In 2024, 33.6 percent of children aged 19 and under in the U.S. had Medicaid health insurance, this share was lower in comparison to the previous year. This statistic illustrates the distribution of children aged 19 and under with Medicaid coverage in the United States (U.S.) from 2017 to 2024.

The percentage of Americans covered by the Medicaid public health insurance plan decreased from **** percent in 2021 to around **** percent in 2024. However, the percentage of those insured through Medicaid remains lower than the peak of **** percent in 2015. The expansion of Medicaid The Affordable Care Act (ACA) provided the option for states to expand Medicaid eligibility to people whose income was below a particular threshold. The ACA’s major coverage expansion came into force in 2014, and the number of individuals estimated to be enrolled in Medicaid has since surpassed ** million. More than ** million children were enrolled in the program in 2018, representing ** percent of overall Medicaid enrollment. State Medicaid coverage Initially, the ACA mandated that all state Medicaid programs would have to be extended to provide medical coverage to nearly all low-income groups. However, the Supreme Court rejected that part of the act in 2012, leaving the door open for states to make their own decision on whether they expand their plans. As of September 2021, ** states plus the District of Columbia have adopted the Medicaid expansion.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received a well-child visit paid for by Medicaid or CHIP, overall and by five subpopulation topics: age group, race and ethnicity, urban or rural residence, program type, and primary language. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results include enrollees with comprehensive Medicaid or CHIP benefits for all 12 months of the year and who were younger than age 19 at the end of the calendar year. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Medicaid and CHIP enrollees who received a well-child visit in 2020." Enrollees are identified as receiving a well-child visit in the year according to the Line 6 criteria in the Form CMS-416 reporting instructions. Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to an urban or rural subpopulation based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF (Rural Medicaid and CHIP enrollees in 2020). Enrollees are assigned to a program type subpopulation based on the CHIP code and eligibility group code that applies to the majority of their enrolled-months during the year (Medicaid-Only Enrollment; M-CHIP and S-CHIP Enrollment). Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

In the state of California, there were approximately *** million children enrolled in Medicaid and CHIP insurance plans in March 2025. Additionally, Texas, New York, and Florida all had more than *** million children enrolled in the programs. How many people are enrolled in Medicaid/CHIP? State Medicaid programs provide medical coverage to millions of Americans, including children, pregnant women, and parents. The Children’s Health Insurance Program (CHIP) was introduced in 1997 to help uninsured children who were previously not eligible for Medicaid. The total number of individuals enrolled in Medicaid and CHIP was approximately **** million in May 2021, and California has the largest state program. How is income eligibility determined? The Affordable Care Act established a new methodology to assess income eligibility for Medicaid and CHIP. The adoption of the Modified Adjusted Gross Income (MAGI) methodology helped to align eligibility rules that previously varied nationwide. In general, an individual’s eligibility is now determined by their MAGI and where it falls in relation to the federal poverty level (FPL). For Medicaid and CHIP plans across all states in 2021, the median upper income eligibility level for children was *** percent of the FPL.

In 2023, some 47.6 percent of Medicaid and CHIP enrollees were aged between 18 and 64 years, while adults aged 65 years accounted for only eight percent of enrollees. Medicaid program is funded jointly by the federal and the state governments, it provided coverage to nearly 19.5 percent of the U.S. population in 2022. Medicaid vs CHIPMedicaid and the Children’s Health Insurance Program (CHIP) both provide health insurance coverage for children from low-income families. Children who are not eligible for Medicaid but who would otherwise be unable to obtain insurance through a family plan are covered by CHIP. More than five million children were enrolled in CHIP in the U.S. in 2023. Medicaid and CHIP funding rateThe Federal Medical Assistance Percentages (FMAPs) are used to calculate the amount of federal matching funds for State Medicare and CHIP programs. To encourage states to expand coverage for uninsured children the federal matching rates for CHIP are generally 15 points higher than the Medicaid rate. However, unlike permanent federal funding for Medicaid, CHIP federal funding is capped and due to expire in FY 2027.

