A Closer Look at the $50 Billion Rural Health Transformation Program

Published: Sep 18, 2026

Editorial Note: Originally published on July 16, 2025, this brief has been updated over time to include new information and data about the Rural Health Transformation Program.

On July 4, 2025, President Trump signed a budget reconciliation bill—once known as the “One Big Beautiful Bill”—into law that included significant reductions in federal health care spending, large tax cuts, and other changes. It was projected that the law would reduce federal Medicaid spending by $911 billion over ten years (based on estimates released shortly after enactment), including by an estimated $137 billion in rural areas, according to KFF analysis. To help mitigate the impact on rural areas, the law created the Rural Health Transformation Program (referred to here as the “rural health fund”), which will award $50 billion in state grants from 2026 to 2030 to support rural health care.

This brief provides an overview of the rural health fund. Key takeaways include the following:

  • The $50 billion rural health fund represents a large investment in rural health care and is intended to transform the delivery of care through a wide variety of activities.
  • The $50 billion fund could mitigate but will not fully offset estimated cuts to federal Medicaid spending in rural areas ($137 billion over ten years according to KFF analysis) included in the same law. Unlike most of the federal Medicaid spending cuts, the fund is also time limited.
  • While the fund was established in part to address concerns about the impact of the reconciliation law on rural hospitals, the funding is being used for a much broader set of purposes, and there are restrictions on how hospitals can benefit.
  • Half of the funding is being divided equally among approved states. The rest is being distributed based on measures of state need, state initiative scores, state policy, and other factors.
  • All 50 states were approved, with first-year awards ranging from $147 million to $281 million. First-year awards per rural resident range from less than $100 in ten states to more than $500 in eight.
  • It remains to be seen how the funding will be distributed within states across various activities and entities.

How Is the Rural Health Fund Structured and How Can Funds Be Used?

Structure

The rural health fund will provide $50 billion in grants to states over five years.

The rural health fund was added to the 2025 reconciliation law as a political compromise just prior to the law’s passage. The fund emerged during Senate negotiations in response to concerns about the impact of federal spending cuts on rural hospitals. Nonetheless, the program is not specific to rural hospitals but instead supports a much broader set of activities (see below). The law specifies that the Centers for Medicare & Medicaid Services (CMS) will oversee the program. It grants the agency substantial leeway to determine how to distribute funding across states and flexibility to expand the permitted uses of funding and determine the terms and conditions. CMS is administering the program through the new Office of Rural Health Transformation.

Under the rural health fund, CMS will award $10 billion in grants to approved states each year from fiscal years 2026 to 2030, a five-year period, for a total of $50 billion. States will be allowed to spend funds that they receive at a given point through the end of the following fiscal year, and CMS will redistribute any unused funds over time, but all funds must be spent by the end of fiscal year 2032. States will administer their programs, subject to terms agreed upon with CMS. However, the funding is occurring through a mechanism known as a “cooperative agreement,” which “require[s] substantial CMS project involvement after an award is made.”  

States had a one-time opportunity to apply for funding and all states were approved, meaning that they are eligible for funding for all five years of the program. However, CMS may withhold, reduce, eliminate, or recover funding over time if it determines that a state is not in compliance with program rules, the state has not made “satisfactory progress,” or that funding is no longer “in the government’s best interest.” The law indicates that there will be no administrative or judicial review of these and other funding decisions made by CMS.

The law and CMS established a fast-paced timeline for states to apply for funding and initiate programs during the first year of the program. CMS issued a Notice of Funding Opportunity in September 2025 with guidance on how to apply. States then had less than two months to prepare their applications. Those applications affect the scope of activities states can engage in and the amount of funding they receive for the life of the program. CMS announced first-year awards in December 2025. States were then given less than a year to finalize their plans through discussions with CMS, develop their own application process for entities within the state to receive funding, process applications, obligate funding, and submit their first annual progress reports (which will affect second-year awards). States likely differ in their capacity to manage procurement processes and have varied widely in terms of how quickly they have distributed funds during the first year.

Key Dates

Enactment and State Applications

  • July 4, 2025: The 2025 reconciliation law is enacted. The law includes large cuts to federal health care spending and the creation of the rural health fund.
  • September 15, 2025: CMS releases Notice of Funding Opportunity that includes guidance on how CMS will administer the program and how states can apply.
  • November 5, 2025: Deadline for states to apply.

First-Year Awards (fiscal year 2026)

  • December 29, 2025: CMS announces awards, totaling $10 billion.
  • Following first-year award announcement: States work with CMS to reconcile their plans with awarded amounts and program requirements and to determine how funds will be apportioned across initiatives, after which CMS makes first-year funding available.
  • August 31, 2026: Deadline for states to submit first of five annual reports.
  • October 30, 2026: Deadline for states to obligate funding.
  • November 29, 2026: Deadline for states to submit first of thirteen quarterly reports.
  • September 30, 2027. Deadline for states to spend first-year awards. CMS will redistribute unused funds in fiscal year 2028.

Second-Through Fifth-Year Awards (fiscal years 2027-2030)

  • October 31 of fiscal year: CMS will announce fiscal year awards totaling $10 billion by this date.
  • September 30 of following fiscal year: Deadline for states to spend awards. CMS will redistribute unused funds in the following fiscal year.

Program Wind-Down

  • February 27, 2031: Deadline for states to submit final report.
  • September 30, 2031: Deadline for states to spend fifth-year awards. CMS will redistribute unused funds in the next fiscal year.
  • September 30, 2032: Deadline for states to spend any remaining dollars redistributed by CMS.
  • October 1, 2032: Unused funds returned to Treasury Department.

The rural health fund is intended to transform the delivery of health care in rural communities and is being used to support a wide variety of activities.

The rural health fund is designed to help “support…rural communities to improve healthcare access, quality, and outcomes through system transformation” according to CMS. CMS also indicated that it “expects States to design initiatives that invest in long-term, sustainable improvements rather than temporary fixes or funding perpetual operating expenses.” States can use funding for eleven purposes detailed in law and through guidance from CMS, with certain restrictions (see textbox below and Appendix Table 1). CMS has also identified five strategic goals of the program that align with these uses: make rural America healthy again, sustainable access, workforce development, innovative care, and tech innovation (see Appendix Table 2).

In line with the broad scope of the rural health fund, states are implementing a wide variety of activities under the program. For example, states are using funds to promote prevention and chronic disease management interventions, support collaboration among rural health care facilities (such as by sharing administrative services) and between rural providers and regional health systems, recruit clinical workers to rural areas, promote technological advancements (such as by expanding telehealth or promoting AI diagnostic tools), invest in existing hospital buildings and infrastructure, help hospitals determine which services should and should not be maintained, and support the adoption of value-based care and alternative payment models.

Specific state examples include the following (each state is undertaking multiple initiatives):

  • Alabama is funding the use of telerobotics to provide ultrasounds remotely.
  • Alaska is funding the use of drones to deliver medications to remote areas.
  • California is funding new provider collaboration networks, connecting regional hospitals with critical access hospitals, clinics, birthing centers, and other providers.
  • Michigan is funding an initiative to bring “services closer to where people work and live,” such as by “expanding…home-based care for older adults to allow them to age in place.”
  • North Carolina is increasing access to healthy foods, such as by “facilitat[ing] farm-to-hospital [programs], mobile food markets, and community-based food access.”
  • Montana is helping rural hospitals “right size” their services, which could entail eliminating some service offerings to improve hospitals’ financial sustainability.
  • Nevada is funding an expansion of its rural workforce, such as through provider recruitment incentives.

Permitted Uses

States must use funding for at least three of the following permitted uses.

  • Promote consumer tech solutions. For the prevention and management of chronic diseases. Examples include remote patient monitoring (e.g., through wearable devices), apps that connect patients with providers and health information, and digital health tools in community access points. States can also provide seed funding for innovative, high-impact tech solutions through a Rural Tech Catalyst Fund, subject to spending restrictions.
  • Support IT advances. Such as by expanding access to telehealth, upgrading or replacing electronic health record systems (replacements are subject to spending restrictions), facilitating health information exchange and interoperability, enhancing cybersecurity, and promoting artificial intelligence for clinical and administrative uses.
  • Provide training and technical assistance for technology that improves care delivery in rural hospitals. Such as for “remote [patient] monitoring, robotics, artificial intelligence, and other advanced technologies.”
  • Recruiting and retaining clinical workers. Such as by promoting health careers among local high school students, developing new residency and fellowship programs, offering advanced training for clinical workers, and providing tuition reimbursement or other incentives. Clinical workers who directly benefit must commit to serve rural areas for at least five years.
  • Improving prevention and chronic disease management. Such as through screening and early detection (e.g., mobile cancer screening), nutrition education, improving access to healthy food and to outdoor activities, early maternal and infant interventions (e.g., home visits), and care management programs.
  • Matching service offerings to local need. Such as by expanding access through telehealth, mobile units and satellite sites, strengthening emergency medical services, and providing non-medical transportation. This could also include “right sizing” delivery systems by eliminating services that cannot be sustained.
  • Paying providers for health care items or services. Provider payments are subject to a number of restrictions: they cannot exceed 15% of a state award in a given budget period, be used for short-term relief, supplement or duplicate existing funding sources (including Medicaid), or cover gender-affirming care or most abortion services. Examples of permitted uses include incentive payments for providers to improve quality or reduce costs.
  • Supporting innovative models of care. Including value-based care arrangements and alternative payment models. Such as by helping providers participate in the Achieving Healthcare Efficiency through Accountable Design (AHEAD) model (which, among other things, replaces traditional hospital reimbursement from multiple payers with global budgets for a given facility).
  • Investing in existing health care facility buildings and infrastructure. Investments cannot exceed 20% of a state award in a given budget period and cannot be used for new buildings or equipment. Examples include repairing existing buildings and equipment, minor renovations, interior modifications, upgrading lighting and electrical systems, and installing or upgrading security systems.
  • Fostering collaboration among providers. Such as through hub-and-spoke models (which connect anchor facilities, like larger regional hospitals, with local “spokes,” like clinics and small rural hospitals), shared services or group purchasing (e.g., of administrative services), or clinically integrated networks (groups of providers that join together to improve care and reduce costs without formally merging).
  • Supporting access to behavioral health care services. Such as through telehealth options, substance use disorder and opioid treatment, Certified Community Behavioral Health Clinics, and mobile crisis teams and centers.

States may also use up to 10% of their award in a given budget period on administrative expenses. Program restrictions listed above are not comprehensive.

Uses for Hospitals

Rural health funds are not just for hospitals, and there are restrictions on how hospitals can benefit.

While the fund emerged in response to concerns about the impact of the reconciliation law on rural hospitals, the extent to which it will benefit these facilities is unclear. States can choose how much of the funds will go to hospitals versus other rural providers and various other entities, such as contractors providing technical assistance, universities participating in workforce initiatives, regional health systems in urban areas collaborating with rural providers, and vendors developing new health technologies. Of the dollars going to rural hospitals, it is not yet clear which specific facilities will receive funding and the extent to which states will target resources to particular types of hospitals, such as those that are isolated or in financial distress. Additionally, hospitals that are not in rural areas can also receive funding, as long as it is to the benefit of rural communities and residents.

Initiatives could benefit hospitals to varying degrees. For example, uses of the funds that could more directly benefit hospitals include investing in existing hospital infrastructure (permitted within limits), strengthening collaboration among rural facilities and other providers, and supporting alternative payment models. Other initiatives, such as programs to promote health literacy and healthy behaviors, may have less direct or no obvious benefits for hospitals. The benefit to rural hospitals—and to other providers, patients, and rural communities—will also depend on how effective state initiatives are, which is difficult to predict. 

While funding could benefit hospitals in a number of ways, there are also limitations on how it can do so. For example, CMS guidance indicates that rural health funds cannot be used for:

  • Propping up struggling hospitals with temporary relief. The funds are not intended “to be used for perpetual operating expenses, but rather for investments…that will have sustainable impact beyond the end of the program,” according to CMS.
  • Payments to providers for care that exceed 15% of a state award in a given budget period. Payments to providers must be related to the strategic goals of the program, such as bonus payments for providing high-quality care, and cannot be used to supplement or duplicate existing funding, including payments from Medicaid or private insurance.
  • Construction, building expansion, or purchasing buildings, though they can be used for certain investments in existing rural health care facility buildings and infrastructure, not to exceed 20% of a state award in a given budget period.
  • Replacements for previous HITECH-certified electronic medical record (EMR) systems that exceed 5% of a state award in a given budget period.
  • Funds for gender-affirming care (a limitation that is not restricted to care for minors, as are many other federal measures) and reimbursement for most abortion services. There are also limitations related to “citizenship documentation requirements for payments made with respect to an individual.” Many hospitals do not currently collect patient immigration status but may need to do so to be reimbursed for patient care with rural health funds.

