Poll Finding

KFF Tracking Poll on Health Information and Trust: Use of Social Media and AI For Health Information and Advice

Published: Jun 17, 2026

Findings

Key Takeaways

  • Adults in the U.S. are turning to social media and AI to advise them on health issues. KFF’s latest Tracking Poll on Health Information and Trust finds three in ten adults (31%) using social media at least monthly for health information and advice. This is similar to the share (29%) who now say they use AI tools or chatbots for health information monthly, a number that has nearly doubled in the past two years – up from roughly one in six (17%). Still, majorities say they either “never” or only “occasionally” use AI tools (71%) or social media (69%) for health information.
  • Although some people turn to both social media and AI for health information, the two audiences are demographically distinct. While younger adults are more likely than older adults to use social media and AI for health information, the youngest cohort is much more likely to rely on social media while 30 to 49 year olds are more likely to turn to AI. Additionally, social media tends to attract lower-income adults, while AI use is more common among those with higher incomes or more advanced education. Hispanic adults stand out as notable adopters of both platforms for health information, unlike White adults, who are less likely to use either as a source of information.
  • Need for community and immediacy of information drives use of social media for health information and advice. Over a third of those who use social media for health information and advice report that wanting to learn from people with the same health condition or similar experiences is a “major reason” (36%) they turned to social media. A similar share (35%) say it is because they want immediate information or support. While fewer (17%) say that not having a regular health care provider or not being able to afford the cost is a “major reason” for turning to social media, that number rises to a third among adults without insurance and LGBT adults. Notably, similar shares say not being able to afford the cost of seeing a provider (19%) or not having a regular health care provider (18%) are both a “major reason” why they used AI tools for health information in KFF’s March 2026 Tracking Poll on Health Information and Trust as said the same for a reason why they used social media in this poll.
  • The majority of social media and AI users are confident in their ability to parse true or false information, which is perhaps why few take steps to validate the information either from a doctor or some other source. Less than four in ten adults who use social media for health information follow up with a doctor at least most of the time (36%), consult another online source like WebMD (35%), or check with health agency websites, like the CDC (21%).

Social Media and AI Use for Health Information

Three in ten adults report using social media for health information or advice at least once a month. This includes about one in six (16%) who say they use it “every day.” Similarly, three in ten (29%) adults now say they use artificial intelligence (AI) tools or chatbots like ChatGPT, Google Gemini, or Claude for health information and advice monthly, nearly doubling in the past two years, up from roughly one in six (17%) in June 2024. Though they provide health information in different ways, the growing use of these technologies suggests that adults are looking beyond traditional health care sources. Still, a majority of the public say they either “never” or only “occasionally” use AI tools (71%) or social media (69%) for this.

Stacked bar chart showing how often people report using social media or AI tools for health information and advice.

Younger adults (ages 18 to 29), Hispanic adults, Black adults, and those with lower incomes are among the most likely groups to use social media for health information. About four in ten Hispanic adults (42%), those with incomes of $40,000 or less a year (40%), adults under the age of 30 (40%), and Black adults (39%) say they use social media for health information at least monthly.

On the other hand, AI use for health information is common among the youngest cohort (ages 18 to 29) as well as those ages 30 to 49. While those with lower levels of education and income are more likely to go to social media for health information, there is less variation with reliance on AI with about three in ten across income and education groups reporting using it at least monthly. Notably, larger shares of Hispanic adults report using both social media and AI for health information, compared to White adults.

Split bar chart showing the percent of people who report using social media or AI tools for health information and advice at least monthly. Results by total adults, age, race/ethnicity, education, and household income.

Reasons for Using Social Media

People report using social media for health information for a variety of different reasons. Among those who use social media for health information and advice (60% of total adults), over a third (36%) say that wanting to learn from people who have the same health condition or share similar experiences is a “major reason” why. A similar share (35%) says a “major reason” was wanting immediate information or support. Fewer (17%) say that not having a regular health care provider or not being able to afford the cost of seeing a provider is a “major reason” why they turned to social media for health information, though about four in ten (42%) say that it is a reason.

Stacked bar chart showing the percent of people who selected wanting to learn from others, wanting immediate information, and not having a regular health care provider as a reason for using social media to find health information and advice.

The use of social media for health information and advice because of a lack of a regular health care provider or not being able to afford the cost is higher among groups that have historically had a harder time accessing health care. Among social media users, roughly three in ten uninsured adults (32%) say this was a “major reason” and another four in ten (37%) say it is a “minor reason” they turned to social media. Adults with lower incomes are more likely than those with higher incomes to report that not having a regular provider is a “major reason” for using social media for health information, with a quarter of those with an income of less than $40,000 a year saying so, compared to two in ten (19%) of those with an income of $40,000 to $89,999, and less than one in ten (6%) of those with a yearly income of $90,000 or more. LGBT adults are also more likely to say this is a reason they used social media, with three in ten LGBT adults reporting this was a “major reason” and a quarter (24%) saying it’s a “minor reason.” LGBT adults are also more likely to have lower incomes generally, possibly explaining some of the access issues they report, though they may lack a provider due to stigma and discrimination related issues.  

Additionally, larger shares of Hispanic adults (29%) and Black adults (23%) report that not having a regular provider is a “major reason” for seeking advice through social media than White adults (12%).

Stacked bar chart showing the percent of people who said not having a regular health care provider was a reason for using social media to find health information and advice.

Notably, similar shares said not being able to afford the cost of seeing a provider (19%) or not having a regular health care provider (18%) were both a “major reason” why they used AI tools for health information in KFF’s March 2026 Tracking Poll on Health Information and Trust as said the same for a reason why they used social mediain this poll (17%).

Stacked bar chart showing the percent of adults who said not having a regular health care provider, or being unable to afford or get an appointment with one, was a major reason, minor reason, or not a reason they used social media or AI tools for health information and advice.

Women are more likely than men to say that they wanted to learn from people who have the same health condition or shared similar experiences (39% of women v. 32% of men). Young adults under the age of 30 are also among the most likely to say wanting to learn from people with the same condition or experiences is a “major reason” why they sought out health information on social media (44% of those ages 18 to 29 v. 21% of those ages 65 and older).

Split bar chart showing the percentage of adults who said wanting immediate information or support and wanting to learn from people with similar health conditions or experiences, was a major reason they used social media for health information and advice, broken down by total adults, gender, and age group.

Confidence in Discerning True or False Information

Slim majorities of adults say they are confident in their ability to tell what is true or false when it comes to health information from social media (61%) or AI chatbots (56%). In fact, roughly four in ten adults overall say they are “not too” or “not at all” confident in their ability to tell whether health information from AI chatbots (44%) or social media (39%) is true or false. Larger shares are confident when the information comes from more personal sources, with eight in ten saying they are confident they can parse information from a doctor or other health care provider (80%) or their family and friends (77%).

Stacked bar chart showing the percent of adults who said they are not at all confident, not too confident, somewhat confident, or very confident that they can tell true from false health information and advice from AI tools or chatbots, social media, family and friends, and a doctor or health care provider.

Younger adults are more likely to express confidence in their ability to tell whether health advice is true or false on both social media and AI tools or chatbots than their older counterparts. In addition to young adults, adults with a college degree or higher education and those with incomes of $90,000 or more a year are more likely than their counterparts to say they are confident they can tell the difference between true and false health information from social media and AI chatbots.

People who use AI for health advice are more likely than those who do not use it to be confident in their ability to discern what is true when using these tools. However, the difference is less pronounced when it comes to social media. Roughly seven in ten (69%) of those who use AI at least monthly are confident in being able to decipher the truth from that source, compared to half (51%) of those who use AI for health information “occasionally” or “never.” Similarly, a slightly larger share of those who use social media at least monthly say they can tell what is true or not from the health information they find on social media – around two-thirds (65%), compared to six in ten (59%) who don’t use social media for health information.

KFF’s March 2026 Tracking Poll on Health Information and Trust found that trust in AI for reliable health information was largely predicated on use, with most users saying they trust AI for health information compared to few non-users.

Grouped bar chart showing the percentage of adults who say they are very or somewhat confident they can tell true from false health information from social media and from AI tools or chatbots, broken down by total adults, age group, and whether they use each source for health information.

Following Up With Other Sources

While not every health-related social media query requires a follow-up with a doctor or health care professional, few of those who seek health information on social media say they regularly consult any other source for information. Roughly a third of adults who use social media for health information and advice say they followed up with a doctor or other health care professional (36%) “every time” or “most of the time” to verify the accuracy of the information they see on social media. A similar share (35%) say they consulted another online source, such as health websites, like WebMD after using social media for information, and an even smaller share (21%) say they checked with health agency websites, like the CDC, “every” or “most of the time” after using social media for health information and advice in order to verify the accuracy of the information.

In fact, a majority of social media users say they either “some of the time,” “rarely,” or “never” followed up with a health care provider (64%), consulted another online source (65%), or checked a government health agency website (78%) after using social media for health information.

Stacked bar chart showing how often adults who use social media for health information follow up to verify accuracy, ranging from every time to never, across three verification methods: following up with a doctor or health professional, consulting another online source, and checking a government health agency website.

Methodology

This KFF Tracking Poll on Health Information and Trust was designed and analyzed by public opinion researchers at KFF. The survey was conducted May 7 – 31, 2026, online and by telephone among a nationally representative sample of 2,480 U.S. adults in English (2,407) and Spanish (73).

The sample includes 1,977 who were reached through an address-based sample (ABS) and completed the survey online (1,819) or over the phone (158). An additional 503 respondents were reached through a random digit dial telephone (RDD) sample of prepaid (pay-as-you-go) cell phone numbers. Among this prepaid cell phone component, 223 were interviewed by phone and 280 were invited to the web survey via short message service (SMS). Marketing Systems Groups (MSG) provided both the ABS and RDD samples. All fieldwork was managed by SSRS of Glen Mills, PA; sampling design and weighting was done in collaboration with KFF.

Both the ABS and RDD sample frames included disproportionate stratification aimed at reaching Hispanic and non-Hispanic Black respondents. The ABS was also stratified based on model-based prediction of household-members’ party identification (Republican, Democratic, or independent).

Respondents received a $15 incentive for their participation, with interviews completed by phone receiving a mailed check and web respondents receiving an electronic gift card incentive.

In order to ensure data quality, cases were removed if they failed two or more quality checks: (1) attention check questions in the online version of the questionnaire, (2) had over 30% item nonresponse, or (3) had a length less than one quarter of the mean length by mode. Likewise, cases that were reached through ABS who reported a living in a different state than the sampled address were removed for quality assurance. Based on this criterion, 39 cases were removed.

The combined ABS and cell phone samples were weighted to match the sample’s demographics to the national U.S. adult population using data from the Census Bureau’s 2025 Current Population Survey (CPS). The combined sample was weighted by gender by age, gender by education, age by education, race/ethnicity by education, education, race, census region, population density, frequency of internet usage, recalled 2024 vote by quintiles of the county-level 2024 vote share. The weights also take into account differences in the probability of selection for each sample type (ABS and prepaid cell phone). This includes adjustment for the sample design and geographic stratification of the samples, and within household probability of selection. The population density benchmark was from the 2026 Claritas Pop-Facts Premier. The internet frequency benchmarks was from the 2025 National Public Opinion Reference Survey (NPORS) data. The county-level 2024 vote share was from CNN-provided file of 2024 election results by county

The margin of sampling error including the design effect for the full sample is plus or minus 3 percentage points. Numbers of respondents and margins of sampling error for key subgroups are shown in the table below. For results based on other subgroups, the margin of sampling error may be higher. Sample sizes and margins of sampling error for other subgroups are available by request. Sampling error is only one of many potential sources of error and there may be other unmeasured error in this or any other public opinion poll. The following questions included in this survey were designed, analyzed, and paid for by KFF. The demographic questions included in this study were developed and funded jointly by CNN and KFF, with each organization having independent editorial control over its portion of the survey. KFF Public Opinion and Survey Research is a charter member of the Transparency Initiative of the American Association for Public Opinion Research.

