Premier Data Shows OBBBA Will Trigger a $68 Billion Hospital Revenue Impact

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With Access to Care Already a Major U.S. Concern, the Impact on Patients and Population Health Could Be Significant

Key takeaways:

• "One Big Beautiful Bill Act" (OBBBA) changes to premium subsidies and Medicaid eligibility are projected to increase the number of uninsured people, and Premier's analysis estimates the national hospital revenue impact to top $68.6 billion over the course of 2026 and 2027.
• Total impacts vary by state, hospital type and population size, but most facilities will see net patient revenue (NPR) decrease by 2 to 10 percent.
• Using a unique combination of data, technology and advisory expertise, Premier can help hospitals and communities navigate this moment with clarity, precision and confidence.

The One Big Beautiful Bill Act (OBBBA) isn't just reshaping insurance markets - it's putting significant strain on hospital operating margins.

New data from Premier shows that the OBBBA's combined changes to premium subsidies and Medicaid eligibility are projected to strip $68.5 billion from hospital revenues nationwide. That's an average hit of $16.1 million per hospital.

Broken down, this includes an estimated:

• -$33.6 billion reduction in commercial revenue
• -$22.4 billion reduction in Medicaid revenue
• $12.5 billion increase in uncompensated care.

Calculated National Hospital Revenue Impact

Source: Premier analysis

Overall, Premier data predicts that most hospitals will see a net patient revenue (NPR) reduction of between 2 and 10 percent due to OBBBA implementation, with some at the extreme end of the scale set to see reductions that exceed 20 percent.

When combined with losses in coverage, OBBBA cuts could result in decreased access, delayed screenings and diagnoses, and less healthy and vibrant local communities.

States in Crisis

The anticipated OBBBA financial impact varies significantly between states. On average per facility, Florida hospitals are predicted to face the largest deficit at -$51.8 million per hospital. This is followed by Washington, D.C. (-$38.9 million), South Carolina (-38.3 million), Georgia (-$34.4 million) and Texas (-$32.6 million).

Average Total Projected OBBBA Impact on Hospitals, by State

Source: Premier analysis

However, across all hospitals within a state, the total anticipated impact is largely driven by population. When accounting for population, Texas showed the largest calculated total impact of -$11.5 billion, followed by Florida (-$8.8 billion), California (-$4.9 billion), New York (-$4.3 billion) and Georgia (-$4.3 billion).

Calculated State Projected Impacts by Insurer and Overall, in Millions

Source: Premier analysis

Even the Biggest Systems Face Losses Approaching $1 Billion

According to data from Definitive Healthcare (see Methodology section below) nine health systems in the United States have an NPR exceeding $5 billion annually. These systems' revenues from private payers varies between 70 and 91 percent, while their revenues from Medicaid vary between 3 and 12 percent, and their reported uncompensated care varies between $13 million and $268 million. For these systems, the impact of the OBBBA shifts in insurance coverage is expected to range between -$58.6 million and -$997.6 million when measured in dollars, and between -0.9 and -12.3 percent when measured as a change in NPR.

The data is concerning because even the most financially sophisticated, diversified multi-state systems could see up to one-eighth of their total revenue at risk.

Uncompensated Care Projected to Skyrocket by 39 Percent

Premier's research estimates that uncompensated care will rise from $32.4 billion to $44.9 billion (an increase of 38.6 percent), with some systems projected to see $100 million to $200 million increases in uncompensated care alone. This will likely have downstream impacts to hospitals as they grapple with increased visits to their emergency departments and added strain on their providers. These forecasts are likely to hit hospitals in early 2026 as many Americans dependent on Marketplace subsidies choose paying for basic necessities over healthcare.

The Bottom Line: OBBBA is Expected to Exacerbate Financial Challenges for U.S. Hospitals

If your leadership team isn't already building a multi-year counterstrategy, the window is quickly closing.

Premier's analysis suggests leaders should immediately:

• Pressure-test payer mix exposure under the 2026 landscape.
• Model state-specific financial trauma zones.
• Accelerate revenue diversification and shift labor and supply models.
• Build philanthropic and community partnerships to offset uncompensated care surges.
• Reevaluate capital plans assuming 5 to15 percent NPR contraction.

How Premier Can Help

Premier is prepared to help members navigate these and other financial challenges in healthcare with clarity, precision and confidence. Through our Advisory Services team and our proprietary OBBBA Impact Calculator, we can quantifyhospitalrevenue impact of the OBBBA - by facility, by system, state and region.