The rural health fund may help hospitals adapt to the loss of federal funding under the reconciliation law, though the extent to which it will do so is unclear. The reconciliation law made historic reductions in federal support for health care and is expected to result in an unprecedented increase in the number of people without health insurance. An increasing uninsured rate results in fewer patients with health coverage for hospital care, and an increase in the amount of uncompensated care hospitals provide. At the same time, the 2025 reconciliation law made significant changes to Medicaid financing that could result in major reductions to the rates Medicaid pays for hospital services in most states.

Just as it is unclear how much hospitals will benefit under the rural health fund, it is also hard to predict how much hospitals will lose due to spending cuts under the reconciliation law. As detailed below, the rural health fund is smaller than estimated cuts to federal Medicaid spending when looking at rural areas in aggregate, and most of the cuts will persist over time, in contrast to the rural health fund.

The hospital industry and some members of Congress have called for a greater focus on hospitals. The hospital industry has recommended that the rural health fund give greater priority to supporting rural hospitals, including by lifting restrictions on provider payments and capital investments. A group of Senators also recommended that the program focus more on rural hospitals and other rural providers and expressed concern that small rural providers will have a harder time vying with larger systems and organizations for funding. Increasing funding for rural hospitals would do more to address concerns about the financial standing of these facilities, an original motivation for the program, but would involve tradeoffs with competing initiatives.

How Does the Fund Compare to Medicaid Reductions?

Amount

The $50 billion rural health fund is smaller than the $137 billion in estimated cuts to federal Medicaid spending in rural areas included in the same law.

The $50 billion in new funding could offset a little over a third (37%) of the estimated cuts to federal Medicaid spending in rural areas ($137 billion over ten years) based on KFF analysis of CBO estimates from July 2025, or about 5% of the total estimated cuts to federal Medicaid spending ($911 billion over ten years). This does not account for other revenue losses related to the law, including cuts to federal spending for the ACA Marketplaces. Nor does it include revenue losses stemming from the increased number of people who will be uninsured because of the expiration of the enhanced ACA premium tax credits and the implementation of 2025 Marketplace integrity rules. The impact of all of these changes on rural areas, and the extent to which the rural health fund offsets losses, will vary across the country.  

The  Billion Rural Health Fund Is Smaller Than the Estimated Cuts to Federal Medicaid Spending in Rural Areas (7 Billion) Included in the Same Law (Column Chart)

Timing

Rural health funding will be available primarily from 2026 to 2030, while most of the federal Medicaid spending cuts will occur afterwards and persist over time.

While many of the major cuts related to Medicaid and the ACA Marketplaces under the law are not time limited, the rural health fund is temporary. The law provides $10 billion per year through the rural health fund for fiscal years 2026 through 2030, a five-year period. States will be allowed to spend funds that they receive at a given point through the end of the following fiscal year, and CMS will redistribute any unused funds over time, but all funds must be spent by the end of fiscal year 2032.  New legislation would be required to provide additional support to rural areas after the funds dry up.

Rural health funds will be made available before many of the health care spending cuts under the law are fully realized (Figure 2). The rural health fund was put in place to address concerns of lawmakers from rural states, and front-loading these dollars could allow rural communities to make progress in improving care delivery in advance of forthcoming cuts. As described above, funding will first be available for fiscal year 2026, with $10 billion dollars available per year over five years through fiscal year 2030, and all funds must be spent by the end of fiscal year 2032. Yet most of the health care spending reductions are backloaded and occur after fiscal year 2030. For example, based on KFF analysis of CBO estimates, nearly two thirds (64%) of the ten-year reductions in federal Medicaid spending would occur after fiscal year 2030.

Rural Health Funding Will Be Available Primarily From 2026 to 2030, While Most of the Federal Medicaid Spending Cuts Will Occur Afterwards and Persist Over Time (Column Chart)

How Are Funds Being Distributed Across States?

Approach

CMS is distributing half of the funds equally across states, a quarter based on measures of state need, and a quarter based on state initiative scores, state policy, and other factors.

The reconciliation law requires that half ($25 billion) of the rural health fund be distributed equally among states with approved applications while providing CMS with substantial discretion over how to distribute the second half ($25 billion). CMS refers to the former as “baseline funding” and the latter as “workload funding.” CMS is distributing workload funding (the second $25 billion) across all approved states based on 23 factors, weighted to varying degrees (see Appendix Table 3). CMS announced state awards from the $10 billion available for funding in the first year based on this approach and will use the same general approach in subsequent years.

The $50 billion rural health fund is being distributed as follows across all 50 states (CMS will use the same approach but for fewer states if it rescinds funding for some later on) (Figure 3):

  • Equal distribution. Half of the funding (50% or $25 billion) is being distributed equally across states, as required by law.
  • Measures of state need. A quarter of the funding (25% or $12.5 billion) is being distributed across states based on measures of state need, as specified by CMS (Appendix Figure 2 and Appendix Table 3).  Multiple measures have a rural focus, such as the size of the state’s rural population and the number of rural health facilities (a blend of hospitals and other facilities) in the state. Other measures are not explicitly focused on rural areas, such as hospitals’ uncompensated care as a percent of operating expenses and the share of hospitals in the state that receive Medicaid disproportionate share hospital payments (which are payments for hospitals that serve disproportionate numbers of people who are uninsured or enrolled in Medicaid). These factors were calculated once and will be used in all subsequent allocation periods (i.e., will not reflect changes over time, such as in uncompensated care).
  • State proposed initiatives. About one sixth of the funding (16% or $8.0 billion) is being distributed based on how state initiatives are scored. This reflects a qualitative review of the state’s plan and, in later years, the state’s progress in implementing the plan. Not all of the initiatives allowed under the rural health fund are being considered for the allocation, but CMS has laid out those that are being taken into account, such as initiatives related to population health clinical infrastructure, health and lifestyle, rural provider strategic partnerships, and talent recruitment.
  • Make America Health Again (MAHA) and other state policies. Eight percent of the funding ($3.8 billion) is being distributed based on whether a state has adopted, committed to adopting, or made progress towards adopting certain policies that are priorities of the Trump administration. Each of these policies reflect state-wide changes that are not specific to rural areas. Some of the policies are tied to the administration’s MAHA agenda, including requiring schools to reestablish the Presidential Fitness Test; prohibiting SNAP spending on non-nutritious items, like soda or candy; and requiring that nutrition be included in continuing medical education for physicians. Most other policies aim to promote competition among health care providers, such as by not having certificate of need (CON) laws, making it easier for providers to practice in multiple states, and providing an expansive scope of practice for nurse practitioners and other non-physicians.
  • Other factors. The remaining funds (1% or $0.7 billion) are being distributed based on other factors, such as the share of dual eligibles (people who have both Medicare and Medicaid) that are enrolled in plans integrating Medicare and Medicaid benefits and the quality of Medicaid and Children’s Health Insurance Program (CHIP) data reporting to CMS.
CMS Is Distributing 50% of the Funds Equally Across States, 25% Based on Measures of State Need, and 25% Based on State Initiative Scores, State Policy, and Other Factors (Donut Chart)

Amount

All 50 states were approved for funding, with first-year awards ranging from $147 million in New Jersey to $281 million in Texas.

States had a one-time opportunity to apply for funding and all states were approved, meaning that they are eligible for funding for all five years of the program. However, as noted above, CMS may choose to scale back, withhold, reduce, eliminate, or recover funding from a given state over time.

State awards for 2026, the first of five years, average $200 million, ranging from $147 million in New Jersey to $281 million in Texas (Figure 4). Differences in total awards across states in the first year (and most likely in future years) are modest relative to large differences in rural populations and rural health needs more generally. For example, Texas has about thirty times as many rural residents as New Jersey (4.3 million versus about 140,000) but is only receiving about twice as much funding in the first year ($281 million versus $147 million). Differences in total awards across states are relatively modest primarily because half of the rural health fund (50%) is being distributed equally across approved states, regardless of need. Because all states have been approved for funding, each is slated to receive $100 million from this half of the fund in 2026 and in each year from 2027 through 2030.

Texas, Alaska, and California are receiving the largest total awards in the first year. While Texas and California have the largest and fourth-largest rural populations in the country respectively, Alaska has the fifth-smallest rural population. Alaska received a relatively large award, at least in part, because a portion of the fund is being distributed to the five largest states based on land area. Alaska also received the largest award from the pool based on state initiatives, state policy, and other funding factors according to estimates from the UNC Sheps Center (see Appendix Figure 3). New Jersey, Connecticut, and Rhode Island are receiving the smallest awards in the first year. These are all states with relatively small rural populations.

Figure 4

Amount per Rural Resident

First-year awards per rural resident vary widely, ranging from less than $100 in ten states to more than $500 in eight.

State awards are partially, but not closely, tied to rural population, meaning that first-year awards per rural resident are generally relatively small among states with the largest rural populations (Figure 5). For example, Texas has the largest rural population in the country—and the largest total award in the first year—but received the smallest award per rural resident ($66 in 2026). In contrast, states like Rhode Island, New Jersey, and Alaska, with far fewer rural residents, received substantially higher amounts per rural resident ($6,305, $1,069, and $990 respectively, with Rhode Island being an extreme outlier).

First-Year Rural Health Fund Awards Range From Less Than 0 Per Rural Resident in Ten States to More Than 0 in Eight States (Choropleth map)

How Are Funds Being Distributed Within States?

Distribution Within States

It remains to be seen how states will distribute funding across various entities and activities

CMS is tracking the flow of state funding to different entities and activities and will have information about all first-year state obligations to direct recipients towards the end of 2026. CMS is collecting information from states about the distribution of funding across entities and permitted uses (see above) as part of states’ annual and quarterly reporting process. Recipients of state funding will be categorized into standardized groups, including different types of health care providers, state and local government agencies, tribal entities, educational organizations, health IT vendors, other consultants, and other entity types. Beginning with the first quarterly report, CMS will begin tracking the flow of dollars downstream (e.g., if a state pays a contractor to manage a program, and the contractor then sends a portion of the funds to a rural hospital). States are required to obligate first-year funding by October 30, 2026, meaning that all first-year obligations to direct recipients of the funding should be captured in the first quarterly report, due November 29, 2026.

Some information about how states plan to distribute funding are available through approved plans and budgets, but with much less detail.

Some groups have called for greater transparency around funding streams. CMS will release progress reports to the public upon request but does not plan to do so proactively. Obtaining information through a Freedom of Information Act (FOIA) request, if required, could be a long and arduous process. The Bipartisan Policy Center recommended that CMS make key information easily available to the public, such as through an online dashboard. The hospital industry has also recommended greater public reporting as well as collecting additional information, such as existing hospital identifiers, which could facilitate oversight of the types of hospitals receiving funding.

Transparency around state funding will likely be of interest for policymakers, journalists, and researchers as they seek to track where funds are going, who is benefiting, and how effective they are.

Changes Over Time

The distribution of funding across and within states will change over time.

CMS has broad leeway to change the distribution of funding across states in later years, though it is unclear how much it will use its discretion. As described, CMS has broad discretion to withhold, reduce, eliminate, or recover funding over time as it sees fit (e.g., if a state has not made satisfactory progress). If CMS does not do so, changes in state awards in later years could be modest, given that most of the funding is locked in place over time based on statute and CMS guidance (see above).

Funding priorities may shift over time as states learn what does and does not work. The head of CMS, Dr. Mehmet Oz, indicated that states were given room to be creative with their applications, and that the expectation is that states will learn from both program successes and failures over time. States may adjust the details of their work plans but cannot significantly change their underlying strategy according to guidance from CMS. However, it is possible that CMS could reduce funding for states with less successful initiatives over time (see above) or work with states to shift their funding towards more successful programs.

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

Distribution of Funding by Factor

This brief identifies the share of the $50 billion rural health fund that is being distributed based on an equal distribution across states; measures of state need, initiatives, and policies; and other factors (Figure 3). The reconciliation law specifies that half of the fund ($25 billion) must be distributed equally across states, while CMS has indicated that it is distributing the second half ($25 billion) among approved states based on a set of 23 factors, weighted to varying degrees (see Appendix Table 3). CMS refers to the former as “baseline funding” and the latter as “workload funding.” While CMS considers all 23 factors in each year, its calculations for 2 of the 23 factors change beginning in the second year of the program; this brief describes the distribution of funding as of the second year of the program.