GroupN (unweighted)M.O.S.E.
Total2,480± 3 percentage points
Race/Ethnicity 
White, non-Hispanic1,355± 3 percentage points
Black, non-Hispanic435± 6 percentage points
Hispanic420± 7 percentage points
Age  
18-29399± 7 percentage points
30-49888± 4 percentage points
50-64590± 5 percentage points
65+556± 6 percentage points
Party ID  
Democrats774± 5 percentage points
Independents876± 5 percentage points
Republicans607± 5 percentage points

Global COVID-19 Tracker

Published: Jun 16, 2026

Editorial Note: The Policy Actions tracker will no longer be updated as the data source has ceased tracking government responses to COVID-19. For more information, please visit the Oxford Covid-19 Government Response Tracker.

Cases and Deaths

This tracker provides the cumulative number of confirmed COVID-19 cases and deaths, as well as the rate of daily COVID-19 cases and deaths by country, income, region, and globally. It will be updated weekly, as new data are released. As of March 7, 2023, all data on COVID-19 cases and deaths are drawn from the World Health Organization’s (WHO) Coronavirus (COVID-19) Dashboard. Prior to March 7, 2023, this tracker relied on data provided by the Johns Hopkins University (JHU) Coronavirus Resource Center’s COVID-19 Map, which ended on March 10, 2023. Please see the Methods tab for more detailed information on data sources and notes. To prevent slow load times, the tracker only contains data from the last 200 days. However, the full data set can be downloaded from our GitHub page. While the tracker provides the most recent data available, there is a two-week lag in the data reporting.

Note: The data in this tool were corrected on March 18, 2024, to clarify that they represent new cases and deaths over a full week rather than the average per day over a seven-day period.

Policy Actions

This tracker contains information on policy measures currently in place to address the COVID-19 pandemic. Policy categories currently being tracked include social distancing & closure measures, economic measures, and health systems measures. Policies are tracked at the country-, income-, and region-level. Please see the Methods tab for more detailed information on data sources and notes.

Social Distancing and Closure Measures

As countries continue to implement policies to prevent the transmission of SARS-CoV-2, the virus that causes COVID-19, these tables and charts show which social distancing and closure measures are currently in place by country.

Global COVID-19 Policy Actions

Economic Measures

The COVID-19 pandemic has placed an unprecedented strain on country economies. These tables and charts show which economic-related measures, namely income support and debt relief, are currently in place by country.

Global COVID-19 Policy Actions

Health Systems Measures

The COVID-19 pandemic continues to strain and disrupt global health systems. These tables and charts show which health systems measures are currently in place by country.

Global COVID-19 Policy Actions

Methods

Cases and Deaths

SOURCES

As of March 7, 2023, all data on COVID-19 cases and deaths are drawn from the World Health Organization’s (WHO) Coronavirus (COVID-19) Dashboard. Prior to March 7, 2023, this tracker relied on data provided by the Johns Hopkins University (JHU) Coronavirus Resource Center’s COVID-19 Map, which ends on March 10, 2023. Population data are obtained from the United Nations World Population Prospects using 2021 total population estimates. Income-level classifications are obtained from the latest World Bank Country and Lending Groups. Regional classifications are obtained from the World Health Organization.

Policy Actions

NOTES

Policy actions data include the measure that was in place for each indicator at the country-level as of the end of 2022. Policy actions data will no longer be updated as the data source has ceased tracking government responses to COVID-19. For more information, please visit the Oxford Covid-19 Government Response Tracker.

Social Distancing and Closure Measures

Under 'Stay At Home Requirements', exceptions for leaving the house may include anything from being able to leave for daily exercise, grocery shopping, and essential trips, to only being allowed to leave once a week, or one person may leave at a time, etc. Under 'Workplace Closing', partial closing includes instances in which a country recommends closing the workplace (or working from home); businesses are open but with significant COVID-19-related operational adjustments; or when workplaces require closing for only some, but not all, sectors or categories of workers. Under 'School Closing', partial closing includes instances in which a country has recommended school closures; all schools are open but with significant COVID-19-related operational adjustments; or some schools, but not all, are closed; full closing includes schools that are in session but operating virtually. Under 'Restrictions On Gatherings', partial restrictions include restrictions on gatherings of more than 10 people; full restrictions include restrictions on gatherings of 10 people or less. Under 'International Travel Controls', partial restrictions include screening and quarantine requirements for those entering the country. Values for ‘Cancel Public Events’ were not recodified.

Economic Measures

Under 'Income Support', narrow support includes instances in which a country's government is replacing less than 50% of lost salary (or if a flat sum, it is less than 50% median salary); broad support includes instances in which a country's government is replacing 50% or more of lost salary (or if a flat sum, it is greater than 50% median salary). Under 'Debt/Contract Relief', narrow support includes instances in which a country's government is providing narrow relief, such as relief specific to one kind of contract.

Health Systems Measures

Under 'Vaccine Eligibility', partial availability includes availability for some or all of the following groups: key workers, non-elderly clinically vulnerable groups, and elderly groups, or for select broad groups/ages. Under 'Facial Coverings', recommend/partial requirement includes instances in which a country's government recommends wearing facial coverings, requires facial coverings in some situations, and requires facial coverings when social distancing is not possible. 

SOURCES

Data on and descriptions of government measures related to COVID-19 provided by the Oxford Covid-19 Government Response Tracker (OxCGRT). For more detailed information on their data collection and methodology, please see their codebook and interpretation guide.

Key Facts about the Uninsured Population

Authors:

Published: June 16, 2026

This brief was updated on June 16, 2026 to reflect a change in coverage gap estimates.

Executive Summary

Introduction

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The high cost of private insurance and limited availability of public coverage for some individuals with low income—particularly in states that have not expanded Medicaid under the Affordable Care Act (ACA)—continued to leave millions of people without health coverage in 2024. Our fragmented and complex health insurance system also means some people fall through the cracks of coverage when they experience a change in circumstances. The end of continuous enrollment in Medicaid also affected health coverage trends in 2024. Starting in April 2023, states resumed disenrolling Medicaid enrollees, a process known as Medicaid unwinding, after a period of continuous enrollment during the pandemic. Nearly all states had completed renewals to verify eligibility for the program for all enrollees by the end of 2024, leading to the disenrollment of millions of Medicaid enrollees. Most individuals losing Medicaid do not have access to affordable job-based coverage, and while many transitioned to subsidized coverage through the Marketplace, even with enhanced Marketplace subsidies still in place during 2024, coverage was unaffordable for some. These coverage transitions and losses contributed to the first increase in the uninsured rate since 2019.

The number of people who are uninsured is expected to continue to increase in coming years because of changes to Medicaid and the ACA Marketplace included in the 2025 reconciliation law, the expiration of the Marketplace enhanced premium tax credits, and other administrative actions.  The Congressional Budget Office (CBO) projects that over 14 million more people will be uninsured in 2034 due to the combined effects of the Medicaid and Marketplace eligibility changes included in the reconciliation law and the expiration of the enhanced Marketplace subsidies. In addition to these potential coverage losses, the Trump administration’s increased immigration enforcement activities and policy changes are likely to have a broad chilling effect that could cause lawfully present immigrants who remain eligible to decide to disenroll or not enroll themselves or their children in health coverage programs. This anticipated coverage loss will have implications for access to care and financial stability among those losing coverage and could lead to a worsening of disparities in health outcomes.

This issue brief describes trends in health coverage through 2024, examines the characteristics of the uninsured population ages 0-64, and summarizes the access and financial implications of not having coverage. Using data from the American Community Survey (ACS), this analysis examines changes in health coverage from 2023 to 2024. The analysis focuses on coverage among people ages 0-64 since Medicare offers near universal coverage for the elderly, with just 491,000, or less than 1%, of people over age 65 uninsured. 

Key Takeaways

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How many people are uninsured?

For the first time since 2019, the number of people without health coverage and the uninsured rate increased in 2024. The total number of people ages 0-64 without health coverage increased by more than 1.3 million to 26.7 million in 2024, and the uninsured rate for the population under age 65 increased from 9.5% to 9.8%.

A decline in Medicaid coverage drove the increase in the uninsured rate in 2024. While non-group coverage, including ACA Marketplace coverage, increased from 2023 to 2024, the increase did not fully offset the drop in Medicaid coverage from 2023 to 2024 among both adults and children.

Who is uninsured?

In 2024, over eight in ten people who are uninsured were in low-income families (80.1%) and had at least one worker in the family (85.1%), and over six in ten were people of color (63.7%). Reflecting the more limited availability of public coverage in some states, adults ages 19-64 are more likely to be uninsured than children (11.3% vs. 5.9%). Despite coverage gains across groups over time, American Indian or Alaska Native, Hispanic, Black, and Native Hawaiian or Pacific Islander people were more likely to be uninsured than White and Asian people. 

A disproportionate share of uninsured individuals under age 65 (42%) live in the ten states that have not expanded Medicaid. Individuals living in non-expansion states are nearly twice as likely as those in expansion states to be uninsured; the uninsured rate in non-expansion states was 14.5% compared to 8.0% in expansion states.

Why are people uninsured? 

The high cost of insurance is the main reason many people are uninsured. In 2024, 61.7% of uninsured adults ages 18-64 said they were uninsured because coverage is not affordable. Many uninsured people do not have access to coverage through a job, and some people, particularly poor adults in states that have not expanded Medicaid, remain ineligible for public coverage. Among uninsured adults who were working, 71% were not offered or were not eligible for coverage from their employer in 2024.

About half (52.2%) of people who are uninsured may be eligible for Medicaid or subsidized coverage in the Marketplace. However, they may not be aware of these coverage options or may face barriers to enrolling. In addition, with the expiration of the enhanced premium tax credits, Marketplace coverage has gotten more expensive and may be unaffordable for some.

How does not having coverage affect health care access?  

People without insurance coverage are less likely to access care and more likely to delay or forgo care because of costs. In 2024, nearly four in ten uninsured adults (38.6%) reported delaying, skipping, or not getting needed care or medication due to cost, more than twice the share of adults with private coverage (17.0%) and those with public coverage (18.8%).  Among adults with chronic health conditions who need ongoing medical management, those without insurance coverage were three to four times more likely to delay or forgo needed medical care due to cost than adults with the same condition who were insured. Research demonstrates that gaining health insurance, particularly through Medicaid, improves access to care, utilization of services, and reduces mortality.

What are the financial implications of being uninsured? 

Uninsured adults are nearly twice as likely as insured adults to have difficulty paying health care costs. Nearly six in ten (59%) uninsured adults said they or someone living with them had problems paying for health care compared to 30% of insured adults. People who are uninsured are also more likely to experience measures of financial distress, including overdrawing their checking account, having been contacted by a debt collection agency, and having used pay day loans.

Unaffordable medical bills can lead to medical debt, particularly for uninsured adults. More than six in ten (62%) uninsured adults reported having health care debt compared to over four in ten (44%) insured adults. Uninsured adults are more likely to face negative consequences due to health care debt, such as using up savings, having difficulty paying other living expenses, or borrowing money.

Characteristics of the Uninsured Population

Age

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Over eight in ten (83.2%) individuals who were uninsured in 2024 were adults while 16.8% were children. Adults ages 19-44 make up more than half (56.7%) of the uninsured population under age 65. About one in four (26.5%) people who are uninsured are between the ages of 45-64 (Figure 4).