These tools model expected shifts in payer mix, projected Medicaid and marketplace enrollment losses, changes in commercial revenue and anticipated increases in uncompensated care, giving leaders a clear, data-driven view of what OBBBA means for their organization.

Paired with our advisory experts - who bring deep experience in revenue strategy, reimbursement optimization, coverage analytics and operational redesign - our tools help health systems not only understand their risk but build concrete, actionable strategies to mitigate it. At a historic inflection point for the healthcare industry, Premier provides the visibility, modeling sophistication and strategic partnership needed to protect margin, maintain mission and plan boldly for the future.

Click here to learn more.

Data and Methodology

We relied on several different sources for our analysis.

Hospital Data
Definitive Healthcare data were used to pull hospital geographic and financial data for all hospitals across the United States. These include reports of each hospital's net patient revenue (NPR), broken out by revenue from Medicare and Medicaid. We also pulled details about hospitals' uncompensated care and profit margins. For this analysis, we limited the view to hospitals designated as either short-term acute care or critical access. Moreover, we limited the sample to only include hospitals located in a U.S. state or D.C. Finally, some odd cases in the data were excluded, either because their net patient revenue was missing or reported to be less than $0, or because the sum of their Medicare and Medicaid revenue was larger than the reported total net patient revenue. In total, we ended up with 4,248 distinct hospitals.

Population and Insurance Enrollment
Mimilabs4 was used to access census data from the American Community Survey (ACS)5 to pull county-level estimates of population sizes, demographics and insurance enrollment type. This includes an estimate of the total enrollment in the insurance marketplace. However, we found that marketplace enrollment was only populated at the county level in a little over half of states.6 In these instances, we backfilled the marketplace enrollment by applying state enrollment percentages derived from Kaiser marketplace enrollment data.7 This was calculated by dividing the state's marketplace enrollment by the state's total population, which gave us percentage of enrollment. This percentage was then multiplied by the ACS county population.

Estimated OBBBA Impact Data
Finally, we pulled reports from Kaiser8 and the Urban Institute9 to gather geographic level impacts of the OBBBA on enrollment change. The Kaiser report details predicted impacts on Medicaid enrollment at the state level, and the Urban Institute report details the predicted impacts on marketplace enrollment at the state level.

Model Assumptions
The logic behind the model is relatively straightforward. Here are our assumptions:

• No direct impacts to a market's commercial/employer and Medicare enrollment.
• OBBBA only impacts changes in insurance enrollment within three underlying options: Medicaid, marketplace and uninsured. For example, an enrollee with marketplace coverage can either keep that coverage, opt for some other commercial insurance, enroll in Medicaid (under certain circumstances) or opt to be uninsured. However, an enrollee with Medicaid coverage could keep that coverage, move to a commercial insurance plan (marketplace or not) or move to being uninsured.
• We relied on the Kaiser and Urban Institute projections as the starting point to calculate geographic specific impacts). For example, at the national level:
• The insurance marketplace is expected to have ~7.3 million (38 percent) people drop coverage. Moreover, it is projected that ~4.8 million (65 percent) people will become uninsured. From there, we estimate how the remaining 35 percent will shift by using a flat rate of 2 percent moving to Medicaid and the remaining 33 percent (35 percent - 2 percent) to some other commercial option.
• Medicaid is projected to have a 10.3 million (12 percent) reduction in enrollment nationally. Because estimates did not project the number of enrollees expected to become uninsured, we used a flat assumption of 75 percent moving to uninsured and 25 percent opting for commercial insurance.
• Impacts on hospital revenues. It is assumed that changes in the insurance coverage within a geography will directly correlate to hospital revenue.
• A county with 100,000 people enrolled in any kind of commercial insurance (10,000 marketplace and 90,000 commercial/employer), with 50 percent reduction in marketplace coverage, would equate to a new estimate of 95,000 commercially insured people, a net reduction of 5 percent. It is assumed that hospital net patient revenue from commercial patients would also be reduced by 5 percent.
• A similar assumption is used for changes in Medicaid enrollment. If a county has 100,000 Medicaid enrollees, and 15 percent of that enrollment loses coverage, we would assume a similar 15 percent reduction in hospital net patient revenue from Medicaid patients.
• All these market level changes are happening synchronously and were modeled as such.
• We used the most recent Definitive hospital data and applied our calculations as such. The assumption is that the full impact of changes to marketplace enhanced premium tax credits and Medicaid are in full effect.
• The total impact on a hospital is a simple calculation, summing the change in net patient revenue with the change in uncompensated care.
• Total Impact= Change in NPR + Change in Uncompensated Care