The distribution of workload funding ($25 billion) across different categories of factors was calculated based on CMS weights. CMS is scoring some factors (health and lifestyle, individuals dually eligible for Medicare and Medicaid, remote care services, and data infrastructure)—representing $3.75 billion of the $50 billion rural health fund—by evaluating how states rank based on a weighted average of measures from two buckets. For example, health and lifestyle factors are being evaluated based on the state rank of a weighted average of their score on certain state initiatives (75%) and the adoption of a certain policy (25%). The contribution of each bucket in those cases cannot be fully disentangled because of the structure of the calculation, which involves a ranking of a weighted average. In those cases, funding based on these factors was apportioned to each bucket based on the weights used to generate the weighted average (e.g., 75% or 25%).

First-Year State Awards

First-year state awards from the rural health fund (Figure 4) were obtained from the HHS Tracking Accountability in Government Grants System (TAGGS). First-year awards per rural resident (Figure 5) were calculated based on the HRSA definition of “rural”, which CMS uses to allocate a portion of the rural health funds. This definition includes all nonmetropolitan areas as well as some parts of metropolitan areas. Rural population, as defined by HRSA, by state was obtained from the UNC Sheps Center Rural Facility and Population Score Estimates by State, as updated on October 24, 2025.

This brief also describes the estimated first-year awards based on each of the seven measures of state need (Appendix Figure 1), which CMS refers to as “rural facility and population factors.” Appendix Table 3 includes details about these factors. We obtained estimated scores by state for each of these factors and their weighted total by state from the Sheps Center Rural Facility and Population Score Estimates by State. The Sheps Center generated these estimates based on their interpretation of CMS’s Notice of Funding Opportunity (NOFO) and available data. We converted estimated scores for a given factor into a dollar amount by: (1) calculating the share of workload funding in the first year distributed based on that factor (i.e., multiplying $5 billion by the weight for that factor) and (2) multiplying the result by the state share of the distribution based on that factor (i.e., the score divided by 100). Each state’s total distribution from the $2.5 billion based on state need in the first year is the sum of the factor allocations calculated in (2).

Finally, the brief describes estimated first-year awards based on state initiatives, state policy, and other factors (Appendix Figure 3). These numbers were pulled directly from the Sheps Center Funding Amounts and State Policy Actions, as updated on January 8, 2026. The Sheps Center estimated this amount for each state by starting with a given state’s first-year award and subtracting out the allocation distributed equally across states ($100 million per state) and the estimated allocation based on measures of state need.

First-Year Awards by Factor

The five states with the largest land areas received the largest estimated awards in the first year from the pool based on measures of state need.

These five states (Texas, California, New Mexico, Montana, and Alaska) received an estimated $88 to $105 million in the first year from the quarter of funding based exclusively on measures of state need compared to the $50 million states received on average from this pool (Appendix Figure 1). Most of the extra dollars that these five states are estimated to have received relative to other states reflects the fact that a portion of funding is earmarked for them based on their large land area (see below). CMS intends to use the same data and measures for distributing funding based on state need over time.

Appendix Figure 1

Based on criteria published by CMS, the funding tied to measures of need ($2.5 billion in the first year and $12.5 billion in total) is being distributed as follows (Appendix Figure 2):

  • Rural population and rural facilities. 40% of the $12.5 billion is based on the rural population and number of rural health care facilities in a state (20% each). CMS has published how it defines “rural” for purposes of distributing these dollars, though there are many potential ways of doing so. For example, CMS uses a broad definition of “rural hospitals” that includes all hospitals in areas classified as rural by the Health Resources & Services Administration (HRSA) (which itself is broader than some definitions) as well as any other hospital that receives certain Medicare rural payment designations or that is classified by Medicare as urban but reclassified as rural for certain payment purposes.
  • Uncompensated care as a percent of hospital operating expenses. 20% of the $12.5 billion is based on this measure, which is among all hospitals (i.e., not just those in rural areas). Uncompensated care tends to be higher in states that have not expanded Medicaid under the Affordable Care Act, such as Texas and Georgia. Further, CMS is using data from 2021; uncompensated care may have dropped over time among states that have recently expanded Medicaid (like Oklahoma and Missouri in 2021 and North Carolina and South Dakota in 2023).
  • Percent of population in rural areas and percent in frontier regions. 24% of the $12.5 billion is based on these measures (12% each). These factors do not account for the total size of the population in each state or the size of rural health care systems (which is also the case for three other factors, like land area). As a result, states with a relatively large share of the population living in rural and frontier areas but relatively small rural populations and few rural hospitals may still receive a greater than average share of these dollars (e.g., as is the case for Alaska, North Dakota, and Wyoming) while the reverse may be true for states with large rural populations and many rural hospitals (e.g., as is the case for California, Florida, and Texas). Nonetheless, as noted above, 20% of the $12.5 billion is based directly on rural population and 20% on rural facilities.
  • Land area. 10% of the $12.5 billion is based on land area and is only going to the five largest states. These five states will each receive large allocations from this pool (ranging from an estimated $240 to $260 million if all five continue to receive funding), while states just outside of the top five and all other states will not receive funds based on land mass.
  • Percent of hospitals receiving Medicaid disproportionate share hospital (DSH) payments. 6% of the $12.5 billion is based on this measure, which is among all hospitals (not just those in rural areas). Medicaid DSH status is based in part on the extent to which hospitals care for Medicaid and other low-income patients but also on specific criteria that vary across states.
Factors for Determining the Allocation of the .5 Billion of the Rural Health Fund Based on CMS Measures of State Need (Donut Chart)

Estimated awards in the first year based on state initiatives, state policies, and other factors ranged from $21 million in New Mexico to $84 million in Alaska.

Alaska, Texas, Nebraska, New Hampshire, and Hawaii received the largest estimated awards from this pool in the first year, ranging from $65 million to $84 million compared to the $50 million states received on average. This is a diverse group of states. For example, Alaska has the fifth-smallest rural population in the country (about 275,000) while Texas has the largest (about 4.3 million), and President Trump carried three of these states in the 2024 presidential election (Alaska, Nebraska, and Texas) but lost two (Hawaii and New Hampshire). The distribution of these dollars will change over time, for example, based on states’ progress on their proposed initiatives and on fulfilling policy commitments made in their applications.

Appendix Figure 3

Appendix Tables

Permitted Uses of the Rural Health Fund (Table)
Strategic Goals of the Rural Health Fund (Table)
Factors for Determining the Allocation of the Second Half ( Billion) of the Rural Health Fund (Table)

State Fiscal Conditions: Context on Medicaid Budgets for FY 2027

Published: Sep 18, 2026

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 through a federal matching program with no cap. Overall, the federal government typically pays about two-thirds of total Medicaid costs and states pay one-third, though the matching rate varies by state. States also have flexibility to determine how to finance their share of Medicaid payments, within certain limits. Flexibility in administration and financing results in variation in Medicaid eligibility, benefits, and provider payments across the nation.

Medicaid funding is often central to overall state budgetary decisions as it is simultaneously a significant spending item as well as the largest source of federal revenues for states. According to data from the National Association of State Budget Officers (NASBO), in state fiscal year (FY) 2025, Medicaid accounted for 31% of total state spending for all items in the budget. Medicaid accounted for only 17% of expenditures from state funds (including general funds and other state funds) but accounted for 57% of all expenditures from federal funds.

State fiscal conditions are tightening due to slowing revenue growth and increased spending pressures. This, combined with other budgetary pressures, like the implementation of the 2025 reconciliation law that includes significant reductions in federal Medicaid spending, may increase the likelihood of states enacting Medicaid restrictions. This brief describes current fiscal conditions using the latest state revenue and spending data from NASBO and analyzes how these conditions may impact states’ Medicaid budget decisions going forward.

States continue to experience slow revenue growth following pandemic-era highs (Figure 1). State economic conditions worsened rapidly when the pandemic hit but recovered quickly, leading to a period of record-breaking revenue and spending growth for states. However, tax cuts combined with inflationary pressures, stock market volatility, and changes in consumer consumption patterns led to slowing state revenue growth in FY 2023 through FY 2026. While many states ended FY 2026 with revenues above projected amounts, estimated total revenue growth was 2% compared with 5% in FY 2025, and many states saw declines in revenue collections. States’ enacted budgets for FY 2027 are based on projections of another fiscal year of revenue growth between 2-3%. In addition, recent data along with federal policy changes that impact tax codes and reduce federal funding suggest long-term weakness that may present challenges in future years.

General fund spending growth has also moderated in recent years. Spending growth generally follows trends in revenue growth because states generally need to enact balanced budgets. Similar to revenue trends, spending growth peaked in FY 2022 at 14% and then moderated from FY 2023 through FY 2026 (Figure 1). Estimated total general fund spending growth was 8% in FY 2026, and enacted FY 2027 budgets on average included spending growth between 2-3%, indicating that spending growth continues to slow. Rather than expanding state services and committing to new spending items, recently enacted budgets focus on funding for core services and targeted spending adjustments to maintain balance between ongoing revenue and recurring spending items, highlighting the tightening fiscal environment and future uncertainty.

General Fund Revenues and Spending Have Slowed Following Pandemic-Era Highs (Line chart)

How do fiscal conditions vary across states?

State revenue growth varies by state, with 20 states experiencing revenue declines in FY 2026 (Figure 2). At the same time, 30 states had revenue increases above 0% but below 10% and one state saw revenue increases over 10% in FY 2026. On average across states, general fund revenues increased by 2% from FY 2025 to FY 2026. State general fund revenues are mostly comprised of personal income, corporate income, and sales taxes, and revenue growth varies depending on state policy decisions and reliance on tax types. Strong revenue collections from personal income tax have driven the modest revenue growth seen in recent years, though several states have recently enacted cuts to income tax rates which could impact future revenue growth.

In addition, 11 states experienced reductions in general fund spending in FY 2026. This is notable because state spending must typically increase to keep pace with rising costs – particularly in a period of high general inflation – and signals some states have implemented targeted spending cuts or other budget maneuvers. In FY 2026, five states had to enact mid-year budget cuts to avoid shortfalls, which is a small share but the most that have done so since FY 2021. A majority of states (34) had modest general fund spending growth above 0% but below 10%, and six states saw spending growth over 10% from FY 2025 to FY 2026. On average across states, general fund spending increased by 8% in FY 2026. FY 2027 enacted budgets include more budget management strategies like spending cuts or other cost containment measures, with some states reducing spending levels from FY 2026.

General Fund Revenue and Spending Growth Vary by State (Column Chart)

While most states have rainy day funds, balances varied significantly by state and had fallen slightly from pandemic-era highs in FY 2026 (Figure 3). Pandemic-era growth in tax revenues left states with large revenue surpluses over multiple fiscal years. Some of these funds were transferred to rainy day funds that reached record high balances. As revenues moderated, states spent surplus funds, largely on one-time expenditures, or used other one-time budget maneuvers to balance their budgets. By FY 2026, rainy day funds remained elevated but had fallen from their pandemic-era peak, ranging from less than 10% of general fund spending in 17 states to over 30% in three states. General fund ending balances as well as total balances, which include both general fund ending balances and rainy day funds, have also decreased, softening states’ ability to rely on savings. While most states plan to increase or maintain rainy day funds in FY 2027, general fund ending balances and total balances are expected to continue to decline as states spend down prior-year surplus funds.

Most States Maintain Rainy Day Fund Balances Over 10% of General Fund Spending (Choropleth map)

What factors will affect state budgets in FY 2027 and beyond?

State budget priorities may shift after the 2026 elections. As constituents struggle with the cost of living, state legislatures may opt to provide relief through enhancing social support or by enacting tax relief, though both options may become more difficult as fiscal conditions tighten. States are also contending with increasing spending demands from Medicaid, employee health care, education, housing, and disaster response. Following 2026 elections, new governors may shift priorities reflected in state budgets. Of the 37 states with gubernatorial elections (including DC’s mayoral election), there are 19 states where the incumbent is not running and a new governor or mayor may be elected. New governors’ administrations often bring in new policy priorities, new agency staff, and different implementation approaches that may be reflected in future budgets.