Distribution of the Uninsured Population Ages 0-64 by Age, 2024 (Pie Chart)

Adults are more likely to be uninsured than children. The uninsured rate for adults ages 19-64 was 11.3%, nearly twice the rate of 5.9% for children. The lower uninsured rate for children reflects, in part, broader eligibility for Medicaid and CHIP for children. As children age out of eligibility, uninsured rates rise sharply to 14.5% for young adults ages 19-25 and remain high for adults ages 26-34 (14.1%) as 26-year-olds lose coverage under their parent’s health plan. Uninsured rates begin to fall for adults starting at age 35 and are lowest for adults ages 55-64 at 7.4% (Figure 5). The increase in the uninsured rate from 2023 to 2024 was largest for children and young adults. The uninsured rate for children increased by 0.6 percentage points from 2023 to 2024, and the rate for young adults ages 19-25 increased by 0.8 percentage points. Adults ages 26-34 and those ages 55-64 experienced smaller increases (0.4 and 0.2 percentage points, respectively) while the uninsured rates for adults ages 35-44 and 45-54 did not change.

Uninsured Rates Among People 0-64 by Age, 2023-2024 (Grouped column chart)

Family Income

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Eight in ten (80.2%) uninsured people under age 65 in 2024 were in families with incomes below 400% of the federal poverty level (FPL). Nearly half (45.9%) had incomes below 200% FPL while over one-third (34.3%) had family income between 200% and 399% FPL (Figure 6).

Distribution of the Uninsured Population Ages 0-64 by Family Income, 2024 (Pie Chart)

Individuals with incomes below 200% of the federal poverty level (FPL) are significantly more likely to be uninsured than those with higher income. One in six (16.5%) individuals under age 65 living in poverty and those in low-income families (incomes 100%-199% FPL) were uninsured in 2024 compared to fewer than one in twenty (4.5%) with incomes above 400% FPL (Figure 7).  Just over one in ten (11.5%) individuals with incomes from 200%-399% FPL were uninsured. While uninsured rates increased for families at all income levels, families with low income and those in poverty saw the largest increases. From 2023 to 2024, the uninsured rate for people ages 0-64 in families with incomes between 100-200% of the federal poverty level (FPL) increased from 15.5% to 16.5%, and the uninsured rate for families living in poverty also increased to 16.5% in 2024 from 15.7% in 2023.

Uninsured Rates for People Ages 0-64 by Family Income, 2023-2024 (Grouped column chart)

Family Work Status

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In 2024, most (85.1%) uninsured individuals lived in working families. Of the total uninsured population ages 0 to 64, nearly three in four (73.8%) had at least one full-time worker in their family, and 11.3% had a part-time worker in their family (Figure 8). Less than 15% of uninsured individuals were in families with no workers.

Distribution of the Uninsured Population Ages 0-64 by Family Work Status, 2024 (Pie Chart)

Because health insurance is tied to employment for many people in the U.S., individuals living in families with no workers or only part-time workers are more likely to be uninsured than individuals with full-time workers in the family. Individuals ages 0-64 in families with no workers or only part-time workers were nearly twice as likely to be uninsured (14.1% and 13.6% respectively) as individuals in families with multiple full-time workers (8.9%) (Figure 9). But working alone does not ensure access to health coverage. Over one in ten (10.1%) individuals in families with one full-time worker were uninsured in 2024. Although the uninsured rate increased for individuals in families with at least one full-time worker, the increases were larger for individuals in families with only part-time workers and those in families with no workers.

Uninsured Rates Among People Ages 0-64 by Family Work Status, 2023-2024 (Grouped column chart)

Race and Ethnicity

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Nearly two-thirds (63.7%) of those without insurance in 2024 were people of color. Over four in ten (41.9%) uninsured people were Hispanic in 2024, while 12.4% were Black people and 3.7% were Asian people. American Indian or Alaska Native (AIAN) and Native Hawaiian or Pacific Islander (NHPI) people made up smaller shares, accounting for 1% and 0.2% of the uninsured population, respectively. White people comprised 36.3% of people who lacked insurance coverage in 2024 (Figure 10).

Distribution of the Uninsured Population Ages 0-64 by Race/Ethnicity, 2024 (Pie Chart)

Reflecting ongoing disparities in health coverage, Hispanic, Black, AIAN, and NHPI people are more likely to be uninsured than White people. In 2024, AIAN and Hispanic people had the highest uninsured rates (18.9% and 18.4%, respectively). These rates were more than two and a half times the rate for White people (6.8%). The uninsured rates for Black people (10.1%) and NHPI (12.3%) were also higher than the rate for White people (Figure 11). Asian individuals under age 65 had the lowest uninsured rate at 5.7%. Hispanic and Black people ages 0-64 experienced the largest increases in uninsured rates in 2024, increasing 0.5 and 0.4 percentage points respectively from 2023. The uninsured rate for White people increased from 6.5% in 2023 to 6.8% in 2024, while the rates for American Indian or Alaska Native, Asian, and Native Hawaiian or Pacific Islander people did not change.

Uninsured Rates Among People Ages 0-64 by Race/Ethnicity, 2023-2024 (Grouped Bars)

Citizenship

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Most uninsured individuals ages 0-64 (74.6%) were U.S. citizens, while a quarter were noncitizens in 2024. About 8% of uninsured individuals were recent immigrants who have lived in the U.S. for less than 5 years while 17.1% were immigrants who have been in the U.S. for more than five years (Figure 12). An even greater share of uninsured children were U.S. citizens (85.2%), while 14.8% were noncitizens (Appendix Table B).

Distribution of the Uninsured Population Ages 0-64 by Citizenship Status, 2024 (Pie Chart)

Noncitizens are more likely than citizens to be uninsured. Nearly one-third of noncitizen immigrants were uninsured in 2024, including 31.7% of those who have been in the U.S. for less than five years and 30.6% of those who have lived in the U.S. for more than five years. By comparison, the uninsured rate for U.S.-born and naturalized citizens was 8.0% in 2024 (Figure 13). The uninsured rate increased for U.S. citizens and decreased for noncitizens who have in the U.S. for five years or more, though noncitizens remain more than 3.5 times more likely to be uninsured than citizens overall. 

Uninsured Rates of People Ages 0-64 by Citizenship, 2023-2024 (Grouped column chart)

State Residency

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Although most states have adopted the ACA Medicaid expansion, a disproportionate share of uninsured people under age 65 live in states that have not expanded Medicaid. As of 2024, 41 states including DC had expanded Medicaid to cover adults with incomes up to 138% FPL ($20,782 for an individual in 2024). In 2024, about four in ten (42.0%) uninsured people ages 0-64 lived in the ten non-expansion states, including states with large uninsured populations such as Texas and Florida, while nearly six in ten (58.0%) lived in states that expanded Medicaid (Figure 14).  Individuals living in non-expansion states are more likely to be uninsured than those living in expansion states. In 2024, the uninsured rate in non-expansion states (14.5%) was nearly twice the rate in expansion states (8.0%) (Figure 14). 

Uninsured Rates Among People Ages 0-64 by Medicaid Expansion Decision, 2023-2024 (Grouped column chart)

Uninsured rates vary across states. Texas had the highest uninsured rate at 19.2%, nearly double the national rate of 9.8%, while Massachusetts had the lowest rate at 3.3% (Figure 15). The variation in uninsured rates across states reflects differences in per capita income, access to employer coverage, and eligibility for public coverage.

Uninsured Rates Among Population Ages 0-64 by State, 2024 (Choropleth map)

From 2023 to 2024, the uninsured rate for the population ages 0 to 64 increased in 16 states including DC and decreased in two states, California and North Carolina. The District of Columbia and North Dakota saw the largest increases in the uninsured rate for the population under age 65, though the rates remain below the national average in both states (Figure 16). The uninsured rate for children ages 0-18 increased in nine states (Colorado, Florida, Georgia, Kansas, Kentucky, Minnesota, Missouri, Oklahoma, Texas), while the uninsured rate for adults ages 19-64 increased in DC and fourteen states (Colorado, Illinois, Indiana, Kentucky, Louisiana, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, North Dakota, Ohio, Pennsylvania, and Wisconsin) but declined in three states (California, Mississippi, and North Carolina). In three states (Colorado, Kentucky, and Minnesota), the uninsured rates increased for both children and adults ages 19-64.  

Change in Uninsured Rates for People Ages 0-64  by State,  2023-2024 (Bar Chart)

Length of Uninsurance

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Most uninsured adults have been without health coverage for more than a year. Nearly seven in ten (69.4%) adults who were uninsured in 2024 had gone without health coverage for more than a year, including over a quarter who had been uninsured for ten or more years (10%) or had never been insured (16.3%) (Figure 17). People who have been without coverage for long periods may be particularly hard to reach through outreach and enrollment efforts. Just three in ten uninsured adults (30.6%) reported lacking coverage for less than one year. People who lacked insurance for less than one year may have experienced a short-term gap in coverage because of a job change or a change in income that resulted in the loss of employer-based coverage or Medicaid.

Distribution of the Uninsured Population Ages 18-64 by Time Without Health Coverage, 2024 (Pie Chart)

Barriers to Obtaining Health Care Coverage

Reasons for Being Uninsured

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Inability to afford coverage is the most commonly cited reason for being uninsured. In 2024, 61.7% of uninsured adults ages 18-64 said they were uninsured because coverage is not affordable (Figure 18). Uninsured adults faced other barriers to obtaining coverage, including not being eligible for coverage (28.9%) and having difficulty signing up for coverage (21.0%). Over a quarter (28.0%) said they did not need or want coverage. 

Reasons for Being Uninsured Among Uninsured Adults Ages 18-64, 2024 (Bar Chart)

Losing a job or eligibility for public coverage can lead to people becoming uninsured. In 2024, 39.7% of adults who had not had health insurance in the last three years said they were uninsured because they lost their job or changed employers (Figure 19), and about a quarter (25.6%) said they lost coverage because they were no longer eligible for Medicaid, CHIP, or other public coverage. Other reasons for losing coverage included the cost of coverage increased (19.2%), missed the deadline for signing up or paying for coverage (15.9%), or lost eligibility due to age or leaving school (15.0%). 

Reasons for Losing Coverage Among Uninsured Adults Ages 18-64 Who Have Been Uninsured for Less than Three Years, 2024 (Bar Chart)

Barriers to Job-Based Coverage

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Not all workers have access to coverage through their job. In 2024, about 70% of uninsured adults who were working did not have access to health insurance through their employer. Six in ten (60.5%) uninsured adult workers worked for an employer that did not offer health insurance to its employees (Figure 20). A smaller share (9.9%) worked for an offering employer but were not eligible, often because they worked part-time or were a temporary or contract employee. 

Eligibility for Job-Based Coverage Among Uninsured Working Adults Ages 19-64, 2024 (Pie Chart)

Among uninsured workers who are offered coverage by their employers, cost is often a barrier to taking up the offer. From 2015 to 2025, total premiums for family coverage increased by 53%, outpacing wage growth, and the worker’s share increased by 37%. Low-income families with employer-based coverage spend a significantly higher share of their income toward premiums and out-of-pocket medical expenses compared to those with income above 200% FPL. Particularly among people working for small employers, premium contributions for dependents can be unaffordable. 

Limits on Medicaid Eligibility

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Medicaid eligibility varies across states, and eligibility for adults is limited in states that have not expanded Medicaid. As of March 2026, 41 states including DC had adopted the ACA Medicaid expansion (Figure 21). Two states implemented the expansion in 2023—South Dakota in July and North Carolina in December. In states that have not expanded Medicaid, the median eligibility level for parents is just 33% FPL, and adults without dependent children are ineligible in most cases. Additionally, in non-expansion states, millions of poor uninsured adults fall into a “coverage gap” because they earn too much to qualify for Medicaid but not enough to qualify for Marketplace premium tax credits. The 2025 reconciliation law makes changes to Medicaid eligibility for expansion adults by imposing new work requirements and more frequent eligibility determinations starting in January 2027.

