News Release

Capping Per Enrollee Spending Could Reduce Federal Medicaid Expenditures by $532 billion to Nearly $1 Trillion Over 10 Years Depending on How States Respond and Result in as Many as 15 Million People Losing Medicaid Coverage by 2034

Eliminating the Medicaid Expansion Match Rate at the Same Time Could Push Federal Medicaid Spending Declines to as Much as $2.1 Trillion and Cause 30 Million to Lose Medicaid Coverage 

Published: Feb 26, 2025

As Congress considers ways to cut Medicaid spending to help finance the extension of federal tax cuts, a new KFF analysis finds that imposing a cap on federal spending per Medicaid enrollee—known as a “per capita cap”—could trigger a decrease in federal Medicaid spending over a 10-year period of $532 billion to almost $1 trillion, depending on how states respond to the cuts. An estimated 15 million people could lose Medicaid coverage by 2034, if states were to respond to the change by reducing their own Medicaid spending and curtailing eligibility.

The size of the cuts and which states would be hit hardest would depend on how states respond, and also whether the policy is combined with other changes, such as ending the 90% federal match for the Affordable Care Act’s Medicaid expansion.

The analysis shows that if states choose to increase their own Medicaid spending to offset federal reductions and maintain coverage and benefits, federal Medicaid spending would fall by $532 billion and state costs would increase by the same amount. State responses to federal cuts may vary. 

However, if Congress at the same time eliminates the enhanced federal matching rate for the Medicaid expansion (another significant policy being discussed, and which was examined by a previous KFF analysis), the impact would be bigger. Federal Medicaid spending cuts could range from $1 trillion–if states offset costs–to $2.1 trillion–if states respond by cutting state spending and eligibility over 10 years, with 30 million people losing Medicaid coverage by the end of the period.

In a party-line vote, the Republican-controlled House last night passed a budget resolution that would target cuts to Medicaid of up to $880 billion or more over a decade to help pay for tax cuts.

“The current proposals being discussed by Congress would lead to the largest Medicaid spending cuts and enrollment declines in the program’s history with an unprecedented cut in federal Medicaid funding to states,” said KFF President and CEO Drew Altman. “As our polling and focus groups with voters show, Americans, including many Trump voters, are not expecting, nor would they want, cuts to Medicaid, which would be felt across the country.” 

The analysis examines the potential impacts of two of the Medicaid proposals being discussed that would generate significant federal savings. It looks at the combination of them because lawmakers may pursue multiple, simultaneous changes to the program that would have interacting effects. Other proposals being discussed reportedly include imposing Medicaid work requirements, reducing the minimum federal matching rate, restricting states’ use of provider taxes to finance their share of Medicaid spending, and repealing certain Medicaid regulations. Future KFF analyses will examine these proposals as well.

Under the current system, the federal government reimburses states for a share of Medicaid enrollees’ costs, with no upper limit on expenditures, and states pick up the rest. Capping the federal contribution would force states to choose how to offset the funding reductions and could lead to increases in the uninsured rate and reduced revenue for health plans, hospitals and nursing homes.

Other key takeaways of the analysis include:

  • Maintaining current Medicaid benefit levels and enrollment would require states to pay $1,500 more per enrollee under a per capita cap, or up to $2,300 more per enrollee under a per capita cap that is combined with the elimination of the enhanced Medicaid expansion match rate, by FY 2034.
  • Decreases in Medicaid enrollment would vary by state and could be as high as 57% in some states if Congress implements both per capita cap financing and the elimination of the Medicaid expansion match.
  • Spending reductions under a per capita cap would compound in future years as the per enrollee cap levels diverge further from spending levels expected without the cap, limiting states’ ability to meet changing program needs.

All states would be affected by a per capita cap, but the magnitude would vary due to differences in the mix of the types of Medicaid enrollees in each state. The effects would vary across eligibility groups because spending for different groups is expected to grow at different rates over time.  Also, the elimination of the enhanced Medicaid expansion match rate would only affect the 40 states and the District of Columbia that have adopted the expansion. 

For detailed state-by-state impacts of the proposed Medicaid financing changes on spending and enrollment, see Appendix Tables 1 and 2.

A related report released this week highlights the experiences and opinions of Medicaid enrollees who participated in five virtual focus groups that KFF conducted in January with enrollees who voted for President Trump or for Vice President Harris. Despite differences in political leanings, participants reported having favorable experiences with Medicaid and concerns about potential cuts to the program. While some Trump voters enrolled in Medicaid believed there is fraud in the program and were open to work requirements, they also didn’t think that President Trump would follow through on cuts to Medicaid because they believed he understood their financial struggles.

Medicaid covers one in five people in the U.S., and accounts for nearly $1 out of every $5 spent on health care. It covers 41% of all births, nearly half of children with special health care needs, and five in eight nursing home residents.

A Medicaid Per Capita Cap: State by State Estimates

Published: Feb 26, 2025

There are several options under consideration in Congress to significantly reduce Medicaid spending to help pay for tax cuts, with the recently passed House budget resolution targeting cuts to Medicaid of up to $880 billion or more over a decade. Medicaid is the primary program providing comprehensive health and long-term care to one in five people living in the U.S and accounts for nearly $1 out of every $5 spent on health care. Medicaid is administered by states within broad federal rules and jointly funded by states and the federal government, meaning restrictions in federal Medicaid spending could leave states with tough choices about how to offset reductions through cuts to Medicaid, cuts to other programs, or tax increases.

This analysis examines the potential impacts on states, Medicaid enrollees, and providers of implementing a per capita cap on federal Medicaid spending, which is one proposal that has been discussed in Congress. The analysis assumes, based on proposals floated in Congress, that the plan would cap federal Medicaid spending growth per enrollee for each of the five major eligibility groups at medical inflation. Given the likelihood of multiple, simultaneous changes to Medicaid and the interactive nature of those changes, the analysis also illustrates the effects of a per capita cap on Medicaid if implemented jointly with the elimination of the 90% federal match rate for the Affordable Care Act (ACA) expansion, another significant policy change that has been discussed in Congress and which was examined by a previous KFF analysis. Other proposals to reduce federal Medicaid spending have also been reportedly raised, including work requirements, a reduced federal matching rate, limits on provider taxes to finance the state share of Medicaid spending, and repeal of certain Medicaid regulations issued by the Biden administration. Future KFF analyses will examine these proposals as well.

Key takeaways

  • The estimated effects of a per capita cap depend highly on what assumptions are made about policy specifications, future growth in Medicaid spending, and states’ responses to federal cuts.
  • Capping per enrollee spending could reduce federal spending by $532 billion to nearly $1 trillion dollars between FY 2025 and FY 2034. Depending on how states respond, the policy could shift costs to states by $532 billion and leave total Medicaid spending unchanged or total Medicaid spending could decline by 14% (or $1.4 trillion).
  • If per capita caps were implemented jointly with the elimination of the enhanced ACA expansion match rate, federal Medicaid spending could decline by $1 trillion to $2.1 trillion dollars between FY 2025 and FY 2034. Depending on how states respond, this combination of policies could shift costs to states by $1 trillion and leave total Medicaid spending unchanged or total Medicaid spending could decline by a quarter (or $2.6 trillion).
  • If states reduced Medicaid eligibility proportionally to the cuts in federal spending, 15 million enrollees could lose Medicaid coverage under a per capita cap by the final year of the analysis, with that figure doubling to 30 million when combined with elimination of the ACA expansion match rate.
  • States would face tough choices about Medicaid’s future under a per capita cap: maintaining current Medicaid benefit levels and enrollment would require states to pay $1,500 to $2,300 more per enrollee in the final year of the analysis.
  • The effects of a per capita cap differ across eligibility groups because spending for different eligibility groups is expected to grow at different rates, with larger estimated effects among children and adults who are not eligible because they have a disability or are ages 65 and older.
  • All states would be affected by a per capita cap, but the size of the effects vary due to differences in the mix of enrollees. Depending on state responses, state spending could increase up to 57% in some states if they chose to pay for the cuts. Enrollment could decrease by similar levels if states chose to restrict eligibility in response to the federal funding cuts.

Spending reductions under a per capita cap would compound over time as expected increases in Medicaid spending diverge from the caps. The effects would be smaller immediately following implementation, larger in FY 2034, the final year of this analysis, and continue to grow in the years after 2034. A per capita cap can provide lower and more predictable federal costs over time, but it would also fundamentally change the Medicaid federal-state partnership by eliminating the federal guaranteed match and transferring new financial risk to states. States would face significant challenges in efforts to pay for federal cuts and there would be pressure to reduce benefits and eligibility, with even larger effects if a per capita cap were paired with other Medicaid cuts. Beyond reduced Medicaid spending and enrollment, there could be increases in the number of people who are uninsured, fewer covered benefits for future Medicaid enrollees, and reduced revenues available for health plans and providers such as hospitals and nursing facilities.

What is the proposed policy change?

Medicaid spending is currently shared by states and the federal government with a guarantee to states for federal matching payments without a cap on federal expenditures. The percentage of costs paid by the federal government (known as the federal medical assistance percentage or “FMAP”) for most Medicaid enrollees is determined by a formula set in law designed to provide a higher federal match rate for states with lower per capita incomes. There are also higher match rates for certain services and populations like the ACA expansion group (90%). This leads to variation in the federal share of Medicaid spending across states. There is also considerable variation in per enrollee spending across states, due to state flexibility to determine eligibility levels, benefits, and provider payment, and across eligibility groups,reflecting differences in health care needs and utilization.

This analysis estimates the impact of implementing a per capita cap on the federal share of Medicaid spending. One proposal under consideration would “establish a per capita cap [on federal Medicaid expenditures] for each of the different enrollment populations set to grow at medical inflation.” While specifics on the implementation of this policy would be included in a legislative proposal, further details have yet to be released, and assumptions made here may differ from details included in proposed legislation. To estimate a per capita (i.e., per enrollee) cap policy, this analysis first establishes FY 2025 per enrollee spending as the base year estimate; then, starting in FY 2027, the analysis limits federal spending growth for the five major eligibility groups (children, adults, expansion adults, people with disabilities and aged 65+) to the consumer price index (CPI-U) plus 0.4 percentage points, which is KFF’s estimate of the difference between CPI-U and medical inflation (CPI-M) over the past 20 years (see Methods).

The analysis also estimates the combined impact of implementing a per capita cap and eliminating the ACA expansion federal match rate. The combined policy would include the same per capita caps on federal spending and also assumes that, starting in FY 2027, expenditures for people eligible through Medicaid expansion would be matched at each state’s traditional FY 2026 FMAP rate. This part of the analysis accounts for the interactive effects of these two policy changes; therefore, savings are lower than if each policy was modeled separately and the totals were added together (see Methods). There are a number of other Medicaid policy changes that have been suggested, and policy estimates would likely differ depending on the combination of policies and their interactive effects.

What is the potential impact on Medicaid spending?

This analysis does not make assumptions about specific state behavioral responses and instead examines how the impacts of the two policy alternatives vary based on two types of state responses to the cuts. The state responses are designed to illustrate the spectrum of potential policy change effects. However, in practice, each state is likely to respond to the policy change differently and spending impacts overall would likely fall within the range. While some states may choose to increase state spending to maintain current programs with substantially reduced federal funding, many would likely need to make programmatic cuts, making both the lower end and higher end estimates unlikely. The analysis does not explore people’s insurance coverage after losing Medicaid; some may enroll in another source of coverage, but many others would likely become uninsured. The estimates presented here are not directly comparable to the estimates of federal savings from the Congressional Budget Office (CBO) because CBO’s estimates account for people enrolling in other coverage and make assumptions about how states would respond in the aggregate. While the estimates assume that spending per enrollee by eligibility group would grow uniformly across states based on CBO’s national projections, it is likely that growth rates would vary by state, and that a cap would therefore have varying effects

Per Capita Cap

In analyzing the effects of a per capita cap on Medicaid spending, KFF considered the following two types of state responses.

  • Pay for Federal Cuts: States maintain per enrollee spending and eligibility at current levels, picking up new costs due to the federal cap on per enrollee spending. Enrollment and total spending would remain constant while costs would shift from the federal government to the states. States would have to make offsetting cuts in programs other than Medicaid or raise revenues.
  • Reduce Spending and Eligibility: States cap their share of per enrollee spending at medical inflation – e.g., by reducing payment rates to health care providers — and also reduce eligibility by the same percentage that federal spending is cut for each eligibility group to reflect the fact that the federal government is contributing less towards the cost. As a result, there would be decreases in enrollment and total, federal, and state spending. 

Capping per enrollee spending could shift costs to states or reduce total Medicaid spending by 14% ($1.4 trillion) over a 10-year period (Figure 1). If states offset the federal cuts, federal Medicaid spending could decrease by 8% or $532 billion over the 10-year period, and states would pay those costs, increasing the state share by 14% across all states. If instead, states cap their share of per enrollee spending and reduce Medicaid eligibility, federal Medicaid spending could decline by 15% or $989 billion, reflecting the fact that per enrollee spending is capped and enrollment goes down. State spending could decline by 12% or $450 billion. Combined, Medicaid spending could decrease by 14% or $1.4 trillion over the 10-year period. The analysis assumes states would reduce Medicaid eligibility proportionally to the cuts in federal spending, and the effects compound over time, meaning spending and enrollment effects are smaller in years just following implementation but grow over time. By the end of the 10-year period, enrollment could be 17% lower than current policy, meaning 15 million people could lose Medicaid coverage. Some who lose Medicaid may enroll in another source of coverage, but many others would become uninsured.

Capping Per Enrollee Spending Could Shift Costs to States or Reduce Total Medicaid Spending by 14% Over 10-Year Period

Per Capita Cap and Elimination of the ACA Expansion Match Rate

In analyzing the effects of a per capita cap on Medicaid spending if it were combined with the elimination of the ACA expansion match rate, KFF considered the following two types of state responses.

  • Pay for Federal Cuts: States maintain per enrollee spending and eligibility at current levels, picking up new costs due to the federal cap on per enrollee spending and the loss of the higher match rate for expansion enrollees. Enrollment and total spending would remain constant while costs would shift from the federal government to the states.
  • Reduce Spending and Eligibility: States cap their share of per enrollee spending at medical inflation, drop the ACA Medicaid expansion, and reduce eligibility by the same percentage that federal spending per enrollee is cut for each eligibility group, resulting in changes to enrollment and to total, federal, and state spending as well as per enrollee spending.

Capping per enrollee spending and eliminating the ACA expansion match rate could shift costs to states or reduce total Medicaid spending by a quarter ($2.6 trillion) over a 10-year period (Figure 2). If states pay for the cuts, federal Medicaid spending could decrease by 15% or $1 trillion over the 10-year period, and states would pay those costs, increasing the state share by 27% across all states. If instead, states cap their share of per enrollee spending and reduce Medicaid eligibility, federal Medicaid spending could decrease by 32% or $2.1 trillion, and state spending could decrease by 15% or $571 billion. Combined, Medicaid spending could decrease by 26% or $2.6 trillion over the 10-year period. Enrollment losses could increase each year proportionally with the increase in federal spending cuts, resulting in 30 million (or 36%) fewer people with Medicaid coverage by the end of the 10-year period.

Capping Per Enrollee Spending and Eliminating the ACA Expansion Match Rate Could Shift Costs to States or Reduce Total Medicaid Spending by a Quarter Over 10-Year Period

Impacts on State Spending if States Pay for Federal Cuts to Medicaid

Under both policy alternatives, costs would shift significantly from the federal government to the states if states chose to maintain current benefits and eligibility, causing state Medicaid spending per enrollee to increase by $1,500 to $2,300 in FY 2034 (Figure 3). With federal Medicaid spending per enrollee capped, state spending per enrollee could increase from $5,500 under current policy to $7,000 with a per capita cap and $7,800 if the per capita cap were paired with the elimination of the ACA expansion match rate. By FY 2034, the federal share of Medicaid spending on average across states could fall from 64% to 54% with a per capita cap and 49% if the per capita cap were paired with elimination of the ACA expansion match rate.

Capping Per Enrollee Spending Could Shift Substantial Costs to States

All states would be affected by a per capita cap, but the specific effects vary depending on the mix of enrollees in a state, with state spending increasing by as much as 57% in some states if paired with the elimination of the ACA expansion match rate (Figure 4). If states opted to pay for the federal Medicaid cuts, state spending on Medicaid could increase anywhere from 6% to 57% over 10 years. Expansion states could experience much larger state cost increases, ranging from 18% to 57% if the per capita cap were paired with the elimination of the ACA expansion match rate, whereas state cost increases for all non-expansion states could remain at or below 21%. While this analysis assumes that growth rates for each eligibility group are uniform across states under current policy, it’s likely that growth rates would vary by state in any given period based on policy choices and underlying factors related to their economies and health systems.

All States Would be Affected by a Per Capita Cap Though State Spending Increases Vary Across States

Impacts on Medicaid Spending and Enrollment if States Respond to Federal by Cutting Spending and Eligibility

The effects of per capita caps differ across eligibility groups because spending for different eligibility groups grows at different rates, with larger effects among children and adults who are not eligible because they have a disability or are ages 65 and older. The effects vary by eligibility group because spending estimates under current policy assume that per enrollee spending for each group grows at different rates (aligning with CBO per enrollee spending growth assumptions), but the per capita cap policy would limit the growth for all groups using the same inflation rate. Spending grows at different rates largely based on the percentage of spending that comes from use of long-term care for each eligibility group. Although Medicaid enrollees who use long-term care have much higher per enrollee costs, CBO expects those costs to grow more slowly in future years. By FY 2034, the decline in per enrollee spending under a per capita cap could be: 24% for expansion adults, 20% for other adults, 19% for children, 11% for people eligible because of a disability, and 6% for adults ages 65 and older.

This analysis assumes that states would reduce eligibility in proportion with the cuts to federal spending, resulting in larger total spending and eligibility cuts among children and adults who are not eligible because they have a disability or are ages 65 and older (Figure 5). Under a per capita cap, total spending would drop to reflect the lower per person costs and the reductions in eligibility, which would be proportional to the cuts in federal spending. In FY 2034, an estimated 15 million fewer people could be covered by Medicaid including:

  • 5.3 million children,
  • 4.8 million adults eligible through the ACA expansion,
  • 2.9 million parents and other adults under age 65,
  • 1.3 million people with disabilities, and
  • 0.6 million people ages 65 and older.

An additional 15 million expansion enrollees could lose Medicaid coverage (totaling about 20 million expansion enrollees by FY 2034) if the ACA expansion match rate is also eliminated. Some people losing Medicaid would be eligible for ACA marketplace coverage (those with incomes 100-138% of the poverty level) and others would be able to obtain employer-sponsored health insurance. But, others would become uninsured. Most people over age 65 and some who qualify for Medicaid based on a disability would generally be able to maintain Medicare coverage but could lose access to wrap-around services not covered by Medicare.

Capping Per Enrollee Spending Could Result in Larger Total Spending and Enrollment Reductions Among Children and Adults Not Eligible Based on Disability or Age (65+)

All states would be affected by a per capita cap, but the specific effects vary, with enrollment decreasing by as much as 57% in some states if paired with the elimination of the ACA expansion match rate in 2034 (Figure 6). If states respond to federal cuts by reducing eligibility, Medicaid enrollment could decrease anywhere from 12% to 57% in 2034. Expansion states could experience much larger enrollment declines if paired with the elimination of the ACA expansion match rate, ranging from 31% to 57%, whereas enrollment declines for all non-expansion states could remain at or below 17%.

All States Would be Affected by a Per Capita Cap Though Enrollment Declines Vary Across States

What are other implications to consider?

Medicaid per capita caps lock in historical spending patterns, and the effects would compound overtime so the full implications would not be visible until after FY 2034. Per capita caps are initially set to reflect historical spending patterns that vary by state and eligibility group. Spending per enrollee will grow at the same rate for all states and eligibility groups, meaning that the low-spending states today will continue to be low-spending states indefinitely, and the same is true for spending across the eligibility groups. Moreover, the caps are typically designed to constrain federal Medicaid spending growth to a rate slower than is expected under current law, which is how they achieve federal savings. As time passes, the effects compound, limiting states’ ability to meet changing needs and demands. Federal spending reductions in FY 2034, the final year of the analysis, are larger than reductions over the full 10-year period (Figure 7), and the effects on enrollment and spending in future years would continue to grow.

The Effects of a Per Capita Cap Would Be Larger in FY 2034 and Continue to Grow

The effects of a per capita cap on Medicaid spending and enrollment are also highly sensitive to policy design, inflation rates, and how states respond to the cuts; and estimates are highly sensitive to assumptions about those factors. Decisions about how to calculate the per enrollee allotments for the base year and how to grow the allotments over time would determine the magnitude of costs shifted to states. The effects also depend on how much Medicaid costs grow over time and how they compare with changes in the inflator used to calculate the caps. States’ responses to the cuts would determine how much total spending and enrollment changed. If per capita caps are paired with other cuts to Medicaid, effects would be larger, and there would be more pressure on states to respond with programmatic cuts. Estimates of the effects of different per capita cap proposals may find a wide range of outcomes depending on what assumptions are made to complete the analysis.

A per capita cap would fundamentally change the Medicaid federal-state partnership by eliminating the federal guaranteed match and transferring new financial risk to states. Per capita caps allow federal spending to rise with enrollment; however, spending would not rise to account for: increasing costs due to the emergence of new technology such as cell and gene therapies, changes in population health status that increase per enrollee spending, or increased provider payment rates enacted to address workforce shortages. Medicaid is currently a partnership between the federal and state governments with both entities sharing the financial risk. Under a per capita cap scenario, federal spending would be lower and more predictable. The federal government would only bear risk associated with enrollment changes and the states would assume 100% of the risks associated with other factors that affect health care spending.

Under any per capita cap policy, states would face challenges and there would be pressure to reduce benefits and eligibility, but the effects would be larger if a per capita cap were paired with other Medicaid cuts. To maintain current policy, states would have to increase state tax revenues or decrease spending on non-Medicaid services such as education, which is the largest source of expenditures from state funds. Given the size of the federal funding cuts, states would face significant challenges in efforts to replace the loss of federal funds, which would be exacerbated if paired with other reductions in federal funding for areas beyond Medicaid. The loss of federal revenues would create significant pressure to eliminate the Medicaid expansion and restrain the growth in per enrollee spending for other enrollees. Medicaid spending per enrollee already grows at a slower rate compared with private insurance and Medicare, leaving fewer options for cutting per enrollee costs. States would all respond differently but could reduce spending by cutting optional benefits (which includes prescription drugs and nearly all home care, also known as home and community-based services or HCBS), reducing provider payment rates, or cutting eligibility for the specific eligibility groups with higher per person spending, such as those linked to the use of long-term care.

If states are unable to maintain Medicaid eligibility, benefits, and payment rates, there could be increases in the number of people who are uninsured, reduced access to care, and significant reductions in payment rates to providers. Reduced Medicaid eligibility would mean an increase in the number of uninsured people, with the most notable increases likely among people eligible for coverage through the ACA expansion, though people with disabilities may be particularly vulnerable on account of their more extensive health needs. Enrollees with incomes between 100% and 138% of poverty could be eligible for coverage through the ACA marketplaces, but ACA coverage could soon become more costly for enrollees if the enhanced subsidies expire at the end of 2025, and few low-income people have access to insurance through their employer. An increase in the number of uninsured people could reverse gains in financial security, access to care, and health outcomes as well as lead to loss of revenues and increased uncompensated care costs for providers. Providers could also face revenue losses from lower Medicaid payment rates or coverage of fewer services, which could exacerbate issues with access to care for Medicaid enrollees and within the health care system more broadly.

