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.

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

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.

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.

Dataset Overview

This dataset contains information about individuals' demographic, lifestyle, and healthcare costs, likely used for analyzing Medicare or insurance-related expenses. It consists of 1,338 entries and 7 columns.

Columns Description

1. age (int):

   • Age of the individual.
   • Range: 18 to 64 years
   • Mean: 39.2 years

2. sex (object):

   • Gender of the individual.
   • Values: 'male', 'female'

3. bmi (float):

   • Body Mass Index, a measure of body fat based on height and weight.
   • Range: 15.96 to 53.13
   • Mean: 30.66

4. children (int):

   • Number of children/dependents covered by health insurance.
   • Range: 0 to 5
   • Mean: 1.09

5. smoker (object):

   • Smoking status of the individual.
   • Values: 'yes', 'no'

6. region (object):

   • Residential region in the U.S.
   • Values: 'southeast', 'southwest', 'northeast', 'northwest'
   • Most common: 'southeast'

7. charges (float):

   • Individual medical costs billed by health insurance (in USD).
   • Range: $1,121.87 to $63,770.43
   • Mean: $13,270.42
   • Standard Deviation: $12,110.01

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.

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.

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

More Datasets

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...

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.

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.

Dataset Card for Medical Insurance Cost Prediction

The medical insurance dataset encompasses various factors influencing medical expenses, such as age, sex, BMI, smoking status, number of children, and region. This dataset serves as a foundation for training machine learning models capable of forecasting medical expenses for new policyholders. Its purpose is to shed light on the pivotal elements contributing to increased insurance costs, aiding the company in making more informed… See the full description on the dataset page: https://huggingface.co/datasets/rahulvyasm/medical_insurance_data.

In the United States, average employee premium contributions and deductibles as a percentage of median household income have risen in the past decade. In 2020, an employee’s total potential out-of-pocket medical costs (premium and deductible) amounted to 11.6 percent of median income. This included 6.9 percent in employee premium contributions and 4.7 percent in deductibles. However, states varied greatly in median income spent on premiums and deductibles, with workers in Mississippi having to spend on average 19 percent of their income on potential out-of-pocket medical costs.

Employer sponsored health insurance In 2020, over half of the U.S. population has some type of employment-based health insurance coverage. The Affordable Care Act penalizes large employers (with 50 or more full-time employees), if they do not provide health insurance to their employees. Nevertheless, of the uninsured aged under 65 years, the large majority worked either full or part-time (or someone in their household did).

Out-of-pocket medical costs Despite having insurance coverage, most plans have a deductible, the amount an insured must pay themselves that year before their insurance starts covering for them. The average annual deductible for single coverage amounted to roughly 1,700 U.S. dollars in 2021. Even after reaching their deductible, most insured have other forms of out-of-pocket health costs in the form of co-payments and co-insurance for health services or prescription drugs.

The Medical Travel Insurance Cost Report by Squaremouth analyzes thousands of travel insurance policies to provide insights into the cost and value of medical-only coverage for U.S. travelers. The dataset includes comparisons of average costs, daily rates, and coverage types, as well as trends by traveler age and policy type. The data shows generational pricing differences and distinguishes between the cost of medical-only plans versus comprehensive plans, illustrating how coverage inclusions affect premiums.

This dataset provides information about 100,000 individuals including their demographics, socioeconomic status, health conditions, lifestyle factors, insurance plans, and medical expenditures.

It is designed to support machine learning and statistical modeling tasks, such as:

1. Predicting annual medical costs (regression)
2. Classifying individuals by risk level
3. Clustering based on health and insurance profiles
4. Analyzing relationships between demographics, health factors, and costs

The dataset can be useful for insurance cost prediction, risk scoring, claims analysis, and healthcare analytics projects.

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.

Basic, mandatory health insurance in the Netherlands costed on average almost ***** euros per year per person in 2024, an increase of almost 100 euros compared to the previous year. This number only covers health insurance under the so-called Dutch Health Insurance Act (or Zvw), and excludes private, additional health insurance. Also note that this is an average, as premiums vary per person. Some people can receive a discount, for example by taking on a voluntary excess (in Dutch: vrijwillig eigen risico) on top of their already existing mandatory excess (or verplicht eigen risico) in exchange for a lower premium.

A survival of the fittest?

Health insurance in the Netherlands is a hybrid, of sorts. On the one hand, the Dutch government is responsible for the contents of the health insurance package. It is then, however, up to the ** health insurance groups to offer this product via the free market. These insurance groups are obliged to accept all residents of the Netherlands, regardless of age or state of health. To add to the competitiveness within Dutch health insurance, clients can switch insurance provider at the end of every year. If consumers find a health insurance which, for example, is cheaper or provides a better service, they can end their current contract and choose a new company. For example, in 2023, *** percent of the individuals cancelled their health insurance and switched to another company.

Curbing costs

The idea behind this system is two-fold. First, by means of the competitive free market, it is a way for the Dutch government to make healthcare as affordable as it can be. Whether this works is difficult to assess as national healthcare expenses in the Netherlands have grown at a faster rate in recent years, exceeding 100 billion euros since 2020. Second, the system is meant to make consumers more aware of how expensive healthcare is. This is where the aforementioned verplicht eigen risico or mandatory excess comes in. From the age of **, it is compulsory to pay this set amount of money on healthcare during a year before the health insurance starts to reimburse.

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.

China Insurance Premium: Year to Date: LI: Hexie Health Insurance Co Ltd data was reported at 4,891.350 RMB mn in Dec 2021. This records an increase from the previous number of 379.260 RMB mn for Dec 2020. China Insurance Premium: Year to Date: LI: Hexie Health Insurance Co Ltd data is updated monthly, averaging 66.129 RMB mn from Apr 2007 (Median) to Dec 2021, with 144 observations. The data reached an all-time high of 107,031.329 RMB mn in Dec 2016 and a record low of 0.092 RMB mn in Jan 2011. China Insurance Premium: Year to Date: LI: Hexie Health Insurance Co Ltd data remains active status in CEIC and is reported by National Financial Regulatory Administration. The data is categorized under China Premium Database’s Insurance Sector – Table CN.RGD: Insurance Premium: Monthly Summary by Company: Life Insurance. NAFR(CBIRC) no longer publishes monthly insurance company data.

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.

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)