Economic changes and recent federal actions, including the passage of the 2025 reconciliation law, create additional budget uncertainty. States’ fiscal outlooks may be affected by continued inflationary pressures and slowing consumer spending. States are also facing uncertainty about tariffs, increasing national debt, and a fluctuating job market. In addition, the 2025 reconciliation law includes significant policy changes and federal funding cuts, such as tax code changes as well as Medicaid and SNAP funding cuts. The implementation of the reconciliation law’s provisions also requires costly administrative and systems changes for many states.

In response to mounting budget pressures and the 2025 reconciliation law, states may reduce Medicaid spending. The combination of tighter state fiscal conditions, other economic factors, and the implementation of the 2025 reconciliation law may result in state reductions to Medicaid spending. The impact of the 2025 reconciliation law will vary across states based on expansion status and reliance on provider taxes and state-directed payments. States have limited options to respond to reductions in federal Medicaid spending (Figure 4). States may try to raise additional revenues or reduce spending in other areas of the budget, though this is likely challenging given tightening state fiscal conditions. Instead, states may seek to restrict Medicaid provider reimbursement rates, benefits, or eligibility to reduce state Medicaid spending. A few states had already implemented Medicaid spending cuts for FY 2026 (and proposed cuts for FY 2027), and Medicaid cuts may ramp up as more provisions of the 2025 reconciliation law are implemented.  

Figure 4

State and Federal Reproductive Rights and Abortion Litigation Tracker

Last updated on

The Supreme Court’s Dobbs ruling, overturning Roe v. Wade, returned the decision to restrict or protect abortion to states. In many states, abortion providers and advocates are challenging state abortion bans contending that the bans violate the state constitution or another state law. Additionally, new questions have arisen regarding the intersection of federal and state authority when it impacts access to abortion and contraception.

This litigation tracker presents up-to-date information on the ongoing litigation in state and federal courts involving access to contraception and abortion. Use the buttons below to navigate between cases related to: Pregnancy and Work, Emergency Care, Family Planning, Privacy, Medication Abortion, Minors Access, and State Abortion Bans. 

Litigation Involving Reproductive Health and Rights in the Courts, as of September 16, 2026 (Table)

Women’s Experiences Accessing Health Information Online: Trusted Sources and Contraceptive Information

Findings from the 2026 KFF Women's Health Survey

Published: Sep 16, 2026

The internet, social media, and artificial intelligence (AI) have all changed the way people share and research health information. All of these platforms can make health information extremely accessible but also can increase the ability of misinformation to spread rapidly. KFF has been tracking these dynamics through its extensive polling work on Health Information and Trust. The KFF Women’s Health Survey, a nationally representative survey of 4,688 women and 1,148 men ages 18 to 64 fielded between March 11, 2026 and April 14, 2026, asked people whether they have used these platforms to look for health information or advice and whether they trust the information they are receiving.  This brief focuses on reproductive age (18 to 49) women (n = 3,538) and men (n = 840). It also looks at exposure to false and misleading information about contraception and assesses changes in contraceptive use in response to online information among reproductive age women.   

Accessing Health Information

  • The majority of reproductive age people ages 18 to 49 have looked for health information online, and large shares seek mental health information. Most reproductive age women (83%) and men (81%) have looked for health information or advice through an internet search engine in the past year, while four in ten have used an AI tool or chatbot or social media. Nearly half of women (47%) and men (42%) ages 18 to 49 have sought information on mental health. This rises to 57% of women and 54% of men ages 18 to 25 who have sought information on mental health. Almost half (46%) of women ages 36 to 49 have looked for information about menopause, and over a quarter (27%) of all men (ages 18 to 49) have sought information on testosterone.  
  • Health care providers remain the most trusted sources for reliable health care information for reproductive-age women despite widespread use of online sources and social media. Health care providers are the most trusted source for reliable health care information among reproductive age women (85% say they trust them a great deal or a fair amount), while one in four say they trust AI tools and chatbots (25%) for reliable health information and fewer (14%) trust social media and social media influencers. About half (48%) of women trust federal health agencies for reliable health care information and 26% trust the head of Health and Human Services (HHS), Robert F. Kennedy Jr. Higher shares of Democratic women trust their health care provider, state and local health departments and Federal health agencies compared to Republican women, while higher shares of Republican women trust Robert F. Kennedy Jr. And AI tools and chatbots compared to Democratic women.  

Contraception on Social Media 

  • Regardless of whether they sought it out, a higher share of younger women has seen or heard information about contraception on social media compared to their older counterparts. One in three (35%) women of reproductive age have seen or heard something about contraception on social media in the past 12 months, rising to 42% of younger women (ages 18 to 25). 
  • Younger women (18 to 25) are more likely than women ages 36 to 49 to talk to their doctor, seek more information online, or change their contraceptive behavior based on something they saw on social media. Among women who saw or heard something about contraception on social media, larger shares of young women ages 18 to 25 compared to women ages 36 to 49 stopped using their hormonal birth control method (12% vs. 5%), started or changed to a new birth control method (13% vs. 6%), sought more information from a doctor or healthcare provider (26% vs. 15%), or sought more information through an online search or AI (46% vs. 29%). 

Exposure to False or Misleading Statements About Contraception 

Large shares of reproductive age women report being exposed to false and misleading statements about contraception. About half (53%) of women of reproductive age say they have seen or heard the false statement that hormones in contraceptives are harmful to your health on social media or elsewhere and about four in ten (43%) have been exposed to the false claim that hormones in contraceptives limit your ability to get pregnant in the future. About one in three (32%) have heard that natural family planning methods are as effective as hormonal contraceptives at preventing pregnancy (when it is less effective) and emergency contraceptive pills, such as Plan B, cause abortions (emergency contraceptive pills do not end a pregnancy).  

Accessing Health Information  

The majority of reproductive age women (87%) and men (86%) have looked for health information or advice online either through an internet search engine, social media, or AI tools. Most reproductive age women (83%) and men (81%) have used internet search engines, such as Google or Bing, in the past year to look for health information or advice (Table 1). Women are more likely than men to use social media to search for health information (44% vs. 38%) but are as likely to look for health information through an AI tool or chatbot such as ChatGPT, Google Gemini, or Claude (42% for women vs. 46% for men). Nearly one in four (24%) women say they have used all three methods — internet search engines, AI tools, and social media — to search for health information (data not shown).

Table 1 shows the share of women ages 18 to 49 who say they have looked for health information or advice from an AI tool or chatbot (42%), social media platforms (44%), or an internet search engine (83%) in the past year. The table compares women and men ages 18 to 49. Larger shares of reproductive age women have looked for health information or advice on social media platforms compared to men. Among women ages 18 to 49 the table presents data by age, race/ethnicity, and income. Larger shares of younger women less than age 36 have looked for health information or advice through social media platforms compared to women ages 36 to 49.

Larger shares of Asian (55%) and Hispanic (44%) women say they used AI tools or chatbots for health information in the past year compared to White women (39%).  In general, smaller shares of people report using social media platforms for health information or advice. However, half of Asian (50%) and Hispanic (48%) women report looking for health information or advice on social media compared to four in ten White women (41%). Over half (53%) of women ages 18 to 25 also report using social media for health information. Larger shares of women with low incomes looked for health information on social media compared to women with higher incomes (48% vs. 41%). This aligns with previous KFF polling findings that have found younger adults and adults with lower incomes are more likely to use social medial for health information and are more likely to say they do so because they can’t afford to see a provider or don’t have a regular provider.  

The survey asked whether individuals sought information about different health topics through these various platforms and nearly half of reproductive age women say they sought information about mental health (47%) (Table 2). This rose to 57% of women ages 18 to 25. A quarter of women of reproductive age (26%) sought information about menopause online, but almost half (46%) of women between the ages of 36 and 49 looked for this information online. Three in ten women of reproductive age (30%) say they looked for information about pregnancy and childbirth. However, among women who were pregnant or gave birth in the past three years, seven in ten (71%) report seeking information about pregnancy and childbirth online (data not shown in table). One in three (33%) women ages 18 to 25 sought information about contraception and one in six (18%) sought information about abortion.

Table 2 is titled "Nearly Half of Young Women and Men Sought Information on Mental Health Online, While Almost Half of Women Over Age 36 Looked for Information on Menopause." This table shows certain topics that men and women sought information about online from AI, social media, or internet search engines. Of the topics asked about, the largest share of men and women sought information about mental health.

Slightly smaller shares of reproductive age men sought health information through social media (38% vs. 44%) compared to women, but similar shares looked for information via internet search engines (81% vs. 83%) and AI tools and chatbots (46% vs. 42%). Of the health topics the survey asked about, the largest share of reproductive age men sought information about mental health (42%), including over half (54%) of men ages 18 to 25 and 47% of men ages 26 to 35. Over a quarter (27%) of men looked for information about testosterone levels and 16% searched for information about erectile dysfunction. Not surprisingly, fewer men than women looked for information about pregnancy and childbirth, but nearly one in four (22%) men ages 26 to 35 did. One in ten (10%) reproductive age men sought information about vasectomies and 6% of men looked for information about abortion, although 13% of men ages 18 to 25 looked for information on abortion.

Contraception on Social Media  

Regardless of whether they sought it out, one in three (35%) women of reproductive age have seen or heard something about contraception on social media in the past 12 months, with larger shares of younger women reporting exposure (Figure 1). Social media has become a common place for people to view information about contraception. Of those who have seen or heard something about contraception on social media, 78% report using contraception in the past 12 months with the majority using hormonal methods (62%) (data not shown). A larger share of contraceptive users report seeing information about contraception on social media compared to non-contraceptive users (38% vs. 27%). 

Figure 1 is a stacked horizontal bar chart among women ages 18 to 49 titled "One in Three Reproductive Age Women Say They Heard or Saw Something on Social Media About Birth Control." The green bar shows the share of reproductive age women who have seen or heard anything on social media about contraception (35%), the dark blue bar is the share of reproductive age women who have not seen or heard anything on social media about contraception (46%), and the light blue bar shows the share of reproductive age women who are not sure if they have seen or heard anything on social media about contraception (19%). Larger shares of women ages 18 to 25 (42%) and 26 to 35 (39%) compared to women ages 36 to 49 (28%) have seen or heard something about contraception on social media in the past 12 months, as well as contraceptive users (38%) compared to contraceptive non-users (27%). Smaller shares of Asian (30%), Black (30%), and Hispanic (33%) women have seen or heard anything on social media about contraception compared to White women (38%).

Contraceptive information seen online can lead women to seek more information or make a change to the contraceptive practices. One in ten women who saw contraceptive information on social media said they changed their contraceptive use behavior, such as stopping their hormonal birth control (8%, 3% of all women ages 18 to 49) or starting or changing to a new birth control method (9%, 3% of all women ages 18 to 49), one in five (19%) who saw contraceptive information (7% of all women ages 18 to 49) talked to a doctor or health care provider about what they saw or heard, and a third (36%) sought more information through an online search or AI (12% of all women ages 18 to 49) (Figure 2). Larger shares of young women ages 18 to 25 compared to women ages 36 to 49 stopped using their hormonal birth control (12% vs. 5%), started or changed to a new birth control method (13% vs. 6%), sought more information from a doctor or healthcare provider (26% vs. 15%), or sought more information through an online search or AI (46% vs. 29%). 

Figure 2 is a grouped vertical bar chart titled "One in Ten Younger Women Who Have Seen Something About Contraception On Social Media Have Made a Change to Their Contraceptive Use" and shows women overall ages 18 to 49 in gray, women ages 18 to 25 in green, women ages 26 to 35 in blue, and women ages 36 to 49 in dark blue. Among women who have seen or heard something on social media about contraception, one in three (36%) have sought more information through an online search or AI, one in five (19%) have talked talked to a doctor or health care provider about what they saw or heard, and one in ten (12%) have stopped using hormonal birth control or started or changed to a new birth control method. Higher shares of younger women ages 18 to 25 have done all of these things compared to women ages 36 to 49.

False or Misleading Statements About Contraception 

Many women report seeing content on social media or elsewhere that promotes contraceptive misinformation. The survey asked whether women had seen or heard four widely spread pieces of contraceptive misinformation (Table 3). About half (53%) of women of reproductive age had seen or heard that hormones in contraceptives are harmful to your health and about four in ten (43%) had seen or heard that hormones in contraceptives limit your ability to get pregnant in the future. Women of color report lower exposure to hearing that hormones are harmful, while larger shares of young women had been exposed to this false statement.