Appendix

Changes in Medicaid Spending and Enrollment Due to Capping Per Enrollee Spending by State
Changes in Medicaid Spending and Enrollment Due to Capping Per Enrollee Spending and Eliminating the ACA Expansion Match Rate by State

Methods

Data: To project Medicaid enrollment, spending, and spending per enrollee by state and eligibility group, this analysis uses the Medicaid CMS-64 new adult group expenditure data collected through MBES for FY 2023 (downloaded in December 2024), Medicaid new adult group enrollment data collected through MBES for June 2024 (downloaded in December 2024), the 2019-2021 T-MSIS Research Identifiable Demographic-Eligibility and Claims Files, and the June 2024 Congressional Budget Office (CBO) baseline.

Overview of Approach:

  • Develop baseline projections of Medicaid enrollment, spending, and spending per enrollee by state and eligibility group from FY 2025 through FY 2034 (a 10-year period). This model estimates Medicaid enrollment and spending under the status quo with no policy changes.
  • Estimate Medicaid enrollment, spending, and spending per enrollee by state and eligibility group over the same 10-year period after accounting for the effects of proposed policy changes.
  • Calculate differences in Medicaid enrollment, spending (including federal, state, and total spending), and spending per enrollee in the policy change scenario relative to the baseline projections.
  • The estimates do not predict states’ responses to federal policy changes, but we examine differences in Medicaid enrollment, spending, and spending per enrollee under different scenarios to reflect the range of outcomes depending on state responses.

Definitions and Limitations:

  • At the time of publishing, CBO had released their January 2025 baseline. However, this analysis uses CBO’s June 2024 baseline because it was the most recent baseline with spending projections by Medicaid eligibility group.
  • The estimates assume that all states experience the same growth rates for Medicaid enrollment and spending; and that total spending grows at the same rate as federal spending.
  • FMAP calculations do not account for the other services that are matched at a higher rate, which include family planning, services received through an Indian Health Services facility, expenditures for Medicare beneficiaries enrolled in the “Qualifying Individuals” program, and health home services that are matched at a 90% rate. For this reason, the model may underestimate the federal share of spending in some states.
  • Estimates of total spending include all spending that is matched as medical assistance but exclude states’ administrative costs which are matched at a separate rate. Federal payments for administrative costs are less than 4% of total federal spending, according to the CBO June 2024 baseline.
  • The analysis does not account for secondary effects or people’s behavioral responses.
  • The analysis does not include policy effects for states that had not expanded Medicaid under the ACA as of February 2025 but would have done so in the absence of the policy change.
  • We implement the elimination of the expansion FMAP in FY 2026 and the per capita cap in FY 2027; we assume they take effect immediately.
  • To implement a per capita cap, this analysis uses CPI-U + 0.4% instead of CPI-M because projections of CPI-M are not available. Studies and data show that in any given year, either measure may be higher so it’s unclear whether savings would be larger or smaller using a different measure. We chose to add 0.4% to CPI-U because over the past 20 years, CPI-M was 0.4% higher than CPI-U.

We provide more details about the baseline model below.

1.     Estimate initial Medicaid spending and enrollment by eligibility group using the most recent years’ data available (FY 2023 for spending data and FY 2024 for enrollment data).

  • First, we pull the quarterly Medicaid CMS-64 new adult group expenditure data collected through MBES for FY 2023 and aggregate total spending by state for enrollees in the ACA expansion group and for all other Medicaid enrollees. Spending reflects an accrual basis of accounting.
  • We exclude spending on DSH by calculating the share of spending on DSH from the FY 2023 CMS-64 Financial Management Report and reducing medical assistance among non-expansion enrollees by that share.
  • Separately, we pull the Medicaid new adult group enrollment data collected through MBES for June 2024. This data includes enrollment by state and is broken into ACA expansion group enrollees and all other Medicaid enrollees. MBES enrollment includes individuals enrolled in limited benefit plans and only includes individuals whose coverage is funded through Medicaid (not CHIP).
  • To obtain spending and enrollment estimates across the remaining eligibility groups (seniors, individuals with disabilities, children, and other adults), we apply the distribution of spending and enrollment across the groups and by state from T-MSIS to the FY 2023 spending data and June 2024 enrollment data. We use the average distribution from 2019 to 2021 to mitigate the impact of the continuous enrollment provision (data in states denoted as “unusable” for a given year by the DQ atlas were excluded from the averages).

2.     Calculate initial spending per enrollee in FY 2024.

  • We grow Medicaid spending in FY 2023 by CBO’s growth rates for federal benefit payments by eligibility group to get Medicaid spending in FY 2024. The June 2024 enrollment data is used as our FY 2024 enrollment.
  • We divide Medicaid spending in FY 2024 by Medicaid enrollment in FY 2024 (for each state and eligibility group) to get Medicaid spending per enrollee in FY 2024.

3.     Project total spending and spending per enrollee for fiscal years 2025 through 2034 using CBO growth rates and use those estimates to calculate future years’ enrollment.

  • Starting with spending data for FY 2024, we apply the CBO growth rates to estimate Medicaid spending in FY 2025 through FY 2034.
  • Starting with per enrollee spending in FY 2024, we apply the CBO growth rates for average federal spending on benefit payments per enrollee to estimate Medicaid spending in FY 2025 through FY 2034.
  • We calculate enrollment growth in FY 2025 through FY 2034 by dividing estimated Medicaid spending by estimated spending per enrollee.

4.     Split total Medicaid spending over the 10-year period into federal and state spending.

  • We calculate federal and state spending by using a 90% match rate for the ACA expansion group and the traditional state FMAPs for the remaining eligibility groups. We use the FY 2025 FMAPs for FY 2025 and FY 2026 FMAPs for FY 2026 and beyond.

We provide more details about the policy change scenarios below.

1.     Calculate spending and spending per enrollee under a per capita cap if states pay for federal cuts to maintain spending and eligibility by state.

  • Assume expansion enrollment and total spending remain the same as the baseline model over the 10-year period.
  • Establish the base year of per capita spending as the lessor of FY 2025 or FY 2027. We chose FY 2025 because most per capita cap proposals use spending from the period prior to enactment of the law to prevent states from inflating their base estimates of per capita spending in response to the law. We assume the per capita cap takes effect in FY 2027, so FY 2025 and FY 2026 per enrollee spending are the same as baseline and FY 2027 per enrollee spending is the same as the base year. We also assume that if states’ per enrollee spending for an eligibility group dropped between FY 2025 and FY 2027, the per capita cap would start at the lower baseline level to avoid giving states a higher match rate than they would have received under current policy.
  • After FY 2027, growth in per enrollee spending is capped at estimated medical inflation levels. To estimate medical inflation, we use CPI-U (Consumer Price Index for All Urban Consumers) + 0.4%, which is the difference in CPI-U and CPI-M (CPI Medical Care) over the past two decades.
  • Calculate new federal spending levels based on the capped per enrollee amounts by first multiplying enrollment and new per enrollee levels and then calculating the federal share using the FMAP.
  • For the combined per capita cap and elimination of the ACA expansion match rate, we assume the elimination of the expansion FMAP takes effect in FY 2027, so FY 2025 and FY 2026 federal and state spending are the same as baseline. Starting in FY 2027, we apply the 2026 traditional state FMAPs to the expansion group spending instead of the 90% rate to split total spending into the federal share.
  • State spending is calculated as the difference between baseline total spending (held constant) and new reduced federal spending levels.

2.     Calculate spending and enrollment if states respond to federal cuts by reducing spending and eligibility by state.

  • Per enrollee spending is capped and grown at CPI-U + 0.4% starting in FY 2027 (same as above).
  • Enrollment for each eligibility group is reduced by the same percentage that federal spending has been cut each year. This increases each year, but reaches 24% for expansion adults, 20% for other adults, 19% for children, 11% for people eligible because of a disability, and 6% for adults ages 65 and older by FY 2034. The total federal spending reduction and resulting total enrollment reduction are not equivalent due to differences in the distribution of spending and enrollment across groups.
  • For the combined per capita cap and elimination of the ACA expansion match rate, starting in FY 2027, expansion enrollment is reduced to zero, leading to zero total spending for expansion enrollees for FY 2027 – FY 2034.
  • Calculate total spending for other eligibility groups by multiplying new enrollment by capped per enrollee levels.
  • Split total Medicaid spending for other eligibility groups into federal and state spending using traditional state FMAPs.

3.     Calculate differences in Medicaid enrollment, spending (including federal, state, and total spending), and spending per enrollee relative to the baseline projections. 

 

The Debate Over Federal Medicaid Cuts: Perspectives of Medicaid Enrollees Who Voted for President Trump and Vice President Harris

Published: Feb 25, 2025

Report

The Republican-led Congress is considering plans to cut Medicaid to help pay for tax cuts, with the House budget resolution targeting $880 billion or more in potential reductions to federal Medicaid spending. Medicaid is the primary program providing comprehensive health and long-term care to one in five people living in the U.S and accounts for nearly $1 out of every $5 spent on health care. Reductions in Medicaid could have implications for enrollees as well as plans, providers, and state budgets. While there are several policy options under consideration in Congress to achieve savings, it is not clear how much support there is from Republicans (including President Trump) about these specific policies. The discussions in Congress come at a time when support for the Medicaid program continues to be strong. According to KFF polling, Medicaid is viewed favorably by a large majority (77%) of the public and an even larger share of those on the program (84%). As Congress considers reducing Medicaid spending, nearly half (46%) of all people and nearly two-thirds (62%) of Medicaid enrollees believe the federal government is currently not spending enough on the program.

To better understand the experiences of Medicaid enrollees and their perceptions of potential changes to the program, KFF conducted five virtual focus groups in January, including three groups with participants who had voted for President Trump in the 2024 election and two groups with participants who had voted for Vice President Harris. Focus group participants were asked about their experiences with their Medicaid coverage, views on government’s role in health care, and perceptions of the recent election. Participants were also asked for their reaction to current proposals to reduce federal spending on Medicaid and impose work requirements. Despite differences in who they voted for in November 2024, participants had consistently favorable experiences with Medicaid and concerns with potential cuts to the program. Key findings from our groups include the following:

  • Many Trump and Harris voters said that their top voting issue in the 2024 election was the economy, though some Trump voters cited immigration, and some Harris voters cited women’s rights as their top issues, and most participants said they did not recall hearing about changes to health care programs (including Medicaid) during the campaign. Most participants said the government has a role to play in making health care more affordable and accessible, but some Trump voters argued the private sector does a better job of controlling costs. When asked about fraud in the Medicaid program, many participants said they thought fraud exists, but views differed on whether it is a major issue and what was the primary cause. Several Trump voters believed the problem was due to people enrolled who were not eligible; however, other participants, including both Trump and Harris voters countered that state verification procedures prevent individuals from defrauding the program on a large scale and that providers and insurance companies were more likely the main source of program fraud.
  • At the time of the focus groups, most participants had not heard about proposals to reduce federal spending on Medicaid, and while most did not know why the reductions were proposed, some Trump voters suggested they were part of the crackdown on illegal immigration and aimed at removing undocumented immigrants from the program (undocumented immigrants are not eligible for federally-funded Medicaid). Participants opposed cutting Medicaid funding to pay for tax cuts that they did not believe would benefit them. Both Trump and Harris voters expressed fears that these changes would jeopardize the program, take away access to health care, result in worse health outcomes, and increase out-of-pocket costs. A few Trump voters did not believe Trump would follow through on the cuts to Medicaid because they believed he understood their financial struggles.
  • Both Trump and Harris voters valued their Medicaid coverage and the access to health care services, mental health services, and medications for themselves and their children it provides. Participants also valued Medicaid because it helps to protect them from financial disaster, alleviates stress, improves health outcomes and often supports their ability to work. Participants said losing Medicaid would “be devastating” and lead to serious consequences for their physical and mental health and exacerbate pre-existing financial challenges.
  • If work requirements were introduced to Medicaid, participants who were working generally felt confident in their ability to meet the requirements; however, they worried about the burden of monthly reporting requirements when those were described to them. Many participants across parties noted that access to treatment for chronic conditions, including prescription medications and mental health treatment, were key in helping to support their ability to work. More Trump voters supported a work requirement but some who were not working were convinced they would qualify for an exemption. Other participants, including both Trump and Harris voters, who were not currently working felt they would face challenges in meeting the requirements. Those who were not working said they wanted to work (and many had been previously working for many years) but were generally unable to because of disability or because they were caring for young children or a sick parent.
  • Both Trump and Harris voters wanted policymakers to focus on improving Medicaid instead of cutting it. For example, some participants said they would like to see enhanced dental benefits, increased doctor availability, and fewer prior authorization requests. Focus group participants wanted policymakers to consider the implications of federal cuts to Medicaid for people, their health, financial stability, and ability to be productive members of society.

General Situation

Most focus group participants were experiencing financial challenges and were managing an array of physical and/or mental health conditions. Medicaid eligibility requirements mean those on the program, by definition, have low incomes. Most participants described struggling with high food prices and noted the past few years have been financially difficult. Some focus group participants reported difficulties with the current job market or described injuries or disabilities that made it difficult to find employment. Focus group participants were managing an array of health conditions including high blood pressure, diabetes, physical disabilities, chronic pain, asthma, and anxiety and depression. Some were managing more complex and potentially disabling conditions, such as cystic fibrosis and hidradenitis suppurativa (HS). Along with managing their own conditions, some participants were also caring for parents or other family members in nursing care.

“Times are tough right now. You know, everything’s overpriced and no one’s working and can’t afford anything and my health is terrible, so it’s kind of tough times.”

50-year-old, White female(Trump voter, Nevada)

Experiences with Medicaid

Participants valued their Medicaid coverage and the access to health care services, mental health services, and medications for themselves and their children it provides. Along with regular physical exams for themselves and their children, focus group participants reported using Medicaid to see specialists, access mental health and substance use disorder treatment, receive necessary surgeries, and get prescription medications. Some participants with health conditions requiring frequent visits with specialists or multiple daily medications said they could not imagine day-to-day life without Medicaid.

“Doctor’s visits, I take 30 pills a day, so it covers all that, which is nice. I see the ENT like every other week.”

35-year-old, White female (Trump voter, North Carolina)

“I’m really grateful for it. When I first got on it, it covered for 90 days for me to go to a rehab and then it has covered my prescriptions with no questions asked.”

33-year-old, White female(Trump voter, Arizona)

Participants described Medicaid coverage as affordable, noting that it protects them from financial disaster and alleviates stress. Participants expressed gratitude that they could access necessary medications with little to no cost sharing, and in general were appreciative that they had no premiums and low out-of-pocket costs. Participants said that having Medicaid reduces stress related to unexpected medical costs. Prior to enrolling in Medicaid, many participants had been uninsured and had gone long periods of time without seeing a doctor. These participants were grateful that they were now able to access regular care. Those who had previously looked into or been enrolled in private insurance described Medicaid as a more affordable source of coverage.

“I never took insurance from where I was employed at because it was always so expensive. By the time they would take out the money, there wasn’t much of a check. So I was basically gonna be paying for insurance, which I know a lot of people have to do. Went a while without anything so Medicaid’s been really great as far as helping me out with doctor appointments, used to help me out with dental. I used it a little bit for mental therapy when I lost my daughter unexpectedly. So it’s been good.”

61-year-old, White female(Trump voter, Kentucky)

While participants said Medicaid was generally working well for them, some would like to see improvements, including enhanced dental benefits, increased doctor availability, and fewer prior authorization requests. Participants noted that it can be difficult to find doctors accepting Medicaid and frustrating to navigate prior authorizations for needed care. Other complaints included high turnover rates among providers at clinics that accept Medicaid and certain prescriptions not being covered by the program. Many focus group participants also wished that their state either covered dental benefits or had more generous dental benefits.

“There’s not like every doctor available, thankfully the doc I had before, I still am on the same doctor ’cause he is under my Medicaid, which is good. But there’s not coverage everywhere and certain things, so that’s kind of, you know, slight disadvantage there.”

59-year-old, White male (Harris voter, Pennsylvania)

Views on Government’s Role in Health Care

Participants felt that being able to easily access affordable health care services is essential to ensuring they can work and lead productive lives. Across voting parties, most participants felt that everyone deserved access to affordable health coverage, with many saying that people should not have to pay for what they described as “life or death” care. Some participants noted that being able to access health care services helps them to work, be more productive, and contribute to society. However, a few Trump voters talked about the need for people to take responsibility for their health suggesting that they did not believe health care was a right for everyone.

“Healthcare is a right because you want the American people to work. So in order for the American people to work, they need to be healthy to work.”

52-year-old, Black female (Trump voter, Pennsylvania)

“If we’re healthier, it makes our country healthier and we produce. If you got a bunch of sick people that have no insurance, all you’re gonna do is cause debt, death, and god knows what else.”

56-year-old, White male(Harris voter, Ohio)

Most participants said the government has a role to play in making health care more affordable and accessible; however, some Trump voters opposed government playing too large a role in running the health care system. Both Trump and Harris voters said the government has a role in making coverage more affordable, but some Trump voters noted that they felt private businesses may be more effective at keeping health care costs affordable than the federal government. More Harris voters (and some Trump voters) felt that the government should play a role in helping everyone access health care and in making the system work better. Both Trump and Harris voters compared the U.S. to other countries with nationalized health care systems, though takeaways from these comparisons differed. Some Trump voters referenced long wait times for care in other countries as evidence for why they did not think the U.S. should move to a socialized medicine model. Others (including both Trump and Harris voters) noted that the government should offer free care for all citizens, similar to other countries.

“It should be available for everybody. And it should be affordable. Because not everybody can afford the same thing… it’s usually the private sector does a better job with lowering costs and making things affordable and having options for people, not the government. I pay enough already in taxes that I don’t need to control anymore what I have to pay taxes for.”

45-year-old, Black male (Trump voter, Kentucky)

“It shouldn’t be an issue in a country this rich that people are going without it. I mean, it shouldn’t even be a question. It should be cut and dry. And we look at other countries, you know, it’s something they already have that the citizens have. And for a country that’s rich as America, it shouldn’t be your money or your life. You shouldn’t have to choose between medicine or buying food, or medicine and paying your life bill. It’s a right of an American citizen.”

61-year-old, Black female (Harris voter, Kentucky)

Election Experiences

Many Trump and Harris voters said that their top voting issue in the 2024 election was the economy. Most Trump and Harris voters cast their ballot based on economic concerns and which candidate they thought would address their pocketbook issues, including housing costs and grocery prices. Some Trump voters noted that their standard of living was better under the first Trump administration while some Harris voters were worried that Trump would cut benefits. Immigration was a top voting issue for some Trump voters, especially for those living in border states. A few Harris voters cited women’s issues and preserving democracy as the motivations for their votes.

“When Trump was in office from ‘16 to ‘20, you know, my standard of living was better than it is now.”

43-year-old, White male (Trump voter, Pennsylvania)

“Someone who’s not about to cut food stamps, cut housing, cut WIC, cut many stuff that we everyday people need.”

45-year-old, Black female (Harris voter, Ohio)

Most participants said they did not recall hearing either candidate mention changes to health care programs (including Medicaid) during the campaign. Because other issues, including immigration and the economy, dominated the campaign, most participants were unaware of either candidate’s health care priorities and any policy changes they planned to make. Some Harris voters recalled Harris discussing women’s health care and abortion access, and a couple of participants said they heard that Trump would either try to get rid of Obamacare (the Affordable Care Act) or would fix it. However, for the most part, health care issues were not a dominant factor in the election for these voters.

“I didn’t hear a peep about healthcare. Nope. It’s immigration for me.”

56-year-old, White male(Trump voter, Arizona)

“I think Kamala talked about healthcare like for women’s rights a lot. I feel like that was kind of one of her main points… I had never really heard Donald Trump talk about it. I heard about it in like Project 2025.”

25-year-old Black female (Harris voter, Pennsylvania)

Proposals to Reduce Federal Medicaid Spending

At the time of the focus groups, most participants had not heard about proposals to reduce federal spending on Medicaid, but Trump and Harris voters had different opinions on why the cuts were being proposed. No Trump voters and only a very few Harris voters said they were aware of proposals in Congress to reduce federal spending on Medicaid, and many were surprised to hear of the proposed cuts. Although most participants were not sure why the spending reductions had been proposed, some Trump voters theorized that it was part of the administration’s crackdown on illegal immigration and an effort to remove undocumented immigrants from the program (undocumented immigrants are not eligible for federally-funded Medicaid). A few Trump voters did not think Trump would follow through on the cuts because they believed he understood their financial struggles. Some Harris voters felt the proposals reflected a pattern by Republican lawmakers to reduce benefits for poor Americans.

“I’m a border state, so we’ve had so many illegals coming through and the previous administration they got all free social services. So I imagine that’s part of the thing that we were giving Medicaid to people who have been here hours and stuff. And so it’s one way to prevent or to get some cost cutting.”

59-year-old, Hispanic female(Trump voter, Arizona)

“Their goal is to make sure that we don’t have anything. So why they’re taking everything outta everything because the rich wanna get richer.”

58-year-old, Black female (Harris voter, Ohio)

“I think Trump knows that people are struggling right now, and I don’t think he’s gonna do, at least not right now, cut anything Medicaid because he just knows people’s financial problems right now.”

45-year-old, Hispanic male (Trump voter, Arizona)

When asked specifically about fraud and abuse in Medicaid, some participants across both groups believed there is fraud and abuse in the Medicaid program, but opinions were mixed on whether the source of the fraud is people enrolled who should not be or providers and insurance companies taking advantage of the system. The Trump administration has tied current actions to reduce federal spending to eradicating fraud, waste, and abuse within government programs. Many focus group participants agreed there was fraud in the Medicaid program; however, some described fraud as a major problem in the program and others reasoned there is fraud in Medicaid because there is fraud everywhere. When identifying the source of fraud in Medicaid, several Trump voters believed fraud was primarily due to people enrolled who were not eligible. Other participants, including both Trump and Harris voters countered that it would be too difficult for individuals to defraud the program on a large scale, describing how their states verify their income and other information at application and renewal. Some participants believed that providers and insurance companies overcharging the program or billing for services they did not provide were to blame rather than individuals. These participants offered examples of providers in their states who were convicted of fraud.

“Fraud is probably pretty prevalent, just like it was in everything else… People can abuse anything, so. If they have access to that, I’m sure there’s been some fraud over the years with Medicaid.”

56-year-old, White male(Trump voter, Arizona)

“I think it’s organizations more than people. I think it’s kind of hard to defraud with Medicaid. I mean, what are you doing going and asking for prescriptions and then selling them on the side? I mean, I don’t know how you would or having a high paying job and pretending you don’t work. I mean everything is available now on the internet. Everything’s tied in. Like me, our local Medicaid in Arizona was able to access my paychecks even before I saw what I was going to get one time they had it already on their screen.”

59-year-old, Hispanic female(Trump voter, Arizona)

“Most of the fraud that I’ve heard about comes from the actual provider billing for things they didn’t do.”

45-year-old, Black female(Harris voter, North Carolina)

Both Trump and Harris voters opposed cuts to the program fearing that Medicaid spending reductions would jeopardize the program and take away access to health care for poor people. Likely because of their reliance on the Medicaid program, participants opposed reducing spending on Medicaid, and many used strong language to describe the dire consequences of making major cuts to the program. Some participants predicted people would lose coverage if cuts were made to the program, and one participant suggested the economy would suffer because many of the people currently on the program would no longer be able to get the care they need. Others anticipated that states would cut benefits, particularly for prescription medications and mental health care, and that providers would stop participating in the program.

“We shouldn’t have to suffer because of somebody wanting to propose cuts to it, you know, because we, we didn’t do anything. So, you know, let it, it can come from somewhere else. I just, I would oppose it.”

60-year-old, Black male (Trump voter, Missouri)

“People would be unable to take care of themselves and be healthy and get mental health issues taken care of, to get vision and dental; people would suffer. They wouldn’t be able to work. And the economy would suffer.”

