encompassing the primary activities over a span of three full years (2017, 2018 and 2019) concerning non-life health insurance portfolio. This dataset comprises 228,711 rows and 42 columns. Each row signifies a insured (individual) policy, while each column represents a distinct variable.

Context

The Affordable Care Act (ACA) is the name for the comprehensive health care reform law and its amendments which addresses health insurance coverage, health care costs, and preventive care. The law was enacted in two parts: The Patient Protection and Affordable Care Act was signed into law on March 23, 2010 by President Barack Obama and was amended by the Health Care and Education Reconciliation Act on March 30, 2010.

Content

This dataset provides health insurance coverage data for each state and the nation as a whole, including variables such as the uninsured rates before and after Obamacare, estimates of individuals covered by employer and marketplace healthcare plans, and enrollment in Medicare and Medicaid programs.

Acknowledgements

The health insurance coverage data was compiled from the US Department of Health and Human Services and US Census Bureau.

Inspiration

How has the Affordable Care Act changed the rate of citizens with health insurance coverage? Which states observed the greatest decline in their uninsured rate? Did those states expand Medicaid program coverage and/or implement a health insurance marketplace? What do you predict will happen to the nationwide uninsured rate in the next five years?

China Insurance Premium: Year to Date: Health: Group data was reported at 228.000 RMB mn in Dec 2024. This records a decrease from the previous number of 236.000 RMB mn for Nov 2024. China Insurance Premium: Year to Date: Health: Group data is updated monthly, averaging 18.152 RMB mn from Jan 2006 (Median) to Dec 2024, with 219 observations. The data reached an all-time high of 1,733.000 RMB mn in Sep 2023 and a record low of 0.054 RMB mn in Jan 2007. China Insurance Premium: Year to Date: Health: Group data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under Global Database’s China – Table CN.RGD: Insurance Premium: Monthly Summary by Region: Health Insurance.

Insurance Premium: Year to Date: Health: Zhejiang data was reported at 13,724.000 RMB mn in Feb 2025. This records an increase from the previous number of 5,715.000 RMB mn for Jan 2025. Insurance Premium: Year to Date: Health: Zhejiang data is updated monthly, averaging 4,500.370 RMB mn from Jan 2006 (Median) to Feb 2025, with 230 observations. The data reached an all-time high of 53,760.000 RMB mn in Dec 2024 and a record low of 117.007 RMB mn in Jan 2007. Insurance Premium: Year to Date: Health: Zhejiang data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under Global Database’s China – Table CN.RGD: Insurance Premium: Monthly Summary by Region: Health Insurance.

Insurance Premium: Year to Date: Health: Yunnan data was reported at 5,478.000 RMB mn in Feb 2025. This records an increase from the previous number of 2,966.000 RMB mn for Jan 2025. Insurance Premium: Year to Date: Health: Yunnan data is updated monthly, averaging 2,431.784 RMB mn from Jan 2006 (Median) to Feb 2025, with 230 observations. The data reached an all-time high of 16,972.000 RMB mn in Dec 2024 and a record low of 46.002 RMB mn in Jan 2006. Insurance Premium: Year to Date: Health: Yunnan data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under Global Database’s China – Table CN.RGD: Insurance Premium: Monthly Summary by Region: Health Insurance.

Insurance Premium: Year to Date: Health: Hunan data was reported at 28,908.000 RMB mn in Oct 2025. This records an increase from the previous number of 27,439.000 RMB mn for Sep 2025. Insurance Premium: Year to Date: Health: Hunan data is updated monthly, averaging 5,634.101 RMB mn from Jan 2006 (Median) to Oct 2025, with 238 observations. The data reached an all-time high of 32,850.000 RMB mn in Dec 2022 and a record low of 58.700 RMB mn in Jan 2006. Insurance Premium: Year to Date: Health: Hunan data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under Global Database’s China – Table CN.RGD: Insurance Premium: Monthly Summary by Region: Health Insurance.

Insurance Premium: Year to Date: Health: Shanghai data was reported at 37,270.000 RMB mn in Oct 2025. This records an increase from the previous number of 34,908.000 RMB mn for Sep 2025. Insurance Premium: Year to Date: Health: Shanghai data is updated monthly, averaging 10,785.601 RMB mn from Jan 2006 (Median) to Oct 2025, with 238 observations. The data reached an all-time high of 40,468.000 RMB mn in Dec 2024 and a record low of 246.151 RMB mn in Jan 2006. Insurance Premium: Year to Date: Health: Shanghai data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under Global Database’s China – Table CN.RGD: Insurance Premium: Monthly Summary by Region: Health Insurance.