Generative AI for Medical Claim Denial Appeals: Adoption and Future Impact

The Claim Denial Problem

Introduction

Writing appeal letters for denied insurance claims is a tedious but essential task for U.S. healthcare providers. Physicians and hospital staff often spend hours crafting detailed letters and gathering evidence to persuade insurers to overturn denials – an administrative burden that contributes to burnout and waste techstartups.comtargetedonc.com. Recently, generative AI (“AI agents”) have emerged as a promising solution to automate this process. Hospitals, health systems, and even individual doctors are beginning to use AI tools to draft appeal letters in minutes, saving time and potentially recovering revenue from unpaid claims. This report explores how startups and established companies are deploying generative AI for claim denial appeals, examines current denial statistics and appeal rates, projects a future state where nearly all denials are appealed using AI, and analyzes the financial and operational implications of this shift.

The Growing Challenge of Denied Claims in the U.S.

Denied insurance claims are a widespread issue in American healthcare. Recent analyses show that 15–20% of all medical insurance claims are initially denied by payers premierinc.comkff.org. In 2021, insurers on HealthCare.gov (ACA marketplace plans) denied about 17% of in-network claims on average kff.org, and new 2023 data shows denial rates around 19% for in-network claims (ranging from 1% to over 50% by insurer) kff.orgkff.org. A Premier Inc. survey of private insurers similarly found nearly 15% of all claims are denied initially premierinc.com – often even claims that had received prior authorization. Denials tend to be especially common for high-cost treatments (average denied claim >$14,000 in charges) premierinc.com.

Most denied claims are never appealed. Despite patients’ right to appeal, the vast majority of denials go unchallenged. According to Kaiser Family Foundation, fewer than 1% of people insured on ACA marketplace plans appealed their denied claims in 2021kff.org. (Many consumers are unaware they even can appeal cityviewnc.com.) Providers may attempt some “rework” of denials through billing staff, but formal appeals are rare relative to the volume of denials. Table 1 summarizes key denial and appeal statistics:

Metric (U.S.)	Recent Estimate
Claims submitted to private insurers annually	~3 billion premierinc.com
Initial denial rate (private insurers)	~15% of claims premierinc.com (similar ACA marketplace ~17–19%kff.orgkff.org)
Number of claims denied per year	~450 million (15% of 3 billion) targetedonc.com
Percentage of denied claims appealed by patients	< 1% (ACA plans, 2021)kff.org
Overturn rate for appealed claims (internal appeals)	~41% overturned (ACA plans) businessinsider.com; over 54% overturned (private plans)premierinc.com
Average cost to providers per appeal (admin labor)	~$44 per claim premierinc.com
Estimated annual provider cost to fight denials	~$19–20 billion premierinc.comtargetedonc.com

Table 1: U.S. health insurance claim denials and appeals (recent data). Denial rates and outcomes indicate a large gap between how many claims are denied and how few are ever appealed. Notably, over half of denials that are appealed ultimately get overturned in favor of payment premierinc.com, yet most denials are “never reworked” and the claims remain unpaid targetedonc.com. Providers currently spend nearly $20 billion annually on the labor-intensive process of pursuing appeals, at about $44 in administrative costs per claim appeal premierinc.com.

These figures highlight a huge opportunity: hundreds of millions of denied claims (representing potentially billions of dollars in medical payments) could be reversed if appeals were pursued. This is where generative AI is now stepping in – to close the gap by making the appeals process faster, cheaper, and more accessible for providers and patients.

Rise of AI-Powered Appeal Writing Tools

A new crop of AI-driven tools and services is emerging to help draft appeal letters automatically, leveling the playing field for providers and patients facing denials. Both startups and established healthcare companies are deploying large language models (LLMs) – similar to GPT-4 – that can generate persuasive, evidence-backed appeal correspondence in a fraction of the time it takes humans. Below we profile several notable examples and how they work.