55-year-old, White female (Trump voter, Oklahoma)

“I would oppose [cutting Medicaid] just because there’s a lot of people who need it, who would be affected by it negatively.”

29-year-old, White male(Trump voter, Pennsylvania)

Participants opposed cutting Medicaid funding to pay for tax cuts that they did not believe would benefit them. Participants explained that because they had low incomes and were already in a low tax bracket, they did not expect their taxes would change much under any tax cut proposal. Both Trump and Harris voters said they would prefer Medicaid coverage to continue unchanged, arguing that the negative consequences of any changes to Medicaid would outweigh any small benefits they would experience from tax cuts. They said other government spending should be targeted to finance tax cuts.

“I don’t make much money to get my taxes affected by that. It would hurt my Medicaid, my medical more.”

50-year-old, White female (Trump voter, Nevada)

“They need to start taxing the right people properly first and then we can discuss that matter. Because we’re the only ones that are paying the taxes… They could put more into the programs if they tax the proper people properly.”

56-year-old, White male(Harris voter, Ohio)

Participants expected significant changes to the Medicaid program if federal funding were reduced and they worried they would lose coverage or face higher costs. Possible Medicaid spending cuts felt very personal to participants who expected they would be negatively affected by the proposed changes. Participants expressed anxiety over how reduced federal spending may affect out-of-pocket expenses, doctor availability, and covered benefits. Some described life and death consequences of not being able to access mental health care and prescription medications to manage their chronic conditions. Others focused on the financial implications of losing coverage and the impact that would have on their ability to work as well as on out-of-pocket costs for needed care. For participants with family members in nursing homes, the challenge of caring for them at home seemed daunting.

“I would be very worried. It would [mean] not being able to get my antidepressants [and] see a psychiatrist. Yeah, it would, it might crush me.”

45-year-old, Hispanic male (Trump voter, Arizona)

“States are gonna have to start dropping people off the rolls. People like us who are probably single and childless.”

45-year-old, Hispanic male(Harris voter, Arizona)

“It’s gonna be higher out of pocket costs for sure. You know, and that’s something I can’t afford. It’s not just me, it’s me and five other people, you know. So I can’t afford that for me, nonetheless them.”

45-year-old, Black female(Harris voter, Ohio)

Work Requirements

While some participants were working full-time, many who were working part-time or not working said they wanted to work or work more hours but were unable to because of disability or because they were caring for young children or a sick parent. Participants were working a variety of jobs, including home health aide, dental assistant, tax preparer and gig and contract work, but they needed Medicaid because they were not offered insurance through their work. Several said they were working part-time or not working because of illness or disability or because they were caring for young children or aging parents. Others said that they wanted to be working but have been unable to find employment. For those who were not working for a reason other than disability or illness, several said that to be able to work, they would need supports like affordable childcare, transportation, internet access, or better opportunities in their communities.

“I do self work with Instacart because …I get to pick and choose the days I’m able to work and dealing with my dad, getting in that nursing home and also dealing with my mom now because she’s getting into that phase where she’s needing more doctor appointments.”

52-year-old, Black male(Trump voter, Missouri)

“I can’t work right now because of my back. And I mean, I believe that my back got as bad as it did because I couldn’t go to the doctor when I didn’t have insurance.”

41-year-old, White female(Trump voter, North Carolina)

“Ever since I haven’t been working, I haven’t been able to find a job that’s legal or decent enough for working from home…They all want somebody in the office to stand up or sit down for long periods of time. I can’t even walk to my vehicle without being in pain. Or get into a vehicle and drive that vehicle because of the stress all behind that.”

51-year-old, Black female(Harris voter, Oklahoma)

Participants who were working said having Medicaid meant they could get the care they needed, especially medications, and provided financial peace of mind that enabled them to work. With high rates of chronic disease among focus group participants, the ability to manage their conditions was described as critical to their ability to work. This was especially true for participants who said their work sometimes exacerbated their health conditions, such as asthma or chronic pain. Keeping Medicaid was important to participants who were working, and several participants noted the challenge of managing work hours to maintain eligibility. One participant described how she lost coverage for one month because she worked too many hours. The income volatility that many workers on Medicaid experience can put them at risk of losing coverage and access to needed prescriptions and health care for a month or longer.

“I can say that even doing the part-time work, if I did not have Medicaid or wasn’t able to do pain management, I wouldn’t even be able to do those, those small amount of hours.”

45-year-old, Black female (Harris voter, North Carolina)

“It would be really hard for me to work a full-time, 9-5 job with all my doctor’s appointments as well as I’m immunocompromised. It’s definitely positive that I can do something I like, something I wanna do and not work as much and still be able to get insurance.”

35-year-old, White female(Trump voter, North Carolina)

“I found out with Medicaid that there’s a cap on how much I can earn. I wasn’t aware of that. And so actually in the fall I was kicked off for about a month because I apparently had earned too much.”

59-year-old, Hispanic female (Trump voter, Arizona)

Some participants who were not currently working expressed concerns about imposing work requirements in Medicaid, saying they would face challenges meeting the requirements, while others who supported the policy were convinced they would qualify for an exemption. While most participants had not heard about proposals to introduce work requirements for Medicaid, many Trump and Harris voters who were not working said they did not think they would be able to meet the requirements because of chronic pain or other disabilities. Although not currently working, several of these participants described the high demands of jobs they previously held, noting they had to leave those positions because of injuries or other health conditions. More Trump voters than Harris voters supported a work requirement policy, but several Trump voters who were not working and supported the idea of work requirements strongly believed they would qualify for an exemption because they have a disability or caregiving responsibilities. However, most participants with a disability were not receiving disability income and, therefore, may not meet disability exemptions, which in past proposals have been based on receiving Supplemental Security Income (SSI).

“I can’t because I have chronic pain and I just can’t. I worked until I couldn’t work no more.”

57-year-old, White female(Trump voter, Missouri)

“There’s nothing out here from miles and miles. I live in between two towns and it’s still nothing, you know, so people don’t always have the resources or availability to do what they ask.”

39-year-old, Black female (Harris voter, North Carolina)

“I mean, if you’re able bodied then, then you should still be working and trying and proving to them that you’re able to, ’cause like I said earlier, I want to work, but because of daycare costs, financially I can’t.”

34-year-old, White female(Trump voter, Kentucky)

“I already know I am exempt because I’ve seen this proposal and I already know I was exempt from it. But no, I wouldn’t be able to meet it if I wasn’t exempt.”

57-year-old, White male(Harris voter, Pennsylvania)

Participants who were working generally felt confident in their ability to meet the requirements; however, some worried about the burden of monthly reporting requirements. Given the number of hours they were working, most participants who were working felt that they would be able to meet any new requirements. But on the issue of reporting on work status monthly, participant opinions diverged. Some said that they were already submitting this information regularly to programs such as SNAP, so they were not worried about this requirement also being required in Medicaid. Others, however, expressed concern about having to report to the state each month, noting that they are human and prone to forget and that reporting requirements can be onerous. They also worried about the consequences of losing coverage for a month if they forget to report their work information in a month. As an alternative to submitting additional paperwork, some suggested an automated system, similar to how income is verified at renewal, would be more efficient.

“Required? Oh yeah. Easy. Oh yeah, absolutely. Mind you, I can’t do certain jobs. I can’t drive, if you will, but yeah, I can, I could do it. I can make it work.”

45-year-old, Hispanic male(Harris voter, Arizona)

“It’s gonna be devastating and upsetting to, you know, if you lose your health insurance if I forget as we tend to, we are only humans, sometimes we forget things. So if I don’t do this [report work hours], it affects the rest of my household and I don’t like that.”

45-year-old, Black female(Harris voter, Ohio)

“I would be very worried about them making mistakes. There’s been many times I’ve sent in paperwork and they didn’t get it and coverage was stopped. You know, a lot of room for clerical error and things like that.”

50-year-old, White female(Trump voter, Nevada)

Consequences of Losing Medicaid Coverage

Both Trump and Harris voters said that losing Medicaid coverage would be “devastating” and would lead to serious consequences for their physical and mental health. Participants emphasized that the health care services and prescriptions they and their children receive through Medicaid helps them “survive.” Across groups, participants said that losing their Medicaid coverage would create financial challenges and expressed anxiety at the thought of being unable to afford prescriptions, doctor visits, or higher premiums on top of pre-existing financial challenges if there were major changes to Medicaid. Although focus group participants were not aware of the nuances of congressional proposals, all participants were residing in Medicaid expansion states and those who were eligible due to Medicaid expansion could be especially vulnerable to proposed changes in the program.

“I think obviously, not having access to healthcare, or having to have the financial ability to pay for your medical needs, your basic medical needs, is something that we shouldn’t have to worry about because we worry about how we’re going to eat. We worry about how we’re gonna pay our bills… Not having Medicaid would be, not distressful, it would be detrimental because I need to see a primary care doctor, I need to see my specialist.”

58-year-old, Black female(Harris voter, Ohio)

“For me it would, it would probably lead to death, and that’s kinda harshly speaking, but it’s the way that it would be. I’ve relied upon Medicaid for myself in order to survive. For my son, it would be survivable, but it would be difficult. He has real bad allergies, he wouldn’t be able to hear.”

55-year-old, White female (Trump voter, Oklahoma)

When asked to respond to proposals to reduce federal Medicaid spending, participants appealed to policymakers to consider how these changes would negatively impact people. Participants felt that reducing federal funding for Medicaid would have serious consequences and hurt many people on the program. Some participants pointed out that many people enrolled in Medicaid could not afford any other alternatives and would have no way to access care if they were to lose coverage. The message of several Trump voters to policymakers was to focus on improving Medicaid instead of cutting it. Across groups, participants asked policymakers to remember the human impact of potential changes to the program.

“If you take money from Medicaid, you’re just creating another problem elsewhere. It’s gonna be a group of people that are being hurt over here to help the people over there so it doesn’t add up. It doesn’t make sense.”

45-year-old, Hispanic male(Trump voter, Arizona)

“Leave it alone and make it better.”

57-year-old, White female (Trump voter, Missouri)

“I would just beg them please to do their best to keep medical coverage for people that need it. And I mean, I live every day, day to day taking my meds and I need it. I don’t know what I would do without it.”

39-year-old, Black male (Trump voter, Ohio)

“Well, I think they should step back and look at it and realize that we’re not just a number on a spreadsheet or something that. We’re actually people and what they decide to do has consequences.”

39-year-old, White male(Harris voter, Kentucky)

“Ask yourself, if you’re the person to make the decision to cut [Medicaid], if it was you and someone in your family [who would be affected], what would you do if it was you?”

59-year-old, White male(Harris voter, Pennsylvania)

Methodology

For this project, five focus groups were conducted in January 2025 virtually among a total of 34 adults who self-identified as having Medicaid coverage. Participants all resided in Medicaid-expansion states that went to Trump in the 2024 election (including Arizona, Kentucky, Nevada, North Carolina, Missouri, Ohio, Oklahoma, and Pennsylvania). Groups were stratified by voting history, with three groups being conducted among those who had voted for President Trump in the 2024 election and two groups being conducted among those who had voted for Vice President Harris.

For each group, participants were chosen based on the following criteria: must be between 18 and 65 years of age, must self-identify as currently being enrolled in Medicaid, and must have voted in the most previous election for Trump or Harris. All participants had used their Medicaid coverage in some way in the past 12-months (e.g., doctor visit, filling a prescription). Participants included a mix of adults by gender, race/ethnicity, age, length of time enrolled on Medicaid, health status, disability status, and work and family status.

KFF worked with PerryUndem Research/Communication to conduct the focus groups. The screener questionnaire and discussion guides were developed by researchers at KFF in consultation with PerryUndem. Groups lasted between 90 minutes and two hours and were conducted in English with 6-8 participants each. Groups were audio and video recorded with participants’ permission. Each participant was given an incentive of $150 after participating. Individuals who were able to participate in our groups needed to have two hours of time, a quiet space, a computer, and internet. These characteristics alone may not fully represent many Medicaid enrollees, so findings may not be generalizable to the entire Medicaid population.

Characteristics of Focus Group Participants

How Many Uninsured Are in the Coverage Gap and How Many Could be Eligible if All States Adopted the Medicaid Expansion?

Authors: Sammy Cervantes, Clea Bell, Jennifer Tolbert, and Anthony Damico
Published: Feb 25, 2025

Issue Brief

Since implementation of the Affordable Care Act’s (ACA) Medicaid expansion in 2014, all but ten states have adopted the expansion to cover adults on Medicaid with income up to 138% of the federal poverty level (FPL) helping to drive the uninsured rate among the population under age 65 to record low levels. While the number of people who fall into the coverage gap has declined as more states implemented the expansion, 1.4 million uninsured individuals remain in the coverage gap in the ten states that have not expanded Medicaid.

Limited Medicaid eligibility in non-expansion states leaves many adults without children, people of color, and those with disabilities without coverage. Most adults in the coverage gap are in working families, though about one in six have a disability that requires ongoing health care and may limit their ability to work. Using data from 2023, this brief estimates the number and characteristics of uninsured individuals in these ten non-expansion states who could gain coverage if Medicaid expansion were adopted.

The future of the Affordable Care Act’s (ACA) Medicaid expansion is uncertain as Congress considers significant changes to Medicaid financing. Some proposals under consideration would eliminate the enhanced 90 percent federal matching rate for the expansion population or make other changes to federal payments to states for this group. Any cuts in federal funding for expansion enrollees would likely lead a number of states to rollback coverage for this population and would increase the number of people who fall into the coverage gap and become uninsured.

How many people are in the coverage gap?

The coverage gap exists in states that have not adopted the ACA’s Medicaid expansion. Under the ACA, Medicaid was expanded to cover adults ages 19 to 64 with incomes up to 138% FPL (or $21,597 for an individual in 2025). This income threshold applied to parents and to adults without dependent children who were previously not eligible for Medicaid. While the ACA intended to require all states to implement the Medicaid expansion, a 2012 Supreme Court ruling made expansion optional for states. As of February 2025, 41 states, including the District of Columbia, have adopted Medicaid expansion (Figure 1).

Status of State Action on the Medicaid Expansion Decision, as of February 2025

In the ten states that have not adopted Medicaid expansion, an estimated 1.4 million individuals remain in the coverage gap. These adults have incomes above their state’s Medicaid eligibility threshold but below the poverty level, making them ineligible for ACA Marketplace subsidies (Figure 2). Because the Medicaid expansion was expected to be mandatory for states, the ACA did not provide eligibility for subsidies in the Marketplaces for people below poverty.

Medicaid eligibility remains limited in states that have not expanded their programs. All non-expansion states, except Wisconsin (which provides coverage through a waiver), do not offer Medicaid to adults without children, regardless of their income (Figure 3). As a result, 80% of the individuals in the coverage group are adults without dependent children.

Medicaid Income Eligibility Limits for Adults in States That Have Not Implemented the Medicaid Expansion

Uninsured rates in states without Medicaid expansion are nearly twice as high as those in expansion states (14.1% vs. 7.6%). People without insurance have more difficulty accessing care, with almost one in four uninsured adults in 2023 not receiving needed medical treatment due to cost. Uninsured individuals are also less likely than those with insurance to receive preventive care and treatment for major health conditions and chronic diseases.

What are the characteristics of people in the coverage gap?

Nearly three-quarters of adults in the coverage gap live in just three Southern states. Texas accounts for 42% of individuals in the coverage gap, the highest share of any state, while Florida and Georgia account for an additional 19% and 14%, respectively (Figure 4). Overall, 97% of those in the coverage gap live in the South. Of the 16 states in the region, seven have not adopted Medicaid expansion.

Distribution of Adults Ages 19-64 in the Coverage Gap by State, 2023

Nearly six in ten people in the coverage gap are in a family with a worker and over four in ten are working themselves. (Figure 5). However, these individuals work in low-wage jobs that leave them below the poverty level and often work for employers that do not offer affordable job-based insurance. Over half (53%) of workers in the coverage gap are in the service, retail, and construction industries, with common jobs including cashiers, cooks, servers, construction laborers, housekeepers, retail salespeople, and janitors. In non-expansion states, even part-time work can make parents ineligible for Medicaid.

Work Status of Adults Ages 19-64 in the Coverage Gap, 2023

About one in six (16%) people in the coverage gap have a functional disability. The share of people in the coverage gap with disabilities increases with age (Figure 6). Over a quarter (26%) of adults ages 55 to 64 in the coverage gap have a disability compared to one in ten adults under age 25. Adults ages 55 to 64, who often face increased health care needs, account for 17% of all people in the coverage gap. Despite these challenges, many of these individuals do not qualify for Medicaid through a disability pathway, leaving them uninsured. Research shows that uninsured people in this age group may delay necessary care until they become eligible for Medicare at 65.

Interactive DataWrapper Embed

People of color make up a disproportionate share of individuals in the coverage gap. Six in ten people in the coverage gap are people of color, a higher share than among adults in non-expansion states (49%) and nationwide (44%) (Figure 7). These differences in part explain persisting disparities in health insurance coverage across racial and ethnic groups.

Race/Ethnicity of Adults Ages 19-64 in the Coverage Gap Compared to Other Adults, 2023

How many uninsured could gain coverage if all states adopted the Medicaid expansion?

Approximately 2.7 million uninsured adults would gain coverage if all states adopted Medicaid expansion. This includes 1.4 million people in the coverage gap and 1.3 million uninsured adults with incomes between 100% and 138% of the FPL, most of whom are eligible for Marketplace coverage but not enrolled (Figure 7 and Table 1). While many of these adults above poverty qualify for zero-premium Marketplace plans, Medicaid generally provides more comprehensive benefits with lower out-of-pocket costs. The potential number of people who could gain coverage through expansion varies by state.

Uninsured Adults Ages 19-64 in Non-Expansion States Who Would Become Eligible for Medicaid if Their States Expanded, 2023

Uninsured Adults Ages 19-64 in Non-Expansion States Who Would Become Eligible for Medicaid if Their States Expanded, by Current Eligibility for Coverage

Sammy Cervantes, Clea Bell, and Jennifer Tolbert are with KFF. Anthony Damico is an independent consultant.

Appendix Tables

Characteristics of Adults Ages 19-64 in the Coverage Gap

Uninsured People Ages 19-64 Who Would Be Eligible if States Expanded Medicaid, by Race and Ethnicity

Uninsured People Ages 19-64 Who Would Be Eligible if States Expanded Medicaid, by Age

Uninsured People Ages 19-64 Who Would Become Eligible if States Expanded Medicaid, by Parents and Childless Adults

Uninsured People Ages 19-64 Who Would Become Eligible if States Expanded Medicaid, by Income

Uninsured People Ages 19-64 Who Would Be Eligible if States Expanded Medicaid, by Family Work Status

Data And Methods

This analysis uses data from the 2023 American Community Survey (ACS). The ACS provides socioeconomic and demographic information for the United States population and specific subpopulations. Importantly, the ACS provides detailed data on families and households, which we use to determine income and household composition for ACA eligibility purposes.

Medicaid and Marketplaces have different rules about household composition and income for eligibility. The ACS questionnaire captures the relationship between each household resident and one household reference person, but not necessarily each individual to all others. Therefore, prior to estimating eligibility, we implement a series of logical rules based on each person’s relationship to that household reference person in order to estimate the person-to-person relationships of all individuals within a respondent household to one another. We then assess income eligibility for both Medicaid and Marketplace subsidies by grouping individuals into household insurance units (HIUs) and calculate HIU income using the rules for each program. For more detail on how we construct person-to-person relationships, aggregate Medicaid and Marketplace households, and then count income, see the detailed Technical Appendix A.

Undocumented immigrants are ineligible for federally-funded Medicaid and Marketplace coverage. Since ACS data do not directly indicate whether an immigrant is lawfully present, we draw on the methods underlying the 2013 analysis by the State Health Access Data Assistance Center (SHADAC) and the recommendations made by Van Hook et. Al.1 ,2  This approach uses the 2023 KFF/LA Times Survey of Immigrants to develop a model that predicts immigration status for each person in the sample.  We apply the model to ACS, controlling to state-level estimates of total undocumented population as well as the undocumented population in the labor force from the Pew Research Center. For more detail on the immigration imputation used in this analysis, see the Technical Appendix B.

Individuals in tax-filing units with access to an affordable offer of Employer-Sponsored Insurance (ESI) are still potentially MAGI-eligible for Medicaid coverage, but they are ineligible for advance premium tax credits in the Health Insurance Exchanges. Since ACS data do not designate policyholders of employment-based coverage nor indicate whether workers hold an offer of ESI, we developed a model that predicts both the policyholder and the offer of ESI based on the Current Population Survey (CPS). Additionally, for families with a Marketplace eligibility level below 250% FPL, we assume any reported worker offer does not meet affordability requirements and therefore does not disqualify the family from Tax Credit eligibility on the Exchanges. For more detail on the offer imputation used in this analysis, see the Technical Appendix C.

As of January 2014, Medicaid financial eligibility for most adults ages 19-64 is based on modified adjusted gross income (MAGI). To determine whether each individual is eligible for Medicaid, we use each state’s reported eligibility levels as of May 2024, updated to reflect 2025 Federal Poverty Levels. Some adults ages 19-64 with incomes above MAGI levels may be eligible for Medicaid through other pathways; however, we only assess eligibility through the MAGI pathway.3 

An individual’s income is likely to fluctuate throughout the year, impacting his or her eligibility for Medicaid. Our estimates are based on annual income and thus represent a snapshot of the number of people in the coverage gap at a given point in time. Over the course of the year, a larger number of people are likely to move in and out of the coverage gap as their income fluctuates.

Starting with our estimates of ACA eligibility in 2017, we transferred our core modeling approach from relying on the Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) to the American Community Survey (ACS). ACS includes a 1% sample of the US population and allows for precise state-level estimates as well as longer trend analyses. Since our methodology excludes a small number of individuals whose poverty status could not be determined, our ACS-based population totals appear slightly below CPS-based totals and some ACS population totals published by the Census Bureau. This difference is in large part attributable to students who reside in college dormitories. Comparing the two survey designs, CPS counts more of these individuals in the household of their parent(s) than ACS does.

Technical Appendix A: Household Construction

In KFF’s estimates of eligibility for ACA coverage, income eligibility for both Medicaid and Marketplace subsidies is assessed by grouping people into “health insurance units” (HIUs) and calculating HIU income according to Medicaid and Marketplace program rules. HIUs group people according to how they are counted for eligibility for health insurance, versus grouping people according to who they live with (e.g., “households”) or are related to (e.g., “families”). HIU construction is an important step in assessing income as a share of the federal poverty line (FPL) because it impacts whose income is counted (and thus the total income for the unit) and how many people share that income (and thus the corresponding FPL to use for comparison, since FPL varies by family size). Our HIUs are designed to match ACA eligibility rules for both Medicaid and Marketplaces. Below we describe how we construct HIUs for this analysis. The programming code, written using the statistical computing package R v.4.4.1, is available upon request for people interested in replicating this approach for their own analysis.

Person to Person Relationships

We construct spousal and parent-to-child person-to-person linkage variables within each household of the microdata. The American Community Survey (ACS) includes only the relationship of each person in a household to one central reference person. Using the household reference person’s known relationships to all other individuals within each household, we iterate through every pair of individuals present in each household to determine probable person to person links for possible mother, father, and spousal pairs. Our approach to determining probable family interrelationship linkages closely follows the construction documented by IPUMS-USA with the notable exception of unmarried partner relationships.4  We intentionally diverge from IPUMS-USA because the presence of an unmarried partner relationship does not impact federal program eligibility. Among individuals designated as married with a spouse present in the household, our constructed spousal pointer matches the IPUMS SPLOC variable 99% of the time in the 2013 microdata. Our construction of mother and father pointers match the IPUMS MOMLOC, POPLOC, MOMLOC2, and POPLOC2 variables for more than 99% of all person-records.

