The percentage of people in the United States with health insurance has increased over the past decade with a noticeably sharp increase in 2014 when the Affordable Care Act (ACA) was enacted. As of 2023, around ** percent of people in the United States had some form of health insurance, compared to around ** percent in 2010. Despite the increases in the percentage of insured people in the U.S., there were still over ** million people in the United States without health insurance as of 2023. Insurance coverage Health insurance in the United States consists of different private and public insurance programs such as those provided by private employers or those provided publicly through Medicare and Medicaid. Almost half of the insured population in the United States were insured privately through an employer as of 2021, while **** percent of people were insured through Medicaid, and **** percent through Medicare . The Affordable Care Act The Affordable Care Act (ACA), enacted in 2014, has significantly reduced the number of uninsured people in the United States. In 2014, the percentage of U.S. individuals with health insurance increased to almost ** percent. Furthermore, the percentage of people without health insurance reached an all time low in 2022. Public opinion on healthcare reform in the United States remains an ongoing political issue with public opinion consistently divided.

As of 2023, 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 2023, 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.

In 2023, 25 million people in the United States had no health insurance. The share of Americans without health insurance saw a steady increase from 2015 to 2019 before starting to decline in 2020 to 2023. Factors like the implementation of Medicaid expansion in additional states and growth in private health insurance coverage led to the decline in uninsured population, despite the economic challenges due to the pandemic in 2020. Positive impact of Affordable Care Act In the U.S. there are public and private forms of health insurance, as well as social welfare programs such as Medicaid and programs just for veterans such as CHAMPVA. The Affordable Care Act (ACA) was enacted in 2010, which dramatically reduced the share of uninsured Americans, though there’s still room for improvement. In spite of its success in providing more Americans with health insurance, ACA has had an almost equal number of proponents and opponents since its introduction, though the share of Americans in favor of it has risen since mid-2017 to the majority. Persistent disparity among ethnic groups The share of uninsured people is higher in certain demographic groups. For instance, Hispanics continue to be the ethnic group with the highest rate of uninsured people, even after ACA. Meanwhile the share of uninsured White and Asian people is lower than the national average.

In 2023, 10.9 percent of people aged 18 to 64 in the United States didn't have health insurance, the lowest in the provided time interval. This statistic contains data on the percentage of U.S. Americans without health insurance coverage from 1997 to 2023, by age.

In 2023, over 178 million people in the United States had private health insurance through their employer, compared, while a further 33.8 million people had private health insurance through direct purchase. This statistic shows the number of people in the United States with private health insurance in 2023, by type.

Medicare is an important public health insurance scheme for U.S. adults aged 65 years and over. As of 2023, an estimated 18.9 percent of the U.S. population was covered by Medicare, an increase from the previous year. As of 2021, California, Florida, and Texas had the largest number of adults aged 65 years and older. The Medicare program Medicare has two primary parts: Medicare Part A covers hospital care and Medicare Part B covers medical and preventative services. Both parts of Medicare are available to those aged 65 years and older under certain conditions. Medicare premiums are variable and depend on the enrollee’s income. Despite a majority of the Medicare enrollees being above the federal poverty line, there are still several programs in place to help cover the costs of healthcare for the elderly. Opinions on elderly care in the U.S. It is estimated that about 23 percent of Medicare enrollees are in fair/poor health. But there are lots of questions about who should pay for or help with elderly care long-term. In a recent survey of U.S. adults, about half of the respondents said that health insurance companies should pay for elderly care. However, a majority of adults also supported a long-term government sponsored health plan like Medicaid. The issue is still hotly debated and politicized in the United States.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black). Later vintages of this layer have a different age group for children that includes age 18. This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Graph and download economic data for Health Insurance Coverage: Total Number of People in New York (DISCONTINUED) (NYHICTOTAL) from 1999 to 2012 about health, insurance, NY, persons, and USA.

Graph and download economic data for Health Insurance Coverage: Total Number of People in Ohio (DISCONTINUED) (OHHICTOTAL) from 1999 to 2012 about health, insurance, OH, persons, and USA.

This layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black)This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Life And Health Insurance Market Outlook

In 2023, the global market size for life and health insurance was valued at approximately USD 4.9 trillion and is anticipated to reach around USD 9.2 trillion by 2032, growing at a compound annual growth rate (CAGR) of 7.2% during the forecast period. The growth of this market is primarily driven by increasing awareness about the necessity of insurance, rising healthcare costs, and an aging global population.

One of the major growth factors for the life and health insurance market is the rising global awareness regarding the importance of insurance coverage. With increasing education and access to information, more individuals understand the financial protection and benefits that life and health insurance provide. Governments and private organizations are also running multiple awareness campaigns to educate the masses about the significance of insurance, which is boosting market growth. Additionally, the legislative push in many countries to make health insurance mandatory is creating a substantial market demand.

Another critical driver for this market is the escalating cost of healthcare. As medical treatments become more advanced and specialized, the associated costs have significantly increased, making it almost imperative for individuals to have health insurance to cover these expenses. This trend is particularly noticeable in developed nations where healthcare costs are skyrocketing. Consequently, people are increasingly purchasing health insurance policies to protect themselves from financial distress in case of medical emergencies.

The aging global population is another significant factor pushing the demand for life and health insurance. With advancements in healthcare, global life expectancy has increased, resulting in a larger elderly population. This demographic shift is creating a substantial need for both life and health insurance products. Older individuals are more prone to health issues, making health insurance a critical necessity for them. Moreover, life insurance policies are gaining traction as people look to ensure financial security for their dependents after their demise.