Status of State Action on the Medicaid Expansion Decision, as of March 2026 (Choropleth map)

Barriers to Coverage for Immigrants

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Immigrants face barriers to eligibility for public programs. Many lawfully present immigrants must meet a five-year waiting period after receiving “qualified” immigration status before they can enroll in Medicaid if they meet other eligibility criteria. States have the option to cover eligible lawfully present children and pregnant people without a waiting period, and as of April 2025, 38 states including DC have elected the option for children, and 32 states including DC have taken up the option for pregnant individuals (Figure 22). Undocumented immigrants are ineligible for federally funded coverage, including Medicaid or Marketplace coverage. Some states provide fully state-funded coverage to some groups of immigrants who are not eligible for federal coverage due to their immigration status but meet other eligibility requirements such as income.  The 2025 reconciliation law imposes new restrictions on immigrant eligibility for Medicaid and ACA Marketplace premium tax credits with some of the changes starting in 2026.

Federally-Funded Coverage of Lawfully Residing Immigrant Children and Pregnant People Without a 5-Year Waiting Period as of April 2025 (Choropleth map)

Eligibility for ACA Coverage Among Uninsured

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About half of the people who are uninsured may be eligible for financial assistance available under the ACA. Just over half (52.9% or 14.1 million) of uninsured individuals in 2024 were estimated to be eligible for financial assistance either through Medicaid or through subsidized Marketplace coverage (Figure 23). However, the remaining half of the uninsured population (47.1% or 12.6 million) were likely ineligible for free or subsidized coverage because their state did not expand Medicaid, their immigration status made them ineligible, or they were deemed to have access to an affordable Marketplace plan or employer coverage offer. 

Eligibility for Coverage Among Uninsured People Ages 0-64, 2024 (Donut Chart)

Barriers to Accessing Care for People Who Are Uninsured

Barriers to Care for Uninsured Adults

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Uninsured adults are less likely than insured adults to have a usual place of care or to have seen a doctor in the past year. In 2024, nearly half (46.2%) of uninsured adults ages 18-64 reported not seeing a doctor or health care professional in the past 12 months compared to 14.7% with private insurance and 12.8% with public coverage. A main barrier to accessing care among uninsured adults is that many (40.8%) do not have a regular place to go when they are sick or need medical advice (Figure 24).

Share of Adults Ages 18-64 Who Did Not See a Doctor or Lacked a Usual Source of Care, by Insurance Status, 2024 (Grouped column chart)

Uninsured adults are much more likely than their insured counterparts to delay or forgo needed care because of cost. In 2024, nearly four in ten uninsured adults (38.6%) reported delaying, skipping, or not getting needed care or medication due to cost, more than twice the share of adults with private coverage (17.0%) and those with public coverage (18.8%) (Figure 25). For many uninsured individuals, skipping or forgoing care can lead to worse health.  According to a KFF survey that found higher percentages of both uninsured and insured people delaying or forgoing needed care due to cost than reported above, four in ten uninsured adults (42.0%) reported that their health got worse after skipping or postponing care due to cost.

Share of Adults Ages 18-64 Who Delayed or Went Without Health Care, by Insurance Status, 2024 (Split Bars)

Barriers to Care for Uninsured Children

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Compared to children with insurance coverage, uninsured children are less connected to the health care system. In 2024, about one in five (22.6%) uninsured children reported not seeing a doctor or health care professional in the past 12 months compared to 4.1% with private insurance and 4.0% with public coverage. Nearly a quarter (24.4%) of uninsured children did not have a regular place to go when they are sick or need medical advice (Figure 26).

Share of Children Who Did Not See a Doctor or Lacked a Usual Source of Care, by Insurance Status, 2024 (Grouped column chart)

Uninsured children are also more likely than those with private insurance or public insurance to go without needed care due to cost. While children are less likely than adults to report not getting care, children without health coverage face greater access barriers than those with health coverage. In 2024, nearly one in six uninsured children (16.0%) reported delaying, skipping, or not getting needed care or medication due to cost compared to 3.3% of children with private coverage and 3.8% of children with public coverage (Figure 27). 

Share of Children Ages 0-17 Who Delayed or Went Without Health Care, by Insurance Status, 2024 (Split Bars)

Access to Care Among Uninsured Adults with Chronic Conditions

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Uninsured individuals are less likely than those with insurance to receive services to treat chronic conditions. Among adults with chronic health conditions who need ongoing medical management, those without insurance coverage were three to four times more likely to delay or forgo needed medical care due to cost than adults with the same condition who were insured. For example, in 2024, over four in ten (42.2%) uninsured adults with diabetes delayed or did not get needed medical care because of cost compared to 11.1% of insured adults (Figure 28). Beyond forgoing needed care, many uninsured adults live with conditions that have never been diagnosed because they are less likely to see a health professional regularly. Gaining insurance is associated with higher rates of chronic condition diagnosis, demonstrating that many uninsured individuals live with undiagnosed chronic conditions due to their lack of access to care. People without health coverage are more likely to be hospitalized for avoidable health problems and to experience declines in their overall health as a consequence of having undiagnosed conditions and a lower likelihood of receiving preventive and chronic disease management care. When they are hospitalized, uninsured people receive fewer diagnostic and therapeutic services and also have higher mortality rates than those with insurance. 

Share of Adults Ages 18-64 with Select Chronic Conditions Who Delayed or Did Not Get Needed Medical Care Due to Cost, by Insurance Coverage, 2024 (Grouped column chart)

Research demonstrates that gaining health insurance improves access to health care considerably and diminishes the adverse effects of having been uninsured.review of research on the effects of the ACA Medicaid expansion finds that expansion led to positive effects on access to care, utilization of services, the affordability of care, and financial security among the low-income population. Medicaid expansion is also associated with increased early-stage diagnosis rates for cancer, lower rates of cardiovascular mortality, and increased odds of tobacco cessation.  Evidence also indicates that gaining health coverage through the Medicaid expansion saves lives. One recent study found a 2.5% reduction in mortality among low-income adults in Medicaid expansion states and concluded that Medicaid expansion reduced the risk of death by 21% among new enrollees, saving an estimated 27,000 lives from 2010-2022.

Access to Charity Care

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While some uninsured individuals may be eligible for free or discounted health care services, not all uninsured individuals are able to access charity care programs. Public hospitals, community clinics and health centers, and local providers that serve underserved communities provide a crucial health care safety net for uninsured people. However, safety net providers have limited resources and service capacity, and not all uninsured people have geographic access to a safety net provider. Hospital charity care programs provide free or discounted services to eligible patients who are unable to afford their care, though eligibility criteria vary across hospitals. Not all eligible patients benefit from these programs because they may not be aware that charity care is available or do not think they are eligible. They may also have difficulty completing an application or may choose not to apply.

While charity care programs help uninsured patients afford care, they can strain hospital finances. Charity care as a percent of expenses varies widely across hospitals. Hospital charity care costs are generally higher in states that have not expanded Medicaid, which also generally have higher uninsured rates (Figure 29). Moreover, research indicates that Medicaid expansion is associated with reductions in uncompensated care costs and improved financial performance for rural hospitals and other providers.

Charity Care Costs in 2023 Were Generally Higher in States That Had Not Expanded Medicaid (Scatter Plot)

Financial Implications of Being Uninsured

Unaffordable Medical Bills 

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Adults who are uninsured are more likely to report difficulty paying for health care costs than adults with insurance coverage.  While affording health care costs can be challenging regardless of insurance status, uninsured adults are nearly twice as likely as insured adults to say that affording health care costs is difficult (82% vs. 42%). When it comes to paying health care costs, about six in ten (59%) uninsured adults said they or someone living with them had problems compared to 30% of insured adults, and about four in ten (39%) uninsured adults said that they or someone living with them had problems paying for prescription drug costs specifically compared to 28% of insured adults (Figure 30).  

Problems Paying for Health Care  and Prescription Drug Costs in the Past Year Among Adults 18-64, by Insurance Status (Grouped column chart)

Financial Insecurity

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People who are uninsured are more likely to experience measures of financial distress, including overdrawing their checking account, having been contacted by a debt collection agency, and having used pay day loans. Because adults who are uninsured are more likely to have lower income than those with insurance, they are also more financially vulnerable. Almost six in ten (59%) uninsured adults ages 18-64 report that it is probable or certain that they could not find $2,000 if an unexpected need, such as a medical emergency, arose in the next month compared to four in ten (39%) insured adults (Figure 31). Adults who are uninsured also have more difficulty paying their bills. About three in ten (31%) reported being contacted by debt collection in the past year, and one quarter said they used payday loans in the past five years compared to 22% and 16% of insured adults, respectively.

Share of Adults Ages 18-64 Experiencing Certain Financial Difficulties, by Insurance Status, 2024 (Split Bars)

Research suggests that gaining health coverage improves the affordability of care and financial security among the low-income population. Multiple studies of the ACA found declines in trouble paying medical bills and reductions in medical debt in expansion states relative to non-expansion states.  More recent research found that Medicaid expansion decreased catastrophic health expenditures and was associated with greater increases in income among low-income individuals. 

Medical Debt

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Medical bills can quickly translate into medical debt for people who are uninsured as many have low or moderate incomes and have little, if any, savings.  Unaffordable medical bills can lead to medical debt, particularly for uninsured adults.  More than one third (34%) of uninsured adults under age 65 have medical debt, meaning they have one or more unpaid bills from a medical service provider that are past due, compared to 26% of insured adults under age 65 (Figure 32). Using a broader definition of medical debt, which includes health care debt on credit cards or owed to family members, more than six in ten (62%) uninsured adults under age 65 report having health care debt compared to over four in ten (44%) insured adults under age 65. Uninsured adults are more likely to face negative consequences due to health care debt, such as using up savings, having difficulty paying other living expenses, or borrowing money.   

Medical Debt Among Adults Ages 18-64, by Insurance Status (Grouped column chart)

Appendix and Supplemental Tables

Appendix Tables

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Uninsured Rate Among the Population Ages 0-64 by State, 2019, 2023, 2024 (Table)
Characteristics of the Uninsured Population Ages 0-64, 2024 (Table)
Change in Selected Characteristics of Uninsured People Ages 0-64, 2019, 2023, 2024 (Table)

Supplemental Tables

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Health Insurance Coverage of the Population Ages 0-64, 2024 (Table)
Health Insurance Coverage of the Population Ages 0-64 under Poverty, 2024 (Table)
Health Insurance Coverage of Workers Ages 19-64, 2024 (Table)
Characteristics of Uninsured People 0-64 under Poverty (<100% of Poverty), 2024 (Table)
Characteristics of Uninsured Adult Workers Ages 19-64, 2024 (Table)

Out-of-Pocket Costs for Long-Acting Reversible Contraception Among Individuals Enrolled in Employer Sponsored Insurance Plans

Published: Jun 16, 2026

Despite the Affordable Care Act (ACA) requiring contraceptives to be covered without cost-sharing, many privately insured long-acting reversible contraceptives (LARC) users still face out-of-pocket expenses. In this analysis, published in the journal Contraception, KFF’s Linda Li, Brittni Frederiksen, and Alina Salganicoff look at intrauterine device (IUD) and contraceptive implant insertion-related costs among privately insured individuals to better understand why patients are experiencing unexpected expenses for what should be fully covered contraceptive services under the ACA.

Using the 2023 Merative MarketScan Commercial Claims and Encounter Database, a national sample of healthcare claims for people enrolled in employer sponsored insurance plans, the researchers estimated out-of-pocket costs for 98,916 IUD and 30,259 implant insertion encounters among females ages 15-49.

State Choices, Unequal Access: Policies Shaping Reproductive Health Care Across the United States

Published: Jun 16, 2026

Authored by KFF’s Alina Salganicoff, Ivette Gomez, and Usha Ranji, this article for The Milbank Quarterly examines how state policies create varying levels of access to reproductive healthcare services (including contraceptive care, abortion, and maternity care), affecting coverage, availability, and costs.