Family Aggregation

Separate from person-to-person linkage variables, we assemble individual records into family units reproducing the Census Bureau’s Family Poverty Ratio (POVPIP) variable. Although the Census Bureau does not include a unique family identifier on the ACS microdata, we approximate the groupings used to generate the ACS income-to-poverty ratio variable with the following steps:

  • Both non-relatives of the household reference person (RELP of 11-17) and all individuals in non-family households (HHT of 4-7) are categorized as single-person families.
  • Married couples and other family households without subfamilies (PSF of 0) are categorized into single-family households.
  • Married couples and other family households with subfamilies (PSF of 1) are categorized based on their subfamily number (SFN).

This family identifier is used in estimating family-wide statistics, such as the percent of the uninsured Americans in a family below poverty or the count of Medicaid-enrollees with one or more workers in their family. This family aggregation matches the groupings used to determine the income-to-poverty ratio variable, and estimates of health insurance presented by family poverty categories align with Census Bureau publications based on the ACS.5  Since many family members obtain health coverage separately from one another (for example, an elderly parent cohabiting with their working-age child might hold Medicare coverage and Employer Sponsored Insurance, respectively), descriptive statistics focused on family attributes rely on this family identifier but Medicaid and Marketplace eligibility determinations do not.

Overview of KFF-HIUS

We construct two different HIUs for everyone in the sample: a Medicaid HIU and a Marketplace HIU. We use two HIUs because the rules for counting families and income differ between the two programs. For example, in Medicaid, children with unmarried parents have both parents’ income counted toward their income, whereas under Marketplace rules, only the income of the parent who claims the child on his/her taxes counts. In another example, certain tax dependents (e.g., a parent) are treated differently for Medicaid eligibility than they are for Marketplace eligibility. To account for these rules, we developed an algorithm for sorting people into HIUs. We construct HIUs and HIU incomes separately for each person in a household and take into account the family relationships and income of the other people in the person’s household. People in the same household or in the same family may not have the same HIU composition or income for determining either Medicaid eligibility or eligibility for tax credits.

In simplest terms, the HIU algorithm sorts people into tax filing units. For all people in the data set, the algorithm assesses whether they are likely to be a tax filer themselves and, if so, who they are likely to claim or, if not, who is likely to claim them. It also captures whether someone is neither a tax filer nor claimed as a dependent by someone else. Importantly, the HIU construction considers all relationships for each person within the household. This step is particularly important in correctly classifying people in non-nuclear families (e.g., households with more than one generation, with unmarried partners, or with relatives outside the nuclear family such as an aunt or uncle), which may contain either one or multiple tax filing units.

In counting income for both Medicaid and Marketplace HIUs, we use modified adjusted gross income (MAGI), corresponding to the ACA rules. MAGI differs from total income in that some sources of income (e.g., cash assistance payments from TANF or SSI) do not count toward MAGI. We calculate HIU income as a share of poverty using the Health and Human Services Poverty Guidelines.6 

For a small number of people, Medicaid HIU income as a share of poverty does not match Marketplace HIU income as a share of poverty due to the different rules between the programs. This analysis first calculates Medicaid HIU and classifies anyone who meets Medicaid eligibility into that category (including most individuals below 138% FPL in the Medicaid expansion states). We then calculate Marketplace HIU; anyone meeting subsidy eligibility is grouped into that category (above Medicaid and also above 100% FPL up to 400% FPL for most individuals). This approach follows the eligibility rules in the ACA, which specify that people are eligible for tax credits only if they are ineligible for Medicaid.

Steps in Calculating KFF-HIUS

Before we group people into HIUs, we first calculate annual MAGI for each respondent. We compare each person’s income to IRS filing requirements for being a tax filer7  and for being a qualifying relative claimed by someone else.8 

We then group people into HIUs. We begin this process by grouping everyone within a household who is related into “cohabitating families.” Cohabitating families include all family relations; they also include unmarried cohabitating partners and relatives of each cohabitating partner.

Within each cohabitating family, we assess whether any individual is eligible to claim any other individual as a tax dependent. People are eligible to claim others as tax dependents if their income is above the IRS filing threshold for a head of household or, if married, for a married couple. People are eligible to be claimed by others if (a) they are a child (under age 19 or, for tax credits, 23 if a full-time student), and someone else in the cohabitating family has at least twice their income, or (b) they are below the limit to be a tax filer, have income below the qualifying relative limit, and someone else in the cohabitating family has at least twice their income. Within each cohabitating family, we assess who is likely to claim whom, using the assumptions that:

  • People who are claimed by others are more likely to be claimed by close relatives (e.g., a parent) than by others (e.g., a grandparent).
  • Married couples (who file) file jointly
  • If more than one person in a cohabitating family is eligible to claim others within that cohabitating family, the wealthiest person claims the eligible dependents.

Once we determine who within the cohabitating family is likely to claim each other, we know the HIU size and are able to apply income rules for the HIU. We apply Medicaid and Marketplace rules for whose income counts in calculating Medicaid HIUs and Marketplace HIUs, respectively.9  People who are filers but are not eligible to claim someone else or to be claimed by someone else are an HIU of 1. People who are not filers and are not claimed by filers have their HIU size and income counted according to Medicaid non-filer rules.10 

Inflation Factors

In order to determine ACA eligibility during calendar year 2023, we compared tax filing unit income against the most current premiums available, for open enrollment 2025.11  We relied on the Bureau of Labor Statistics Employment Cost Index (ECI), Private Wages and Salaries to inflate the income of each HIU by approximately 8.0% to align 2023 incomes to 2025 premiums.12  Since most state Medicaid eligibility determinations through the MAGI pathway are calculated as a percent of HHS Poverty Guidelines for that year and not a fixed dollar amount, inflation was not necessary to assess the Medicaid eligibility of individuals.

After inflating 2023 tax filing unit incomes to match 2025 premiums, we similarly inflated 2023 IRS thresholds for both filing requirements13  and for qualifying relative tests14  by the same factor so that these thresholds aligned with the inflated income amounts.

Limitations

As with any analysis, there are some limitations to our approach due to the level of detail that we can obtain from available survey data. Key limitations to bear in mind include:

  • We currently are not able to appropriately group anyone who lives outside the household with a household that claims them as a tax dependent. For example, we are not able to connect students living away from home or children with a non-custodial parent with the people who may be claiming them (and whose income should count to their HIU). We are also not able to determine married people who file separately.
  • To group people into tax filing units, we have to make assumptions about how people are likely to file their taxes. We assume that tax filers claim qualifying relatives they are able to claim. We make this assumption based on the fact that Medicaid and Marketplace eligibility rules are determined not by who is actually claimed on the tax return but by who is allowed to be claimed. However, people may sort themselves into different tax filing units than we estimate.

Technical Appendix B: Immigration Status Imputation

To impute documentation status, we draw on the methods underlying the 2013 analysis by the State Health Access Data Assistance Center (SHADAC) and the recommendations made by Van Hook et. al..15 ,16  This approach uses the 2023 KFF/LA Times Survey of Immigrants to develop a model that predicts immigration status for each person in the sample.17  We apply the model to a second data source, controlling to state-level estimates of total undocumented population as well as the undocumented population in the labor force from the Pew Research Center.18  Below we describe how we developed the regression model and applied it to the American Community Survey (ACS). We also describe how the model may be applied to other data sets. The programming code, written using the statistical computing package R v.4.4.1, is available upon request for people interested in replicating this approach for their own analysis.

Data Sources

We used the 2023 KFF/LA Times Survey of Immigrants l data to build the regression model. The 2023 Survey of Immigrants dataset contains questions on citizenship and legal status at the person level. The KFF/LA Time Survey of Immigrants19  is a probability-based survey exploring the immigrant experience in the U.S. and draws on three different sampling frames including an address-based sample (ABS), a random digit dial (RDD) sample of pre-paid cell phone numbers, and callbacks to an RDD sample in which the individual did not speak English or Spanish. The survey includes interviews with 3,358 immigrant adults and was offered in ten different languages.

The regression model is designed to be applied to other datasets in order to impute legal immigration status in surveys that do not ask about migration status. The code mentioned above includes programming to apply the model to either the Survey of Income and Program Participation (SIPP) Core files, ACS, or the Current Population Survey (CPS). Because the SIPP Core file contains different survey questions and variable specifications from the ACS and CPS, we create unique regression models to apply the model to each dataset. For the analysis underlying this brief and other KFF estimates of eligibility for ACA coverage, we apply the regression model to the 2013 ACS and then each subsequent year of the ACS.

Due to underreporting of legal immigration status in survey datasets, in imputing immigration status we control to state and national-level estimates of the total undocumented population and also the undocumented population in the labor force from the Pew Research Center. Pew reports these estimates for all states and the District of Columbia.20 

Construction of Regression Model

We use the 2023 Survey of Immigrants to create a binomial, dependent variable that identifies a respondent as a potential unauthorized immigrant. The dependent variable is constructed based on the following factors:

  1. Respondent was not a United States (US) citizen,
  2. Respondent did not have permanent resident status or a valid work or student visa, , and
  3. Respondent does not have other indicators that imply legal status.21 

We use the following independent variables to predict unauthorized immigrant status:

  1. Year of US entry,
  2. Job industry classification,
  3. State of residence,
  4. Household Income,
  5. Ownership or rental of residence,
  6. Number of occupants in the household (< or >= six occupants),
  7. Whether all household occupants are related,
  8. Health insurance coverage status,
  9. Sex, and
  10. Ethnicity.

The regression model was sub-populated to remove respondents who could not be considered unauthorized. People who could not be considered unauthorized include people who are US citizens or have other indicators that imply legal status.

Imputing Unauthorized Immigrants in Other Datasets

We use the Pew estimates as targets for the total number of unauthorized immigrants that the imputation generates. We first apply this strategy to the 2013 ACS, which contains health insurance information prior to the ACA’s coverage expansions. We stratify the targets by state and the District of Columbia and by participation in the labor force. We impute immigration status within each of these 102 strata.22 

To generate the imputed immigration status variable, we first calculated the probability that each person in the dataset was unauthorized based on the 2023 Survey of Immigrants regression model. Next, we isolated the dataset to each individual stratum described above. Within each stratum, we sampled the data using the probability of being unauthorized for each person. After sampling, we summed the person weights until reaching the Pew population estimate for each stratum. The records that fell within the Pew population estimate were considered to be unauthorized immigrants. We repeated the process of sampling using the probability of being unauthorized and subsequently summing the person weights to reach Pew targets five times, creating five different unauthorized variables per record. These five imputed authorization status variables were then incorporated into a standard multiple imputation algorithm, closely matching the imputed variable analysis techniques used by the Centers for Disease Control and Prevention for the National Health Interview Survey.23 

We used this first pass on the ACS 2013 to inform our sampling targets for the latest available microdata (ACS 2023). Looking at the results of our undocumented imputation on the ACS 2013, we calculated the share of undocumented immigrants lacking health insurance within each of those 102 strata prior to the ACA’s coverage expansions and transferred that information into a new dimension of sampling strata for the ACS 2023. We split each of the 102 sampling strata used on the pre-ACA ACS 2013 into uninsured versus insured categories, resulting in 204 sampling strata for subsequent years. We then repeated our imputation on the ACS 2023 with the newly-divided strata, allowing for a small decline in the undocumented uninsured rate based off of the percent drop in the uninsured rate among citizens.24 

To easily apply the regression model to other data sets, we created a function that applies this approach to a chosen data set. The function first loads the dataset of choice, then standardizes the data to match the independent variables from the 2023 Survey of Immigrants regression model, and finally applies the multiple imputation to generate a variable for legal immigration status.

Technical Appendix C: Imputation Of Offer Of Employer-sponsored Insurance

An integral part of determining ACA eligibility is assessing whether workers without employer-sponsored insurance (ESI) hold an offer through their workplace that they decline to take up. In most cases, an affordable offer of ESI disqualifies members of the tax filing unit of the worker from receiving subsidized coverage on the ACA Health Insurance Marketplace. The American Community Survey (ACS) does not ask about employer offers of ESI; however, the Current Population Survey Annual Social and Economic Supplement (CPS-ASEC) includes questions about whether each worker received an offer of ESI from his or her employer at the time of interview. We use the CPS-ASEC offer of ESI variable to inform a regression-based multiple imputation of whether each tax filing unit constructed in the ACS had at least one offer at work, and also assess affordability for the employee and, separately, for any potential dependents within the unit. Since the health insurance coverage variables available in the CPS-ASEC 2024 capture sources of coverage at any point during calendar year 2023 (versus at the time of survey, as with the offer rate variable), a subset of sampled individuals had a change in their employer-based coverage status across the two distinct time periods.25  Therefore, among workers who potentially experienced a shift in offer status across the two time periods, we recoded or imputed offer rates in 2023 using the offer status in 2024. After constructing this revised offer variable for workers in CPS, we aggregated the results at the tax filing unit level to create a prediction model to apply to the ACS. Below we describe these recodes and imputation. The programming code, written using the statistical computing package R v.4.4.1, is available upon request for people interested in replicating this approach for their own analysis.

Recoding and Imputing Offer Rate Data in the CPS

As a first step in our analysis, we divided CPS-ASEC survey respondents into five distinct groups:

  1. All individuals who did not work during 2023 and also did not hold an offer of ESI in 2024 were assumed not to have an offer in 2023.
  2. All individuals who reported being an ESI policyholder (that is, anyone reporting having taken-up their offer of ESI) during 2023 and also reported holding an offer of ESI during early 2024 were assumed to have an offer in 2023.
  3. All workers in 2023 who held their own ESI policies during 2023 but then reported not holding an offer during 2024 were re-coded as holding an offer of ESI in 2023.
  4. All non-workers during 2023 who reported holding an offer during 2024 were re-coded as not holding an offer of ESI in 2023.
  5. Some workers during 2023 who did not report being ESI policyholders but did report holding an offer of ESI during early 2024 were imputed to not have an offer of ESI during 2023.

For many groups, including those in groups (1) and (2) listed above, the offer status did not change across the two time periods. In contrast, we recoded offer status for people in groups (3) and (4): every non-offered worker in group (3), which includes people who held ESI policies in their own name in 2023, were considered to have an offer of ESI in 2023, and offered workers in group (4), which includes people who did not work themselves in 2023, were considered to not have their offer of ESI in 2023. Last, we implemented a probability-based random sample imputation of offers of ESI for people in group (5), described in more detail below. Only a subset of the group was re-coded from holding an offer in 2024 to not holding an offer in 2023.The number of workers selected from this population was equal to the population size of (3) subtracted by the population size of (4), thereby assuming an unchanging offer rate for the total worker population across the period.

Imputing Offer Rates for CPS Respondents with Ambiguous Offer Rate Status

The CPS-ASEC worker-level regression model was designed to be applied to a single dataset where ESI offer status is known at one point in time but not another. The code mentioned above includes programming to apply the model to the Current Population Survey (CPS-ASEC) (for years 2014 on). For the analysis underlying KFF’s current estimates of ACA eligibility, we apply the regression model to workers in the 2024 CPS-ASEC.

We use the 2024 point-in-time worker offer variable provided by the US Census Bureau26  to create a binomial, dependent variable that identifies a respondent as a recipient of an offer of employer-sponsored insurance at his or her workplace in early 2024. The dependent variable was constructed at the worker-level based on individuals not holding their own ESI policy at time of interview and also reporting an ESI offer or eligibility to be covered that was then voluntarily declined.

We use the following independent variables to predict offer status in 2023 among workers not covered by their own ESI during both 2023 and early 2024 but potentially holding an offer of ESI in 2023:

  • Any public coverage,
  • Any nongroup coverage,
  • Worker earnings among all jobs,
  • Full-time versus part-time status,
  • Age of worker,
  • Work within the construction industry.

The regression model was sub-populated to remove respondents already covered by their own ESI and also to remove non-workers. Since this imputation does not account for the affordability of the offer or whether it meets the minimum value test, we included an assumption that workers in tax filing units with a MAGI below 250% FPL do not hold affordable offers of ESI and therefore might be eligible to purchase subsidized coverage on the Exchanges.27 

As mentioned above, we assume an unchanging offer rate for the total worker population across the two time periods. We determined the needed size of the population to impute by subtracting the population of (4) from the population of (3) to ensure an equivalent number of offers were gained and lost. This left only workers who reported holding an offer of ESI during early 2024, since (3) represented a larger count of workers than (4). We then calculated the probability that each worker in the dataset was offered ESI during calendar year 2023 based on our 2024 CPS-ASEC regression model. Next, we selected workers within the potential population (5) using the sampling probabilities resultant from our model.

Construction and Application of ACS Regression Model

For the analysis underlying KFF estimates of ACA eligibility, we construct a prediction model of having an offer of ESI using the 2024 CPS-ASEC and then apply this regression to tax filing units in the 2023 ACS to estimate who has an ESI offer in ACS.

We aggregate the worker offer variables constructed the 2024 CPS-ASEC as described above to create a binomial, dependent variable that identifies each tax filing unit as either holding or not holding an affordable offer of employer-sponsored insurance.

We use the following independent variables to predict offer status among tax filing units:

  • Any senior citizen in the household,
  • Oldest member of the tax-filing unit,
  • Any member of the tax-filing unit has employer-sponsored insurance coverage,
  • Any member of the tax-filing unit has nongroup coverage,
  • Any uninsured individuals in the tax filing unit,
  • Share of adults working full-time and part-time, and
  • Highest worker earnings.

Since the imputation of documentation status (discussed in Technical Appendix B) required a multiply-imputed approach, this secondary imputation and subsequent worker sampling was only conducted once per implicate, keeping the number of ACS implicates to five.

Endnotes

  1. State Health Access Data Assistance Center. 2013. “State Estimates of the Low-income Uninsured Not Eligible for the ACA Medicaid Expansion.” Issue Brief #35. Minneapolis, MN: University of Minnesota. Available at: http://www.rwjf.org/content/dam/farm/reports/issue_briefs/2013/rwjf404825. ↩︎
  2. Van Hook, J., Bachmeier, J., Coffman, D., and Harel, O. 2015. “Can We Spin Straw into Gold? An Evaluation of Immigrant Legal Status Imputation Approaches” Demography. 52(1):329-54. ↩︎
  3. Non-MAGI pathways for nonelderly adults include disability-related pathways, such as SSI beneficiary; Qualified Severely Impaired Individuals; Working Disabled; and Medically Needy. We are unable to assess disability status in the ACS sufficiently to model eligibility under these pathways. However, previous research indicates high current participation rates among individuals with disabilities (largely due to the automatic link between SSI and Medicaid in most states, see Kenney GM, V Lynch, J Haley, and M Huntress. “Variation in Medicaid Eligibility and Participation among Adults: Implications for the Affordable Care Act.” Inquiry. 49:231-53 (Fall 2012)), indicating that there may be a small number of eligible uninsured individuals in this group. Further, many of these pathways (with the exception of SSI, which automatically links an individual to Medicaid in most states) are optional for states, and eligibility in states not implementing the ACA expansion is limited. ↩︎
  4. Steven Ruggles, Sarah Flood, Ronald Goeken, Josiah Grover, Erin Meyer, Jose Pacas, and Matthew Sobek. IPUMS USA: Version 8.0 [dataset]. Minneapolis, MN: IPUMS, 2018. https://doi.org/10.18128/D010.V8.0 For a detailed description of how IPUMS constructs family interrelationships variables, see https://usa.ipums.org/usa/chapter5/chapter5.shtml ↩︎
  5. According to the Public Use Microdata Sample (PUMS) documentation, “Estimates generated with PUMS microdata will be slightly different from the pretabulated estimates for the same characteristics published on data.census.gov. These differences are due to the fact that the PUMS files include only about two-thirds of the cases that were used to produce estimates on data.census.gov, as well as additional PUMS edits.” ↩︎
  6. Medicaid eligibility in 2024 is based on 2025 poverty guidelines, available at: U.S. Department of Health and Human Services, Office of The Assistant Secretary for Planning and Evaluation, Poverty Guidelines. https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines. Tax credit eligibility in 2025 is based on 2024 poverty guidelines, available at: U.S. Department of Health and Human Services, Office of The Assistant Secretary for Planning and Evaluation, 2024 Poverty Guidelines https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines/prior-hhs-poverty-guidelines-federal-register-references. ↩︎
  7. See Internal Revenue Service, Publication 501, Table 1.2023: Filing Requirements Chart for Most Taxpayers. Available at: https://www.irs.gov/publications/p501#en_US_2023_publink1000270109. ↩︎
  8. See Internal Revenue Service, Publication 501, Qualifying Relative. Available at: https://www.irs.gov/publications/p501#en_US_2023_publink1000220939. ↩︎
  9. A detailed explanation of Medicaid and Marketplace income counting rules can be found in Center on Budget and Policy Priorities webinar available at: http://www.healthreformbeyondthebasics.org/wp-content/uploads/2013/08/Income-Definitions-Webinar-Aug-28.pdf ↩︎
  10. A detailed explanation of Medicaid and Marketplace HIU size calculations can be found in the Center on Budget and Policy Priorities webinar available at http://www.healthreformbeyondthebasics.org/wp-content/uploads/2013/08/Household-Definitions-Webinar-7Aug13.pdf ↩︎
  11. This is the same underlying data as the 2024 Health Insurance Marketplace Calculator. Available at: https://modern.kff.org/interactive/subsidy-calculator/ ↩︎
  12. See Congressional Budget Office, Economic Projections. Available at: https://www.cbo.gov/system/files/2024-06/51135-2024-06-Economic-Projections.xlsx. ↩︎
  13. See Internal Revenue Service, Publication 501, Table 1.2023: Filing Requirements Chart for Most Taxpayers. Available at: https://www.irs.gov/publications/p501#en_US_2023_publink1000270109. ↩︎
  14. See Internal Revenue Service, Publication 501, Qualifying Relative. Available at: https://www.irs.gov/publications/p501#en_US_2023_publink1000220939. ↩︎
  15. State Health Access Data Assistance Center. 2013. “State Estimates of the Low-income Uninsured Not Eligible for the ACA Medicaid Expansion.” Issue Brief #35. Minneapolis, MN: University of Minnesota. Available at: http://www.rwjf.org/content/dam/farm/reports/issue_briefs/2013/rwjf404825. ↩︎
  16. Van Hook, J., Bachmeier, J., Coffman, D., and Harel, O. 2015. “Can We Spin Straw into Gold? An Evaluation of Immigrant Legal Status Imputation Approaches” Demography. 52(1):329-54. ↩︎
  17. This data source is a change from previous KFF analyses, which used microdata from the 2008 Panel of the Survey of Income and Program Participation (SIPP) ↩︎
  18. This data source is a change from previous KFF analyses, which used estimates from the Department of Homeland Security. ↩︎
  19. More information about the survey methods is available at https://modern.kff.org/report-section/understanding-the-u-s-immigrant-experience-the-2023-kff-la-times-survey-of-immigrants-methodology/ ↩︎
  20. Pew updates these estimates periodically. We use the most recent estimates available at the time of our analysis, and in some cases incorporate estimates received from correspondence with researchers at Pew prior to their publication – however we do not release these numbers ourselves. We draw on Pew directly for all published data and interpolate years missing from their trend. Our analysis uses the year applicable to the year for the data sets to which we apply the regression model. The most recent estimates as of the time of our analysis were: J Passel, J Krogstad. What we know about unauthorized immigrants living in the U.S.. (Pew Research Center), July 2024. Available at: https://www.pewresearch.org/short-reads/2024/07/22/what-we-know-about-unauthorized-immigrants-living-in-the-us/. ↩︎
  21. Indicators that imply legal status include: (i) respondent entered the US prior to 2000, (ii) respondent is enrolled in Medicare or military health insurance, or (iii) respondent reports Medicaid coverage but resides in a state that does not offer coverage to the undocumented population beyond CHIP’s From-Conception-to-End-of-Pregnancy (FCEP) option. ↩︎
  22. For more information, see SHADAC 2013, footnote 1. The table created for this function contains estimates of the undocumented across 2013-2023. ↩︎
  23. For more detail, see documentation available at: National Health Interview Survey. 2023 Imputed Income Files. Available at: https://www.cdc.gov/nchs/nhis/documentation/2023-nhis.html. ↩︎
  24. As an example of this calculation, we found that approximately 66% of undocumented uninsured individuals did not have health coverage in 2013. We allow the undocumented rate to drop slightly after 2013. We base the percent drop in the uninsured rate among the undocumented on the drop for citizens (half the scale of the drop for citizens) each year until 2023, resulting in the final undocumented uninsured rate of 51% in calendar year 2023. Prior to implementing this new sampling dimension, we found unrealistic drops in the uninsured rate of the undocumented population that we largely attributed to our prediction model’s inability to discern this group from legally-present non-citizens, many of whom are eligible for assistance under the ACA’s coverage expansions. Although a few states have implemented programs that allow for coverage of the undocumented population, these programs are state-funded and relatively small in scale compared to the nationwide coverage expansions accompanying the ACA. ↩︎
  25. For example, anyone who did not work during 2023 who then held an offer of ESI in early 2024 would appear incongruous in our CPS-based eligibility model.  In the other direction, workers covered by health insurance through their own employer in 2023 who lost their offer of ESI during the early months of 2024 (perhaps due to a job change) would also appear incongruous due to the discrepancy across the two time periods. ↩︎
  26. Available at: https://www.census.gov/data/datasets/time-series/demo/health-insurance/cps-asec-research-files.html. For more detail about these microdata, see: J. Abramowitz, B. O’Hara.  New Estimates of Offer and Take-up of Employer-Sponsored Insurance (US Census Bureau), 2016.  Available at: https://www.census.gov/library/working-papers/2016/demo/Abramowitz-2016.html. ↩︎
  27. For an explanation of affordability, see: KFF. Employer Responsibility Under the Affordable Care Act. February 2024. Available at: https://modern.kff.org/infographic/employer-responsibility-under-the-affordable-care-act/. ↩︎

Challenges with Effective Price Transparency Analyses

Published: Feb 25, 2025

Promoting price transparency in health care is a policy approach with bi-partisan support in Congress and the public at large, and the first Trump administration finalized regulations that require group health plans and insurers to make detailed data with all their in-network payment rates available with the objective that such transparency would increase price competition and ultimately drive down health care costs.