AI Assistance for Doctors and Hospitals

Physicians and revenue cycle staff are among the early adopters of generative AI for denials management. For example, the physician social network Doximity launched a beta “DocsGPT” tool (built on ChatGPT) to help doctors craft pre-authorization and appeal letters to insurers aha.org. Doctors can input key details about a patient’s case and denial, and the AI will produce a draft appeal letter within minutes. Dr. Clifford Stermer, a rheumatologist in Florida, demonstrated this by prompting ChatGPT to write an appeal for an echocardiogram denial – the AI generated a multi-paragraph letter with cited medical literature in about one minute aha.org. While the draft required some fact-checking and editing, Stermer noted it provided an excellent time-saving templateaha.org. Such tools, integrated into physician workflows, aim to streamline “time-sapping” paperwork so clinicians can focus more on care aha.org.

Hospitals and health systems are also partnering with AI vendors to automate appeals. A wave of startups focused on providers has emerged. For instance, SmarterDx, a San Francisco-based startup, rolled out an AI denial-management tool in late 2024 that generates appeal letters “in a fraction of the time” for hospital billing teams cthosp.org. The software analyzes the insurer’s denial reason and the patient’s electronic medical record to identify supporting evidence (e.g. documentation that a hospital admission was medically necessary), then feeds that data into a custom large language model to draft a tailored appeal letter cthosp.org. According to co-founder Dr. Michael Gao, three health systems were using the tool as of early 2025 cthosp.org. SmarterDx charges clients based on money recovered (a contingency model) and is initially focused on hospital inpatient claim denials (such as disputes over correct diagnosis coding for admissions) cthosp.orgcthosp.org. Gao explains that their goal is “evening the playing field” against insurers’ algorithms cthosp.orgcthosp.org – giving providers an AI assistant to counter the AI many insurers use in claims processing.

Another major player is Waystar, a well-established healthcare payments technology company. In January 2025, Waystar announced AltitudeCreate, a generative AI tool that automatically drafts appeal letters for denied claims facebook.com. Waystar processes over $1.2 trillion in claims annually (nearly half of U.S. patient volume) techstartups.com, and it reports that hospitals spend huge resources – “close to $20 billion annually” – trying to overturn denials techstartups.com. By embedding AI in its claims platform, Waystar aims to help providers appeal denials at scale and recover more of the 450 million claims denied each year techstartups.com. “More than half of denied claims ultimately get overturned, but the appeal process is time-consuming, complex, and error-prone,” says Waystar CEO Matt Hawkins targetedonc.com. The new AI assistant (part of Waystar’s AltitudeAI suite) addresses this by generating appeal letters autonomously – pulling in the relevant contract language, clinical justifications, and reference data needed to make a strong case techstartups.com targetedonc.com. Waystar cites that 63% of claim denials are actually recoverable with proper appeals, though most are never pursued targetedonc.com. By drastically lowering the effort to appeal, tools like AltitudeCreate could enable hospitals to appeal every denial, even low-dollar claims that previously might be written off.

Even some health systems are building in-house AI solutions. New York University’s Langone Medical Center created an internal AI team that has used generative models to improve claims processing and automate pieces of the denial workflow cthosp.orgcthosp.org. However, many provider organizations lack the resources to develop their own AI, which is why third-party vendors are filling the gap. Industry analysts note a “surge in interest” over the last 18 months in these AI denial management solutions as large language models have matured cthosp.org. Hospitals see the appeal (no pun intended) of reducing manual paperwork and potentially recouping revenue that would otherwise be lost.