Over ** million Americans were estimated to be enrolled in the Medicaid program as of 2023. That is a significant increase from around ** million ten years earlier. Medicaid is basically a joint federal and state health program that provides medical coverage to low-income individuals and families. Currently, Medicaid is responsible for ** percent of the nation’s health care bill, making it the third-largest payer behind private insurances and Medicare. From the beginning to ObamacareMedicaid was implemented in 1965 and since then has become the largest source of medical services for Americans with low income and limited resources. The program has become particularly prominent since the introduction of President Obama’s health reform – the Patient Protection and Affordable Care Act - in 2010. Medicaid was largely impacted by this reform, for states now had the opportunity to expand Medicaid eligibility to larger parts of the uninsured population. Thus, the percentage of uninsured in the United States decreased from over ** percent in 2010 to *** percent in 2022. Who is enrolled in Medicaid?Medicaid enrollment is divided mainly into four groups of beneficiaries: children, adults under 65 years of age, seniors aged 65 years or older, and disabled people. Children are the largest group, with a share of approximately ** percent of enrollees. However, their share of Medicaid expenditures is relatively small, with around ** percent. Compared to that, disabled people, accounting for **** percent of total enrollment, were responsible for **** percent of total expenditures. Around half of total Medicaid spending goes to managed care and health plans.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received mental health (MH) or substance use disorder (SUD) services, overall and by six subpopulation topics: age group, sex or gender identity, race and ethnicity, urban or rural residence, eligibility category, and primary language. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands, ages 12 to 64 at the end of the calendar year, who were not dually eligible for Medicare and were continuously enrolled with comprehensive benefits for 12 months, with no more than one gap in enrollment exceeding 45 days. Enrollees who received services for both an MH condition and SUD in the year are counted toward both condition categories. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and select states with TAF data quality issues are not included. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Medicaid and CHIP enrollees who received mental health or SUD services in 2020." Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to a sex or gender identity subpopulation using their latest reported sex in the calendar year. Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to an urban or rural subpopulation based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF (Rural Medicaid and CHIP enrollees in 2020). Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

Medicaid and CHIP Eligibility Levels

  Description

The following table provides eligibility levels in each state for key coverage groups that use Modified Adjusted Gross Income (MAGI), as of April 1, 2018. The data represent the principal, but not all, MAGI coverage groups in Medicaid, the Children’s Health Insurance Program (CHIP), and the Basic Health Program (BHP). All income standards are expressed as a percentage of the federal poverty level (FPL). The MAGI-based rules… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/medicaid-and-chip-eligibility-levels.

California has more Medicaid and CHIP enrollees than any other state in the United States. As of April 2023, approximately ** million Americans were enrolled in the Medicaid health insurance programs in California, which accounted for approximately ** percent of the total number of Medicaid enrollees nationwide (**** million). Blow to Medicaid expansion plans California is one of many states that has expanded its Medicaid program under the Affordable Care Act (ACA) to encourage more low-income adults to sign up for health coverage. One of the original aims of the ACA was to limit some of the variations in state Medicaid programs, but the Supreme Court ruled that the expansion should be optional. Governors of the states that did not expand said they were concerned about long-term costs. California is the leading state for Medicaid expenditure, spending approximately **** billion U.S. dollars in FY2020. Health coverage for children The Children’s Health Insurance Program (CHIP) was created as a complement to Medicaid, expanding the reach of government-funded health coverage to more children in low-income families. As of May 2021, over **** million children were enrolled in Medicaid/CHIP programs in California, more than any other state. As of January 2021, the median Medicaid/CHIP eligibility level for children was *** percent of the federal poverty level.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received a well-child visit paid for by Medicaid or CHIP, overall and by five subpopulation topics: age group, race and ethnicity, urban or rural residence, program type, and primary language. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results include enrollees with comprehensive Medicaid or CHIP benefits for all 12 months of the year and who were younger than age 19 at the end of the calendar year. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Medicaid and CHIP enrollees who received a well-child visit in 2020." Enrollees are identified as receiving a well-child visit in the year according to the Line 6 criteria in the Form CMS-416 reporting instructions. Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to an urban or rural subpopulation based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF (Rural Medicaid and CHIP enrollees in 2020). Enrollees are assigned to a program type subpopulation based on the CHIP code and eligibility group code that applies to the majority of their enrolled-months during the year (Medicaid-Only Enrollment; M-CHIP and S-CHIP Enrollment). Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by urban or rural residence. Results are shown overall; by state; and by four subpopulation topics: scope of Medicaid and CHIP benefits, race and ethnicity, disability-related eligibility category, and managed care participation. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands who were enrolled for at least one day in the calendar year, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results shown overall (where subpopulation topic is "Total enrollees") and for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the race and ethnicity, disability category, and managed care participation subpopulation topics only include Medicaid and CHIP enrollees with comprehensive benefits. Results shown for the disability category subpopulation topic only include working-age adults (ages 19 to 64). Results for states with TAF data quality issues in the year have a value of "Unusable data." Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Rural Medicaid and CHIP enrollees in 2020." Enrollees are assigned to an urban or rural category based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to a disability category subpopulation using their latest reported eligibility group code and age in the year (Medicaid enrollees who qualify for benefits based on disability in 2020). Enrollees are assigned to a managed care participation subpopulation based on the managed care plan type code that applies to the majority of their enrolled-months during the year (Enrollment in CMC Plans). Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by primary language spoken (English, Spanish, and all other languages). Results are shown overall; by state; and by five subpopulation topics: race and ethnicity, age group, scope of Medicaid and CHIP benefits, urban or rural residence, and eligibility category. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands who were enrolled for at least one day in the calendar year, except where otherwise noted. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and select states with data quality issues with the primary language variable in TAF are not included. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown overall (where subpopulation topic is "Total enrollees") exclude enrollees younger than age 5 and enrollees in the U.S. Virgin Islands. Results for states with TAF data quality issues in the year have a value of "Unusable data." Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Primary language spoken by the Medicaid and CHIP population in 2020." Enrollees are assigned to a primary language category based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to an urban or rural subpopulation based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF (Rural Medicaid and CHIP enrollees in 2020). Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