This report documents how the vast troves of data reported in pursuit of those goals include misleading and unlikely prices, inconsistencies, and other oddities that pose significant challenges for researchers, industry and others seeking to make sense of the data.

The transparency regulations set out in significant detail the methods that payers should follow in reporting their rates, generating huge amounts of publicly available data since reporting began in 2022. The analysis, which relies on the extensive collection of this data downloaded and maintained by Turquoise Health, includes examples about each of the challenges identified and how they complicate efforts to use the data for its intended purposes.

The analysis is available through the Peterson-KFF Health System Tracker, an information hub dedicated to monitoring and assessing the performance of the U.S. health system.

What Does the Federal Government Spend on Health Care?

Published: Feb 24, 2025

Congressional Republicans and President Trump are in search of trillions of dollars in cuts to mandatory federal spending that could help offset the cost of extending expiring tax cuts. With spending on health programs accounting for a substantial share of federal spending, those programs are an obvious target to achieve overall spending goals in current budget reconciliation discussions. Medicaid has been the primary focus for federal spending cuts, but cuts to Medicare and the Affordable Care Act have also been floated. Cuts to discretionary spending, which includes funding for several federal health agencies, veterans health care, and global health, are not part of the reconciliation process, but the Trump Administration has taken unilateral actions to reduce this spending. Proposed cuts to federal spending on health programs and services have trade-offs and could increase the number of people without insurance; reduce access to health care; increase consumer costs for health care; and reduce payments for hospitals, nursing homes, and other providers. The effects would be felt by people of all incomes but would likely be concentrated among people with low incomes.

To provide context for ongoing discussions about federal spending, this brief analyzes current support from the federal government for health programs and services, including both spending and tax subsidies (that is, forgone tax revenues from provisions that reduce tax liability for people and businesses with qualifying health-related spending). The data come from the Office of Management and Budget, U.S. Treasury Department, and the Congressional Budget Office (see Methods).

Key takeaways

  • The federal government spent $1.9 trillion on health care programs and services in fiscal year (FY) 2024, 27% of all federal outlays in that year, and collectively the largest category of federal spending.
  • Forgone tax revenues to the federal government resulting from tax subsidies for employer sponsored insurance coverage (ESI) and a portion of the Affordable Care Act (ACA) premium tax credits together totaled $398 billion in FY 2024.
  • Over 80% of all federal support for health programs and services, including spending and tax subsidies, goes to programs that provide or subsidize health insurance coverage, with 36% going to Medicare, 25% going to Medicaid and CHIP, 17% going to employment-based health coverage, and 5% going to subsidies for Affordable Care Act (ACA) coverage.
  • Discretionary spending is a relatively small component of overall federal support for health programs and services. Over half (52% or $128 billion) of discretionary health spending paid for hospital and medical care for veterans. Discretionary health spending also provides funding for agencies such as the National Institutes of Health (NIH) (19% of discretionary health spending) and the Centers for Disease Control and Prevention (CDC) (4%), as well as global health (4%).

How does the federal budget support health programs and services?

Over one out of every four dollars in federal spending was used to pay for health programs and services in FY 2024 (Figure 1). The next largest categories are Social Security (21%), national defense (13%), and interest payments on the federal debt (13%). Combined, these four categories account for nearly three quarters of all federal spending.

Federal Spending on Health Programs and Services Accounted for More Than One Fourth of Net Federal Outlays in FY 2024

Seventy percent of government support for health programs and services comes from mandatory spending, with tax subsidies accounting for 19% and discretionary spending accounting for 11% (Figure 2). There are three ways that the federal government provides support for health programs and services: mandatory spending (outlays), discretionary spending (outlays), and tax subsidies (forgone tax revenue, also called tax expenditures or tax preferences).

  • Mandatory spending, also known as “direct spending,” is governed by regular legislative action in Congress and not determined through the annual appropriations or “spending” bills. Mandatory health spending includes nearly all Medicare spending ($839 billion), federal spending on Medicaid and CHIP ($584 billion in federal funding), and the refundable portion of the health insurance premium tax credit for coverage through the ACA Marketplaces ($111 billion in federal funding) (Appendix Table 1). (This does not include ACA premium tax credits that offset income taxes individuals owe to the federal government.)
  • Discretionary spending is funded through annual appropriations bills. The largest component of discretionary health spending ($128 billion) is for veterans’ health care. Discretionary health spending also provides funding for agencies such as the National Institutes of Health (NIH) and the Centers for Disease Control and Prevention (CDC), as well as global health, or international health assistance, much of which is channeled through the Department of State and U.S. Agency for International Development (USAID). (For a more detailed discussion of federal funding for global health, including the potential impact of the Trump administration’s executive order pausing foreign aid, see KFF briefs, 10 Things to Know About U.S. Funding for Global Health, How Much Global Health Funding Goes Through USAID?, and The Status of President Trump’s Pause of Foreign Aid and Implications for PEPFAR and other Global Health Programs) (Appendix Table 2).
  • Tax subsidies allow businesses and individuals to reduce the amount of taxes they must pay based on the amount of money they spend on qualifying health programs and services. Most of the foregone revenue to the federal government from health-related tax subsidies (85%) comes from the exclusion of employer contributions for health insurance, which totaled $384 billion in 2024. Other notable tax subsidies that support health care include the non-refundable portion of the tax credit for coverage through the ACA Marketplaces ($14 billion), contributions to medical and health savings accounts ($14 billion), deductions for medical expenses ($13 billion), and deductions for charitable contributions to health institutions ($10 billion) (Appendix Table 3).

What is the budget reconciliation process?

Congress will likely use reconciliation to make reductions in mandatory spending to help offset some of the cost of extending the expiring tax cuts. Budget reconciliation is a special legislative process used to make changes to taxes and mandatory spending that allows the Senate to pass legislation with only 50 votes rather than the customary 60 votes. There are limits to what kinds of legislation can be passed through budget reconciliation, and it can only be used for policies that make non-incidental changes to mandatory spending or revenues. Congress initially enacted the 2017 Tax Cuts and Jobs Act through reconciliation, and it is expected that the reconciliation process will be used again for an extension. That law made a set of broad but temporary tax cuts, which expire at varying years starting in 2025. The cost of extending these tax cuts has been estimated at $4.0 trillion between FY 2025 and FY 2034.

Reconciliation was originally intended to reduce budget deficits, and there are several unique rules governing the reconciliation process. The budget reconciliation process begins with the adoption of a budget resolution that is passed in both houses of Congress but not signed by the President. The budget resolution provides each Congressional committee with the dollar amount of budgetary changes that must be achieved over a specified budget “window,” which is usually either a five-year or ten-year period. These budget changes can either increase the deficit or decrease it. Budget resolutions often suggest specific policies to achieve budgetary changes, but those suggestions are not binding or enforceable. Committees of jurisdiction must meet the dollar targets in the budget resolution but have discretion as to how to meet the targets. A bill with all the details developed by committees would have to pass both houses of Congress and be signed by the president to become law.

To maintain privileged status in the Senate, a reconciliation bill cannot:

  • Increase the deficit in years after the budget period (though it can increase the deficit during the budget period),
  • Change Social Security spending or revenues,
  • Be “extraneous” to the budget, meaning the reconciliation bill cannot include policies that have “merely incidental” fiscal impacts, or
  • Make changes to discretionary spending.

How might a budget reconciliation package affect health insurance coverage?

There are four primary sources of health insurance coverage in the U.S.: Medicare, Medicaid, ACA Marketplaces, and employer sponsored coverage. Each of these sources of coverage could be subject to changes in a reconciliation bill. Of these four programs, Medicare accounts for the largest share (36%) of total federal support for health programs and services (including both spending and tax expenditures), followed by Medicaid and CHIP (25%), employer coverage (17%), and ACA Marketplaces (5%). Reconciliation could be used to reduce federal financial support for each of these programs because they are all funded through mandatory spending and/or financed with tax subsidies.

Existing discussions surrounding a reconciliation package have focused on reductions in mandatory federal health spending, the largest components of which are Medicare (52% of mandatory health spending) and Medicaid (36%) (Figure 3, Appendix Table 1). A 50-page menu of options for policies that could be included in a reconciliation package is largely focused on reducing federal spending to finance an extension of the 2017 tax cuts. Medicaid is the largest source of proposed cuts, but there are also options to reduce spending on Medicare and the ACA subsidies.

Spending on Medicare and Medicaid Accounts for the Majority of Mandatory Federal Spending on Health Programs and Services

Medicaid: Medicaid covers 83 million low-income people, accounts for one fifth of health care spending in the U.S., and covers 61% of long-term care costs. Despite most adults having favorable views of Medicaid and only 13% thinking Medicaid cuts are a top priority, federal Medicaid funding ($584 billion in 2024, see Appendix Table 1) is at significant risk under Republican proposals to reduce federal spending by nearly one third over ten years. Changes to Medicaid under consideration include imposing a per capita cap on federal spending, reducing the federal government’s share of costs for the ACA expansion group, limiting provider taxes states use to help pay for their share of Medicaid costs, and imposing work requirements. Such policy changes would fundamentally alter how Medicaid financing works and large federal spending reductions would force states to make tough choices whether to raise new revenue, restrict the number of people covered, cover fewer benefits, or cut payment rates for physicians, hospitals, nursing homes, and other providers. Millions or even tens of millions of people could lose Medicaid coverage depending on how the policy was structured.

Medicare: Medicare provides health insurance coverage to nearly 68 million older adults and younger people with long-term disabilities and accounted for just over half (52% or $839 billion) of mandatory spending on federal health programs and services in FY 2024. Despite President Trump’s campaign promises not to cut Medicare, Republican lawmakers have put several Medicare savings proposals on the table in recent budget reconciliation talks, including implementing site-neutral payment policies, making changes to Medicare payment of uncompensated care, bad debt, and other hospital payments, and reforming Medicare payment for graduate medical education, among other changes. Altogether, these specific proposals could yield around $500 billion in 10-year savings, and would have the greatest impact on hospitals, with indirect effects on patients, depending on how hospitals responded to payment reductions.

ACA Marketplaces: Healthcare.gov and State-Based Marketplaces cover over 24 million people in 2025 (about 7% of the US population), most of whom are low-income. Federal support totaled $125 billion, including direct spending and tax subsidies in FY 2024, when about 19 million people received a subsidy.

ACA Marketplace subsidies are provided through the tax system, with most subsidized enrollees receiving an advanced payment of the premium tax credit, which they reconcile when they file their taxes the following year. Because incomes can be very volatile for ACA Marketplace enrollees (many of whom work shifts, are self-employed, or gig workers), predicting one’s income a year in advance can be difficult. The ACA currently limits how much an enrollee must pay back in the tax credit if their income is below four times the poverty level. However, a Ways and Means Committee document proposes to remove repayment limits for people who receive excess tax credits.

Since 2021, enhanced premium tax credits have lowered premium payments across all subsidized enrollees and made middle income people (over four times poverty) newly eligible for subsidies. These enhanced tax credits were originally passed as COVID relief and extended by the Inflation Reduction Act of 2022, but they are set to expire at the end of 2025. If the enhanced tax credits are not renewed by Congress, out-of-pocket premium payments for enrollees are expected to increase by over 75%, though this amount will vary by income and location. The cost to renew the subsidies would be $335 billion over ten years, according to CBO projections.

What health programs and services are discretionary, and subject to the annual appropriations process?

Only 11% of federal support for health care programs and services is discretionary spending, and over half of that amount (52%) pays for veterans’ health care (Figure 4, Appendix Table 2). In FY 2024, $128 billion in federal funding supported care for more than 7 million veterans. The next largest source of discretionary spending is the National Institutes of Health, which received $46 billion in 2024 (19% of discretionary spending). Smaller sources of federal discretionary spending include public health and social services emergency funding ($11 billion; 4%), global health ($10 billion; 4%), and the Centers for Disease Control and Prevention ($9 billion; 4%). (Global health totals presented here are outlays, which represent actual cash flows, and therefore do not match those presented in other KFF resources, such as the U.S. Global Health Budget Tracker, which highlight the budget authority totals as provided by Congress in annual appropriations and include some other funding components that are counted elsewhere in this analysis.)

Spending on Veterans' Hospital and Medical Care is the Largest Portion of Federal Discretionary Health Spending

Making changes to discretionary health spending through the appropriations process requires 60 votes in the Senate, meaning changes would require Democratic support, unless President Trump takes unilateral actions to reduce federal spending. Congress is supposed to pass appropriations bills by June 30 each year that provide funding for discretionary programs from October 1 through September 31 of the following year (the federal fiscal year). However, in most years, Congress does not pass the appropriations bills on time, and instead uses continuing resolutions to prevent lapses in federal funding for discretionary programs. The current continuing resolution funds the federal government through March 14, 2025. Extending funding for discretionary programs beyond that date will require a majority vote in the House and 60 votes in the Senate.

In the early weeks of President Trump’s second term in office, the administration has taken unilateral action to reduce federal funding, such as by laying off federal employees and issuing executive orders to freeze federal funding in various programs. Declining to spend appropriated funds is also known as “impoundment.” In 1974, Congress enacted the Impoundment Control Act in response to President Nixon’s attempts to refuse to spend Congressionally-appropriated funds. During the campaign, President Trump promised to “restore Impoundment Power,” and the administration characterizes the Impoundment Control Act as unconstitutional. The Trump administration also indicates that the current funding freezes are “programmatic delays” rather than deferrals. It is currently unclear the extent to which President Trump will be able to significantly reduce federal spending through these and other unilateral actions.

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

Components of Federal Support for Health Programs and Services in FY 2024

Components of Federal Support for Health Programs and Services in FY 2024

Components of Federal Support for Health Programs and Services in FY 2024

Methods

This analysis is based on data on federal outlays from the Office of Management and Budget (OMB) FY 2025 President’s Budget, tax expenditures from the U.S. Department of the Treasury, and the tax exclusion for employment-based coverage from the Congressional Budget Office (CBO). Specifically, we use FY 2024 data on federal outlays from Table 25-1. Budget Authority and Outlays by Budget Function, Category, and Program, FY 2024 data on tax expenditures from Table 1. Estimates of Total Income Tax Expenditures for Fiscal Years 2024-2034, and FY 2024 data on the tax exclusion for employment-based coverage from CBO, Health Insurance and Its Federal Subsidies: CBO and JCT’s June 2024 Baseline Projections.

The federal budget groups spending into roughly 20 categories called ‘budget functions,’ which are groups of activities or programs that fulfill specific purposes, such as defense, transportation, and health. This analysis focuses on non-defense health spending, which is defined to include spending in the following categories within four budget functions:

150: International Affairs:

151: International development and humanitarian assistance: Global health

550: Health:

551: Health care services

552: Health research and training

554: Consumer and occupational health and safety

570: Medicare

700: Veterans Benefits and Services

703: Hospital and medical care for veterans

Each category includes both mandatory and discretionary spending, where applicable.

Spending totals in this analysis are outlays, which represent actual cash flows, rather than budget authority, which represents the amounts authorized by Congress for new obligations by federal agencies. Global health outlay totals presented here do not match those presented in other KFF resources, such as the U.S. Global Health Budget Tracker, which highlight the budget authority totals as provided by Congress in annual appropriations and include some other funding components that are counted elsewhere in this analysis. As noted above, in this analysis ‘global health’ is a category of spending within budget function 151: International development and assistance, which accounts for the majority of global health funding. Additional global health funding at NIH and CDC is included under budget function 550: Health.

This analysis does not include spending by the Department of Health and Human Services that falls outside of the ‘Health’ or ‘Medicare’ budget functions, which consists mainly of spending on social services and income security for children and families through the Administration for Community Living (ACL) and Administration for Children and Families (ACF), which falls within budget functions 500 (Education, Training, Employment, and Social Services) and 600 (Income Security). A separate KFF brief, How Does the Department of Health and Human Services (HHS) Impact Health and Health Care?, has a more complete description of these operating divisions within HHS.

UNFPA Funding and Kemp-Kasten: An Explainer

Published: Feb 21, 2025

Editorial Note: Originally published in April 2017, this resource is updated as needed, most recently on Feb. 21, 2025, to reflect the latest developments. 

Key Points

  • On January 24, 2025, President Trump directed the Secretary of State to “take all necessary actions to ensure U.S. taxpayer dollars do not fund organizations or programs that support or participate in the management of a program of coercive abortion or involuntary sterilization.” This provision of law, known as the Kemp-Kasten amendment, was first enacted by Congress in 1985 and has been included in appropriations language annually.
  • Kemp-Kasten has often been used, as determined by presidents along party lines, to withhold U.S. funding to the United Nations Population Fund (UNFPA, the lead U.N. agency focused on global population and reproductive health).
  • The U.S. government provided $194.4 million in FY 2023 for UNFPA – $30.6 million in core support and $163.8 million more for other project activities – making it the largest government contributor in that year.
  • While framed broadly, Kemp-Kasten was originally intended to restrict funding to UNFPA specifically, after concerns arose about China’s population control policies and UNFPA’s work in China; to date, it has only been applied to UNFPA. Evaluations by the U.S. government and others have found no evidence that UNFPA directly engages in coercive abortion or involuntary sterilization in China, and more generally, UNFPA does not promote abortion as a method of family planning or fund abortion services.
  • Kemp-Kasten has been used to withhold funding from UNFPA in 19 of the past 40 fiscal years. Under current law, any U.S. funding withheld from UNFPA is to be made available to other family planning, maternal health, and reproductive health activities.

What is the Kemp-Kasten Amendment?

The Kemp-Kasten amendment, first enacted in 1985, is a provision of U.S. law that states that no U.S. funds may be made available to “any organization or program which, as determined by the [p]resident of the United States, supports or participates in the management of a program of coercive abortion or involuntary sterilization.”1  It was the congressional response to a Reagan administration decision in 1984 to temporarily withhold some funding from UNFPA and to begin conditioning its funding on assurances that the agency did not engage in or provide funding for abortion or coercive family planning. This policy change was made after concerns arose about whether UNFPA supported China’s coercive population policies.2  It was announced by the Reagan administration at the 2nd International Conference on Population in 1984, in conjunction with the “Mexico City Policy.”3  The Mexico City Policy required foreign NGOs to certify that they would not “perform or actively promote abortion as a method of family planning” with non-U.S. funds as a condition of receiving U.S. family planning assistance; the Trump administration recently expanded this restriction to include all U.S. global health assistance (see the KFF explainer on the policy).

Box 1: The Original Language Regarding UNFPA in the U.S. Policy Statement at the 2nd International Conference on Population, 1984

“With regard to the United Nations Fund for Population Activities [UNFPA], the US will insist that no part of its contribution be used for abortion. The US will also call for concrete assurances that the UNFPA is not engaged in, or does not provide funding for, abortion or coercive family planning programs; if such assurances are not forthcoming, the US will redirect the amount of its contribution to other, non-UNFPA, family planning programs.”4 

What U.S. funding does Kemp-Kasten apply to?

Kemp-Kasten applies to all funds appropriated under the State and Foreign Operations appropriations act as well as any unobligated balances from prior appropriations. This includes all funding provided to the State Department and USAID, which, in turn, includes the vast majority of U.S. global health funding.5 

When has Kemp-Kasten been in effect?

The Kemp-Kasten amendment has been in effect for 40 years. First enacted in 1985,6  its language has been included in the State and Foreign Operations appropriations act every fiscal year since then. (Although the provision is present in current law, language similar to Kemp-Kasten was also included in President Trump’s presidential memorandum reinstating the Mexico City Policy on January 24, 2025.7 ) While Congress has kept the amendment in place annually, it remains up to the president to determine whether or not to invoke Kemp-Kasten as a reason to withhold funding from an organization (see below).8 

Though Kemp-Kasten technically could apply to funding provided to any organization or program (including U.S. NGOs, non-U.S. NGOs, multilateral organizations, and foreign governments), the U.S. government has issued determinations about only one organization, UNFPA, thus far. The U.S. played a key role in the launch of UNFPA in 1969 and was, until 1985, the largest government donor to the agency.9  However, the U.S. has withheld funding from UNFPA due to presidential determinations that it violated Kemp-Kasten as often as it has provided funding since 1985 (in 19 of the past 40 fiscal years, to date), and in some years, funding was also withheld from UNFPA based on other provisions of the law, such as the dollar-for-dollar withholding requirement10  (see below). These determinations have been made along party lines with only one exception – the first year of President George W. Bush’s administration (see Figure 1 and Table 1).

How much funding does the U.S. provide to UNFPA?

In 2023, the U.S. was the largest government donor to UNFPA, having contributed 11% of all contributions (funding amounts for 2024 are not yet available). Total funding from the U.S. in FY 2023 for UNFPA was $194.4 million – $30.6 million in core support as well as $163.8 million in non-core support (see Box 2).11  See Figure 1 and Table 1 for historical funding data.

Box 2: Core and Non-Core Support to UNFPA

According to UNFPA, contributions to core resources allow the agency to support any activity, while contributions to non-core resources – funds earmarked for a specific purpose – may only be used for the stated project or activity.12  Governments provide contributions toward UNFPA core and non-core resources on a voluntary basis, since UNFPA does not assess a required contribution from governments.

U.S. Funding for UNFPA, FY 1985 - FY 2024
Kemp-Kasten and U.S. Funding for UNFPA (Core Support Only), FY 1985–FY 2025

How is a determination about Kemp-Kasten made?

