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.

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 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 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

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.

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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• 🚨 Your notebook can be here! 🚨!

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...

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: Indemnity Health Insurance Plans (PCU5241145241142) from Dec 2002 to Sep 2025 about medical, health, insurance, PPI, industry, inflation, price index, indexes, price, and USA.

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?

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.

Health Insurance Marketplaces

Rates, Benefits, Coverage and Networks

By Data Society [source]

About this dataset

Do you want to explore the complexities of Health Insurance Marketplace and uncover insights into plan rates, benefits, and networks? Look no further! With this dataset from the Centers for Medicare & Medicaid Services (CMS), you can investigate trends in plan rates, access coverage across states and zip codes, compare metal level plans (across years), as well as analyze benefit information all in one place.

We’ve provided six CSV files containing combined data from across all years: BenefitsCostSharing.csv provides details on benefits, BusinessRules.csv provides details about premium payment requirements for a plan or set of plans, Network.csv offers details about health plans’ networks of providers who offer services at different cost levels to members enrolled in a given plan or set of plans; PlanAttributes.csv gives attributes like age off dates for various plans; Rate.csv delivers information on rate changes; ServiceArea.csv reveals demographic characteristics related to each service area associated with a specific issuer and two CSV files that join data across years (Crosswalk2015 & Crosswalk2016).

So come on board and use your creativity to unlock the mysteries behind changes in benefits in relation to costs while exploring network providers within different regions!!!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset contains information about the health insurance plans offered in the US Health Insurance Marketplace. It includes data on plan benefits, cost-sharing, networks, rates and service areas for different states. The data can be used to compare and analyze plan characteristics across different states and ages which will help guide users decision making when purchasing a health insurance plan.

To begin using the dataset, you should start by looking at the columns available. These include State, Dental Plan, Multistate Plan (2015 & 2016), Metal Level (2015 & 2016), Child/Adult Only (2015 & 2016), FIPS Code, Zip Code Crosswalk Level, Reason for Crosswalk, Multistate Plan Ageoff (2016 & 2015) and MetalLevel Ageoff (2016 & 2015). These columns provide important information on each plan that can be used to compare them across states or between years.

Using this data you can explore several interesting questions such as: How do benefit levels vary among states? Are there any differences in network providers between states? What factors influence plan rates?

In order to answer these questions you should join together relevant tables from across years using Crosswalk 2015/2016 CSV files then organize your data accordingly so that it is easier to visualize differences in features between plans sold across different states or years. Once the information is organized it might be helpful to use visualizations such as line graphs or bar charts to view comparison between feature values of two plans versus one another more clearly in order differentiate variations of plans among Consumers.

By doing this you can gain a better understanding of how certain factors may affect rate changes over time or how certain benefit levels might differ by state which will allow Consumers make an informed choice when selecting their next health insurance plan

Research Ideas

• Analyzing the effectiveness of different plan benefits and how they affect premiums to determine a fair price point for different types of healthcare plans.
• Examining the variation in rates, benefits and coverage by state or zip code to identify potential trends or disparities in access to quality health care services across regions.
• Developing an algorithm that can predict premium prices based on certain factors such as age groups, type of plan (metal levels), multistate coverage, etc., to help consumers more easily understand the true cost of their health insurance plans before committing to purchase them

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 -...

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.

This statistic shows the U.S. government health administration and net cost of private health insurance in select years between 1960 and 2018. In 2000, these costs came to 81.3 billion U.S. dollars. Eighteen years later, costs stood at approximately 306 billion U.S. dollars.

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.

As of 2024, nearly *** million people in the United States had some kind of health insurance, a significant increase from around *** million insured people in 2010. However, as of 2024, there were still approximately ** million people in the United States without any kind of health insurance. Insurance coverage The United States does not have universal health insurance, and so health care cost is mostly covered through different private and public insurance programs. In 2021, almost ** percent of the insured population of the United States were insured through employers, while **** percent of people were insured through Medicaid, and **** percent of people through Medicare. As of 2022, about *** percent of people were uninsured in the U.S., compared to ** percent in 2010. The Affordable Care Act The Affordable Care Act (ACA) significantly reduced the number of uninsured people in the United States, from **** million uninsured people in 2013 to **** million people in 2015. However, since the repeal of the individual mandate the number of people without health insurance has risen. Healthcare reform in the United States remains an ongoing political issue with public opinion on a Medicare-for-all plan consistently divided.

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.

This data package contains the information of Medicare and Medicaid healthcare spending and healthcare cost and percentages by state.

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.

The global Short Term Health Insurance market is experiencing robust expansion, projected to reach an estimated USD 1,500 million by 2025 and exhibiting a compound annual growth rate (CAGR) of approximately 12% over the forecast period of 2025-2033. This significant growth is fueled by a confluence of factors, primarily driven by increasing healthcare costs, evolving consumer preferences for flexible insurance solutions, and a growing segment of the population seeking temporary coverage alternatives to more comprehensive, long-term plans. The market's dynamism is further stimulated by government initiatives aimed at expanding healthcare access and the continuous innovation within the insurance sector, leading to more tailored and affordable short-term options. The Commercial segment is anticipated to be a dominant force, driven by businesses seeking to provide supplementary or interim health benefits to their employees, while the Residential segment is expected to witness steady growth as individuals and families opt for these plans to bridge coverage gaps or manage temporary health needs. The market's upward trajectory is supported by several key trends, including the digitalization of insurance services, enabling faster policy issuance and claims processing, and the introduction of specialized short-term plans catering to specific demographic groups or health concerns. Emerging economies, particularly in the Asia Pacific region, are expected to contribute significantly to market expansion due to a burgeoning middle class and an increasing awareness of health insurance benefits. However, the market also faces certain restraints, such as stringent regulatory frameworks in some regions, the inherent limitations of short-term plans in providing comprehensive coverage, and potential consumer hesitations regarding the long-term adequacy of such policies. Despite these challenges, the persistent demand for agile and cost-effective health insurance solutions positions the Short Term Health Insurance market for sustained and dynamic growth throughout the forecast period. This in-depth report provides a comprehensive analysis of the global Short Term Health Insurance market, spanning the Study Period: 2019-2033, with the Base Year: 2025 and Forecast Period: 2025-2033. Leveraging extensive data from the Historical Period: 2019-2024, this report offers unparalleled insights into market dynamics, key players, and future trajectories. The global market valuation, estimated at USD 15.3 billion in the Estimated Year: 2025, is projected to witness robust growth, fueled by evolving healthcare landscapes and consumer demands.