Recent State Actions Related to Immigrants’ Access to Services and Immigration Enforcement

Published: Jun 16, 2026

During the 2025 and 2026 legislative sessions, states enacted or proposed a range of legislation that will impact immigrants’ access to state-funded health coverage and other services as well as actions related to how states may enhance or limit federal enforcement activities. Several states have rolled back or plan to scale back state-funded health coverage programs for immigrants to reduce budget deficits amid economic uncertainties. Some states have also enacted laws to support the Trump administration’s increased interior immigration enforcement activities, including sharing data from Medicaid or other state agencies with federal enforcement officials. In contrast, some states are expanding access to health coverage or other benefits for immigrants, including lawfully present immigrants losing eligibility for federally funded health coverage under the 2025 reconciliation law, and/or enhancing protections for immigrants. While some states are seeking to enhance protections for immigrants, the Trump administration signed an executive order directing federal agencies to suspend federal grants and contracts with states or local jurisdictions identified as obstructing enforcement of federal immigration laws, or “sanctuary jurisdictions.” So far federal challenges to state and local sanctuary jurisdictions have largely failed. However, the federal stance may limit state or local actions.

This brief summarizes recent and proposed actions by states related to access to state-funded health coverage and other services for immigrants and immigration enforcement activity during the 2025 and 2026 legislative sessions. It reflects activity as of June 2026 based on KFF analysis of publicly available materials and the National Conference of State Legislatures’ Immigration Legislation Database. Several state legislatures were still in session as of June 2026, so additional actions may be taken during the 2026 session that are not reflected here. Additionally, states may have implemented similar policies prior to their 2025 legislative session that are not included.

Access to State-Funded Health Coverage and Other Services

As of June 2026, six states, including DC, have recently eliminated, reduced, or plan to scale back state-funded health coverage for immigrants due to budget pressures. Economic uncertainties and federal funding reductions that may reduce state revenues and the rising costs of health care and social services have driven states across the country to consider measures to reduce spending. Some states have eliminated or plan to eliminate coverage for some adults in their state funded coverage programs for immigrants, including Illinois, Minnesota, and DC. Several states have closed enrollment or reduced enrollment caps or income eligibility limits for some adults in their state-funded programs for immigrants, including California, Colorado, DC, and Washington. In California, some adults remaining in the program will face cuts to dental benefits and new premiums, and the governor has proposed implementing work requirements and more frequent six-month renewals, which would align with new Medicaid requirements under the 2025 reconciliation law, as well as further increasing premiums for some adults. A few states are reducing coverage for immigrant children and pregnant people. Colorado plans to cap enrollment and limit benefits for state-funded coverage for immigrant children and pregnant people beginning in January 2027. Additionally, North Carolina enacted a Medicaid funding bill in April 2026 that limited immigrant eligibility to coverage that the state is federally required to provide starting October 1, 2026. This would eliminate the state’s optional Medicaid coverage for lawfully residing children and pregnant women without a five-year wait. However, the governor has called for the state legislature to reinstate this coverage and some state legislators have indicated that the coverage cut was unintentional. These program reductions will likely have negative impacts on health care access and outcomes as research suggests that coverage expansions for immigrants are associated with lower uninsured rates and improved access to care.

In contrast, three states have plans to expand state-funded coverage to fill gaps in benefits that will be created by the 2025 reconciliation law eligibility restrictions for lawfully present immigrants. New Mexico plans to use state funds to cover Deferred Action for Childhood Arrivals (DACA) recipients who have already been ineligible for federally funded health coverage and lawfully present immigrants who will lose Medicaid, subsidized Affordable Care Act (ACA), and Supplemental Nutrition Assistance Program (SNAP) benefits under the 2025 reconciliation law. New York plans to use state funds to cover lawfully present immigrants losing Medicaid coverage and federally-subsidized health coverage through its Essential Plan. Under a longstanding court ruling, New York is required to provide state-funded coverage to lawfully present immigrants who would be eligible for Medicaid except for their immigration status. Additionally, Washington increased funding for the state-funded Food Assistance Program, which provides the same benefits as SNAP, in order to provide assistance to lawfully present immigrants who were eligible for SNAP benefits prior to the 2025 reconciliation law changes. California governor’s 2026-27 budget proposes using state funds to continue providing nutrition assistance to immigrants who were eligible for state-funded assistance prior to the 2025 reconciliation law and to offer assistance to income-eligible individuals age 55 and older regardless of immigration status starting October 1, 2027.

As of June 2026, some states have enacted legislation that would limit immigrant access to certain other benefits. In 2025, Idaho enacted legislation that decreases the maximum income refugees can earn to remain eligible for the Refugee Medical Assistance program from 150% to 133% of the federal poverty level. Idaho also enacted legislation preventing undocumented immigrants from accessing certain public benefits that were previously exempt from immigration status verification, including publicly funded vaccinations, communicable disease testing, prenatal and postnatal care, crisis counseling, and food assistance for children. Florida enacted legislation that made undocumented immigrants ineligible for in-state tuition rates at the state’s public universities as of July 2025. Tennessee enacted legislation that will hold churches and charitable organizations liable for providing housing aid to immigrants without legal status who commit crimes.

In contrast, several states have enacted legislation to coordinate or increase access to benefits and services for certain immigrants, including refugees, military members, youth, and aging immigrants. In 2025, Massachusetts enacted legislation requiring resettlement agencies to coordinate the provision of services to immigrant and refugee families and pregnant women. New York enacted legislation to direct its Military Immigrant Family Legacy Program to connect noncitizen military members and their families to immigration legal assistance. Utah created a new Refugee Services Office to coordinate services and benefits available to refugees. California will fund legal counsel for certain noncitizen immigrant youth and direct the state’s Department of Aging to identify recommendations to support older and aging immigrants.

Some states have taken action to protect or facilitate immigrants’ access to educational opportunities. In 2025, Oregon enacted legislation exempting asylum seekers enrolled in the state’s public universities from paying non-resident tuition and fees, and Colorado passed legislation that removed a requirement for immigrants to attest that they have applied or will apply for lawful presence when applying for in-state tuition at the state’s public universities. Oregon also enacted legislation in 2026 that would prevent school boards from declining to admit immigrant children due to their immigration status and adds immigration status as a protected class under anti-discrimination law. New York and Virginia enacted legislation protecting the right to education regardless of immigration status, with Virginia also prohibiting discrimination against students based on immigration status.

Several states have also passed legislation to enhance immigrants’ access to the workforce, including the health care workforce. Washington and Oklahoma enacted legislation in 2025 that would allow international medical graduates to practice in health care facilities in certain situations. An executive order by Washington’s governor also established a state Office of Equity to support coordination between state agencies responsible for implementing services for immigrants, including education, entrepreneurship, licensing, and workforce training. Hawaii and Rhode Island created a pathway for certain foreign medical school graduates to receive medical licensure, and Maine enacted legislation to direct the state to identify alternative pathways for foreign dentists to receive licensure. Wisconsin repealed restrictions on DACA recipients from working in jobs that require professional licensure, such as nursing. New Mexico established a New Americans division in the state Workforce Solutions Department to assist with expanding educational, workforce training and other initiatives for immigrants and to study their economic impact on the state.

Immigration Enforcement and Data Sharing

Several states have enacted legislation or executive orders to enhance immigration enforcement activities, building on state actions taken in prior years and multiple Trump administration executive orders directing federal agencies to take punitive actions against states and cities that limit cooperation with federal immigration enforcement. For example, Florida and Indiana passed legislation in 2025 that enhances criminal penalties for undocumented immigrants who are convicted of certain crimes. In 2026, Idaho passed legislation that would make it a state crime for noncitizens to enter or remain in the state after violating federal immigration laws, and Tennessee added a criminal penalty for someone who remains in the state after receiving a federal deportation order. Some states have prohibited localities and state entities from implementing policies that would limit cooperation with federal immigration enforcement authorities for civil immigration law violations, often referred to as sanctuary policies, including North Dakota, New Hampshire, Indiana, and Mississippi. Additionally, some states passed legislation to promote cooperation with federal immigration enforcement. New legislation in Kansas allows local law enforcement to enter into agreements with federal immigration enforcement authorities without local approval. Legislation in Mississippi directs the state’s Department of Public Safety to identify the number of undocumented immigrants residing in the state and requires all local detention facilities to enter into agreements with federal immigration enforcement. Governor executive orders in Texas and Nebraska also direct law enforcement and state agencies to cooperate with federal immigration enforcement.

Some states have implemented increased immigration verification requirements for driver’s licenses and voting, continuing earlier trends of driver’s licensure laws impacting immigrants. For example, Wyoming enacted legislation in 2025 invalidating driver’s licenses held by undocumented immigrants that were issued out-of-state, and Tennessee enacted legislation to publish lists of out-of-state driver’s licenses issued to undocumented immigrants that would be invalid in Tennessee. States have also enacted legislation related to voting. Legislation in Kansas creates a database of noncitizens holding driver’s licenses that would be cross-referenced with voter registration rolls to identify ineligible voters, and Alabama prohibits foreign driver’s licenses from being used as voter identification. Several states, including Mississippi, South Dakota, and Wyoming, enacted legislation since 2025 that would allow the state to verify immigration status during voter registration either by using the Department of Homeland Security’s (DHS) Systematic Alien Verification for Entitlements (SAVE) system or by requiring applicants to provide documentation of citizenship. 

In addition to enhanced enforcement and verification measures, several states have also implemented new requirements for state agencies to share data on immigrants with federal immigration enforcement officials or statewide databases. Missouri enacted legislation in 2025 that requires law enforcement to include the citizenship or immigration status of anyone arrested in reports submitted to the statewide crime reporting system, building on the Missouri governor’s executive order earlier in the year to expand analysis of crimes committed by undocumented immigrants. In 2026, Indiana, Louisiana, North Carolina, Tennessee, and Wyoming enacted legislation and Oklahoma’s governor issued an executive order requiring state agencies to report applicants or recipients of Medicaid and/or other public benefits whose immigration status could not be verified and/or who were verified to not have lawful presence to DHS or other federal authorities, or in the case of Tennessee, to a central state immigration enforcement agency. In Indiana and Wyoming, reporting may also include applicants’ household members determined to not be lawfully present. Tennessee also makes it a crime for government employees to not report undocumented immigrants to the central state immigration enforcement authority, and local governments could lose state funding if the state determines that they are not complying with state law.

In contrast, some states have enacted legislation and executive orders to limit federal immigration enforcement and/or collection or sharing of data for immigration enforcement purposes in certain settings, such as health care facilities and schools. California, Colorado, Maryland, New Jersey, New York, and Oregon have enacted legislation limiting civil immigration enforcement activity in “sensitive locations,” such as schools, health care facilities, libraries, courthouses, and places of worship. These state actions respond to a prior federal policy limiting federal immigration enforcement in sensitive areas that was eliminated by the Trump administration. New York’s legislation also prohibits local jails from detaining individuals on civil immigration charges. Illinois enacted legislation that bans civil immigration enforcement inside and near public areas such as state courthouses, hospitals, and colleges. California, Illinois, New Jersey, and Oregon enacted legislation requiring health care facilities to treat immigration status as protected health information, which would limit sharing personal data for immigration enforcement purposes, and to set protocols for when immigration enforcement officers appear on hospital grounds. Oregon also prohibits hospitals from retaliating against employees who share information about immigration legal services with patients. Rhode Island enacted legislation prohibiting health care facilities from asking patients about their immigration status or for proof of lawful presence in the U.S. Illinois and Oregon enacted legislation requiring school districts and colleges to develop an alert system to notify students and parents if federal agents appear on school property, and Connecticut and Delaware enacted legislation requiring every school to have a designated administrator and plan for interacting with federal immigration authorities and prohibiting public schools from sharing student information without a warrant. Pending court cases have challenged state policies asserting that they conflict with federal law, but recent federal actions against these states and local jurisdictions have not survived legal challenges.