By law, it is up to the president to determine whether any organization or program should be ineligible for funding due to a violation of the Kemp-Kasten amendment (in practice, this authority has generally been delegated to the State Department). In most recent years, legislative language has also specified that this determination must be: 1) made no later than six months after the date of enactment of the law that includes the provision and 2) accompanied by the evidence and criteria used to make the determination.13 

Most recently, on January 24, 2025 at the beginning of his second term, President Trump directed the Secretary of State to begin the process of Kemp-Kasten determination by taking “all necessary steps.” These determinations are usually made after the annual appropriations process is completed. For example, in 2017, the Trump administration’s determination was made on March 30, 2017, at the six month mark after the passage of the FY 2017 continuing resolution appropriations bill and was accompanied by a two-page justification memorandum.14 

Has there ever been evidence that UNFPA supports coercive abortion or involuntary sterilizations?

To date, there has not been evidence that UNFPA supports coercive abortion or involuntary sterilizations. Several evaluations by the U.S. government (including one by an assessment team sent to China by the State Department in 2002) as well as other groups, such as the British All-Party Parliamentary Group on Population, Development, and Reproductive Health (in 2002) and the Interfaith Delegation (in 2003), have found no evidence of direct engagement by UNFPA in such activities in China or elsewhere.15  In addition, UNFPA does not promote abortion as a method of family planning or fund abortion services.16  In years when a determination has been made that UNFPA violated Kemp-Kasten, the U.S. government has stated that the determination was based on its conclusion that UNFPA support to or partnering with the Chinese government for other population and reproductive health activities was sufficient grounds for invoking the amendment to withhold funding. In the March 30, 2017, determination by the Trump administration, for example, the justification memorandum stated that: “While there is no evidence that UNFPA directly engages in coercive abortions or involuntary sterilizations in China, the agency continues to partner with the NHFPC [China’s National Health and Family Planning Commission] on family planning, and thus can be found to support, or participate in the management of China’s coercive policies for purposes of the Kemp-Kasten amendment.”

What other legislative requirements apply to U.S. funding for UNFPA?

In addition to Kemp-Kasten, there are several other provisions of law that Congress has enacted in recent years to set conditions on U.S. funding for the agency.17  These provisions:

  • require UNFPA to keep U.S. funding to the agency in a separate account, not to be commingled with other funds;
  • prohibit UNFPA from funding abortion;
  • prohibit UNFPA from using any U.S. funds for their programming in China;
  • reduce the U.S. contribution to UNFPA by one dollar for every dollar that UNFPA spends on its programming in China (“dollar-for-dollar withholding”); and
  • in some years, state that not more than half of funding designated for the U.S. contribution to UNFPA is to be released before a particular date, which varies by fiscal year (this provision is not currently in effect).

What happens to funding that is withheld from UNFPA?

For several years, including FY 2017, FY 2018, FY 2019, and FY 2020, Congress has required that funding withheld from UNFPA be reallocated to USAID’s family planning, maternal, and reproductive health activities.18  The enactment of this provision first affected reallocation of FY 2002 funds.19  It is now typically included in the State and Foreign Operations appropriations act each year.20 

  1. U.S. Congress, FY 2017 Consolidated Appropriations Act (P.L. 115-31), May 5, 2017; KFF, The U.S. Government and International Family Planning & Reproductive Health: Statutory Requirements and Policies, fact sheet. ↩︎
  2. Congressional Research Service (CRS), The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010; “Policy Statement of the United States of America at the United Nations International Conference on Population (Second Session), Mexico City, Mexico, August 6-14, 1984,” undated. ↩︎
  3. “Policy Statement of the United States of America at the United Nations International Conference on Population (Second Session), Mexico City, Mexico, August 6-14, 1984,” undated; United Nations Division of Economic and Social Affairs/Population Division, “United Nations Conferences on Population,” webpage, undated, http://www.un.org/en/development/desa/population/events/conference/index.shtml. ↩︎
  4. “Policy Statement of the United States of America at the United Nations International Conference on Population (Second Session), Mexico City, Mexico, August 6-14, 1984,” undated. ↩︎
  5. KFF, The U.S. Congress and Global Health: A Primer; and KFF U.S. Global Health Budget Tracker, available at: https://modern.kff.org/interactive/u-s-global-health-budget-tracker/. ↩︎
  6. Via FY 1985 supplemental appropriations, per CRS, The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010. ↩︎
  7. Specifically, in this memorandum, President Trump stated, “I further direct the Secretary of State to take all necessary actions, to the extent permitted by law, to ensure that U.S. taxpayer dollars do not fund organizations or programs that support or participate in the management of a program of coercive abortion or involuntary sterilization.” ↩︎
  8. However, after UNFPA ended its program in China in 1997 but then began a new program there in 1999, this resulted in Congress withholding funding from UNFPA that year. ↩︎
  9. CRS, The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010; PAI, Why the United States Should Maintain Funding for UNFPA, May 2015. ↩︎
  10. In FY 1999, Congress prohibited UNFPA funding in response to the initiation of a new UNFPA program in China (this was unrelated to Kemp-Kasten), and in some other years when the U.S. made a contribution to UNFPA, UNFPA’s China program meant some UNFPA funding was withheld under the “dollar-for-dollar withholding” provision. ↩︎
  11. KFF analysis of data from: Congressional Appropriations Bills, Press Releases, and Conference Reports; Federal Agency Budget and Congressional Justification documents and Operating Plans; ForeignAssistance.gov; Office of Management and Budget, personal communication; UNFPA, personal communication; Biden Administration, “Memorandum on Protecting Women’s Health at Home and Abroad,” presidential actions, Jan. 28, 2021, Biden White House Archives, https://bidenwhitehouse.archives.gov/briefing-room/presidential-actions/2021/01/28/memorandum-on-protecting-womens-health-at-home-and-abroad/. ↩︎
  12. UNFPA, Annual Report 2013, 2014. ↩︎
  13. Typically included in annual State and Foreign Operations appropriations since FY 2008, including in FY 2017 under the terms of the continuing resolution. CRS, The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010; KFF analysis of appropriations bills. ↩︎
  14. State Department: Letter to Bob Corker, Chairman, Committee on Foreign Relations, from Joseph E Macmanus, Bureau of Legislative Affairs, State Department, dated April 3, 2017, and accompanying “Determination Regarding the ‘Kemp-Kasten Amendment,’” dated March 30, 2017, and “Memorandum of Justification for the Determination Regarding the “Kemp-Kasten Amendment,” undated. Available online (follows the article) at: https://www.buzzfeednews.com/article/jinamoore/the-us-wont-give-any-more-money-to-the-un-population-fund. ↩︎
  15. CRS, The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010. ↩︎
  16. UNFPA, “Frequently Asked Questions,” webpage, updated January 2025, http://www.unfpa.org/frequently-asked-questions#abortion. ↩︎
  17. KFF, The U.S. Government and International Family Planning & Reproductive Health: Statutory Requirements and Policies, fact sheet. ↩︎
  18. KFF analysis of Congressional Appropriations Bills. ↩︎
  19. “Although such reallocation began in practice in FY 2002, it was first authorized by Congress in legislation beginning in FY 2004 with reference to FY 2002 and FY 2003 funds,” per KFF, The U.S. Government and International Family Planning & Reproductive Health: Statutory Requirements and Policies, fact sheet. ↩︎
  20. The activities to which Congress directs reallocated funds varies by fiscal year; in FY 2003, for example, reallocated funding supported assistance to vulnerable children and victims of trafficking in persons. CRS, The U.N. Population Fund: Background and the U.S. Funding Debate, RL32703, July 2010. ↩︎

5 Key Facts About Medicaid Coverage for Adults with Mental Illness

Published: Feb 21, 2025

Options under consideration in Congress to significantly reduce Medicaid spending could have major implications for adults who live with mental illness. Nationwide, an estimated 52 million nonelderly adults live with mental illness, and Medicaid covers nearly one in three (29%) of them, or about 15 million adults. Changes to Medicaid under consideration include imposing a per capita cap on federal spending, reducing the federal government’s share of costs for the ACA expansion group, and imposing work requirements. Such policy changes would fundamentally alter how Medicaid financing works and large federal spending reductions would force states to make tough choices on whether to raise new revenue, restrict the number of people covered, cover fewer benefits, or cut payment rates for physicians, hospitals, and other providers. For people with mental illness, losing Medicaid coverage would reduce access to mental health treatment and other health care, which could have negative implications for their mental and physical health.

1. More than one in three adult Medicaid enrollees have a mental illness.

More than one in three nonelderly adults enrolled in Medicaid have a mental illness (35%), including 10% with a serious mental illness. These rates are higher than the rates among adults with private insurance or no coverage (Figure 1). Serious mental illness generally involves more severe symptoms and may include other neurological factors, both of which can complicate treatment and impact daily functioning. Data in Figure 1 come from the National Survey on Drug Use and Health (NSDUH), which categorizes respondents as having a probable mild, moderate, or serious mental illness through a combination of mental health scales and indicators of functional impairment. Generally, adults with severe symptoms and with greater impairments in daily functioning would meet the threshold for serious mental illness, while “any mental illness” includes adults who meet criteria for mild, moderate or serious mental illness (see methods). Among Medicaid adults, any mental illness is most prevalent among White adults, rural or small metro residents, those aged 26-34, and females (Appendix Table 1). Rates of any mental illness among adult Medicaid enrollees vary widely by state, from 22% in New Jersey to 51% in Iowa. Similarly, the percentage of adult Medicaid enrollees with a serious mental illness ranges from 4% in Mississippi to 22% in Wyoming and Missouri (Appendix Table 2).

One in Three Nonelderly Adult Medicaid Enrollees have a Mental Illness, Higher than Other Coverage Groups

2. Mental health treatment rates for Medicaid-enrolled adults are higher or similar to those with private insurance.

Nonelderly adults in Medicaid receive mental health treatment at rates that are higher or similar to those with private insurance, and much more often than those who are uninsured. In 2023, 59% of adult Medicaid enrollees with any mental illness received treatment – somewhat above the rate for privately insured adults (55%) and far higher than for those who are uninsured (37%). Across all coverage types, treatment rates increased with the illness severity, with adults diagnosed with serious mental illness reporting the highest rates of treatment. Although adults with mild mental illness covered by Medicaid or private insurance report similar treatment rates, Medicaid-enrolled adults with moderate and serious mental illnesses report higher treatment rates than those with private coverage. In every category, adults with either Medicaid or private insurance receive treatment at much higher rates than those who lack health coverage. These data indicate only that care was accessed, not the adequacy or quality of that care. In an effort to increase access to care, many state Medicaid programs have expanded covered services and adopted policies to address workforce shortages.

Mental Health Treatment Rates for Medicaid-Enrolled Adults are Higher Than or Similar to Those with Private Insurance

3. Adults enrolled in Medicaid experience a range of mental health diagnoses.

Anxiety and depressive disorders are the most frequently diagnosed mental illnesses among nonelderly Medicaid-enrolled adults (over 5 million diagnoses for anxiety alone). Serious mental illnesses – such as bipolar disorder and schizophrenia or other psychotic disorders – were diagnosed in over 2.3 million adult Medicaid enrollees (Figure 3). Many people experience overlapping mental health conditions (e.g., a person with depression may also have anxiety). Estimates of the number of people with specific types of mental illnesses come from Medicaid administrative data (i.e. claims data) which only capture diagnoses for people with a mental illness diagnosis recorded in their medical claims. This is not a measure of overall prevalence of mental illness because not everyone is screened, and diagnoses are not always recorded. Prevalence rates estimated through surveys are generally higher than the prevalence rates observed in claims data.

Medicaid-Enrolled Adults Experience a Range of Mental Health Diagnoses

4. Medicaid enrollees with mental illness have higher rates of chronic conditions.

Medicaid enrollees diagnosed with mental illness have higher rates of chronic conditions and substance use disorder compared to those without a mental health diagnosis. Approximately two-thirds of adult enrollees with any mental illness have at least one other chronic condition – twice the rate of those without a diagnosed mental illness (Figure 4). Enrollees with serious mental illness have the highest rates of chronic conditions with 76% having at least one chronic condition. Chronic conditions are those that last at least a year and require ongoing medical care or limit daily activities, such as heart disease, diabetes, cancer, and mental illnesses. The most common chronic condition among Medicaid enrollees with mental illness is substance use disorder. These often overlap with mental illness, potentially due to shared risk factors. One in four enrollees diagnosed with any mental illness also have a diagnosed substance use disorder, and about 40% of those diagnosed with SMI do, compared to 5% of enrollees without a mental health diagnosis (Figure 4).

Medicaid Enrollees Diagnosed with Mental Illness Experience a Greater Chronic Disease Burden

5. Average annual spending for enrollees with a mental illness is twice that of those without.

Average annual Medicaid spending per nonelderly adult enrollee is twice as high for those with any mental health diagnosis—about $14,000 per year—compared to roughly $7,000 for those without a mental health diagnosis. Spending is highest among adults diagnosed with a serious mental illness, at approximately $21,000 per enrollee per year—three times higher than the annual spending for those without a mental illness (Figure 5). Medicaid spending for adults with any mental illness accounts for one-third of the total Medicaid spending for non-elderly adults enrolled only in Medicaid. Higher rates of other chronic diseases among adults with mental illness may contribute to higher spending (Figure 3).

Average Annual Spending for Medicaid Enrollees with Any Mental Illness is Twice That of Medicaid Enrollees Without a Mental Illness

Appendix Tables

Mental Illness Among Nonelderly Medicaid-Enrolled Adults

Methods

Medicaid Claims Data: This analysis used the 2021 T-MSIS Research Identifiable Files including the inpatient (IP), long-term care (LT), other services (OT), and pharmacy (RX) claims files merged with the demographic-eligibility (DE) files from the Chronic Condition Warehouse (CCW).

Identifying Mental Health, Serious Mental Health and Substance Use Disorder Diagnoses in Medicaid Claims Data:Mental illness, serious mental illness (SMI) and substance use disorder (SUD) diagnoses were identified using an algorithm adapted from the Behavioral Health Service Algorithm (BHSA) reference codes provided by The Urban Institute. The BHSA identifies these conditions with ICD-10 diagnosis codes, procedure codes, service codes, and National Drug Codes (NDCs). “Any mental illness” is a comprehensive category that includes the diagnosis of anxiety, depression, post-traumatic stress (PTSD) or other trauma disorders, personality disorders, bipolar disorders, schizophrenia/psychotic disorders, and/or other mental illnesses not fitting within these categories. “Any SMI” is a subcategory of any mental illness that specifies mental disorders that result in severe functional impairment. This analysis follows other literature and includes bipolar disorders and schizophrenia/psychotic disorders in the definition of SMI. “Any SUD” is a comprehensive category that includes alcohol, opioids, marijuana, inhalants, sedatives, hallucinogens, psychostimulants, and/or substances labeled as “other” or “unspecified” in claims data.

See: Victoria Lynch, Lisa Clemans-Cope, Doug Wissoker, and Paul Johnson. Behavioral Health Services Algorithm. Version 4. Washington, DC: Urban Institute, 2024.

Defining Chronic Conditions in Medicaid Claims Data: This analysis used the CCW algorithm for identifying chronic conditions (updated in 2020). This analysis also included in its definition of chronic conditions substance use disorder, obesity, HIV, hepatitis C, and intellectual and developmental disabilities (ASPE definition). Mental illness was not included the in the count of chronic conditions in Figure 4 since the analysis is stratified by mental illness.

Enrollee Inclusion Criteria in Medicaid Claims Data:Enrollees were included if they were ages 18-64, had full Medicaid or CHIP coverage for at least one month, and were not dually eligible for Medicare.

State Inclusion Criteria in Medicaid Claims Data: To assess the usability of states’ data, the analysis examined quality assessments from the DQ Atlas for OT claims volume and OT managed care encounters and compared the share of adults diagnosed with any mental illness (AMI) in each states’ Medicaid data to estimates for adult Medicaid enrollees from the 2021-2022 restricted National Survey on Drug Use and Health (NSDUH). States were excluded if: (1) they received a “High Concern/ Unusable” rating on the relevant DQ Atlas assessment measure, and (2) their Medicaid estimate of AMI differed from the NSDUH estimate by more than 15.1 percentage points (the 75th percentile of all differences).

If at least 70% of a state’s Medicaid enrollees were covered by either managed care or by fee for service, only the corresponding DQ Atlas indicator was considered (i.e. managed care encounters volume or claims volume (FFS)). For states with more mixed delivery systems, both sets of indicators were considered; in these cases; a “High Concern/Unusable” rating on either measure, combined with a difference above 15.1 percentage points, led to exclusion. Based on these criteria, Mississippi was excluded, leaving 49 states and D.C. in the analysis.

National Survey on Drug Use and Health. The National Survey on Drug Use and Health (NSDUH) is a nationally representative survey that, among other topics, collects information about symptoms of mental illness and related functional impairments from adult respondents. It uses a combination of mental health scales, suicidality symptoms, functional impairments and other indicators to classify respondents as having a probable mild, moderate, or serious mental illness. Thresholds for each category were developed by NSUDH through methodological work comparing survey responses with psychiatric clinical interviews using the DSM-IV diagnostic criteria. Adults whose responses meet or exceed the highest severity threshold are categorized as having a probable serious mental illness, which reflects greater functional impairment due to more severe mental illness symptoms.

National data reported in this analysis uses the most recent NSDUH data (2023) to identify Medicaid enrollees ages 18-64 who meet DSM-IV criteria for any or serious mental illness. State-level data reported in Appendix Table 2 is drawn from the most recent state-level data publicly available (2021-2022 restricted NSDUH files).

NSDUH generally reports higher rates of mental illness than claims-based data, as it includes people who have not received a formal diagnosis. Still, NSDUH may underestimate prevalence because it excludes people without an address (such as those who are unhoused, institutionalized, or incarcerated)–groups likely to have higher rates of mental illness.

The Outlook for PEPFAR in 2025 and Beyond

Published: Feb 20, 2025

PEPFAR, the U.S. global HIV/AIDS program, is – for the first time in its two-decade history – facing significant challenges that could impede its ability to fulfill its mission. One of President Trump’s first actions was to issue an executive order to re-evaluate and realign foreign aid, requiring a 90-day pause in foreign aid funding while a review was undertaken, as well as dismissal of thousands of USAID staff and contractors, and other changes, effectively halting most programs, including for PEPFAR, around the world. Despite PEPFAR receiving a limited waiver to continue some services and the courts stepping in to provide temporary relief, services are still disrupted. In addition, PEPFAR’s current short-term authorization expires on March 25, 2025, about a month before the 90-day aid review is scheduled to be completed, and Congress is increasingly looking for program reforms and ultimately scale down.

The current situation, coupled with uncertainty about future changes, poses potential risks to health outcomes for a program that has been shown to have saved millions of lives and helped to build health infrastructure in sub-Saharan Africa; already, analyses have estimated that the foreign aid freeze and ensuing service disruptions have led to increases in HIV-related deaths and new HIV infections. This policy brief provides an overview of these recent events and ongoing challenges facing the program.

Background

Despite almost two decades of strong, bipartisan support and demonstrated success and impact, PEPFAR began facing growing headwinds in recent years. This was due to several external shifts, including pressures on the global economy; an increasingly crowded global health and development space; and shrinking resources to address the global HIV epidemic, with a concomitant and growing reliance on the United States, the largest donor to HIV.

Within the U.S., members of Congress were increasingly asking questions about PEPFAR’s “end game,” pressing the program for its plans for the future to scale down and transition services, programming and, ultimately, financing to countries. In addition, some members began raising concerns that PEPFAR was supporting abortion activities, which is prohibited under federal law and policy. Together, these issues rendered PEPFAR unable to secure a five-year reauthorization for the first time in its history. Instead, Congress reauthorized the program for just one year (from March 23, 2024, to March 25, 2025), pushing further decision until after the 2024 election. In the meantime, ongoing concerns about abortion prompted Senator Risch to put a $1 billion hold on the program in September 2024.

What to Watch

Against this backdrop, several recent developments have made PEPFAR’s future particularly precarious; many of these intersect with one another, adding uncertainty and complexity to an already shifting landscape. These include:

  • Increasing Abortion Concerns. In January, just before President Trump assumed office, PEPFAR notified Congress that some funds had, in violation of the Helms amendment, mistakenly been used to support a limited number of abortions in Mozambique, where abortion is legal in certain circumstances. According to one report, this was discovered by U.S. officials in late October 2024 when routine compliance measures found that some PEPFAR-funded nurses had not received required training on the prohibition on paying for the performance of abortion in U.S.-funded services, with four found to have performed abortions. In a statement issued on January 17, PEPFAR enumerated the steps it took to halt and remediate the violation and to prevent future violations, including immediately suspending funding and obtaining reimbursement from the Government of Mozambique for the amount (reported to be $4,100 spent on the nurse’s salaries) and putting in place new, additional measures, such as “requiring an annual signed attestation by PEPFAR-funded clinical service providers to ensure compliance with U.S. funding restrictions.” While this was the first time there had been evidence of any PEPFAR violation of the prohibition on abortion, it raised significant additional concerns among members of Congress who called for further investigation. This has led to increased scrutiny of the program and is likely to figure significantly in any discussion of reauthorization and PEPFAR’s future more broadly.
  • President Trump’s Foreign Aid Funding Freeze and PEPFAR’s Limited Waiver. Beginning on the first day of his second term, President Trump issued several executive actions that affected and continue to affect PEPFAR’s operations, most notably a January 20 Executive Order reevaluating foreign aid. The order called for a 90-day freeze on U.S. foreign aid, including PEPFAR funding, to allow for a review of foreign assistance programs for alignment with Trump administration policy. While the order focused on pausing funding for new obligations and disbursements, on January 24, Secretary of State Rubio issued a stop-work order on all existing operations (those already underway), with limited exception. This, coupled with actions affecting USAID, PEPFAR’s main U.S. government implementing agency (see below), effectively halted service delivery.Although PEPFAR was able to secure a limited waiver on February 1 to allow some services to continue, communication about the waiver has been slow or unclear and the payment system remained unavailable. In addition, the waiver was limited to care and treatment only, as well as PMTCT and PrEP for pregnant and breastfeeding women; no other prevention services, including PrEP for those at risk of HIV infection or already on PrEP, were allowed. Even where the waiver might have been communicated to implementers, the capacity to deliver services has already been negatively affected with thousands of aid workers having already lost their jobs.In a set of lawsuits brought by organizational recipients of U.S. foreign aid, the court issued a temporary restraining order on February 13, requiring the administration to end the foreign aid freeze. Still, the case continues to move through the legal process and the government has since indicated that, despite the requirement to resume funding, it acted within its authority to cancel most grants and contracts. It is also unknown how much of the damage already done to service capacity can be repaired, should funding resume. Finally, the administration’s foreign aid review is ongoing, and expected to conclude by April 19 with recommendations for programmatic changes and potential cuts. How PEPFAR fares in this process is unclear but could have significant implications for its future. It is also unknown how any recommendations about changes to PEPFAR under the foreign aid review will be met by Congress and/or figure into Congress’ own deliberations about reauthorization.
  • The Potential Dismantling of USAID. PEPFAR is overseen by the State Department but implemented primarily by other U.S. government agencies – particularly USAID and CDC. In FY 2023, 60% of PEPFAR’s bilateral HIV assistance was obligated and implemented by USAID. Shortly after the foreign aid pause was announced, however, President Trump and others in the administration announced their intention to dissolve USAID and implemented a series of actions that affected its operations and capacity including: taking down its website and payment and data systems, letting go of hundreds of staff and plans to put thousands more on leave (although a federal judge has temporarily enjoined the administration from doing so), closing the USAID building, and appointing the Secretary of State as the Acting Administrator of USAID. As mentioned above, this has already significantly affected PEPFAR’s operations even with a limited waiver issued, including widespread reports that there are no USAID personnel to communicate about the waiver, answer questions about waiver implementation, or facilitate payment. More long-term, it remains unclear what will happen with the agency including the recommendations that will be made by the State Department and whether Congress will accept proposed changes. Given the current reliance of PEPFAR on USAID as one of its main implementing agencies, any change stands to impact programming.
  • The Reinstatement of the Expanded Mexico City Policy. As was expected, President Trump reinstated the Mexico City Policy, marking the resumption of the expansion of the policy from his first term that, for the first time, included PEPFAR. The Trump administration’s 2017 expanded policy required foreign non-governmental organizations (NGOs) to certify that they would not “perform or actively promote abortion as a method of family planning” using funds from any source (including non-U.S. funds) as a condition of receiving U.S. government global family planning funding and most other bilateral U.S. global health assistance (prior to this time, only family planning assistance had been subject to the policy). An analysis of the impact of Trump’s expanded policy found significant decreases in services offered by PEPFAR implementing organizations, including reductions in HIV testing and counseling among other services. The newly reinstated policy calls for the Secretary of State, in coordination with the Secretary of Health and Human Services, to develop a plan to implement the policy, and it is possible that the plan will reach even further than during Trump’s first presidency, as some have called for.
  • PEPFAR’s Reauthorization Uncertainty. As mentioned earlier, PEPFAR’s current authorization expires March 25, which means that eight time-bound provisions would lapse if Congress does not act to extend them. However, the PEPFAR program overall would continue, so long as funding is appropriated. Still, how concerns raised by some members of Congress about abortion and increasing pressure on PEPFAR to demonstrate more concrete plans about its future, will figure into reauthorization have yet to be seen. It is possible that the new measures announced by PEPFAR to assure compliance with U.S. law, the reinstatement of the Mexico City Policy, and, presumably, a new PEPFAR coordinator appointed by President Trump, will alleviate abortion concerns. At the same time, the current upheaval in PEPFAR services and disruptions around the world may accelerate Congress’ interest in playing a more active role in charting its future, as will its interest in seeing more active sustainability reforms – for example, Congress could assess whether to include new provisions in PEPFAR authorizing language, such as country co-financing or graduation requirements.
  • Future Funding. Finally, while PEPFAR’s funding has been relatively flat for several years, it now enters a much more uncertain funding environment. Last year, during budget negotiations, both the House and Senate’s final FY 2025 appropriation bills for State, Foreign Operations, and Related Programs (which funds most of PEPFAR) included level funding for program. Still, Congress could not agree on an overall budget for FY 2025 and the entire government is operating under a continuing resolution through March 28, 2025, requiring Congress to either agree on a FY 2025 budget or adopt another continuing resolution (or the government shuts down), and reports already indicate that Republicans will be looking for deep cuts in the budget. This changes the overall funding calculus for PEPFAR potentially for FY 2025 but also beyond. Contributing to this is the likelihood that President Trump’s first budget request for FY 2026, which will be released soon, will call for funding cuts to global health, including PEPFAR, as it did during his first term – at that time, Congress balked at those cuts but it is much less certain how they will respond now, given current fiscal and political pressures.