Table 3 is titled "False or Misleading Statements About Contraception Are Widespread" and shows the share of women ages 18 to 49 who have heard or read four false or misleading statements about contraception, including: hormones in contraceptives are harmful to your health (53%), hormones in contraceptives limit your ability to get pregnant in the future (43%), natural family planning methods are as effective as hormonal contraceptives at preventing pregnancy (32%), and emergency contraceptive pills, such as Plan B, cause abortions (32%). Higher shares of young women ages 18 to 25 and 26 to 35 compared to women ages 36 to 49 have heard or read that hormones contraceptives are harmful to your health and hormones in contraceptives limit your ability to get pregnant. Lower shares of of Asian women have heard or read all four false and misleading statements and lower shares of Black and Hispanic women have heard or read that hormones in contraceptives are harmful to your health. Women with low incomes were less like to have heard or read that hormones in contraceptive are harmful to your health, but more likely to have heard that emergency contraceptive pills, such as Plan B, cause abortions. There were no differences by party ID.

Natural family planning or fertility awareness-based methods have been promoted on social media to appeal to people who erroneously think hormones are harmful to your health or those who are seeking non-hormonal methods. One in three (32%) reproductive age women say they have seen or heard that natural family methods are as effective as hormonal contraceptives at preventing pregnancy. Natural family planning methods fall under fertility awareness-based methods, which the American College of Obstetricians & Gynecologists say are 77%-98% effective at preventing pregnancy, whereas hormonal contraceptives are 93-99.9% effective.  

One in three (32%) reproductive age women have seen or heard on social media that emergency contraceptive pills, such as Plan B, cause abortions, which is also untrue. Emergency contraceptive pills cannot terminate an existing pregnancy, cannot prevent the implantation of a fertilized egg, and cannot affect a developing embryo.  

Trusted Sources for Health Care Information 

When asked who they trust to provide reliable health information, the majority of reproductive age women say they trust their health care provider a great deal or fair amount (86%) slightly higher than 79% of reproductive age men (Figure 3 and Table 4). While trust in health care providers is consistently highest across different groups, it declines slightly among lower income groups (Table 4). Over half (55%) of all women also say they trust state and local health departments and even higher shares of Asians (63%) and Democrats (64%) trust these sources.  

The survey also finds one quarter (25%) of reproductive age women trust AI tools and chatbots a great deal or a fair amount for reliable health information, which is similar across demographic groups. A higher share of reproductive age Asian women trust AI tools or chatbots. Few women trust social media and social media influencers (15%) for reliable health care information; however, this rises to over one in five (21%) 18- to 25-year-women.

Figure 3 is a stacked horizontal bar chart titled "Reproductive Age Women Trust Health Care Providers the Most to Provide Reliable Health Care Information" with "A great deal" colored dark blue, "A fair amount" colored blue, "A little" colored green, and "Not at all" colored dark green. The majority of women ages 18 to 49 trust their health care provider and state and local health departments a great deal or fair amount to provide reliable health care information. Women trust social media and AI tools or chatbots the least to provide reliable health care information, with majorities of women also having little trust in federal health agencies and Robert F. Kennedy Jr.

About half (48%) of women ages 18 to 49 trust federal health agencies a great deal or fair amount for reliable health care information (Figure 3). This comes after a year of significant layoffs of federal health workers and changes to federal health websites like the Centers for Disease Control and Prevention (CDC) and Health and Human Services (HHS). About a quarter (26%) of reproductive age women say they trust the head of HHS, Robert F. Kennedy Jr. to provide reliable health care information.

Table 4 show the share of reproductive age women who trust each of the following a great deal or fair amount to provide reliable health care information: your health care provider (86%), state and local health departments (55%), federal health agencies (48%), Robert F. Kennedy Jr. (26%), AI tools or chatbots (25%), and social media and social media influencers (15%). Larger shares of women trust their health care providers to provide reliable health care information compared to men (86% vs. 79%). Young women ages 18 to 25 are more likely to trust social media and social media influencers compared to women ages 36 to 49 (21% vs. 12%). Smaller shares of Black and Hispanic women trust their health care provider compared to White women and larger shares of women of color trust AI tools or chatbots and social media and social media influencers compared to White women. Smaller shares of women with low incomes trust their health care providers and state and local health departments compared to women with higher incomes. Republican women were also less likely to trust their health care providers, state and local health departments, and federal health agencies compared to Democratic women and more likely to trust Robert F. Kennedy Jr. and AI tools or chatbots.

Contraception: False or Misleading Statements Compared to What the Experts Say (Table)

The 2026 KFF Women’s Health Survey was designed and analyzed by women’s health researchers at KFF. The survey was conducted from March 11 – April 14, 2026, online and by telephone among a nationally representative sample of 5,854 adults ages 18 to 64, including 3,538 women ages 18 to 49. Women include anyone who selected woman as their gender. Sampling, data collection, weighting, tabulation, and IRB approval by the University of Southern Maine’s Collaborative Institutional Review Board were managed by SSRS of Glenn Mills, Pennsylvania in collaboration with women’s health researchers at KFF.

Throughout the reports of findings, we refer to “women.” This includes respondents who said their gender is “woman,” and includes those who selected “woman” in addition to another gender, such as “transgender,” or “non-binary,” or another gender. We followed this approach to try to include as many people as possible but recognize that some people who need and seek abortion and other reproductive health care services may not be represented in the findings or identify as women. Some questions about sexual and reproductive health were only asked among those with a specific sex assigned at birth (i.e. male or female).

The national sample was drawn from two nationally representative probability-based panels: the SSRS Opinion Panel and the Ipsos Knowledge-Panel. The SSRS Opinion Panel is a nationally representative probability-based panel where panel members are recruited randomly in one of two ways: (a) Through invitations mailed to respondents randomly sampled from an Address-Based Sample (ABS) provided by Marketing Systems Groups (MSG) through the U.S. Postal Service’s Computerized Delivery Sequence (CDS); (b) from a dual-frame random digit dial (RDD) sample provided by MSG. For the online panel component, invitations were sent to panel members by email followed by up to five reminder emails. 5,660 panel members completed the survey online and panel members who do not use the internet were reached by phone (n=194). Another 514 respondents were reached online through the Ipsos Knowledge Panel to help reach adequate sample sizes among subgroups of interest, specifically women ages 18 to 49. This panel is recruited using ABS, based on a stratified sample from the CDS. The questionnaire was translated into Spanish, so respondents were able to complete the survey in English or Spanish. 

The national sample was weighted by splitting the sample into three groups: [1] Women 18-49, [2] Women 50-64, and [3] Men 18-64 and each group was separately weighted to match known population parameters (see table below for weighting variables and sources). Weights within the three groups were then trimmed at the 4th and 96th percentiles, to ensure that individual respondents do not have too much influence on survey-derived estimates. After the weights were trimmed, the samples were combined, and the weights adjusted, so that the groups were represented in their proper proportions for a final combined, gender by age-adjusted weight.

DimensionsSource
AgeCurrent Population Survey 2025
Education
Age by Education
Age by Gender
Census Region
Race/Ethnicity by Nativity
Home Tenure
Civic Engagement2023 CPS Volunteering and Civic Life Supplement
Internet FrequencyPew Research Center’s National Public Opinion Reference Survey (NPORS 2025)
Population DensityClaritas Pop-Facts Premier 2026
Voter RegistrationCPS 2024 Voting and Registration Supplement

The margins of sampling error for the national sample of women ages 18 to 64 and reproductive age women ages 18 to 49 are plus or minus 2 percentage points. Numbers of respondents and margins of sampling error for key subgroups are shown in the table below. For results based on other subgroups, the margin of sampling error may be higher. Sampling error is only one of many potential sources of error and there may be other unmeasured error in this survey.

GroupN (unweighted)M.O.S.E.
National Women Ages 18-493,538± 2 percentage points
White, non-Hispanic1,536± 3 percentage points
Black, non-Hispanic620± 5 percentage points
Hispanic944± 4 percentage points
Asian or Pacific Islander304± 6 percentage points
<200% FPL1,300± 3 percentage points
200%+ FPL1,949± 3 percentage points
Private2,117± 3 percentage points
Medicaid785± 4 percentage points
Uninsured456± 6 percentage points
Democrat/Democrat leaning1,752± 3 percentage points
Independent496± 5 percentage points
Republican/Republican leaning896± 4 percentage points

Global COVID-19 Tracker

Published: Sep 15, 2026

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

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

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

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

Social Distancing and Closure Measures

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

Global COVID-19 Policy Actions

Economic Measures

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

Global COVID-19 Policy Actions

Health Systems Measures

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

Global COVID-19 Policy Actions

Cases and Deaths

SOURCES

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

Policy Actions

NOTES

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

Social Distancing and Closure Measures

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

Economic Measures

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

Health Systems Measures

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

SOURCES

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

KFF Tracker: America First MOU Bilateral Global Health Agreements

Published: Sep 15, 2026

Editorial Note: Originally published on January 13, 2026, this resource will be updated as needed, most recently on September 15, 2026, to reflect additional developments.

On September 18, 2025, the U.S. government (USG) released its new America First Global Health Strategy, which details how the U.S. will engage in global health efforts moving forward. As part of this new strategy, the U.S. has announced that it will be establishing bilateral health cooperation agreements with countries that receive U.S. global health assistance. These agreements, or Memorandums of Understanding (MOUs), between the U.S. and partner countries represent five-year plans (for the period 2026-2030) outlining U.S. engagement in each country’s health efforts with the goal of “helping countries move toward more resilient and durable health systems.” Central to these plans is transitioning country programs from U.S. assistance to long-term country ownership, with a pledge from each partner country to increase its domestic health spending, or co-investment in health, over the next five years as the U.S. decreases its health assistance. The U.S. began signing these agreements in late 2025 and this process is ongoing. Implementation is slated for later this year.

This tracker provides an overview of the MOUs signed to date. Data are based on press releases issued by the State Department, U.S. embassies, and partner country Ministries of Health, as well as MOU documents (if publicly available). See Methods for more information. This tracker will be updated as agreements are signed and more data become available.

USG Global Health MOUs by Country (Table)
Signed USG Global Health MOUs by Country (Choropleth map)
Global Health MOU Funding by Country (Bar Chart)
USG Global Health MOU Co-Financing Share by Country (Stacked Bars)
USG Global Health MOU Program Areas by Country (Table)
Historical vs. Proposed 5-Year USG Global Health MOU Funding by Country (Grouped Bars)

Methods

This tracker provides information on U.S. MOU bilateral global health agreements to date. Information is sourced from publicly available U.S. Department of State, U.S. embassies, and partner country Ministries of Health press release statements and MOU texts, and will be updated as more information becomes available and when additional agreements are signed. Currently, MOU text, which contains the most detailed information of these sources, is publicly available for only a limited number of countries; for these countries, data were sourced directly from these MOU documents. For countries with available MOU documents, overall totals are based on the sum of annual amounts presented in the text. 

Program areas are captured using keyword searches; for global health security (GHS) specifically, country agreements were categorized as targeting GHS if they specifically mentioned GHS, or if they included descriptions of outbreak preparedness and response activities and containing health threats. Due to the limited nature of press release statements, this tracker may not comprehensively capture the global health program areas targeted in each country’s agreement.

News Release

Survey: Adults With Multiple or Complex Health Conditions Face Significant Challenges with Health Costs and Commonly Struggle to Access Care 

Uninsured Adults With Multiple Conditions Struggle the Most to Afford and Access Care

Published: Sep 15, 2026

Adults with multiple or complex health conditions, who already face unique physical and mental challenges, commonly struggle to pay their medical bills and access needed care and medication—challenges that fall hardest on uninsured adults, according to a new KFF survey of more than 25 thousand adults. A companion Beyond the Data column by KFF Founding President and CEO Dr. Drew Altman explores the survey’s findings about uninsured adults with greater health needs and considers why the national discussion of the affordability crisis has largely ignored this group.

“If the first obligation of a health care system is to take care of the sick, we are failing that test. Cost and access problems are hitting the chronically ill hard, and the chronically ill and uninsured especially hard,” said Dr. Drew Altman.

The survey’s large sample size allowed KFF analysts to examine the experiences of adults with certain serious health conditions—including cancer, lung disease, diabetes, cardiovascular disease, or a mental health condition—as well as those managing care for multiple health problems.

About a third of adults ages 18-64 with multiple or certain complex health conditions say they struggled to pay or could not pay their medical bills in the past year. Adults with three or more conditions (36%), those with cardiovascular disease (37%), and those with a mental health condition (36%) are particularly likely to report struggling with medical bills. As part of these affordability challenges, about a quarter of adults with three or more conditions say they have had to cut back on household expenses to cover medical costs, compared to just about 1 in 10 of those without active health conditions.