In addition to life and health insurance, the broader spectrum of Life and Non-Life Insurance plays a crucial role in providing comprehensive coverage to individuals and businesses. While life insurance focuses on providing financial security to beneficiaries in the event of the policyholder's death, non-life insurance encompasses a range of products such as property, casualty, and liability insurance. These products protect against various risks, including natural disasters, accidents, and legal liabilities, ensuring that both individuals and businesses can safeguard their assets and maintain financial stability in the face of unforeseen events. The integration of life and non-life insurance products allows for a holistic approach to risk management, catering to diverse needs and preferences across different sectors.

Regionally, North America remains a dominant player in the life and health insurance market due to its well-established healthcare infrastructure and high awareness levels among its population. The Asia Pacific region is emerging as a lucrative market owing to the rapid economic development, increasing middle-class population, and growing awareness regarding the significance of insurance. Europe, Latin America, and the Middle East & Africa are also showing promising growth trends driven by various regional factors.

Type Analysis

The life and health insurance market is segmented by type into term life insurance, whole life insurance, universal life insurance, health insurance, and others. Term life insurance is particularly popular due to its straightforward nature and lower premiums compared to permanent life insurance products. These policies provide coverage for a specified term, usually 10, 20, or 30 years, making them an affordable option for many. The simplicity and lower cost of term life insurance are significant factors contributing to its widespread adoption.

Whole life insurance, on the other hand, offers life-long coverage and includes a savings component known as cash value. This type of insurance is gaining popularity among individuals who are looking for a combination of protection and investment. The cash value component grows over time and can be borrowed against, providing policyholders with a financial cushion. Universal

In 2023, nearly ** percent of people in the United States had public health insurance, the share of people with private health insurance has gradually increased in the provided time interval. This statistic contains data on the number of U.S. Americans with government health insurance coverage from 1997 to 2023.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Graph and download economic data for Health Insurance Coverage: Total Number of People in California (DISCONTINUED) (CAHICTOTAL) from 1999 to 2012 about health, insurance, CA, persons, and USA.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

This layer shows health insurance coverage by type and by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

Snapshot img

Health Insurance Market Size 2025-2029

The health insurance market size is forecast to increase by USD 1,341 billion at a CAGR of 7.3% between 2024 and 2029.

The market experiences robust growth, fueled by the increasing demand for comprehensive coverage due to heightened healthcare awareness and a growing emphasis on preventive health. This trend is further driven by the escalating costs of healthcare services and medical treatments, which underscores the importance of insurance as a financial safeguard. However, market expansion encounters significant challenges. Regulatory hurdles impact adoption, as governments and regulatory bodies implement stringent regulations to ensure affordability and accessibility for consumers. Supply chain inconsistencies, such as disparities in provider networks and reimbursement rates, temper growth potential. This is particularly evident in the rising prevalence of chronic conditions such as cancer, stroke, and kidney failure, which necessitate ongoing medication and hospitalization. Additionally, another trend is the shift towards online sales and digital platforms for purchasing insurance policies and accessing healthcare services.
To capitalize on opportunities and navigate challenges effectively, companies must stay informed of regulatory changes and collaborate with healthcare providers to streamline operations and maintain competitive pricing. By focusing on innovation, transparency, and customer-centric solutions, insurers can differentiate themselves in a competitive landscape and meet the evolving needs of health-conscious consumers.

What will be the Size of the Health Insurance Market during the forecast period?

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In the dynamic market, chronic disease management and mental health coverage have emerged as significant areas of focus. Health insurance networks strive to offer comprehensive solutions, integrating geriatric care, preventive care, and end-of-life care into their offerings. Innovation drives the industry, with wellness programs, home health care, and telemedicine becoming increasingly popular. Compliance with regulations, including those related to maternity care, newborn care, and substance abuse treatment, is crucial.
Specialty care and provider networks continue to shape the landscape, while ethics and claims processing remain critical components of health insurance services. Incorporating mental health coverage into plans and addressing the needs of the aging population are key trends shaping the market.

How is this Health Insurance Industry segmented?

The health insurance industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Service

  Public
  Private


Type

  Life insurance
  Term insurance


Age Group

  Adults
  Senior citizens
  Minors


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Service Insights

The public segment is estimated to witness significant growth during the forecast period.

In the dynamic market, various entities play crucial roles in shaping its landscape. Public organizations, such as the National Health Service (NHS) in the UK and Medicare in Australia, are leading providers due to increased government involvement in ensuring universal healthcare access. These programs offer comprehensive coverage, affordable premiums, and a focus on preventive care. Collaborations with commercial insurers, legislative frameworks, and investments in healthcare infrastructure further expand their reach. Quality is a top priority, with health insurance advisors and brokers facilitating the selection of plans that best fit businesses and individuals. Prescription drug coverage is a significant consideration, and self-funded health insurance and health reimbursement arrangements offer flexibility for employers.

Group health insurance and individual health insurance provide different solutions for various needs, with portability ensuring continuity. Health insurance cybersecurity and technology are essential, with health insurance portals, virtual care, and telemedicine transforming the industry. Health savings accounts, flexible spending accounts, and out-of-pocket maximums help manage costs. Managed care and employer-sponsored health insurance are common, with health insurance plans catering to diverse needs. Regulations and compliance are critical, with long-term care insurance addressing specific healthcare requirements. Disability insurance and life insurance provide additional coverage, while the marketing and transparency ensure consumer understanding. Point-of-service (POS) plans and dental/vision insurance of

In 2023, around ** percent of people in the United States had private health insurance. This represents a steady decrease since 2015. This statistic contains data on the number of U.S. Americans with private health insurance coverage from 1997 to 2023.

Graph and download economic data for Health Insurance Coverage: Total Number of People in Montana (DISCONTINUED) (MTHICTOTAL) from 1999 to 2012 about MT, health, insurance, persons, and USA.