Key Facts About Hospitals

This analysis presents key facts to inform policy discussions about hospitals and hospital spending in the following categories: National Hospital Spending, The Hospital Industry, Rural Hospitals, Use of Hospital Care, Out-of-Pocket Spending and Medical Debt, Hospital Prices, Hospital Finances and Charity Care.

This analysis presents key facts to inform policy discussions about hospitals and hospital spending in the following categories:

Overview

Introduction

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Hospitals account for nearly one third (31%) of total health care spending—$1.5 trillion in 2023—with expenditures projected to rise rapidly through 2032, contributing to higher costs for families, employers, Medicare, Medicaid, and other public payers. In the past, policymakers have looked to reduce spending on hospital care as part of broader efforts to make health care more affordable and reduce the federal deficit and national debt. For example, Republican lawmakers recently floated a number of proposals that could directly or indirectly affect the more than 6,000 hospitals across the country, including major reductions in Medicaid spending, reductions in Medicare spending for uncompensated care and bad debt, establishing site-neutral payments that would achieve Medicare savings by aligning payment rates for a given service across different sites of care, and eliminating federal tax-exempt status for nonprofit hospitals.

Reducing federal spending on hospital care would inevitably involve tradeoffs. On the one hand, doing so could reduce the federal deficit, help offset the cost of a tax bill or other policy priorities, and promote efficiencies. Some options that reduce Medicare reimbursement may also lead to lower beneficiary cost-sharing requirements and premiums. On the other hand, reducing federal payments to hospitals could shift costs onto patients and lead hospitals to offer fewer services—which may result in patients not getting need care—or poorer quality of care. Absorbing reductions in federal spending could be especially challenging for hospitals that are financially vulnerable, such as rural and safety-net hospitals

This analysis presents key facts about hospitals to inform policy discussions about hospitals and hospital spending. Topics include national spending on hospital care, characteristics of the hospital industry, rural hospitals, use of hospital care, out-of-pocket spending and medical debt, hospital prices, hospital finances, and charity care. (For additional information about the data used, see Data Sources.)  

National Hospital Spending

National Spending on Hospital Care

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Spending on hospital care totaled $1.5 trillion in 2023, representing nearly one third (31%) of national health expenditures in that year. Spending on hospital care was the single largest source of national health expenditures in 2023. Hospital care includes both inpatient services and outpatient services (like imaging services or surgical procedures that do not require an overnight stay). Other categories that account for a large share of national health expenditures include spending on physician and clinical services (20%) and retail prescription drugs (9%). (See the Peterson-KFF Health System Tracker for more on national health expenditures.)

Spending on Hospital Care Totaled $1.4 trillion in 2023, Representing Nearly One Third (31%) of National Health Expenditures in That Year

Spending by Payer

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Private health insurance accounted for more than a third of spending on hospital care in 2023 (37%), followed by Medicare (25%) and Medicaid (19%). Private insurance includes coverage offered by employers and insurance purchased through the Affordable Care Act (ACA) health insurance Marketplaces and elsewhere. The federal government subsidizes private insurance through favorable tax treatment for employer-sponsored coverage and through subsidies for coverage purchased through the Marketplaces.

Medicare spending—which is financed by the federal government—includes hospital care provided by traditional Medicare and Medicare Advantage plans. Medicaid spending—which is jointly financed by states and the federal government—includes hospital care provided by fee-for-service Medicaid and Medicaid managed care plans. Federal, state, and local governments also cover hospital spending through other programs, such as the Veterans Health Administration, which is administered by the federal government.

Patient out-of-pocket spending accounted for a relatively small share of hospital spending (3%), though individuals also contribute to hospital spending through health insurance premiums, taxes, and lower wages. 

Private Health Insurance Accounted for More Than a Third of Spending on Hospital Care in 2023 (37%), Followed by Medicare (25%) and Medicaid (19%)

Spending as Percentage of GDP

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Spending on hospital care as a percent of gross domestic product (GDP) is projected to increase from 5.5% in 2023 to 6.0% in 2032. Hospital spending as a share of GDP more than tripled from 1.7% in 1960 to 5.4% in 2010. Between 2010 and 2019, hospital spending as a share of GDP was relatively flat, but spiked in 2020 (i.e., the first year of the COVID-10 pandemic). The share eventually fell below 2019 pre-pandemic levels in 2022 before increasing to 5.5% in 2023, a year that marked the fastest growth rate of hospital spending (10.4%) since 1990. Hospital spending is projected to increase from 5.5% of GDP in 2023 to 6.0% in 2032.

Spending on Hospital Care as a Percent of Gross Domestic Product (GDP) is Projected to Increase From 5.5% in 2023 to 6.0% in 2032

Medicare and Medicaid Spending

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Hospital care accounted for about one third of Medicare and Medicaid spending in 2023 (37% and 32%, respectively). For purposes of comparison, hospital care represented a larger share of Medicare and Medicaid spending (37% and 32%, respectively) than physician and clinical services (25% and 14%) or retail prescription drugs (14% and 6%). Medicare is financed by the federal government while Medicaid is jointly financed by states and the federal government (Medicaid data include expenditures from both). Because hospital care accounts for a large share of Medicaid and Medicare expenditures, it is likely that any large reductions in program spending would impact hospitals. Policies that reduce spending on hospital care could involve tradeoffs, for example, to the extent that they lead hospitals to offer fewer services, reduce staff, or make other cuts, which could result in patients not getting needed care or in poorer quality of care.

Hospital Care Accounted for About One Third of Medicare and Medicaid Spending in 2023 (37% and 32%, Respectively)

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The Hospital Industry

Number of Hospitals

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Most of the 6,093 hospitals in the United States (84%) are community hospitals. Community hospitals are short-term, non-federal, general and specialty hospitals that are open to the general public. While the majority of community hospitals are general medical and surgical hospitals (83%; not shown), the category also includes certain rehabilitation hospitals, acute long-term care hospitals, children’s hospitals, cancer hospitals, and other hospitals (such as rural emergency hospitals and surgical hospitals). Non-community hospitals include federal hospitals, like Veterans Affairs hospitals, and non-federal psychiatric hospitals, among other types (such as non-federal long-term care hospitals).

Most of the 6,093 Hospitals in the United States (84%) are Community Hospitals

Openings and Closings

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From 2010 through 2023, more hospitals closed than opened. Over this 14-year period, 300 hospitals closed and 192 hospitals opened, or 108 more hospital closings than openings. Hospital closures often raise concerns about access to care, and this may especially be the case when there are few or no other hospitals or providers in the area offering a given set of services or when a safety-net hospital closes that had served as an access point for vulnerable populations.

From 2010 Through 2023, More Hospitals Closed Than Opened

Hospital closures outpaced openings to a greater extent in rural versus urban areas. From 2017 to 2023, there were more closures than openings in both rural and urban areas, and especially so in rural areas. In rural areas, 61 hospitals closed compared to 11 that opened, a net reduction of 50 hospitals. In urban areas, there were 87 hospital closures compared to 74 openings, a net reduction of 13 hospitals. Over the twenty-year period from 2005 to 2024, 193 rural hospitals closed.

Hospital Closures Outpaced Openings to a Greater Extent in Rural Versus Urban Areas

Hospital Characteristics

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Most community hospitals (58%) are nonprofits. Nonprofit hospitals are often exempt from federal, state, and local taxes and, in return, are expected to provide benefits to the communities they serve. Nonprofit hospitals may in some circumstances be more attentive than their for-profit counterparts to the needs of their patients and communities, such as by maintaining needed but unprofitable service lines. Nonetheless, some policymakers and researchers have questioned the extent to which nonprofit hospitals behave differently than for-profit hospitals and whether these facilities provide enough community benefits to justify their tax exemption (see Figure 38 in the Hospital Finances section for an estimated value of tax exemption).

While most community hospitals are nonprofit entities, for-profit ownership is common among some types of community hospitals—including acute long-term care hospitals (82%) and rehabilitation hospitals (84%)—as well as non-federal psychiatric hospitals (50%).

Most Community Hospitals (58%) Are Nonprofits

Most community hospitals are nonprofit, and most are part of a larger health system. Most community hospitals (58%) are nonprofit, but a large minority are for-profit (24%) or government hospitals (18%). While about two thirds (69%) of community hospitals are part of a larger health system, the about one third remaining are independent. About one in ten (11% of) hospitals are operated by the Catholic Church. Catholic hospitals have received some media attention in recent years regarding restrictions on reproductive, gender-affirming, and end-of-life care.

About two in five (42% of) hospitals have at least 100 beds, though bed sizes vary; about a quarter (26%) have 25 or fewer beds while about one in seven (16%) have 300 beds or more. More than four in ten hospitals are teaching facilities (44%). About one in three (35%) are in rural (nonmetropolitan) areas.

Most Community Hospitals Are Nonprofit and Part of a Larger Health System, and About Two in Five (42%) Have at Least 100 Beds

Market Concentration and Consolidation

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One or two health systems controlled the entire market for inpatient hospital care in nearly half of metropolitan areas in 2023. Consolidation may allow providers to operate more efficiently and help struggling providers keep their doors open in underserved areas, but it often reduces competition. A substantial body of evidence has found that consolidation can contribute to higher prices, with unclear effects on quality. One or two health systems provided all of the inpatient care in nearly half (47%) of metropolitan areas and at least 75% of the inpatient care in most metropolitan areas (83%) in 2023. Both cases meet the definition of a highly concentrated market based on thresholds in current antitrust guidelines (see below).

The number of health systems in a given metropolitan area tends to increase with the population of the region. For example, regions with four or more health systems accounted for 33% of all metropolitan areas but 77% of the U.S. population living in metropolitan areas.

One or Two Health Systems Controlled the Entire Market for Inpatient Hospital Care in Nearly Half of Metropolitan Areas in 2023

Nearly all (97% of) metropolitan areas had highly concentrated markets for inpatient hospital care in 2023 based on thresholds used in current antitrust guidelines. One way to assess market competitiveness is to evaluate a measure of concentration known as the Herfindahl-Hirschman Index (HHI), which is based on the number of participants in a market and their respective shares. The measure runs from 0 (perfectly competitive) to 10,000 (monopoly market). Nearly all (97% of) metropolitan areas had highly concentrated markets for inpatient hospital care in 2023 when applying thresholds used in current merger guidelines from the Federal Trade Commission and Department of Justice to these regions. Based on the thresholds used in prior merger guidelines, a somewhat smaller share (92%) of metropolitan areas had highly concentrated markets for inpatient hospital care in 2023.

As was the case when looking at counts of health systems in MSAs, larger metropolitan areas tended to be more competitive than less populated metropolitan areas, though many were still highly concentrated. For example, 43 of the 54 metropolitan areas with more than one million residents—including those encompassing Houston, Denver, and Atlanta—had highly concentrated hospital markets.

Nearly All (97% of) Metropolitan Areas Had Highly Concentrated Markets for Inpatient Hospital Care in 2023 Based on Thresholds Used in Current Antitrust Guidelines

The share of hospitals affiliated with health systems increased from 58% in 2010 to 69% in 2023, while the share of hospitals that were independent declined. About two thirds of hospitals (69%) are now part of a larger system, an increase from 58% in 2010. A smaller share of rural than urban hospitals were part of a health system in 2023 (52% versus 78%), though a majority of hospitals were part of a system in both rural and urban areas. Shares have also increased over time for both rural and urban areas: from 43% in 2010 to 52% in 2023 among rural hospitals and from 66% in 2010 to 78% in 2023 among urban hospitals.

The Share of Hospitals Affiliated With Health Systems Increased From 58% in 2010 to 69% in 2023, While the Share of Hospitals That Were Independent Declined

The ten largest health systems in the country operated about one in five (22% of) non-federal general acute care hospital beds in 2023. Consolidation has also contributed to the emergence of large health systems. For example, the ten largest health systems accounted for about one in five (22% of) non-federal general acute care hospital beds in 2023. These systems are the size of large corporations. For instance, HCA Healthcare, the largest system in terms of beds, had greater operating revenues than each of Netflix, Uber, and Starbucks in 2023. Health systems can include many types of providers beyond hospitals (such as ambulatory surgical centers, physician practices, outpatient clinics, home health agencies, and hospices) and sometimes also offer health insurance plans. 

The Ten Largest Health Systems in the Country Operating About One in Five (22% of) Non-federal General Acute Care Hospital Beds in 2023

An increasing share of physicians are employed by a hospital or are part of a practice that is at least partially owned by a hospital or health system. Between 2012 and 2022, the share of physicians employed by a hospital or part of a practice that is at least partially owned by a hospital or health system increased from 29% to 41% based on AMA survey data. Another study found that more than half of physicians were employed directly or indirectly by hospitals or health systems as of January 2024.

Instances where hospitals or health systems employ physicians or buy up physician practices are known as “vertical consolidation.” Vertical consolidation between hospitals and physicians could benefit patients in some instances if, for example, it leads to more integrated and better coordinated care across providers. At the same time, with more and more physicians owned by hospitals and health systems, health systems gain market power, which may lead to higher prices and lower quality by dampening competitive pressure on providers. Prices may also increase following vertical consolidation given that Medicare and other payers often pay higher rates for a given outpatient service when provided by a hospital than in other settings, like freestanding physician offices.

An Increasing Share of Physicians Are Employed by a Hospital or Are Part of a Practice That Is at Least Partially Owned by a Hospital or Health System

Workforce

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Hospitals account for more than 4% of all U.S. workers. Hospitals employed 6.7 million individuals in 2023, making them the sixth largest employer in the country when comparing different industry subsectors. Hospitals followed educational services; food services and drinking places; professional, scientific, and technical services; administrative and support services; and ambulatory health care services in employment rankings. Physicians and other employees in the ambulatory health care services subsector may have close ties to hospitals in some instances (e.g., be owned by the same system as a hospital or see patients at a hospital).

Hospitals accounted for at least 5.0% of total employment in 17 states in 2023 and represented 7.8% of total employment in West Virginia, which was the highest percentage across states.

Hospitals Account for More Than 4% of All U.S. Workers

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Rural Hospitals

Prevalence of Rural Hospitals

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About one third (35%) of community hospitals are in rural areas. In 2023, 1,796 community hospitals operated in rural (nonmetropolitan) areas. Of these rural hospitals, 758 were in micropolitan areas while the remaining 1,038 were not. Regions that are neither metropolitan nor micropolitan areas do not include and are not closely connected to any substantial population center.

About One Third (35%) of Community Hospitals Are in Rural Areas

Rural Hospital Characteristics

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Most hospitals in rural areas were nonprofit (58%) and affiliated with a health system (52%) and half had 25 or fewer beds in 2023. Hospitals in rural areas had similar rates of nonprofit ownership as those in urban areas but were much more likely to be government-owned (33% versus 10%) and were much less likely to have for-profit ownership (9% versus 32%). Rural hospitals were also much less likely than urban hospitals to be affiliated with a broader health care system (52% versus 78%), though system affiliation has increased in both rural and urban areas over time (see Figure 12 in the Hospital Industry section). Finally, rural hospitals tend to be smaller than urban hospitals. For example, half of rural hospitals had 25 or fewer beds compared to 14% of urban hospitals. While nearly a quarter of hospitals in urban areas had at least 300 beds (23%), this was only the case for 1% of those in rural areas.

Most Hospitals in Rural Areas Were Nonprofit (58%) and Affiliated With a Health System (52%) and Half Had 25 or Fewer Beds in 2023

Rural Discharges by Payer

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Medicare covered a larger share of hospital discharges in rural than urban areas while private insurance covered a smaller share in rural than urban areas in 2023. Medicare shares were 53% in rural areas versus 45% in urban areas, while private insurance (not including Medicare and Medicaid plans) accounted for 19% of discharges in rural areas versus 24% in urban areas. Medicaid also covered a slightly smaller share of discharges in rural versus urban areas (19% versus 21%).

Private insurers generally reimburse at higher rates than Medicare and Medicaid (see Prices section for comparisons with Medicare), though the extent to which this is true in rural areas is unclear. Medicare provides more generous reimbursement for most rural hospitals through special rural payment designations, such as for critical access hospitals (rural hospitals with at most 25 beds that with some exceptions are a minimum distance from other facilities). Many state Medicaid programs also have special payment rules for hospitals in rural areas, such as by paying higher rates or based on costs or through supplemental payments. Commercial prices also likely differ in rural areas given the unique market structure of these regions, though it is unclear how rates compare.

Medicare Covered a Larger Share of Hospital Discharges in Rural Than Urban Areas While Private Insurance Covered a Smaller Share in Rural Than Urban Areas in 2023

Rural Profit Margins

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Operating margins were lower than average among rural hospitals in 2023. Operating margins were lower among hospitals in rural (nonmetropolitan) areas than hospitals in urban (metropolitan) areas (3.1% versus 5.4%, respectively). Operating margins were especially low among the nearly 1,000 hospitals in rural areas that were not micropolitan areas (1.7%) (i.e., that do not include and are not closely connected to any substantial population center).

Policymakers have had concerns about the financial health of rural hospitals and the implications for access to care and the local economy. Rural hospitals often face unique financial challenges. For example, they often have low patient volume, which may lead to higher costs, on average, and limit the ability of rural hospitals to offer specialized services. While, as noted above, the government provides additional funds for rural hospitals, including through Medicare rural payment designations (such as for critical access hospitals), rural hospitals continue to have lower operating margins than average.

Recent policy discussions have considered options for supporting rural hospitals, including in the context of discussions about reductions in Medicaid and Medicare spending. Even with an infusion of additional funds, it may be difficult to sustain some rural hospitals, such as those in areas with shrinking populations. In 2023, Medicare began to offer a new rural emergency hospital designation created by Congress, which provides support to hospitals that operate 24/7 emergency departments but do not provide inpatient care, recognizing that some regions cannot support a broader suite of services. In general, maintaining access to services at local rural hospitals involves tradeoffs in scenarios where other providers—such as outpatient clinics and large regional hospitals—are less expensive or offer higher quality of care.

Operating Margins Were Lower Than Average Among Rural Hospitals in 2023

Rural Openings and Closings

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Hospital closures outpaced openings in rural areas from 2017 to 2023. During that seven-year period, 61 hospitals closed compared to 11 that opened, a net reduction of 50 hospitals. Over the twenty-year longer period from 2005 to 2024, 193 rural hospitals closed. Rural hospital closures often raise concerns about access to care, and this may especially be the case when there are few or no other hospitals or providers in an area offering a given set of services and for conditions that require time-sensitive care, such as heart attacks and childbirth.

Hospital Closures Outpaced Openings in Rural Areas From 2017 to 2023

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Use of Hospital Care

Inpatient Utilization

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Hospital inpatient utilization has decreased over time. This is true for both hospital inpatient days and admissions per capita. From 2000 to 2023, the number of hospital inpatient days per 1,000 people fell from 684 to 561, an 18% decrease. Much of this decrease occurred from 2005 to 2014, when inpatient days per 1,000 decreased by 15%. Contributing to the decrease in inpatient days over time was a decrease in both inpatient admissions and average length of stay. Inpatient admissions per 1,000 people decreased by 19% from 2000 to 2023, with much of the change also occurring from 2005 to 2014. The average length of stay decreased from 5.8 in 2000 to 5.4 in 2019, with much of the change occurring from 2000 to 2009, before jumping up during the pandemic (see below). Decreases in inpatient use over time are partly due to increases in procedures performed in outpatient settings.

There were relatively large changes in hospital inpatient utilization during the pandemic. Inpatient days per 1,000 people decreased by 5% in 2020 before increasing towards 2019 pre-pandemic levels in 2021-2023. Inpatient admissions per 1,000 people decreased by 9% in 2020; levels wavered in 2021 and 2022 before increasing again by 2% in 2023, at which point they remained 8% below 2019 pre-pandemic levels. Average length of stay increased from 5.4 in 2019 to 6.0 in 2022 before falling to 5.8 in 2023. (See the Peterson-KFF Health System Tracker for more on trends in health care utilization.)

Hospital Inpatient Volume Has Decreased Over Time

Outpatient Utilization

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While hospital inpatient utilization has decreased over time, hospital outpatient utilization has increased. Hospitals provide a wide array of services on an outpatient basis, including clinic visits, imaging services, drug infusion services, and outpatient surgical procedures. The number of hospital outpatient visits per 1,000 people increased from 1,853 in 2000 to 2,426 in 2023, a 31% increase. One factor likely underlying this trend is the general movement of care from inpatient to outpatient settings. Another factor may be that reimbursement rates are often higher for a given outpatient service when provided in a hospital than in other care settings, which could create an incentive to move services from physician offices to hospital outpatient departments, including by hospitals buying up physician practices.