High health costs can create major barriers to care, sometimes determining who is able to access the treatments and medications they need. About half of adults with three or more health conditions say they skipped or delayed care in the past year, including about 1 in 3 who did so due to cost. About 1 in 5 or more adults with multiple or complex health conditions also report not taking their medications as prescribed because they could not afford the cost.

Skipping or delaying care can have serious consequences. Substantial shares of adults across health conditions say their health got worse because they skipped or delayed care, including about 3 in 10 of those with a mental health condition (32%) or lung disease (29%), one quarter of those with cardiovascular disease (24%), and about 1 in 5 of those with cancer (18%) or diabetes (21%).

In addition to challenges with costs, insured adults with greater health needs commonly encounter insurance coverage delays or denials—problems that occur across specific health conditions. About half of insured adults ages 18-64 with three or more conditions say their insurer denied or delayed coverage for a service, treatment, or medication their doctor prescribed, as do about 4 in 10 or more insured adults with certain complex conditions, including diabetes (38%), lung disease (43%), cancer (43%), cardiovascular disease (45%), or a mental health condition (47%).

Uninsured Adults Struggle the Most to Afford and Access Care
As Drew Altman writes in his new column, health care affordability is most challenging for uninsured adults with multiple health conditions—most of whom say they struggle with medical bills (72%) and half of whom say they cut back on household spending to cover their health costs. Uninsured adults with three or more health conditions are twenty percentage points more likely than their insured counterparts to say they skipped or delayed needed care in the past year (71% vs. 51%). They are also about twice as likely as those who are insured to say they did not take their medication as prescribed due to cost (51% vs. 24%).

For uninsured adults, going without needed care and medications may carry even greater risks that worsen existing barriers to care. Untreated health conditions can worsen over time and become more difficult and costly to treat. Among uninsured adults, about 4 in 10 with multiple conditions (43%) and about half with a mental health condition (47%) say their health got worse after skipping or delaying care—making them about one and a half times as likely as their insured counterparts to experience a decline in health.

Other findings about older adults (aged 65+) with multiple and complex health conditions are available in the full report.

Dr. Altman will discuss KFF’s findings about chronic health conditions and the broader health policy landscape in his keynote address at the National Academy of Medicine’s Annual Meeting in October.

Designed and analyzed by KFF public opinion researchers, KFF’s Survey of Health Access and Caregiving was conducted in English and in Spanish May 4 – 26, 2026, online and by telephone among a large, nationally representative sample of 25,873 adults, including 16,677 who say they have received treatment for at least one serious or complex health condition in the past year. The margin of sampling error is plus or minus one percentage point for the full sample. For results based on other subgroups, the margin of sampling error may be higher.

Poll Finding

Health Care Access and Affordability for Adults with Multiple or Complex Health Conditions: A Snapshot of Patient Experiences

Published: Sep 15, 2026

KFF polling has long shown that many U.S. families struggle to afford health care and how costs shape decisions about whether and when to seek care. In the past year, worries about costs have intensified, with the cost of health care topping the public’s list of economic anxieties. Even adults with health insurance report difficulty affording health care, and many say they have health care debt. These concerns have implications for people’s access to care, health and well-being, and financial security.

While previous KFF polling has examined the public’s experiences with health care costs, sample size limitations have made it difficult to examine the experiences of adults with serious or complex health conditions. The KFF Survey of Health Access and Caregiving helps fill this gap with a large, nationally representative sample of 25,873 adults, including 16,677 who say they have received treatment for at least one health condition in the past year. The survey’s large sample size makes it possible to examine the experiences of adults with specific conditions including cancer, lung disease, diabetes, cardiovascular disease, and mental health conditions, while also allowing for analysis by other demographics like age and insurance coverage.

Key Takeaways

  • While the high cost of health care is felt by many adults, those with multiple or complex health conditions are especially burdened. For example, a third (36%) of adults ages 18-64 with three or more health conditions say they had problems paying or were unable to pay medical bills in the past year, higher than the one in five (20%) without ongoing health conditions. Substantial shares of adults ages 18-64 with multiple health conditions also say they skipped or delayed getting health care due to cost (36%) or did not take their medication as prescribed (25%) in the past year due to the cost. Skipping or delaying health care has serious implications, with about a quarter (27%) of those with multiple conditions saying their health got worse as a result. Similarly high shares of adults with serious health conditions like cardiovascular disease, cancer, or a mental health condition report financial and access challenges. For example, four in ten (42%) adults ages 18-64 with a mental health condition say they skipped or delayed a health care appointment due to the cost and a similar share (37%) of those with cardiovascular disease say they had problems paying medical bills in the past year. 
  • Beyond challenges with access and cost, many insured adults with multiple or complex health conditions also face issues getting their insurance to cover care and treatments they need. About half (49%) of insured adults ages 18-64 with three or more health conditions say their insurance company has denied or delayed a health care service in the past two years, rising to 47% among those with a mental health condition and 43% among those with asthma, emphysema, or lung disease. These issues are common across health insurance types, with many insured adults with multiple or serious health conditions saying they have experienced a denial or delay for a service, treatment, or medication they or their doctor requested in the past two years.
  • Challenges accessing and paying for health care are especially acute among the uninsured population who are being treated for multiple health conditions. While concerns about costs are widespread, about seven in ten (72%) uninsured adults with multiple health conditions say they have had problems paying medical bills in the past year, and half (50%) have had to cut back on household expenses as a result. In addition, uninsured adults with multiple health conditions are about twice as likely as their insured counterparts to say they skipped or delayed care (68% vs. 35%) or did not take their medications as prescribed (51% vs. 24%) in the past year because of the cost. These challenges are compounded by a lack of access to care, with about one in five (18%) uninsured adults with multiple health conditions saying they do not have a usual source of care other than an emergency room.
  • Despite some insulation from costs and high rates of Medicare coverage, about a quarter of adults 65 and older with multiple or complex health conditions have experienced an insurance delay or denial for a service or drug they needed in the past two years. In addition, one in five or more older adults with multiple health conditions and complex health conditions say they have skipped or delayed health care in the past year for any reason, including the cost or not being able to get an appointment. Overall, about one in ten older adults with multiple conditions say their health got worse after skipping or postponing needed care.
  • Adults with mental health conditions face some of the greatest challenges accessing and affording health care. Six in ten adults ages 18-64 with mental health conditions say they skipped or delayed care in the past year (59%) and about half (47%) of insured adults with a mental health condition report experiencing delays or denials by their insurance company in the past two years. One-quarter of adults ages 18-64 with a mental health condition report skipping or not taking their medication as prescribed in the past year because they couldn’t afford it, which may have serious consequences for those who rely on medication to manage their mental health. While mental health conditions disproportionately affect younger adults, those ages 65 and older with a mental health condition also face some challenges despite the prevalence of Medicare coverage, with three in ten (30%) of this group saying they skipped or delayed health care for any reason in the past year and one in seven (14%) saying their health got worse as a result.
  • Substantial shares of adults undergoing cancer treatment report experiencing insurance delays and denials. Among those who have received treatment or medication for cancer in the past year, 43% of adults ages 18-64 and 21% of those ages 65 and older say their insurance has denied coverage of or delayed their ability to get a health care service, treatment, or medication their doctor prescribed in the past year. Given the complicated nature of cancer treatment, these delays and denials may have serious health implications for this group. In fact, about one in five (18%) adults ages 18-64 with cancer say their health got worse as a result of skipping or delaying care in the past year.

Groups Examined in This Report

Researchers take various approaches to define and measure health conditions among the U.S. population. In this report, we examine the experiences of those who say they have received medical treatment or taken prescription medication in the past 12 months for 5 serious or complex health conditions:

  • Diabetes
  • Asthma, emphysema, or lung disease
  • Cardiovascular or heart disease
  • Cancer; or
  • A mental health condition

We also look at adults who are managing multiple health conditions, defined as those who have been treated or taken medication for 3 or more from a list of 18 different health conditions in the past year.1

Throughout this report, we make comparisons to adults who say have not received medical treatment or taken prescription medication for any of these 18 health conditions in the past year. While this group may have interactions with the health care system throughout the year for things like routine care and acute illnesses, they are a group that is relatively healthy in comparison to those with multiple complex conditions. For more details on the demographic characteristics of adults in each of these groups, see the Appendix.

Managing Care for Multiple or Complex Health Conditions Among Adults 18-64

This section examines the unique challenges faced by adults ages 18-64 who are managing complex health conditions. (The experiences of adults ages 65 and over, who are largely covered by Medicare, are examined in a separate section below.) About one in five adults ages 18-64 (18%) are managing three or more health conditions, while about one in six (15%) have been treated for a mental health condition in the past year, about one in ten have been treated for diabetes (9%), or asthma, emphysema, or lung disease (8%), and fewer say they have been treated for cardiovascular disease (3%) or cancer (2%).

Access To Care Among Adults 18-64 With Multiple or Complex Health Conditions

About half (52%) of adults ages 18-64 with three or more health conditions and similar shares of those who have been treated for complex health conditions like lung disease and cardiovascular disease in the past year report they did not get the health care they needed in the past year, rising to about six in ten (59%) for those with a mental health condition. Among those ages 18-64 with three or more health conditions, more than a third (36%) say they skipped or delayed getting care due to the cost, a quarter (25%) couldn’t find a provider with available appointments, and about three in ten (28%) skipped or delayed care for some other reason.

Across adults ages 18-64 with complex health conditions, costs are the most prevalent reason cited for skipping or delaying health care. Those who have been treated for a mental health condition are especially likely to say they’ve not gotten the care they needed in the past year, with about six in ten (59%) saying they’ve skipped or delayed care for any reason, including four in ten (42%) who said it was due to cost. About half of adults with lung disease (55%) or cardiovascular disease (49%) also say they missed care for any of these reasons in the past year, as do 46% of those with diabetes and 43% of those with cancer.

Notably, a substantial share (43%) of adults with no active health conditions from a list of 18 common conditions report skipping or delaying care in the past year. This may reflect skipping or delaying routine check-ups or screenings or care for acute illnesses or injuries.

Split bar chart showing share of adults ages 18-64 that say they tried to get health care but had no appointments available, skipped or delated their care due to cost, or had any other reason besides cost or no appointment for delaying care, as well as the share who gave any of these reasons for delaying care. Reported among total adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

Skipping care results in health consequences for many adults ages 18-64 with serious or multiple health conditions. About three in ten adults ages 18-64 with a mental health condition (32%) or asthma, emphysema, or lung disease (29%) say they skipped or delayed care in the past year and their health got worse as a result. About three in ten (27%) of those managing three or more health conditions also say this, about twice as many as those with no active health condition who report such an outcome (13%). Delays in care also led to worsening health for about a quarter of those with cardiovascular disease (24%) and one in five of those with diabetes (21%), or cancer (18%). Research has shown how postponing or going without needed health care can exacerbate health problems and take more time and resources to treat, which is particularly crucial for adults with complex or multiple health conditions.

Bar chart showing share of adults ages 18-64 who say their health got worse because they skipped or delayed care. Reported among total adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

About one in five or more adults ages 18-64 with multiple or complex health conditions also report not taking their medication as prescribed because they can’t afford the cost. One-quarter of adults with multiple health conditions (25%), lung disease (25%), or a mental health condition (25%) say they have cut pills in half, skipped doses, or decided not to fill a prescription in the past year because they could not afford it. About one in five adults who have diabetes (22%), cardiovascular disease (22%), or cancer (19%) also say they have not taken their medication as prescribed due to the cost. In contrast, about half as many adults without a health condition (10%) say they have not taken medication as prescribed due to the cost in the past year.

Bar chart showing share of adults ages 18-64 who say they cut pills in half, skipped doses of a medication, or decided not to fill a prescription because of the cost in the past 12 months. Reported among total adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

The Financial Burden of Managing Care for Multiple or Complex Health Conditions Among Adults Ages 18-64

The high cost of managing care is a burden for adults ages 18-64 with multiple health conditions, with about a third (36%) of those with three or more conditions saying they have had problems paying medical bills in the past year, and about a quarter (24%) saying they cut back on household expenses as a result. These shares are nearly double the shares reported by adults without complex conditions, among whom one in five (20%) say they had problems paying medical bills and about one in eight (13%) cut back on household expenses as a result.