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...

Medicaid is an important public health insurance for individuals with a low income, those that are pregnant, disabled or are children. It was projected that by 2020 there would be approximately **** million Medicaid enrollees. By 2027 that number is expected to increase to ** million individuals covered.

Medicaid in the focus

Medicaid has recently been in the news for several reasons. A proposed Medicaid expansion was announced with the implementation of the Affordable Care Act in 2010. According to the expansion, all states were given the option to expand Medicaid programs to help provide insurance coverage to millions of U.S. Americans. As of 2019, ** states have accepted federal funding to expand their Medicaid programs. Medicaid, after Medicare and private insurance, provides a significant proportion of the total health expenditures in the United States. In general, Medicaid expenditure, like the number of enrollees, has been growing over time.

Medicaid demographics

A significant proportion of Medicaid enrollees in the U.S. are children and low-income adults. Despite children accounting for most of the enrollees in the Medicaid program, the largest percentage of expenditures for Medicaid is dedicated to those enrolled as a disabled individual. Expenditures for the program also vary regionally. The states with the highest Medicaid expenditures include California, New York and Texas, to name a few.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by race and ethnicity overall and by three subpopulation topics: scope of Medicaid and CHIP benefits, age group, and eligibility category. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, and Puerto Rico who were enrolled for at least one day in the calendar year. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and the U.S. Virgin Islands are not included. Results shown for the age group and eligibility category subpopulation topics only include enrollees with comprehensive Medicaid and CHIP benefits in the year. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on information shown in the brief: "Race and ethnicity of the national Medicaid and CHIP population in 2020." Enrollees are assigned to six race and ethnicity categories using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG). Enrollees are assigned to a child (ages 0-18) or adult (ages 19 and older) subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

In 2015, Medicaid/CHIP participation in the state of Vermont reached 98.7 percent among all eligible children. Several other states, including Alabama and West Virginia, all had participation rates that surpassed 95 percent.

Enrollment projected to increase Medicaid and the Children’s Health Insurance Program (CHIP) combined to provide insurance to around 35 million children in April 2019, with California covering the largest number of enrollees. The Medicaid program alone covers approximately 28 million children across the United States, which represents the largest enrollment group. A steady increase in the number of children covered by the program is expected in the next few years.

How are both programs funded? Medicaid and CHIP differ in terms of size and design, but both are jointly financed by the federal and state governments. For the Medicaid program, the federal government matches costs incurred by states at a 50 percent rate. However, the federal government pays a larger share of costs in poorer states – California had the highest Medicaid expenditure in 2018. An enhanced federal matching rate, which is generally 15 percentage points higher than the Medicaid rate, was created as an incentive for states to expand their CHIP programs.