Some states have also taken action to limit state agencies or localities from entering into enforcement agreements and/or data sharing for federal immigration enforcement purposes. Colorado, Illinois, New Jersey, and Oregon enacted legislation that prohibit state agencies from collecting immigration status information unless required by law, and from disclosing personally identifying information for federal immigration enforcement purposes. Oregon also enacted legislation barring landlords from collecting immigration status information from rental applicants or tenants and from disclosing confidential information with very limited exceptions. Vermont enacted legislation that would prohibit state agencies from entering into agreements with federal immigration enforcement without the governor’s approval. Maryland, New Mexico, and New York enacted legislation that prohibit local entities from creating agreements with federal immigration enforcement. Maryland also enacted legislation prohibiting local correctional facilities from notifying federal immigration enforcement about certain immigrants in their custody and legislation prohibiting state and local agencies from sharing certain personal information with individuals or agencies involved in civil immigration enforcement. Governor executive orders in Massachusetts and New Jersey would also limit state engagement with federal immigration enforcement. An executive order by Washington’s governor directed state agencies to ensure compliance with previously enacted state law, which limits state agencies from collecting immigration status data and from disclosing non-public personal information for federal immigration enforcement purposes, and created a new cross-agency office to coordinate the state’s response to matters such as immigrant data privacy.

The Business of Health with Chip Kahn

Bench to Bedside at AI Speed

June 16, 2026

Video

Audio

About this Episode


Episode 8, AI Series: How can AI determine who gets matched to new therapies, who is identified for clinical trials, and how patient tracking is scaled across large populations? Chip is joined by Dr. A.J. Blood, a practicing cardiologist at Brigham and Women’s Hospital and the co-founder and Chief Executive Officer of AIwithCare, a startup company that delivers AI-enabled solutions for research, clinical operations, and patient care. They discuss the role of AI in identifying patients for clinical trials and new therapies—which is typically a critical bottleneck in drug development—as well as how to ensure clinical trials are representative. Also, Dr. Blood shares insights from his extensive research background and the tool, RECTIFIER (RAG-Enabled Clinical Trial Infrastructure for Inclusion Exclusion Review), designed to enhance patient recruitment for clinical trials by efficiently sifting through complex medical data.

The Host


Headshot photo of Chip Kahn wearing a navy blue suit with a red tie, red pendant on lapel, and glasses.

Sr. Visiting Fellow

Charles N. Kahn III is a senior visiting fellow at KFF. He is also a visiting senior fellow at the American Enterprise Institute and a nonresident senior scholar at the University of Southern California’s Schaeffer Center for Health Policy & Economics. He serves as co-chair of the international Future of Health collaborative.

Guest


Co-founder and Chief Executive Officer, AIwithCare

Dr. Alexander J. “AJ” Blood is Co-founder and CEO of AIwithCare, a startup company that delivers AI-enabled solutions for research, clinical operations, and patient care. Additionally, he is a cardiologist and intensivist in the Cardiac Surgical Intensive Care Unit at Brigham and Women’s Hospital, where he serves as the associate director of the Accelerator for Clinical Transformation research group. Dr. Blood also serves as the director of the Cardiac Intensive Care Unit at Newton-Wellesley Hospital. Board-certified in internal medicine, cardiovascular disease, critical care medicine, and obesity medicine, Dr. Blood is an instructor of medicine at Harvard Medical School.

Dr. Blood completed his residency in internal medicine at Duke University and fellowships in cardiovascular disease and critical care medicine at Brigham and Women’s Hospital. He earned his medical degree from the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell. Additionally, he holds a Master of Science degree from Harvard University and a Bachelor of Arts degree from Johns Hopkins University.

Resources



SERIES

This weekly podcast features insightful conversations between host Chip Kahn and his guests, who discuss the business of health care, connecting the dots between the health care business, policy, and patients.

The podcast’s first series on AI in health care illuminates how AI is changing health care, and features guests who are deploying this technology, managing its consequences, and designing policy around it.

Forthcoming Policy Changes to Medicaid State Directed Payments

Published: Jun 15, 2026

The 2025 reconciliation law reduced federal Medicaid spending by an estimated $911 billion from 2025 through 2034, some of which stems from new restrictions on Medicaid state directed payments (SDPs) for hospital and other health care services. While states are generally prohibited from directing how managed care organizations (MCOs) pay for care, states can implement SDPs that require MCOs to increase rates or set minimum rates for specified Medicaid services. In authorizing SDPs, the Centers for Medicare and Medicaid Services (CMS) aimed to help states improve access to care and provider participation. Many states that contract with MCOs use SDPs to make uniform rate increases that function like supplemental payments in fee-for-service (FFS) Medicaid.

This issue brief describes SDPs and forthcoming policy changes stemming from the 2025 reconciliation law and the proposed regulation to implement those requirements and make other changes. A companion issue brief describes states’ current spending on SDPs before those policy changes take effect.  Key takeaways include:

  • In 2016, CMS established SDPs and their use has grown since, contributing to higher federal Medicaid spending.
  • A 2024 rule on Medicaid managed care spurred additional spending on SDPs but also established new restrictions on how states could pay MCOs to implement them.
  • The 2025 reconciliation law established new limits on SDPs, capping them at or near Medicare rates.
  • CMS released a proposed rule in May 2026 to implement the SDP provisions in the law and included several provisions that would expand the scope of new limits on SDPs, estimating that implementing the changes would reduce federal spending by $510 billion between 2026 and 2034.
  • CMS’ estimated reductions in federal spending exceed those of the Congressional Budget Office (CBO) that accompanied the 2025 reconciliation law, but differences reflect variation in data and timing in addition to provisions that would expand the scope of SDP limits.

It is unknown how states and providers will respond to the new limits on SDPs and FFS Medicaid in the reconciliation law and accompanying rule. States may try to offset reductions in SDPs with increases in base payment rates, but offsetting reductions may be challenging due to other Medicaid financing changes (like limits on provider taxes) and more tenuous fiscal conditions. Some financially vulnerable providers could be forced to close or curtail services with less revenue from Medicaid, particularly if there are revenue losses from increases in the number of people without health insurance coming from Medicaid work requirements and reductions to Affordable Care Act premium subsidies. Other providers may be able to absorb reduced payments without changes to quality or access because research—including by KFF—suggests that average commercial rates are much higher than Medicare, reflecting consolidation in provider markets and constrained Medicare rates. However, providers that serve primarily Medicaid enrollees often have lower operating margins and may be more financially vulnerable than other providers, suggesting that safety net providers may be especially affected by the reduced revenues.

What are state directed payments (SDPs)?

The Centers for Medicare and Medicaid Services (CMS) established SDPs in 2016, allowing states to put in place requirements governing MCO payments to providers. States may use SDPs to require MCOs to adopt minimum or maximum payment rates for providers, provide uniform dollar or percentage increases to providers that supplement base payment rates, or implement value-based payment arrangements. The most common type of SDPs requires uniform rate increases that function similarly to supplemental payments in FFS Medicaid. Uniform rate increases instruct MCOs to make payments on top of their regular payment rates. They, along with SDPs that establish minimum or maximum fee schedules, require the state to specify a “benchmark.” Benchmarks are standardized rates to measure MCO rates relative to other payment rates such as Medicaid FFS, Medicare FFS, or average commercial rates. Since they were introduced in 2016, SDPs have become a core component of provider reimbursement in Medicaid (see Appendix for a timeline of SDP history).

A 2024 rule on Medicaid managed care spurred changes in SDP policy and higher federal spending on SDPs. Before 2024, there was no official cap on the total payment rate that accounted for base rates and SDPs, but CMS noted in the May 2026 proposed rule that it determined to use average commercial rates as the unofficial payment limit starting in 2018. The 2024 rule on Medicaid managed care codified the average commercial rate limit for hospital services, nursing facility services, and professional services at academic medical centers. CMS also indicated that it would continue applying the average commercial rate limit to other providers. Formalizing the payment limit for SDPs at average commercial rates likely increased states’ awareness of the limit and their confidence that SDPs at that level would be permitted to continue moving forward. As a result, the number of SDPs pegged to average commercial rates, and spending on those SDPs, increased after CMS released the final rule.

The 2024 rule also required states to incorporate all SDPs into their capitation rates (e.g., premium payments to MCOs) instead of using separate payment terms, which provide additional payments outside of the capitation rates. The change moves these payments from predictable, separate payments to more complex, risk-based arrangements, which may reduce states’ ability to target reimbursement for specific provider types. CMS eliminated separate payment terms due to concerns that the separate payments undermine the risk-based nature of managed care and are frequently driven by the financing of the non-federal share. MACPAC analysis found that over half of SDP arrangements approved between February 2023 and August 2024 were incorporated through separate payment terms.

Use of SDPs that paid providers with average commercial rates had been growing prior to the 2024 final rule and continued after CMS’ informal practice was codified. Tying payments to average commercial rates—which are substantially higher than the Medicare payment ceiling used for other Medicaid FFS supplemental payments—aimed to help Medicaid attract a broader network of providers and to ensure robust access to care for Medicaid enrollees. However, the new payments to health care providers resulted in higher Medicaid spending. In June 2024, the Congressional Budget Office (CBO) updated its Medicaid spending projections for 2025-2034 to reflect a 4% (or $267 billion) increase, with half of the increase attributed to expected growth in SDPs (driven in part by CMS’ projections in the final rule).

What changes to SDPs were included in the 2025 reconciliation law and CMS’ proposed regulations?

The 2025 reconciliation law created new payment limits for SDPs for four services, capping them at or near Medicare rates instead of average commercial rates. The law specified that the new limits would apply to inpatient and outpatient hospital services, nursing facility services, and professional services at academic medical centers. Under the limits, the total payment amount under the SDP may not exceed 100% of the Medicare payment rate in states that have adopted the Affordable Care Act (ACA) Medicaid expansion (“expansion states”) and 110% of the Medicare payment rate for non-expansion states. Payment rates for services without an applicable Medicare payment rate are limited to Medicaid fee-for-service rates. Certain SDPs are initially grandfathered (e.g., allowed to continue) but the total spending amount will be reduced by 10 percentage points each year (starting January 1, 2028) until they reach the allowable Medicare-related payment limit. At the time the bill was passed, the CBO estimated that revising the payment limit for SDPs would reduce federal Medicaid spending by $149 billion between 2025 and 2034.

CMS released a proposed rule in May 2026 to implement the SDP provisions in the law and included several provisions that would expand the scope of new limits on SDPs. The list below highlights some of the key provisions governing SDPs included in the proposed rule:

  • Expanded scope of services. The 2025 reconciliation law specified that new limits applied to hospital services, professional services at academic medical centers, and nursing facility services. The proposed rule would apply the new payment limits to all services.
  • Applicable in territories. The 2025 reconciliation law only applied to the 50 states and D.C., but the proposed rule would also apply to the territories. In FY 2025, Puerto Rico had four SDPs approved, which were projected to account for $131 million in federal Medicaid spending.
  • Eliminates uniform rate increases. The 2025 reconciliation law established new ceilings on SDP payment limits but did not prohibit certain types of SDPs from being used. The proposed rule would eliminate uniform rate increases in future years, the most common type of SDP. It is unclear whether it will be possible for states to transition uniform rate increases to other types of SDPs, such as minimum or maximum fee schedules. When combined with the elimination of separate payment terms from the 2024 rule, this change effectively precludes states from using SDPs to provide supplemental payments in managed care that parallel arrangements in FFS.
  • Phase-down of grandfathered SDPs. Starting with the first rating period after January 1, 2028, the proposed rule would reduce the total approved payment amount in grandfathered SDPs by 10% each year until they comply with the new limits in the 2025 reconciliation law. For example, if an SDP was approved at $1 billion, the first year’s decrease would be at least $100 million (unless the Medicare limit is reached in year 1 with a decrease of less than $100 million). This will cause some SDPs (particularly benchmarked to higher payment rates) to come into compliance somewhat earlier than if the SDP payment rate had been reduced by 10 percentage points (relative to Medicare rates) each year.