Among those ages 18-64 with specific health conditions, at least three in ten of those with cardiovascular disease (37%), a mental health condition (36%), diabetes (33%), lung disease (32%), and cancer (30%) report problems paying medical bills. At least one in five across these groups say they have had to cut back on household expenses like food, clothing, or basic household items to pay for health care costs, ranging from 20% of those with asthma, emphysema, or lung disease to 28% of those with cardiovascular disease.

Split bar chart showing share of adults ages 18-64 who say they had problems or were unable to pay medical bills or they had to cut back on household expenses due to medical bills in the past 12 months. Reported among total adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

Many Adults Ages 18-64 With Multiple or Complex Health Conditions Experience Insurance Delays and Denials

Navigating health insurance coverage is another challenge those with multiple or complex health conditions face. Most adults ages 18-64 with multiple health conditions have health insurance, with nearly half covered through an employer (46%), three in ten (30%) through Medicaid, one in six (15%) through some other form of insurance, and 4% through non-group insurance. Fewer than one in ten (4%) are uninsured. Among those with specific conditions, uninsured rates are also low, ranging from 3% among adults ages 18-64 with cancer to 6% among those with diabetes, cardiovascular disease, or a mental health condition. These rates are lower than the uninsured rate among the overall population ages 18-64, which may reflect the fact that many uninsured adults live with conditions that have never been diagnosed because they are less likely to see a health professional regularly.

Stacked bar chart showing insurance coverage of adults ages 18-64 with multiple and serious health conditions. Reported among total adults with 3 or more active health conditions and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

About half (49%) of insured adults ages 18-64 with multiple conditions say their insurance company has either denied coverage or delayed their ability to get a service, treatment, or medication their doctor prescribed in the past two years. About four in ten (41%) insured adults ages 18-64 with multiple health conditions say their insurance company denied coverage for a treatment they needed and nearly four in ten (37%) say their insurance company delayed their ability to get treatment. These shares are more than double those reported by insured adults ages 18-64 without serious conditions. Close to half of insured adults ages 18-64 with a mental health condition (47%) or cardiovascular disease (45%) report experiencing insurance delays or denials in the past two years, while roughly four in ten of those with cancer (43%), lung disease (43%) and diabetes (38%) say the same.

These reported insurance delays and denials may reflect a range of care and services, including services that are subject to prior authorization, prescription drugs that are not included in a plan’s formulary, or services like acupuncture, infertility treatment, and hearing aids that are not covered by all insurance plans.

Split bar chart showing share of insured adults ages 18-64 who say their health insurance company denied coverage for or delayed their ability to get a health care service, treatment, or medication that they or their doctor requested in the past two years. Reported among total insured adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

These issues navigating insurance abound across adults ages 18-64 with multiple or complex conditions, regardless of the source of their health coverage. Similar shares of adults ages 18-64 with multiple or complex conditions have experienced delays or denials in the past two years from their health insurance across coverage types. For example, among adults 18-64 with multiple health conditions, about half of those with an employer-sponsored plan (49%) and Medicaid (50%) report experiencing a delay or denial, while 54% of adults ages 18-64 with non-group insurance say the same. Across adults ages 18-64 with specific health conditions such as diabetes and cardiovascular disease, there is a similar pattern, with similar shares of adults reporting problems with their insurance company regardless of the source of their coverage.

Split bar chart showing insurance coverage of insured adults ages 18-64 who say their health insurance company denied coverage for or delayed their ability to get a health care service, treatment, or medication that they or their doctor requested in the past two years. Reported among total insured adults ages 18-64, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

Navigating Multiple or Complex Health Conditions While Uninsured

KFF polling has long shown how a lack of health insurance coverage can exacerbate challenges with health care costs and access to care. In this section, we explore these challenges with access and paying for health care among adults ages 18-64 who are uninsured, who make up about 10% of the adult population ages 18-64. Among the uninsured population under age 65, most (69%) adults say they have not been treated for any health condition in the past year, while about a quarter (23%) have been treated for 1-2 conditions, and about one in ten (8%) have been treated for three or more conditions.

Due to sample size limitations, data in this section are shown only among adults ages 18-64 who say they have been treated for multiple conditions in the past year (8% of all uninsured adults ages 18-64) and among those who received treatment for a mental health condition in the past year (10% of all uninsured adults ages 18-64). Sample sizes for uninsured adults ages 18-64 being treated for other serious health conditions (diabetes, lung disease, cardiovascular disease, and cancer) are too small to report. Notably, this analysis does not include uninsured adults who may be living with these conditions but have never been diagnosed because of lack of access to health care providers and services.

About one in five (18%) uninsured adults ages 18-64 with multiple health conditions say they do not have a usual source of care other than an emergency room, three times as many as their insured counterparts (6%). While about three in ten uninsured adults with multiple health conditions say they go to a private doctor’s office, most, about four in ten (40%), say they usually go to a neighborhood clinic or health center when they are sick or need advice about their health. This is in contrast to adults with multiple health conditions who have insurance, who are most likely to say they visit a private doctor’s office (63%), and fewer (15%) say they usually visit a neighborhood clinic or health center. Adults who are uninsured and being treated for a mental health condition are particularly likely to say they do not have a usual source of care, with about a third (36%) saying this compared to 6% of their insured counterparts.

Stacked bar chart showing where adults ages 18-64 with multiple health conditions say they usually call or go to when they are sick or when they need advice about your health. Reported among insured and uninsured adults with 3 or more active health conditions and adults who were treated for a mental health condition in the past year.

Uninsured adults with multiple health conditions are especially vulnerable to the high cost of health care. About seven in ten (72%) uninsured adults with multiple conditions say they had problems paying medical bills in the past year and half (50%) said they had to cut back on household expenses as a result. This is much higher than their insured counterparts, of whom about a third (35%) and one in five (23%) respectively said they did this in the past year. These real-life impacts of high health care costs are also felt by uninsured adults with a mental health condition, of whom two-thirds (65%) say they had problems paying or were unable to pay medical bills in the past year, and about half (52%) who said they had to cut back on household expenses due to health care costs.  

Split bar chart showing share of adults who say they had problems paying or where unable to pay medical bills or they had to cut back on household expenses due to medical bills in the past 12 months. Reported among insured and uninsured adults with 3 or more active health conditions and adults who were treated for a mental health condition in the past year.

While concerns about health care costs are widespread, uninsured adults ages 18-64 with multiple conditions are more than about twice as likely as insured adults to say they skipped care in the past year because of the cost (68% vs. 35%). This share rises to more than eight in ten (84%) among uninsured adults ages 18-64 with a mental health condition who say they skipped or delayed care due to cost, also about twice as many as their insured counterparts (40%). Fewer uninsured adults with multiple conditions say they skipped care due to not being able to get an appointment (31%) or due to other reasons (37%). In contrast, uninsured adults with a mental health condition are much more likely to say they couldn’t get an appointment than those who have insurance (43% vs. 29%).

Split bar chart showing share of adults ages 18-64 that say they tried to get health care but had no appointments available, skipped or delated their care due to cost, or had any other reason besides cost or no appointment for delaying care, as well as the share who gave any of these reasons for delaying care. Reported among insured and uninsured adults with 3 or more active health conditions and adults who were treated for a mental health condition in the past year.

Skipping or delaying care has serious consequences for uninsured adults’ health outcomes, with about four in ten (43%) with multiple conditions and about half (47%) with a mental health condition saying their health got worse. This is higher than the share of insured adults who say the same (27% among those with multiple conditions, 31% among those with a mental health condition). Not getting needed care may be particularly fraught for uninsured adults, since health conditions can worsen over time and become more costly to treat.

Bar chart showing share of adults ages 18-64 who say their health got worse because they skipped or delayed care. Reported among insured and uninsured adults with 3 or more active health conditions and adults who were treated for a mental health condition in the past year.

Among adults 18-64 with multiple health conditions or a mental health condition, those who lack health insurance are about twice as likely as those who are insured to say they didn’t take their medication as prescribed in the past year because they couldn’t afford the cost. About half (51%) of uninsured adults with multiple conditions say, in the past 12 months, they cut pills in half, skipped doses of a medication, or decided not to fill a prescription because of the cost, about double the share of those who are insured who said the same (24%). A majority (56%) of uninsured adults with a mental health condition say they didn’t take their medication as directed, compared to about a quarter (23%) of their insured counterparts who say this.

Bar chart showing share of adults ages 18-64 who say they cut pills in half, skipped doses of a medication, or decided not to fill a prescription because of the cost in the past 12 months. Reported among insured and uninsured adults with 3 or more active health conditions and adults who were treated for a mental health condition in the past year.

Managing Multiple or Complex Health Conditions Among Adults 65 And Older

Many of the health conditions examined in this report disproportionately affect older adults. At the same time, most adults ages 65 and over are covered by Medicare, which can help prevent or mitigate challenges with health care access and cost. Still, older adults with multiple or complex health conditions are not immune from cost and access problems. Many older adults have multiple health conditions: about four in ten (42%) say they have been treated for three or more conditions in the past year, while about one in five (19%) say they have been treated for diabetes, one in six (15%) have been treated for cardiovascular disease, and smaller shares report being treated for lung disease (9%), cancer (7%), or a mental health condition (6%).

Despite high coverage rates through Medicare, a quarter (25%) of adults 65 and older with multiple health conditions say their insurance has either denied or delayed a health care service, treatment, or medication their doctor prescribed in the past two years. This share includes about one in five (21%) who say their insurance denied treatment and about one in six (15%) who say their insurance delayed treatment. The share of older adults reporting a delay or denial varies by health condition, with about three in ten of older adults with asthma, emphysema, or lung disease (31%) or a mental health condition (29%) saying this, compared to about a quarter of older adults with diabetes (25%) and about one in five among those with cancer (21%) or cardiovascular disease (20%).

While prior authorization is rarely used in traditional Medicare, it is more common in Medicare Advantage and in Medicare Part D plans that cover prescription drugs, which cover large shares of the population ages 65 and over. Further, as noted above, people reporting insurance delays and denials for services may have experienced other situations beyond those related to prior authorization (such as being prescribed a drug not included on their plan’s formulary or needing services not covered by Medicare).

Split bar chart showing share of insured adults ages 65+ who say their health insurance company denied coverage for or delayed their ability to get a health care service, treatment, or medication that they or their doctor requested in the past two years. Reported among total insured adults ages 65+, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

A quarter (25%) of older adults with multiple health conditions and similar shares of those with complex health conditions report not getting the health care they needed in the past year. Similar shares of older adults with multiple conditions say they skipped or delayed care due to cost (10%), because they couldn’t get an appointment (12%), or any other reason (11%). Among older adults, similar shares across complex health conditions say they did not get the care they needed, ranging from three in ten (30%) older adults with a mental health condition to about one in five (21%) with diabetes. 

Split bar chart showing share of adults ages 65+ that say they tried to get health care but had no appointments available, skipped or delated their care due to cost, or had any other reason besides cost or no appointment for delaying care, as well as the share who gave any of these reasons for delaying care. Reported among total adults ages 65+, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

About one in ten (8%) older adults with multiple health conditions experienced worse health as a result of skipping or postponing care, rising to one in seven (14%) among those with a mental health condition. Fewer than one in ten older adults with other serious health conditions say their health got worse from skipping or delaying care, ranging from 5% among those with diabetes to 8% among those with asthma, emphysema, or lung disease.

Bar chart showing share of adults ages 65+ who say their health got worse because they skipped or delayed care. Reported among total adults ages 65+, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

Although most older adults have prescription drug coverage through Medicare, those with multiple or certain complex conditions are more likely to say they didn’t take their medication due to cost compared to those who have no conditions (10% vs. 4%). Overall, one in ten (10%) older adults with multiple conditions say they cut pills in half, skipped doses of a medication, or decided not to fill a prescription because of the cost. This share rises to about one in seven older adults with asthma, emphysema, or lung disease (14%) or a mental health condition (13%).

Bar chart showing share of adults ages 65+ who say they cut pills in half, skipped doses of a medication, or decided not to fill a prescription because of the cost in the past 12 months. Reported among total adults ages 65+, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

Older adults with multiple health conditions are twice as likely to say they had problems paying or were unable to pay medical bills in the past year compared to those with no health conditions (14% vs. 7%), rising to 19% among older adults with a mental health condition. About one in ten (9%) older adults also say they had to cut back on household expenses because of medical bills. Across older adults with complex health conditions, similar shares say they had to cut back on household spending as a result of medical bills.