Children accounted for **** percent of Medicaid enrollees in 2022, which was the largest share of all enrollment groups. The elderly and persons with disabilities had the smallest shares, but together they accounted for ************** of all Medicaid expenditure. Medicaid expenditures per enrollee Medicaid is a joint federal and state health care program in the United States. The program provides medical coverage to millions of Americans and supports a variety of enrollment groups, particularly senior citizens and individuals with disabilities. Medicaid per enrollee spending is significantly higher for these two groups because they require more frequent and costly long-term care in the community and nursing homes. In 2022 of the total U.S. health expenditure on home health care, Medicaid paid one-third. Millions of Americans are uninsured The United States has a multi-payer health care system, meaning that some Americans will be covered by private health insurance, and others will be covered by a government program such as Medicaid. However, approximately **** million people in the U.S. had no health insurance in 2021, and should they require health care, they would have to pay the full price out of their own pocket. This becomes a real problem for many because the United States has the most expensive health care system in the world.

The Healthcare Cost and Utilization Project (HCUP) Kids' Inpatient Database (KID) is the largest publicly available all-payer pediatric inpatient care database in the United States, containing data from two to three million hospital stays each year. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, such as congenital anomalies, as well as uncommon treatments, such as organ transplantation. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The KID is a sample of pediatric discharges from 4,000 U.S. hospitals in the HCUP State Inpatient Databases yielding approximately two to three million unweighted hospital discharges for newborns, children, and adolescents per year. About 10 percent of normal newborns and 80 percent of other neonatal and pediatric stays are selected from each hospital that is sampled for patients younger than 21 years of age. The KID contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes discharge status, diagnoses, procedures, patient demographics (e.g., sex, age), expected source of primary payment (e.g., Medicare, Medicaid, private insurance, self-pay, and other insurance types), and hospital charges and cost. Restricted access data files are available with a data use agreement and brief online security training.

In 2023, just four in ten Medicaid/CHIP enrollees were White, non-Hispanic. In comparison, roughly three-quarters of Medicare beneficiaries were White. The Affordable Care Act (ACA) Medicaid expansion in 2014, has helped reduce racial disparities in access to healthcare in the United States. Medicaid eligibility Medicaid provides health coverage to certain low-income individuals, families, children, pregnant women, the elderly, and persons with disabilities. Each state has its own Medicaid eligibility criteria in accordance with federal guidelines. As a result, Medicaid eligibility and benefits differ widely from state to state. Medicaid expansion provision under the Affordable Care Act (ACA) allows states to provide coverage for low-income adults by expanding eligibility for Medicaid to 138 percent of the federal poverty line (FPL). Medicaid coverage gap Uninsured individuals who live in states that have chosen not to expand Medicaid under the Affordable Care Act (ACA) are referred to as being in the Medicaid coverage gap. As of January 2021, 12 states have not adopted the Medicaid expansion provision under the Affordable Care Act (ACA). More than two million uninsured adults fall into this coverage gap, and among them, more than 60 percent are people of color.

The past five years have marked a period of notable expansion and adaptation across the US dental insurance landscape. Industry revenue is expected to increase at a CAGR of 5.2% to $117.7 billion over the five years to 2025, including an increase of 3.8% in 2025 alone. Propelled by public policy gains that widened the reach of Medicaid and Children’s Health Insurance Program (CHIP), enrollment in dental plans has surged, bringing coverage to a larger share of the population than ever before. New research has deepened understanding of oral health’s vital role in overall well-being, while insurers have responded with broader preventive care initiatives and expanded digital services like teledentistry. Growing awareness about the connections between untreated dental issues and both physical and mental health has made coverage a top priority, especially among younger and underserved populations. Profitability, however, has remained a balancing act for insurers, who’ve faced rising claims, inflation and mounting regulatory requirements. While overall revenue has seen healthy gains, many insurers have felt the squeeze from efforts to stabilize premiums and from new minimum dental loss ratio laws demanding more of each premium dollar go toward patient care. These pressures have prompted companies to rigorously manage administrative expenses and re-examine benefit structures. Even so, profitability hasn’t fallen off—a testament to industry adoption of automation, data analytics and cost containment strategies. Still, with transparency and value-based regulation gathering momentum, insurers will need to stay nimble to keep margin steady and maintain a competitive edge. Looking ahead, the outlook remains positive but somewhat more measured. Industry revenue is expected to increase at a CAGR of 3.2% to $137.5 billion over the next five years, though growth is set to slow as policy support fades and premium subsidies expire. Insurers that succeed will be those that double down on outreach, operational efficiency and creative plan development to retain members and adapt to changing market dynamics. With the expansion of adult Medicaid dental benefits and a continued shift toward value-based care, the industry is well poised for sustainable stability—even as cost pressures and consumer expectations continue to evolve.