A new study by Kodiak Solutions, a revenue-cycle analytics firm, reveals U.S. hospitals collectively absorbed $132 billion in losses last year—primarily from bad-debt write-offs and rejected final claims. The findings highlight a growing financial strain despite hospitals’ escalating investments in revenue-cycle technology, particularly AI solutions marketed to enhance financial outcomes.
Revenue leakage rose by nearly 18% compared with 2024, as write-offs continued to represent about 10% of net revenue last year, the analysis of Kodiak’s proprietary data showed.
Hospital Financial Performance
The institutions have operated on razor-thin margins after the COVID-19 pandemic because of surging operating expenses, growing administrative friction and increasing numbers of uninsured and underinsured patients. Coupled with industry-wide staffing shortages, leaders have invested more in technology, especially AI tools, to bolster their bottom lines.
Collectively, these budgets grew by 7.6% to $69 billion this year, according to a February report from Forrester cited in the Kodiak analysis. Revenue cycle management has become a focal point of hospital IT spending, particularly with emerging agentic AI technologies that promise to automate resource-intensive tasks such as prior authorizations.
Challenges in Revenue Cycle Management
Despite steep investments, the sector continues to face the same revenue-cycle challenges seen over the past few years. The Kodiak analysis found that facilities using its platform lost $52 billion last year from bad-debt and final-claim denial write-offs, a figure that expands dramatically when extrapolated to all 6,100 registered hospitals nationwide.
The write-offs stemmed from bad debt, which has hovered around 7% of net revenue for the past three years. Final denial rates also plateaued at roughly 3% during this period. While these key metrics have not risen, institutions are losing more money overall, likely because of high-value denials, case-mix shifts and a rising tide in total hospital revenue.
With little financial improvement, providers may not be “adequately distinguishing between technology needed to operate the revenue cycle and the capabilities needed to optimize their financial performance,” Kodiak researchers explained. They added that current revenue-cycle technologies may lack the depth of data analysis required to pinpoint why revenue is slipping and where opportunities exist to improve reimbursement and collections.
As the sector continues to invest in AI tools, it may need to rethink technology budgets to implement automated solutions that lift key performance indicators while staying competitive with payers, according to Kodiak. The healthcare industry has been described as a zero-sum environment in which a dollar successfully denied or clawed back adds to a payer’s bottom line while taking from a hospital’s operating margin.
Earlier this year, the Peterson Health Technology Institute reported that more structural changes to how payers design prior authorizations would be more effective in reducing costs across the healthcare system. Prior authorizations have been a top use case for AI in health care, but the institute said the technology has yet to lower system-wide costs despite delivering savings for individual organizations.
AI Adoption Targets Workflow Efficiency and Claim Bottlenecks
These tools may also be making flawed processes more efficient as payers and providers race to implement AI to streamline their workflows and cut costs, according to a report from Peterson Health Technology Institute earlier this year.
AI implementation remains a priority for insurance companies as they seek to clear operational bottlenecks in claim processing and counter hospital revenue increases driven by more aggressive coding enabled by AI billing software. Matching or exceeding payer AI investments has been the difference between sink or swim for providers.