Beyond expanding the scope of new limits on SDPs, CMS’ proposed rule makes parallel changes for FFS payments that target specific providers. The proposed rule aims to align payment requirements across delivery systems by applying the Medicare-based payment limits for SDPs to some FFS payments (which govern all provider payments, not only supplemental payments). The new limits would apply to payments that target specific providers such as physicians, dentists, emergency and non-emergency medical transportation providers, and other licensed professionals. The new limits would not apply to payments that are already governed by other limits (e.g., upper payment limit rules). Those requirements would take effect for the first state fiscal year beginning on or after January 1, 2029.

The proposed rule also specifies the basis for new payment limits in SDPs and in FFS Medicaid payments that target specific providers.  Both types of payment limits would apply on a per-service (or per-discharge) basis, rather than being calculated in aggregate using an upper payment limit-like approach. Where possible, states would be required to use the published Medicare payment rates, drawing from the Medicare physician fee schedule, the hospital inpatient and outpatient prospective payment systems, and the skilled nursing facility prospective payment system. For providers who are paid based on their costs, such as critical access hospitals, cancer hospitals, and freestanding hospitals; states are instructed to use the Medicare cost reports as Medicare does.

Although most of the limits would be calculated similarly in SDPs and in targeted FFS Medicaid payments, there are some small differences. The most notable difference occurs when there are no Medicare payment rates available, as occurs for services that Medicaid covers but Medicare does not. In such instances, SDP payments would be limited to Medicaid FFS rates, which include rates established by 1115 waivers but exclude any supplemental payments. For FFS payments targeting specific providers, states would be required to develop methods for identifying reasonably comparable Medicare rates, which would then be the basis for the payment limit.

How might forthcoming changes affect federal spending on SDPs in the future?

In its May 2026 proposed rule, CMS estimates that SDP changes would reduce federal Medicaid spending by $510 billion between 2026 and 2035. Several factors contribute to the differences between CMS estimates and CBO’s estimate of limiting SDPs in the 2025 reconciliation law (which was $149 billion through 2034).

  • The CMS estimates account for SDPs in preprints available through December 31, 2025. During the 2025 calendar year, many states submitted new SDP proposals (some of which were submitted during deliberations on the reconciliation bill in anticipation of future restrictions). CMS posted many newly approved SDPs after the reconciliation law was enacted, some of which were posted 6 to 12 months after their start date. As a result, there are more SDPs in place than was known during deliberations over the 2025 reconciliation law.
  • The CMS estimates are through 2035. Most of the estimated reductions in federal spending on SDPs do not start until FY 2028. As a result, the period between 2026 and 2035 will have an additional year of substantive changes in SDP spending relative to earlier estimates.  In CMS’ year-by-year analysis, the estimated cuts to federal Medicaid spending from limiting SDPs are $81 billion in the year 2035, which would not have been included in the CBO analysis.

Beyond using different data and covering a different period, CMS provides estimates for some but not all specific provisions and policy decisions included in the rule. It is unknown how much the new provisions contribute to the cost difference because CMS did not itemize the effects of all decisions in the proposed rule. For example, one of the most significant decisions was to eliminate the option for states to use uniform rate increases in SDPs after the new limits are fully implemented. When combined with other policies (including the 2024 prohibition on separate payment terms), this change effectively eliminates the option for states to use SDPs to make supplemental payments in Medicaid managed care. The effects of this change interact with other policy changes (including changes to provider taxes) so it’s difficult to quantify how much this affected CMS’ estimates.

In some cases, the proposed rule describes how much certain decisions affected estimated spending reductions:

  • The biggest single change in dollar terms is the acceleration of grandfathering requirements which will bring SDPs into compliance with the new Medicare-related limits more quickly (estimated to increase the spending reduction by $17 billion over 10 years).
  • CMS estimated that extending the new limits on SDPs to services other than the four enumerated in the law would increase spending reductions by $3.5 billion over 10 years.

New limits on FFS payment rates could reduce federal spending by $1.5 billion over 10 years. CMS estimates that 25 states would have to amend state plans to come into compliance, and that the change would reduce federal Medicaid spending by $1.5 billion over 10 years. Although $1.5 billion seems small compared to the total reduction in federal Medicaid spending, the affected providers account for much smaller shares of overall Medicaid spending. As a result, there could be major implications for affected services in affected states.

This work was supported in part by Arnold Ventures. KFF maintains full editorial control over all of its policy analysis, polling, and journalism activities.

Appendix Figure: Timeline of SDP Policy Changes

Appendix Figure 1
News Release

Federal Medicaid Spending Through State Directed Payments Nears $100 Billion Annually Across 41 States, With New Limits Set to Reduce Funding to States  

KFF analysis shows hospitals have the most spending through state directed payments

Published: Jun 15, 2026

Forty states and DC currently receive $93 billion in annual federal Medicaid spending through state directed payments (SDPs) and may be at risk due to forthcoming limits on these payments, according to new KFF estimates. Annual federal spending on SDPs is highest in California (an estimated $10.6 billion)—followed by Texas ($6.3 billion), North Carolina ($5.2 billion), and Illinois ($5.1 billion). 

Map shows the estimated annual federal spending for state directed payments (SDPs) that require prior CMS approval. At Least 41 States Have State Directed Payments, Estimated at $93 Billion in Annual Federal Medicaid Spending.

The vast majority of federal SDP spending (84%) covers hospital services, totaling an estimated $78 billion annually. Professional services at academic medical centers ($3.2 billion) and nursing facility services ($2.1 billion) account for the next-largest shares of federal SDP spending each year.

First established in 2016, SDPs allow states to direct how managed care organizations pay for services. They may take a variety of forms but most commonly require the managed care organization to make supplemental payments and specify a total payment rate. KFF estimates that 84% of SDP spending is currently benchmarked to commercial (or private) rates, which are notably higher than Medicare rates.

CMS started approving SDPs that linked payments to commercial rates in 2018 because the higher rates were seen as helpful to attracting a broader provider network and ensuring robust access to care. In 2024, a rule on Medicaid managed care codified the payment limit for SDPs at average commercial rates but also spurred additional spending on them as states began pegging more SDPs to the average commercial rates.

Just over a year later, the 2025 reconciliation law established new limits on SDPs, capping payment rates at or near Medicare levels instead of average commercial rates. These new limits will reduce payment rates for Medicaid services in affected states, with the largest effects expected to be on hospitals since they account for the majority of SDP spending. In May, the Centers for Medicare and Medicaid Services (CMS) issued a proposed rule that would expand the scope of the law’s limits on SDPs, according to KFF’s explainer on the policy changes.

CMS estimates that SDP-related changes in both the reconciliation law and the proposed rule would reduce federal Medicaid spending by $510 billion between 2026 and 2035, with effects increasing in size each year.

How states and providers will respond to the new payment limits remains uncertain. States have limited options for offsetting the federal cuts because of other changes to Medicaid financing from the reconciliation law, including new restrictions on provider taxes.

The stakes are particularly high for financially vulnerable hospitals, which are more likely to include safety net providers that primarily serve Medicaid enrollees. Some hospitals could face pressure to close or reduce services, especially if uncompensated care increases because people lose Medicaid or coverage through the ACA marketplaces.

Spending on Medicaid State Directed Payments Before New Limits Take Effect

Authors: Alice Burns, Scott Hulver, Jessica Mathers, Robin Rudowitz, and Patrick Drake
Published: Jun 15, 2026

The 2025 reconciliation law reduced federal Medicaid spending by an estimated $911 billion from 2025 through 2034, some of which stems from new restrictions on Medicaid state directed payments (SDPs) for hospital and other health care services. While states are generally prohibited from directing how managed care organizations (MCOs) pay for care, states can implement SDPs that require MCOs to increase rates or set minimum rates for specified Medicaid services. In authorizing SDPs, the Centers for Medicare and Medicaid Services (CMS) aimed to help states improve access to care and provider participation. Many states that contract with MCOs use SDPs to make uniform rate increases that function like supplemental payments in fee-for-service (FFS) Medicaid. This issue brief analyzes Medicaid spending by state on SDPs that require prior CMS approval to better understand the use of SDPs before new limits in the reconciliation law take effect. A companion issue brief provides more details about the forthcoming changes.

Using a sample of SDPs estimated to currently be in effect, the analysis includes 305 preprints from 41 states, from SDPs that were publicly available and approved from January 1, 2024 through May 12, 2026. Preprints are application forms which document how states direct Medicaid managed care plans to pay providers using SDPs. Preprints are the only national source of data on SDPs but are limited because there are gaps in data provided by the preprints (see Box 1 and Methods for more details).

KFF’s estimates of spending on SDPs are consistent with CMS’ estimates in the May 2026 proposed rule on SDPs. However, KFF estimates provide state-level data and other information not included in the proposed rule, use the most recently approved preprint for each SDP (instead of providing year-by-year estimates and projections), and include SDPs that were approved between January and May 2026 (which are not included in CMS’ analysis). This analysis finds that:

  • KFF estimates that annual spending on SDPs is $137 billion in total spending and $93 billion in federal spending.
  • There are 41 states with SDPs in place (including the District of Columbia, which is hereafter referred to as a state), but the number, structure, and financial impact vary.
  • Most (84%) of estimated SDP spending is for hospital services.
  • Most (84%) of estimated SDP spending is from SDPs that use commercial (private) payment rates as a basis for MCO payments, but data on specific payment levels are often not publicly available.

Much remains unknown about how forthcoming policy changes for SDPs will affect states, providers, and Medicaid enrollees, but data about existing SDPs highlights states and services for which changes could be most substantial.

Box 1. Gaps in Data Available to Analyze State Directed Payments (SDPs)

There are major gaps in the data available to analyze state directed payments (SDPs), which come from “preprints” (documents states submit to CMS outlining how SDPs will work and projecting future spending.) Regulations governing SDPs specify which types of payments require prior approval from CMS and which do not, and the information available through the preprints. Missing information stems from the following lack of certain information and exceptions to reporting requirements governing preprints (see Methods for how KFF handled missing information in the estimates).

  • When states require MCOs to use the state’s FFS payment rates or Medicare FFS payment rates as a basis for payment, they do not have to obtain prior approval from CMS or submit a preprint file to obtain that approval. (Preprints are required if payment rates use a Medicaid or Medicare benchmark but not the exact FFS payment rates.) It is unknown how many states have SDPs that equal FFS Medicaid or Medicare rates. Since the exemption for Medicare rates was only established in a 2024 rule (see Appendix Figure), some SDPs that use Medicare rates still show up in publicly available preprints.
  • Preprints include states’ projected estimates of what they will spend in the future as approved by CMS, but there is no source of information about what states spent. CMS issued guidance in March 2026 specifying that states must start reporting paid amounts in the Transformed Medicaid Statistical Information System (T-MSIS) by September 2026. It is unclear how comprehensive those data will be—most states currently do not report other types of supplemental payments in T-MSIS.
  • For preprints that span multiple types of services, states are not required to specify the projected spending by type of service.
  • States may provide some information in an addendum to the preprint rather than in the publicly available preprint form, and CMS has not published many preprint addendums, resulting in additional missing information. Some of the information that is most frequently placed in addendums relates to states’ specific payment rates and the details around how the state share of SDP spending is financed. For example, among 139 preprints in this analysis that included payments for hospital services (estimated at $80.3 billion in federal spending), the specific payment rate was missing or incomplete for 38 preprints (estimated at $41.4 billion in federal spending).

How much spending currently flows through SDPs?

Using a sample of preprints estimated to be currently in effect, KFF estimates that Medicaid is spending about $137 billion per year through SDPs. Based on states’ projected spending in the preprints, the federal government pays an estimated 68% ($93 billion) of the total, and the remainder is paid through the state share of SDP financing. The federal and state shares of financing are determined using the standard formulas for Medicaid financing and reflect the state’s federal matching assistance percentage, along with adjustments for some services and eligibility groups for which the federal government pays a higher rate. The state share of financing may come from a variety of sources including state general fund revenues, provider taxes, and intergovernmental transfers.