Outpatient visits per 1,000 people decreased in 2020, the first year of the pandemic, before increasing to around 2019 pre-pandemic levels in later years. In 2023, outpatient visits per 1,000 people exceeded pre-pandemic levels by 1%.

While Hospital Inpatient Utilization Has Decreased Over Time, Hospital Outpatient Utilization Has Increased

Discharges by Payer

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Medicare and Medicaid together accounted for about two thirds (67%) of all hospital discharges in 2023. Nearly half of hospital discharges were attributed to Medicare (46%) and more than one fifth were attributed to Medicaid (21%). Private insurance (not including Medicare or Medicaid plans) accounted for 24% of discharges. Four percent were self-pay discharges, which typically includes uninsured patients and insured patients who pay directly rather than use their coverage. It is also possible that uninsured patients could be included under “other” in some instances.

Payer mix varies across hospitals, which has implications for hospitals’ role in the safety net and their finances. For example, private insurance accounted for 24% of discharges overall but at least 33% of discharges among the top ten percent of hospitals based on private insurance shares and 9% or less among the bottom ten percent of hospitals. Private insurers generally reimburse at higher rates than Medicare and Medicaid (see Prices section for comparisons with Medicare). Medicaid accounted for 21% of hospital discharges overall but at least 27% of discharges among the top ten percent of hospitals based on Medicaid shares and 4% or less among the bottom ten percent.

Nearly Half of Hospital Discharges (46%) in 2023 Were Attributed to Medicare

Medicare Advantage Inpatient Days

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Medicare Advantage steadily increased as a share of inpatient days between 2015 and 2023, while the share attributable to traditional Medicare decreased. In particular, the share of total inpatient days attributed to Medicare Advantage enrollees grew from 13% in 2015 to 24% in 2023 among general short-term hospitals in the U.S. During this same period, the share of inpatient days attributed to traditional Medicare declined from 34% to 24%. As of 2023, half of all Medicare inpatient days were attributable to Medicare Advantage patients. The rise in Medicare Advantage enrollment has implications for beneficiaries and hospitals, as Medicare Advantage differs from traditional Medicare. For example, plans often require prior authorization before covering certain services and establish networks of providers, among other factors.

Medicare Advantage Steadily Increased As Share of Inpatient Days Between 2015 and 2023, While the Share Attributable to Traditional Medicare Decreased

Pregnancy & Hospitalizations

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Medicaid covers about four in ten (41% of) births nationally. Medicaid covered at least four in ten births in 25 states and DC in 2023 and covered more than half of births in four states: Louisiana, Mississippi, New Mexico, and Oklahoma. The share was the largest in Louisiana, where Medicaid covered nearly two in three (64% of) births. (See prior KFF work for more about women and Medicaid.)

Medicaid Covers About Four in Ten (41% of) Births Nationally

Maternal and neonatal stays accounted for more than one in five (22% of) hospitalizations in 2021. Maternal stays accounted for about one in ten (11% of) hospitalizations in 2021, and neonatal stays accounted for the same share (hospital stays for a mother and newborn are recorded separately). Other types of hospitalizations were medical (50%), surgical (18%), injury (5%), and mental health and substance abuse (5%) discharges.

Maternal and Neonatal Stays Account for More Than One in Five (22% of) Hospitalizations

Common Inpatient Diagnoses

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Excluding maternal and neonatal stays, sepsis was the most common reason for a hospitalization in 2021, followed by COVID-19, heart failure, and diabetes with complication. Excluding maternal and neonatal stays, the most common reasons for a hospital stay in 2021 were sepsis (739 stays per 100,000), COVID-19 (468 stays per 100,000), heart failure (328 stays per 100,000), and diabetes with complication (206 stays per 100,000). COVID-19 hospitalizations have decreased substantially since 2021. Hospital stays in general were much more common among people ages 75 and older: 30,084 stays per 100,000 compared to 6,665 stays per 100,000 people under 18 (most of which were stays for newborns).

The most common hospitalizations when excluding maternal and neonatal stays varied with age. For instance, people under 18 were most commonly hospitalized for depressive disorders; acute bronchitis; epilepsy, convulsions; and asthma. People ages 18 to 44 were most commonly hospitalized for sepsis, COVID-19, schizophrenia spectrum and other psychotic disorders, and depressive disorders. People ages 75 and older were most commonly hospitalized for sepsis, heart failure, COVID-19, and arrhythmia.

Excluding Maternal and Neonatal Stays, Sepsis Was the Most Common Reason for a Hospitalization in 2021, Followed by COVID-19, Heart Failure, and Diabetes With Complication

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Out-of-Pocket Spending and Medical Debt

Out-of-Pocket Spending

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More than two in five (23% of) patients with a hospital stay in 2022 spent more than $3,000 out of pocket on health care. The rate among individuals who were hospitalized was nearly four times the rate (6%) among people without a hospital stay. Half (50%) of all individuals with a hospital stay had at least $1,000 in out-of-pocket spending, compared to 19% of people without a hospital stay. (See the Peterson-KFF Health System Tracker for more on differences in health care expenditures across the population.)

Total out-of-pocket spending among individuals with a hospital stay includes inpatient hospital care, hospital outpatient department visits, office-based visits, and prescription drugs, among other things. Out-of-pocket costs associated with hospital care may be especially burdensome for uninsured patients, insured patients with high deductibles or relatively less generous coverage, and low-income patients who are not eligible for hospital financial assistance programs or do not know that they are eligible.

Hospital costs have direct implications for affordability among patients receiving treatment and also affect the broader population. Hospital costs impact health insurance premiums and also affect wages and taxes because employers and the government ultimately cover a portion of these costs. Patient out-of-pocket spending accounts for a relatively small share of spending on hospital care (3% in 2023 based on national health expenditure data; see Figure 2 in the Hospital Spending section), with government and private insurers covering the bulk of hospital expenses.

About Two in Five (21% of) Hospitalized Patients Spent More Than $3,000 Out-of-Pocket on Health Care in 2022

Medical Debt

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More than one in six hospitalized adults (18%) had over $250 in medical debt in 2022. The rate among adults who were hospitalized was more than two times the rate of those without a hospital stay (7%). (See the Peterson-KFF Health System Tracker and the KFF Health Care Debt Survey for more on medical debt.) Medical debt takes into account amounts owed to hospitals and other providers.  

Hospitals typically have financial assistance programs, which provide free or discounted services to eligible patients who are unable to afford their care. However, eligibility criteria vary across hospitals, financial assistance programs may not cover the full cost of care, and not all eligible patients receive assistance (e.g., because they do not know to apply).

More Than One in Six Hospitalized Adults (18%) Had at Least $250 in Medical Debt in 2022

Among hospitalized adults with over $250 in medical debt in 2022, the amount of debt exceeded $5,000 for about four in ten patients (39%). That again was greater than the corresponding rate (22%) among adults with over $250 in medical debt but without a hospital stay. 

Among Hospitalized Adults With at Least $250 in Medical Debt in 2022, the Amount of Debt Exceeded $5,000 for About Four in Ten Patients (39%)

More than two thirds (69%) of adults with at least $5,000 in medical debt say that a hospitalization caused at least some of their debt. Additionally, the majority of people with at least $5,000 in medical debt (77%) attributed at least part of their debt to emergency care, which is typically provided by hospitals. Many of those with at least $5,000 in medical debt cited other services that may be provided in hospitals, including lab fees or diagnostic tests (77%), doctor visits (69%), and outpatient surgery (38%). 

More Than Two-Thirds of Individuals With at Least $5,000 in Medical Debt Report That a Hospitalization Contributed to Their Debt.

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Hospital Prices

Price Growth by Payer

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Prices for hospital care paid by private insurance have grown faster than Medicare and Medicaid rates. Inpatient hospital prices paid by private health insurance plans (and other payers aside from Medicare or Medicaid) increased by 50% from June 2014 to December 2024 based on the Producer Price Index. This is twice the growth rate of inpatient hospital prices for Medicare (25%) and more than twice the growth rate for Medicaid (19%) over the same period. There were similar differences when looking at increases in prices for hospital outpatient care (42% versus 17% for Medicare and 6% for Medicaid). (See Peterson-KFF Health System Tracker for more on medical inflation).

Prices for Hospital Care Paid by Private Insurance Have Grown Faster Than Medicare and Medicaid Rates

Prices Paid by Private Insurance

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Prices paid by private insurance for hospital care were 267% of Medicare rates on average in 2022 and varied widely across the country. This is based on the RAND Price Transparency Study—which uses claims data from a large population of commercial patients—and reflects facility claims for both hospital inpatient and outpatient services (while excluding associated professional claims). A KFF review similarly found that commercial prices were nearly double Medicare rates for hospital services when averaging findings across studies. Commercial-to-Medicare price ratios based on the RAND data varied widely across the country, from 166% in Arkansas to 380% in Florida. (See Peterson-KFF Health System Tracker for more on commercial health care prices and variation across the country.) Private payers often benchmark their reimbursement to a percent of Medicare rates.

Policymakers have explored a number of options to rein in commercial prices in an effort to make care more affordable, including by increasing the competitiveness of health care markets and directly regulating prices and spending. 

Prices Paid by Private Insurance for Hospital Care Were 267% of Medicare Rates on Average in 2022 and Varied Widely Across the Country

Prices paid by private insurance as a percent of Medicare can vary widely across hospitals within metropolitan areas. For example, in the New York City-Newark-New Jersey City metropolitan area, the prices paid by private insurance for hospital care were less than 199% of Medicare rates for a quarter of hospitals but were more than 354% for another quarter. Differences in the prices paid as a percent of Medicare rates could reflect a variety of factors, including market power and negotiating leverage, quality, cost structure, and the types of services a given hospital provides. Insurers may try to steer patients away from hospitals with high prices or exclude those hospitals from their provider networks altogether, though doing so may be challenging, especially in the case of highly regarded, “must have” hospitals with local clout and name recognition.

Prices Paid by Private Insurance as a Percent of Medicare Can Vary Widely Across Hospitals Within Metropolitan Areas

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Hospital Finances

Profit Margins

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Hospital margins rebounded in 2023 following a large decrease in 2022. Total margins for hospitals decreased from 10.8% in 2021 to 2.3% in 2022 before increasing to 6.4% in 2023. Similarly, operating margins decreased from 8.9% in 2021 to 2.7% in 2022 before increasing to 5.2% in 2023. While both increased in 2023, they remained below 2019 pre-pandemic levels (6.5% for operating margins and 7.6% for total margins). Total margins reflect profit margins earned on all activities while operating margins reflect profit margins earned on patient care and other operating activities (rather than on other sources such as investments).

Decreases in operating margins in 2022 were likely due to the erosion of COVID funds, costs associated with labor shortages, and increased supply expenses due to high inflation rates, among other factors. Improvements in 2023 may have been due a number of factors, including stabilizing labor expenses, decreases in average length of stay, and increases in revenue. Industry reports indicate that hospital margins improved in 2024 relative to 2023.

Hospital Margins Rebounded in 2023 Following a Large Decrease in 2022

Operating margins were relatively high among for-profit and system-affiliated hospitals and relatively low among hospitals with low market shares and rural hospitals in 2023. For-profit hospitals had much higher operating margins than nonprofit and government hospitals (14.0% versus 4.4% and 3.4%, respectively) in 2023. Differences in operating margins across these and other groups of hospitals could reflect a variety of factors. For instance, for-profit hospitals may have a greater motivation than other hospitals to operate efficiently and engage in other strategic behaviors to increase their margins, such as focusing on relatively profitable services lines, dropping unprofitable service lines (like obstetrics), or locating in wealthier areas that have more residents with commercial insurance and fewer with public or no insurance.

Operating margins were lower among hospitals in rural (nonmetropolitan) areas than hospitals in urban (metropolitan) areas (3.1% versus 5.4%, respectively). Operating margins were especially low among the nearly 1,000 hospitals in rural areas that were not micropolitan areas (1.7%). Regions that are neither metropolitan nor micropolitan areas do not include and are not closely connected to any substantial population center.

Prior KFF analysis provides additional information about differences in margins across hospitals.

Operating Margins Were Relatively High Among For-Profit and System-Affiliated Hospitals and Relatively Low Among Hospitals With Low Market Shares and Rural Hospitals in 2023

Operating margins were lower than average among hospitals with high shares of Medicaid patients and higher than average among hospitals with high shares of commercial patients in 2023. More specifically, operating margins were relatively low (2.3%) among hospitals with high shares of Medicaid patients and were relatively high among hospitals with low shares of Medicaid patients (7.0%). (This compares operating margins among hospitals in the top versus bottom quartiles based on Medicaid as a share of total discharges, weighted by revenues). Notably, operating margins in 2023 were relatively low among hospitals with high Medicaid shares in both rural and urban areas (1.7% and 2.3%, respectively) (data not shown). Some policymakers have been attentive to the financial stability of safety-net hospitals, including those in both urban and rural areas, given their role in providing access to patients with limited resources and other sources of vulnerability. The share of patients covered by Medicaid may signal the extent to which a hospital serves as a safety net for low-income patients.

Operating margins were higher among hospitals with a relatively large share of commercial patients than hospitals with a relatively small share of commercial patients (7.5% versus 3.3%). One factor that likely plays a role in these results is that commercial payers generally reimburse hospital care at higher rates than Medicare and Medicaid (see Prices section for comparisons with Medicare).

Operating Margins Were Lower Than Average Among Hospitals With High Shares of Medicaid Patients and Higher Than Average Among Hospitals With High Shares of Commercial Patients in 2023

Tax Exemption

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The estimated value of tax exemption for nonprofit hospitals grew from about $19 billion in 2011 to about $28 billion in 2020. Over the years, some policymakers have questioned the extent to which nonprofit hospitals—which account for nearly three-fifths (58%) of community hospitals (see Figures 8 and 9 in the Hospital Industry section)–provide enough benefit to their communities to justify tax exemption.

The estimated value of tax exemption for nonprofit hospitals was about $28 billion in 2020 based on a prior KFF analysis. About half of this amount is related to federal tax-exempt status, including the estimated value of not having to pay federal corporate income taxes ($10.3 billion) and assumptions that individuals contribute more to tax-exempt hospitals because they can deduct their donations ($2.5 billion) and that hospitals can issue bonds at lower interest rates because the interest is not taxed ($1.6 billion). About half is related to state and local tax-exempt status, including the estimated value of not having to pay state or local sales taxes ($5.7 billion), local property taxes ($5.0 billion) or state corporate income taxes ($3.0 billion).

The value of tax exemption increased in most years (7 out of 9) from 2011 to 2020. The large decrease in the value of tax exemption in 2018 coincided with the implementation of the Tax Cuts and Jobs Act of 2017, which permanently reduced the federal corporate income tax rate from 35 to 21 percent and therefore decreased the value of being exempt from federal income taxes. The large increase in the value of tax exemption in 2020 may in part reflect unique circumstances related to the COVID-19 pandemic, including the large amounts of government relief provided to hospitals.

Estimating the value of tax exemption requires a number of assumptions. Another analysis using a different methodology estimated that the value of tax exemption was $37 billion in 2021, with the largest differences being much higher estimated value of sales and property tax exemptions.

The Estimated Value of Tax Exemption Grew From About $19 Billion in 2011 to $28 Billion in 2020

340B Drug Pricing Program

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Purchases through the 340B Drug Pricing Program, most of which are made by hospitals, have increased substantially over time. The 340B Drug Pricing Program requires manufacturers participating in Medicaid to sell outpatient drugs to eligible nonprofit and government providers at a substantial discount, with the intent of supporting entities caring for low-income and other underserved populations, such as certain disproportionate share hospitals. The 340B program has grown substantially over time, with total drug purchases growing from $2.4 billion in 2005 to $66.3 billion in 2023.

Hospitals account for the large majority of these drug purchases, and more than 2,600 hospitals participated in the program as of January 2023. The pharmaceutical industry has raised concerns that hospitals are not always using the 340B program to help patients afford health care, while hospitals say that the 340B program provides funds to help safety-net hospitals care for underserved populations and invest in operations. Policymakers have considered a variety of 340B reforms, including options that would preserve the ability of providers to dispense 340B drugs through contract pharmacies, increase transparency, tighten regulation of the program, or scale back its scope.

340B Drug Purchases Have Risen Rapidly in Recent Years, Most of Which Is Driven by Hospitals

Hospital Expenses

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Labor costs were the largest expense category for hospitals in 2023, followed by supply and pharmacy expenses. Labor costs made up almost half (46%) of all hospital expenses in 2023 based on a large sample of community hospitals. That includes the costs of hospital employees but not contract labor (e.g., nurses temporarily hired through staffing agencies), which are part of “other” expenses. Most labor costs were related to direct patient care in 2022 based on another data source. Supplies (12%) and pharmacy (9%) were the next largest expense categories.

Labor Costs Were the Largest Expense Category for Hospitals in 2023, Followed by Supplies and Pharmacy Expenses

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Charity Care

Distribution of Charity Care

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Half of all hospitals reported that charity care costs represented 1.2% or less of their operating expenses in 2023, though the level of charity care varied substantially across facilities. Hospital charity care programs, also known as “financial assistance programs,” provide free or discounted services to eligible patients who are unable to afford their care. While charity care costs represented 0.1% of operating expenses or less on the lower end of the spectrum (for 10% of hospitals), they represented 6% or more among a similar share of hospitals on the higher end. Differences in charity care likely reflect a variety of factors, such as the extent to which patients require financial assistance, hospitals’ eligibility criteria and application procedures, efforts to notify patients of their eligibility, and state requirements (e.g., that hospitals at a minimum extend eligibility to certain groups of patients).

Half of All Hospitals Reported That Charity Care Costs Represented 1.1% or Less of Their Operating Expenses in 2023, Though the Level of Charity Care Varied Substantially Across Facilities

Charity Care and Medicaid Expansion

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Charity care costs in 2023 were generally higher in states that had not expanded Medicaid. As a result of the Affordable Care Act, states have the option of expanding Medicaid to nearly all adults with incomes up to 138% of the federal poverty level. Eight of the ten states with the highest average charity care costs as a percent of operating expenses in 2023 had not expanded Medicaid as of January of that year (one did so in December 2023). For example, Texas had both the highest uninsured rate (16%) and the highest average charity care costs as a percent of operating expenses (6.6%) in the country. Conversely, all thirteen states where average charity care costs as a percent of operating expenses were less than 1.0% had expanded Medicaid. Medicaid expansion can improve hospital finances by extending coverage to uninsured patients who may otherwise qualify for hospital charity care or be unable to pay their bills.

Average charity care costs as a percent of operating expenses across the nation were 2.2% in 2023 (which is higher than the median reported in Figure 41 due to a relatively small share of hospitals with particularly high charity care costs).

Charity Care Costs Tended To Be Higher in States That Have Not Expanded Medicaid as of 2023

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Data Sources

About the Data

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Data sources used for Key Facts About Hospitals are listed below. Some figures pull from other sources, including prior KFF analyses and KFF State Health Facts, which include additional information about the data and methodology. Numbers have been rounded.

American Hospital Association (AHA) Annual Survey. Data from an annual survey of all hospitals in the United States and its associated areas. Non-federal psychiatric hospitals were defined to include psychiatric hospitals as well as hospitals that identified their hospital type as “substance use disorder” or “intellectual disabilities.”

American Medical Association (AMA) Physician Practice Benchmark Survey. As described by the AMA, the Physician Practice Benchmark Survey is a nationally representative survey of “post-residency physicians who provide at least 20 hours of patient care per week, are not employed by the federal government, and practice in one of the 50 states or [DC].”

Census Bureau delineation files. The Census Bureau delineation files map counties and county equivalents to metropolitan areas, micropolitan areas, and other regions. These files were used to group hospitals into metropolitan, micropolitan, and other areas. A metropolitan area is a county or group of counties that contains at least one urban area with a population of 50,000 or more people. A micropolitan area is a county or group of counties that contains at least one urban area with a population of at least 10,000 but less than 50,000. Urban and rural regions were defined as metropolitan and nonmetropolitan areas, respectively.

Census Bureau population estimates. We relied on annual population estimates for the 50 states and DC as of July 1 of a given year from the Census Bureau’s Population Estimates Program.

Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS). The NIS is a sample that includes about 20% of all inpatient discharges from U.S. community hospitals (aside from rehabilitation and long-term care hospitals). It is nationally representative of non-federal short-term hospitals in the U.S. and is sponsored by the Agency for Healthcare Research and Quality. Primary diagnoses are grouped into clinical categories based on Clinical Classifications Software Refined (CCSR). The categories used for rankings are mutually exclusive; when a diagnosis falls under multiple clinical categories, the stay is assigned to a single category based on hierarchical guidelines.

KFF Health Care Debt Survey. The KFF Health Care Debt Survey is a nationally representative survey of U.S. adults that was conducted from February 25 through March 20, 2022.

Medical Expenditures Panel Survey (MEPS). MEPS is a nationally representative survey of the U.S. civilian non-institutionalized population that includes information about health care expenditures and sources of payment, among other things. The analysis of out-of-pocket spending relied on the MEPS Household Component (HC).

National Health Expenditures. These data are published annually by the Centers for Medicare & Medicaid Services and provide estimates of national spending on health care, by payer and by type of service.

Producer Price Index (PPI). These data come from the Bureau of Labor Statistics (BLS). As BLS notes, PPI indices measure “the average change over time in selling prices received by domestic producers of goods and services.” The health care PPIs reflect the reimbursement that providers receive for health care services. The Medicare, Medicaid, and private and other patient PPIs are mutually exclusive. The Medicare and Medicaid PPIs take account of private Medicare and Medicaid plans. The PPI may exclude supplemental payments that are paid to hospitals as a lump sum.

Quarterly Census of Wages and Employment (QCEW). These data also come from BLS. As BLS notes, the QCEW data provide a “quarterly count of employment and wages reported by employers covering more than 95 percent of U.S. jobs.” The QCEW includes workers covered by state unemployment insurance laws as well as federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Analyses of hospital and other employment relied on the average annual employment numbers reported by BLS. Industry subsector rankings were based on 3-digit NAICS codes. Employment for a given industry subsector and employer type were not included in totals when not disclosed by BLS.  

RAND Hospital Data. These data are a cleaned and processed version of annual cost reports that Medicare-certified hospitals are required to submit to the federal government. Cost reports include information about hospital characteristics, utilization, and finances. The RAND Hospital Data also crosswalk hospitals to health systems based on the Agency for Healthcare Research and Quality (AHRQ) Compendium of U.S. Health Systems.

For charity care analyses, missing charity care costs were recoded as $0 if the hospital reported total unreimbursed and uncompensated care costs. Hospitals were excluded if they had missing or negative operating expenses or charity care costs, outlier amounts of charity care as a percent of operating expenses (≥18.1%), or reporting periods less than or greater than one year. Cost report instructions indicate that hospitals should report amounts related to both charity care and uninsured discounts as part of their charity care costs. MedPAC has noted that current HCRIS calculations favor hospitals with higher markups, and it has recommended revisions that would put hospitals on more equal footing and reduce reported charity care costs on average.

RAND Price Transparency Study, Round 5.1. These data are based on commercial claims for employer-sponsored health insurance plan enrollees collected from participating self-insured employers and health plans as well as from all-payer claims databases (APCDs) from 12 states. Commercial-to-Medicare price ratios are based on the actual allowed amount from the claims and an estimate of the allowed amount had Medicare covered the same services. Ratios presented in key facts include facility claims for hospital inpatient and outpatient services but exclude associated professional claims (which are also available through the RAND study). Analyses of metropolitan areas exclude hospitals for which RAND did not disclose relevant data while state and national analyses include all hospitals in the RAND study.

Survey of Income and Program Participation (SIPP). SIPP is a nationally representative survey of the civilian noninstitutionalized population. Among other questions, SIPP asks individuals ages 15 and older about their medical debt. The analysis of medical debt further restricted the sample to adults ages 18 and older.

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