HR1 healthcare cuts projected to add 17 million uninsured by 2034
AI tools now take notes in exam rooms, code patient visits, send billing messages and operate chatbots that text patients about their unpaid balances — a shift that comes as medical debt grows and as Republican-led federal health reforms expected this winter are projected to enlarge the pool of patients who face those bills.
A report released last Tuesday found that more than one in four US adults — including roughly the same share among insured adults — reported owing medical debt in 2025, according to an analysis by the Urban Institute and the Robert Wood Johnson Foundation.
The pressure on patients is expected to intensify. Trump’s HR1, the One Big Beautiful Bill Act, cut roughly $1 trillion in federal spending from the healthcare industry. Combined with Republicans’ refusal to extend subsidies for plans sold through Affordable Care Act marketplaces, the cuts are expected to leave about 17 million people without insurance by 2034.
“Medical debt will grow among ‘both the insured and uninsured, because of how we’re increasingly putting more costs onto individuals for those plans’,” said April Kuehnhoff, a senior attorney at the National Consumer Law Center.
“It’s people who lose their coverage because they can’t afford it, or they can’t meet these new stringent requirements,” Kuehnhoff said. “It’s people who maybe they can afford it but the plan they get isn’t as good, and they are asked to have a higher deductible, higher co-pay, so they just have a higher out-of-pocket [cost].”
As the ranks of the uninsured and underinsured grow, so does what the industry calls “uncompensated care” — the doctor and hospital bills that go unpaid when patients cannot pay. The Urban Institute estimates that HR1 will cause $278 billion in uncompensated care by 2034, leaving cash-strapped hospitals searching for stronger collections tools.
One supplier of those tools is Cedar, an AI-driven billing platform backed by venture capital firms including Andreessen Horowitz and JP Morgan. Cedar screens patients for insurance, including Medicaid, through low-tech questionnaires — a longstanding practice by healthcare providers that helps boost collections but is not new. The company’s innovation, according to its website, lies in hospital and clinical data used to “train a machine learning model capable of predicting a patient’s propensity to pay” and to offer what it calls “AI-driven discounts.” Its chatbot, named Kora, speaks with patients about their bills to reduce call volume to billing departments.
“We have been focused on uninsured and Medicaid-eligible patients for several years now,” said Dugan Winkie, Cedar’s chief strategy officer and an alum of McKinsey as well as Epic, the nation’s largest electronic health records company.
“That’s where Cedar shines in my mind: our entire business is focused on ‘Patient A’, who is a single mother who has a $10,000 balance,” Winkie said. “We need to engage with you much differently than if you are a late-stage executive with a $50 copay.”
Cedar helps “get those more-difficult-to-collect-from patients who may not be digitally engaged aware of these offers,” such as zero-financing payment plans offered through providers, Winkie said.
Cedar is one of several firms wiring AI into the medical billing pipeline. AI now helps debt collectors determine personalized discounts for settlements — an analogue of the personalized pricing criticized by the Federal Trade Commission — and helps debt-buying companies decide what to pay for portfolios of unpaid bills.
The use of AI in clinical coding — the scribes that listen to and translate patient-doctor conversations into billing — has attracted particular scrutiny. In spring 2026, the Blue Cross Blue Shield Association, which represents state Blue Cross insurers, released a white paper finding that women in childbirth were increasingly being billed after severe blood loss during delivery, even as blood transfusion rates remained steady. The paper described in-room scribes converting conversations into “structured notes,” which AI then used alongside electronic health records to suggest enhanced coding — and, in turn, higher billing. In effect, the paper argued, AI was “boosting hospital billing.”
A second BCBS report in September estimated that AI coding had added $1 billion in healthcare costs in a year. One medical scribe company, also backed by Andreessen Horowitz, claimed in investor materials that its listening software produced an additional $13,000 in revenue per clinician per year through greater “coding accuracy.”
The American Hospital Association, an industry lobby, disputed the analyses. In a blog post, the group argued the analyses “raise concerns about coding trends, but it does not demonstrate that hospitals are coding patients inaccurately or that AI tools are driving inappropriate spending.”
The BCBS reports are the latest turn in a long-running dispute between insurers and providers over who bears responsibility for high US healthcare costs. Critics have raised separate concerns about AI being deployed on the payer side. Under Health Secretary Robert F. Kennedy Jr.’s health department, Medicare — the public insurance program for the elderly — recently launched a program to use AI to issue prior authorization for some conditions, an approach critics say mirrors tactics used by private insurers.
Anthropic’s Dario Amodei has promised to cure all diseases in a decade — a claim scientists remain skeptical of — while JP Morgan financial analysts have celebrated AI in coding, billing and collections as “early wins.”