Annual Spending on SDPs is Estimated at 7 Billion in Total Spending and  Billion in Federal Spending (Donut Chart)

Financing for SDPs is often complex, and providers may pay for part of the state share of spending through provider taxes and intergovernmental transfers. States may finance the state share of Medicaid spending through provider taxes and intergovernmental transfers (such as transfers from public hospitals), which means those payments are not new revenues for the providers receiving them. In the proposed rule on SDPs, CMS reports that among current SDPs with payment rates above Medicare rates:

  • 40% are financed wholly or in part by intergovernmental transfers,
  • 27% are financed wholly or in part by provider taxes, and
  • 14% are financed wholly or in part by both intergovernmental transfers and provider taxes.

Combined, 81% of those SDPs are financed wholly or in part by intergovernmental transfers and provider taxes. In such cases, it is difficult to determine the amount of new revenues for health care providers. For that reason, KFF’s analysis focuses on changes in federal spending rather than changes in total spending.

How many states have publicly available SDPs?

Nearly all states with comprehensive managed care in Medicaid are estimated to use state directed payments, but the number, structure, and financial impact of these payments vary. Of the 42 states that contract with MCOs, all but two states (Arkansas and North Dakota) have approved SDPs that are estimated to still be in effect. (Arkansas has two approved SDPs for the 2022 rating period, but none have been approved since.)

Vermont does not contract with comprehensive, risk-based MCOs but does have an SDP to implement an accountable care organization program that is transitioning providers to value-based payments through Medicaid. Under the accountable care model, provider groups contract with state Medicaid agencies to assume accountability for the costs and quality of care. The Accountable Care Organization distributes payments to contracted providers in the way comprehensive MCOs pay contracted providers. In essence, the SDP functions similarly but is directing payments through an accountable care organization instead of through an MCO.

The number of SDPs and dollars spent through SDPs varies by state:

  • New Jersey and Ohio have the largest number of SDPs (28 and 20 respectively), while two states (Minnesota and West Virginia) and DC have one SDP each (data not shown).
  • California has the highest projected federal SDP spending ($10.6 billion), followed by Texas ($6.3 billion), North Carolina ($5.2 billion), and Illinois ($5.1 billion).

Vermont has the lowest projected federal SDP spending ($12.4 million), followed by Maryland ($52.6 million), Missouri ($145 million), and Minnesota ($161 million). Although this analysis focuses on trends in federal spending, patterns are similar when looking at total spending (Appendix Table 1). All 10 states with the highest federal spending also are in the top 10 states for total spending. Many—but not all—of these SDPs could be affected by the new requirements for SDPs in the 2025 reconciliation law.  

At Least 41 States Have State Directed Payments, Which are Projected at Nearly 0 billion in Annual Federal Spending (Choropleth map)

How are SDPs used across provider types?

An estimated 84% of federal dollars spent through SDPs that require CMS approval pay for hospital services (Figure 3). Of $93 billion in annual projected federal SDP spending, an estimated $78.0 billion (84%) is directed to hospital services. (The share of total spending that pays for hospital services is the same as the share of federal spending.) Professional services at academic medical centers ($3.2 billion) and nursing facility services ($2.1 billion) comprise the next largest shares of federal SDP spending. Although most spending is from SDPs exclusively targeting hospital services, many SDPs include spending for multiple service types and do not specify how much of the total spending is for each service, which creates uncertainty in the estimates (see Methods).

The largest number of SDPs also pay for hospital services, although 64 SDPs are directed to multiple service types, including hospitals. Specifically, of the 305 preprints included in this analysis, 107 were exclusively for hospital services. The next most frequent services were behavioral health services (20 SDPs), professional services at academic medical centers (18), and nursing facility services (17) (data not shown). The remaining preprints were directed exclusively to other services, or to combinations of services.

Most (84%) of Estimated SDP Spending is Directed to Hospital Services (Donut Chart)

What types of payment rates do existing SDPs require of MCOs?

Most spending (84%) comes from SDPs that use average commercial rates as a benchmark, which likely reflects the federal requirements that determine which SDPs require a preprint. The share of spending for SDPs that use average commercial rates is high relative to the share of preprints that use average commercial rates: Nearly two-thirds (65%) of preprints are benchmarked to average commercial rates. The dominance of average commercial rates in the publicly available preprint data likely reflects the fact that when benchmarks equal FFS Medicare or Medicaid rates, no preprint is required. Only a small share of spending is from SDPs that do not require a benchmark.

Most Spending on SDPs is Benchmarked Using Average Commercial Rates (ACR) (Donut Chart)

Roughly a quarter of SDP spending ($23 billion) is paid at or above 90% of average commercial rates, while over one third ($38 billion) is benchmarked to ACR rates that are not publicly available. An additional $10 billion is paid at 70%–90% of average commercial rates. Among the SDPs that do not use ACR as a benchmark, missing payment rates are somewhat less common. Among SDPs that use Medicare rates as a benchmark, just over half result in total payment rates greater than what Medicare pays. (Other SDPs that use Medicare rates as a benchmark may pay at or below Medicare.)

Roughly a Quarter of SDP Spending Is at or Near Average Commercial Rates, While Over One Third Is Benchmarked to ACR Rates That Are Not Publicly Available (Donut Chart)

This work was supported in part by Arnold Ventures. KFF maintains full editorial control over all of its policy analysis, polling, and journalism activities.

Patrick Drake, an independent consultant, contributed to the analysis of SDP data.

KFF appreciates the contributions of external reviewers who provided comments on earlier versions of this analysis.

Methods

Data source: This analysis uses data available from the list of approved state directed payment preprints published by the Centers for Medicare and Medicaid Services (CMS) as of May 12, 2026. The approved state directed payment (SDP) preprints are PDF versions of forms that are completed by states and approved by CMS. States are required to seek approval using such a preprint for any SDP that requires managed care organizations (MCOs) to pay for services at any rate other than fee-for-service (FFS) Medicare or Medicaid rates. The approved preprints are often posted online 6–12 months after their start date, although some approved preprints are posted online much later.

KFF developed a Python script to download the available PDFs, extract relevant data from them, and standardize certain fields. Each preprint was turned into one row in a spreadsheet. Data from tables within the preprint were extracted and converted into separate tables in KFF’s data file with each row in the preprint table converted into a row in the spreadsheet table.

SDP preprint inclusion criteria: KFF included all SDPs in the analysis with a rating period start date of January 1, 2024 onwards for the 50 states and Washington DC (hereafter referred to as a state). Puerto Rico was the only territory that had published SDPs, which were excluded. In each case, KFF only kept the most recent preprint for any given SDP. For example, if an SDP had an initial approval in 2024 and then renewals in 2025 and 2026, KFF would only include the 2026 renewal in the final dataset. Out of the 305 preprints included in this analysis, 24 (totaling $8.8 billion in federal spending) ended in calendar year 2024.

A small number of SDP preprints were excluded due to file formatting or data validity issues. Specifically:

  • Data from five preprints excluded from this sample were encoded differently, so the data could not programmatically be extracted into the dataset, and were therefore excluded from the analysis (two from New Hampshire, one from Ohio, and two from Florida, totaling $89 million in federal spending for one year).
  • Data from preprints that had obvious data quality issues were excluded from this sample.  For instance, two were from Illinois (which projected total annual spending of more than $100 billion) while one from Minnesota did not report spending data in the preprint.

KFF also reviewed all preprints with end dates prior to July 1, 2025, and excluded preprints for the following reasons.

  • The preprint was likely funded from COVID-19 relief dollars (including the increased federal funding for home care from the American Rescue Plan Act) and so unlikely to still be in place.
  • The preprint was likely combined into a different preprint when renewed or was otherwise renamed when renewed.
  • The preprint ended in 2024, and online research suggests that the payment was discontinued.

See Methods Table 1 for a list of the inclusion criteria, the counts of preprints after each criterion was applied, and the federal spending for preprints that were retained at each stage.

Calculating total spending on SDPs: This analysis used the states’ projected total, federal, and state spending from the preprint. Most preprints are for a one-year period but some are for longer or shorter periods. In such cases, KFF adjusted the data to be a one-year equivalent. When preprints were for periods shorter than 12 months, dollars were scaled up (e.g., if the preprint was for 6 months, the spending was multiplied by two) and for preprints that were for periods longer than 12 months, spending was scaled down (e.g., retaining two-thirds of spending if the preprint extended for 18 months).

KFF also manually reviewed the federal spending numbers because some states reported them as percentages and others reported them as dollar amounts. Manual review ensured the Python script had adequately handled the different reporting structures.

In most cases, the state and federal shares equaled the total share, but in 8 states, this was not always the case (see Appendix Table 1).

Calculating SDP spending by service type: For preprints that made payments for multiple service types (which accounted for $32.6 billion in federal spending), spending was apportioned across service types.

  • For SDPs directed to hospital and non-hospital services, 90% of spending was allocated to hospital services. Remaining dollars were apportioned equally among any other service types.
  • For SDPs directed to both inpatient and outpatient hospital services, 68% of hospital spending was allocated to inpatient services and 32% was allocated to outpatient services. This assumption does not affect the estimates of spending by service type but is relevant for calculating the amount of spending by benchmark rate.
  • For SDPs that did not direct any spending to hospital services, spending was allocated equally among named services.

Apportioning spending across service types is difficult and KFF used a variety of sources to approach developing the most realistic assumptions feasible. KFF analyzed data on Medicaid spending including CMS-64 spending by service type, data on Medicaid spending by service type from the National Health Expenditures, the Congressional Budget Office Medicaid baseline, and existing studies on hospital payment policies such as those from the Medicaid and CHIP Payment and Access Commission (MACPAC). All of those data points suggest that the vast majority of SDP spending pays for hospital services, and $53.1 out of the $60.5 billion in federal spending from preprints directed to a single provider type went to hospital services. KFF also strove to use an assumption that resulted in estimates of hospital SDP spending that are similar to what could be expected on the basis of other data and research as described above.

When identifying the service types in the preprints, the Python script attempted to align service types between preprint Table 2 (which specifies payment rates for sets of providers) and preprint question 20 (a checklist of services included in the SDP). In many cases, this alignment involved some uncertainty, requiring manual review and classification of service types.

Identifying benchmarks for MCO payments: The most common type of SDPs requires MCOs to make payments that are on top of the regular base payment rate (as opposed to limiting or replacing the negotiated rate). In such cases, payments are measured using a “benchmark” or standardized rate to compare the MCO rates to other payment rates such as those of Medicaid FFS, Medicare FFS, or the average among commercial payers (“average commercial rates”). Among the 305 preprints in this sample (accounting for $93.1 billion in federal spending), 264 preprints are required to report a benchmark (accounting for $87.9 billion in federal spending). KFF used the Python script to identify the applicable benchmark type from the preprint, but also manually reviewed the data since states sometimes used inconsistent terminology to report the same benchmarks.

Identifying payment levels: To identify how current payment rates align with the new limits on SDPs in the reconciliation law, KFF first needed to identify payment levels in the preprints. The level is specified as a percentage of the benchmark (e.g., 90% of average commercial rates or 140% of Medicare rates). Both types of payments were pulled from Table 2 when available.  Payment rates for inpatient and outpatient hospital services were tracked separately with each row in Table 2 when applicable.

Methods Table 1

Analysis StepCount of PreprintsFederal Spending Among Preprints (billion $)Analysis Step
Preprints listed on CMS’s website as of May 12, 20261,038 

 

All preprints pulled from CMS website987246.4Some links are broken or duplicates
Preprints in time period and states570 
166.1
 
Includes the most recent preprint for each state directed payment (SDP) from January 2024 onwards for the 50 states and DC
Most recent SDP submission or renewal35899.6

 

Preprints without data quality issues35299.6KFF dropped preprints that were missing information about the start date, end date, spending amounts, etc.
Preprints manually reviewed and dropped30593.1KFF dropped preprints from older years that were subsumed into newer preprints and those that were temporary policies started during the COVID-19 pandemic

Appendix Table: States’ Number of and Spending on SDPs

SDP Spending and Preprint Count by State (Table)