Split bar chart showing share of adults ages 65+ who say they had problems or were unable to pay medical bills or they had to cut back on household expenses due to medical bills in the past 12 months. Reported among total adults ages 65+, by number of active health conditions, and among adults treated for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition.

The KFF Survey of Health Access and Caregiving was a series of questions designed and implemented by KFF with the SSRS Opinion Panel Mega-Omnibus. The survey was conducted May 4 – May 26, 2026, online and by telephone among a nationally representative sample of 25,873 U.S. adults in English (n=25,422) and in Spanish (n=451).

The SSRS Opinion Panel is a nationally representative probability-based panel where panel members are recruited randomly in one of two ways: (a) Through invitations mailed to respondents randomly sampled from an Address-Based Sample (ABS) through the U.S. Postal Service’s Computerized Delivery Sequence (CDS); (b) recruited via random digit dial (RDD) telephone sample of cell phone numbers connected to a prepaid cell phone. Both samples were provided by Marketing Systems Group (MSG). The combined sample was reached either online (n=24,875) or over the phone (n=998) based on the panelist’s stated preference. For the online panel component, invitations were sent to panel members by email followed by up to four reminder emails and up to two reminder text messages (if consented to receive SMS).

The questions designed by KFF were included as part of a multi-stakeholder effort designed to survey all individuals currently empaneled in the SSRS Opinion Panel, with each organization paying for and having independent editorial control over its survey questions.  Substantive questions from other outside stakeholders are redacted in this report. The SSRS survey team designed the questionnaire in order to minimize potential bias from question ordering. For more information, please contact SSRS.

Respondents who completed on the web received a $5 electronic gift card incentive (some harder-to-reach groups received a $10 electronic gift card). Respondents who completed the survey on the phone received $10 via a physical check in the mail. In order to ensure data quality, cases were removed if they failed two or more quality checks: (1) attention check questions in the online version of the questionnaire, (2) had over 10% item non-response, or (3) had a length of less than 30% of the mean length by mode. Based on this criterion, 69 cases were removed.

Data were weighted to represent adults 18+ in the United States. The Panel-wide base weight adjusts for the SSRS Opinion Panel recruitment and retention process. Because all current panelists (except 2026 recruits) were invited to participate and no further sampling was performed, no further adjustments to the Panel-wide base weight were necessary before applying it to the survey data.

With the Panel-wide base weight applied, the survey-data were weighted to match the sample’s demographic profile to the same target population parameters used in the calibration of the entire SSRS Opinion Panel. The demographic variables included in weighting for the general population sample are gender, age, race/ethnicity, and education (including interactions between these categories), as well as region, civic engagement, density, frequency of internet use, voter registration, political party identification, religion, household makeup, and home ownership. Final calibrated weights are trimmed at the 2nd and 98th percentiles to prevent individual interviews from having too much influence.

The margin of sampling error including the design effect for the full sample is plus or minus 1 percentage points. Numbers of respondents and margins of sampling error for key subgroups are shown in the table below. For results based on other subgroups, the margin of sampling error may be higher. Sample sizes and margins of sampling error for other subgroups are available on request. Sampling error is only one of many potential sources of error and there may be other unmeasured error in this or any other public opinion poll. KFF public opinion and survey research is a charter member of the Transparency Initiative of the American Association for Public Opinion Research.

GroupN (unweighted)M.O.S.E.
Total25,873±1 percentage point
   
Serious and Complex Health Conditions16,677± 2 percentage points
Diabetes2,951± 3 percentage points
Asthma, emphysema, or lung disease2,309± 3 percentage points
Cardiovascular or heart disease1,575± 3 percentage points
Cancer831± 5 percentage points
A mental health condition3,781± 2 percentage points
   
Number of Serious and Complex Health Conditions  
09,196± 1 percentage point
1-29,710± 1 percentage point
3+6,967± 2 percentage points

Who Has Multiple or Complex Health Conditions?

Among all adults, about one in seven (13%) report they have been treated for a mental health condition in the past year, while about one in ten say they have been treated for diabetes (11%) or lung disease including asthma and emphysema (8%). Small shares have received treatment for cardiovascular disease (6%) or cancer (3%).

Mental health conditions are more commonly reported among the young adult population, with about one in six adults ages 18-29 and ages 30-49 saying they have been treated for one in the past year. Older adults are much more likely to have been treated for cancer or cardiovascular disease in the past year than their younger counterparts. Older adults also experience higher rates of treatment for diabetes than younger adults. In contrast, rates of lung disease, asthma, or emphysema treatment are largely similar across age, with about one in ten adults saying they have received treatment for the condition in the past year.

There are also differences by gender. Women report higher rates of receiving treatment for a mental health condition (15% vs. 9%) and lung disease, asthma, or emphysema (10% vs. 6%) than men. In contrast, men report higher rates of treatment for cardiovascular disease (7% vs. 4%) and diabetes (13% vs. 10%) than women.

The prevalence of treatment for health conditions varies across racial and ethnic groups and by type of health condition. For example, diabetes disproportionately affects Black and Hispanic adults, while receiving treatment for a mental health condition is more common among White adults.

Split bar chart showing share of adults who say they have received treatment or medication for diabetes, asthma, emphysema or lung disease, cardiovascular disease, cancer, or a mental health condition in the past year. Reported among total adults and by age, gender and race/ethnicity.

Among the total adult population, about one in four (24%) say they have been treated for three or more serious or complex health conditions in the past year, while about a third (36%) have been treated for one or two conditions, and about four in ten (40%) have not been treated for any condition asked about in the past year.

Older adults (42% of those ages 65 and over) are much more likely than younger adults to be in active treatment for multiple health conditions, and women are somewhat more likely than men to report this (26% vs. 21%). White adults (26%) and Black adults (25%) are more likely to report receiving treatment for multiple conditions in the past year compared to Hispanic (18%) and Asian or Pacific Islander adults (13%), which may reflect access to treatment as well as underlying health status.

Stacked bar chart showing share of adults who have been treated in the past year for zero, 1-2, or 3 or more health conditions. Reported among total adults and by age, gender and race/ethnicity.
  1. The full list of health conditions asked about in the survey includes: allergies (not associated with hay fever), arthritis, back pain, cancer or a malignancy of any kind, cardiovascular disease/heart disease, diabetes, hypertension or high blood pressure, high cholesterol, mental health condition, migraines, obesity, sinusitis, sleep disorder, thyroid problems, Parkinson’s disease, kidney disease, substance use disorder, or asthma, lung disease or emphysema.  ↩︎

The Business of Health with Chip Kahn

FDA Regulation and the Dynamic Nature of AI

September 15, 2026

Video

Audio

About this Episode


Episode 15, AI Series: Dr. Brian Miller has seen medical technology regulation from every side — as a hospitalist, a former FDA official, and now an associate professor at Johns Hopkins University, where he leads a research group on market-driven approaches to FDA regulation and Medicare payment policy. In this episode, Chip talks with Miller about what happens when the FDA applies its 1976 medical device framework to AI — a technology that learns and changes.

Miller’s argument may surprise you: the manual system of medicine we have today is already less safe and less consistent than most people assume. What keeps him up at night isn’t the speed of AI — it’s the risk that fear-driven regulation will cost us the opportunities AI offers. The conversation was recorded shortly before the FDA released a discussion paper outlining possible regulatory approaches and inviting stakeholder feedback. Chip weighs in on the paper at the end of the episode.

The Host


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

Sr. Visiting Fellow

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

Guest


Associate Professor of Medicine at the Johns Hopkins University School of Medicine; Visiting Fellow, Hoover Institution

Brian Miller, MD, MBA, MPH, is a practicing hospitalist at the Johns Hopkins Hospital, an Associate Professor of Medicine and Business (courtesy) at Johns Hopkins University, and a Visiting Fellow at the Hoover Institution. Dr. Miller runs a multi-disciplinary, twenty-person research group that analyzes market-driven solutions in FDA regulatory policy and Medicare payment policy. He has broad regulatory experience at the Centers for Medicare & Medicaid Services, the Federal Trade Commission, the Federal Communications Commission, and the U.S. Food and Drug Administration and is familiar with merger review, software and medical device product review, and payment policy.

Dr. Miller serves as a Commissioner on the Medicare Payment Advisory Commission which advises Congress on the $1 trillion Medicare program and as a Trustee for the North Carolina State Health Plan, a $4.5 billion health plan covering over 750,000 state employees, dependents and retirees. He serves as an advisor to members of Congress and other elected officials and lives in Washington, D.C.


SERIES

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

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

VOLUME 54

Correcting False Health Claims and Navigating AI-Generated Information


Highlights

Recent research on correcting false or misleading claims finds that corrections can improve the accuracy of people’s beliefs, but their impact on engagement may depend on reaching people before a claim has already spread widely.

And research on AI-generated search results suggests that people may be less likely to visit the original sources behind AI-generated answers. As these tools become more common, health organizations may need to consider how changes in information-seeking behavior affect their ability to reach audiences and build trust.


What We’re Watching

Social Media Fact-Checks Can Reduce Belief in False Claims, But Timing Matters For Limiting Reposts

As the public navigates information environments with large volumes of conflicting information from different sources, health communicators face the challenge of understanding how and when to address false claims. A growing body of research suggests that corrections after someone has been exposed to a claim on social media can reduce belief in misinformation. At the same time, the timing of corrections may matter for limiting reposts that give false claims further spread.

In recent years, social media platforms have scaled back or changed approaches designed to limit the spread of misleading content through professional fact-checking programs and instead invested in crowd-sourced fact-checking. Though professional fact-checkers may be perceived as more credible because of their training and expertise, corrections can still be effective in reducing belief in misinformation even when they come from a source that is perceived as less credible. In fact, crowd-sourced fact-checks can be as effective as expert fact-checks in reducing confidence in misinformation. X is one platform that uses a crowd-sourced fact-checking feature, known as Community Notes, to correct information deemed incorrect by its users. Recent investigations into Community Notes indicate that when added, they reduced the subsequent shares of misleading posts by 61.2%. But by the time a Community Note was published, the misleading post had often already been spread. The average time between a post being published and a note being added was about 63 hours, while posts typically had already received half of their first 36-hour reposts within about six hours after publication. As a result, Community Notes may be less effective at reducing the overall number of reposts than they are at limiting further reposts once they are added, suggesting that corrections may be most effective at limiting the spread of false claims when they appear early.

Why This Matters

While corrections can improve accuracy, their impact on reposts may depend on reaching audiences before a claim has already spread widely. Although different approaches can reduce belief in false claims to a similar degree, differences in their speed may matter alongside the accuracy of the content itself.


AI & Emerging Technology

AI-generated search results and other AI health tools are changing the way people encounter health information online, potentially making it less likely that users visit the organizations and websites that originally produced the information.

An analysis published last year by Pew Research Center tracked the web browsing activity of a nationally representative panel of 900 U.S. adults over one month in 2025. Google users rarely clicked on a link cited in an AI Overview in Google search results, doing so in just 1% of cases. When AI Overviews were present in search results, Google users were also less likely to click links from the search results that followed, doing so 8% of the time compared to 15% for pages without AI Overviews.

A March KFF poll found that about two-thirds of adults reported seeking physical or mental health information and advice from an internet search engine (68%) in the past year. With many search engines providing AI-generated summaries of search results, the Pew Research Center analysis suggests that people may be receiving information from websites without directly encountering those sources. For health organizations and other trusted messengers, evolving user behavior could change the relationship between providing information and building recognition or trust.

As AI features expand and user behaviors continue to evolve, some organizations are using techniques to increase the likelihood that their content will appear in AI-generated answers. Health care and pharmaceutical companies were early adopters of a practice called Generative Engine Optimization (GEO), designed to help sources appear more often in AI systems. One study showed these techniques increased a source’s visibility in AI responses by up to 40%, although effects varied across domains.

About The Health Information and Trust Initiative: the Health Information and Trust Initiative is a KFF program aimed at tracking health misinformation in the U.S., analyzing its impact on the American people, and mobilizing media to address the problem. Our goal is to be of service to everyone working on health misinformation, strengthen efforts to counter misinformation, and build trust. 


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The Monitor is a report from KFF’s Health Information and Trust initiative that focuses on recent developments in health information. It’s free and published twice a month.

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Support for the Health Information and Trust initiative is provided by the Robert Wood Johnson Foundation (RWJF). The views expressed do not necessarily reflect the views of RWJF and KFF maintains full editorial control over all of its policy analysis, polling, and journalism activities. The data shared in the Monitor is sourced through media monitoring research conducted by KFF.