Patient-Focused AI Appeal Startups

It’s not just providers – entrepreneurs are also equipping patients with AI tools to fight claim denials. One high-profile startup is Claimable, founded in 2024 by Warris Bokhari (a former ICU doctor and insurance executive). Claimable’s platform uses AI and a vast database of medical evidence and insurance rules to help patients generate personalized appeal lettersbusinessinsider.comgetcoai.com. Users answer an online questionnaire about their denial (taking ~30 minutes), and the system produces a draft appeal letter that includes the patient’s story, relevant clinical guidelines, and even references to scientific literature or policy termscthosp.org. The service then mails the appeal to the insurance company – and even cc’s relevant regulatory agencies to put additional pressure on the insurerbusinessinsider.com. Claimable charges patients a flat $39.95 per appeal (regardless of claim size or outcome) businessinsider.com cthosp.org. Early results are striking: Claimable reports about an 85% success rate in overturning denials for the appeals it has submitted businessinsider.com businessinsider.com. By late 2024, the startup had helped file hundreds of appeals for treatments like autoimmune drugs and migraine therapies, with many wins businessinsider.com. Bokhari describes these appeals as a productive, non-violent way for frustrated patients to push back against an unfair system businessinsider.com businessinsider.com. He notes that in the U.S., only through appeals can patients often get a human to review their case (insurers’ initial denials may be algorithmic) getcoai.com. Claimable plans to expand coverage to 100+ medical conditions in 2025 getcoai.com, reflecting huge demand from patients who previously felt helpless when claims were denied.

 Screenshot of an AI-driven appeal platform (Counterforce Health). The interface allows users to input a denial scenario (e.g. an emergency surgery miscoded as elective) and then click “Appeal This Denial.” The AI pulls in the patient’s coverage policy and denial letter, and within seconds generates a comprehensive appeal letter for the insurer. This free tool also offers an automated agent that can call the insurance company on the patient’s behalf to follow up cityviewnc.com cityviewnc.com.

Another free resource, Counterforce Health, was launched in 2025 by a North Carolina team to help patients contest denials without the hassle cityviewnc.com. Counterforce provides two AI “agents”: one that generates a customized appeal letter and another (nicknamed “Maxwell”) that can automatically call the insurer to escalate the appeal via phone cityviewnc.com cityviewnc.com. “The end game is reducing the patient burden fully,” says co-founder Neal Shah cityviewnc.com. Since its beta launch in January 2025, thousands of patients have used Counterforce’s letter generator, and a few small clinics are even leveraging it on behalf of their patients cityviewnc.com. The AI is trained on a wealth of data – from healthcare service codes to legal databases of past denial lawsuits – so it can cite regulations and correct billing codes in the appeal text cityviewnc.com cityviewnc.com. In testing, Counterforce’s generative model produced a thorough three-page appeal letter (complete with citations) in under a minute cityviewnc.com cityviewnc.com. By equipping patients with the same sophistication that insurers use (Shah calls it a “symmetrical weaponry” approach cityviewnc.com), tools like this aim to dramatically raise the rate of appeals filed.

Other notable examples include FightHealthInsurance.com, a free AI tool created by software engineer Holden Karau in 2023. It uses a simple prompt: users input information from their denial and medical history, and the tool outputs a ready-to-send appeal letter getcoai.com. Even tech giants in the insurance space are taking note: UnitedHealthcare’s recent controversies (a murder of its CEO and allegations of AI-driven wrongful denials) have shone a spotlight on denial practices getcoai.com, likely accelerating interest in consumer-facing appeal aids. In summary, a range of AI solutions – from physician-facing assistants to patient self-service apps – are rapidly emerging. They all share a common promise: to auto-generate well-crafted appeal letters that can turn an initial “No” from the insurer into a paid claim, with minimal human effort.

A Future of Near-Universal Appeals (Next 3 Years)

Industry experts predict that within a few years, appealing denied claims could become standard practice for nearly every denial, thanks to the negligible cost and effort with AI. We are likely heading toward a future state where virtually 100% of denied claims are appealed by providers or patients, as AI agents make the process as easy as clicking a button. Here’s how such a scenario might look by around 2028:

• Every Denial Triggers an Instant Appeal: The moment an insurer denial is received (electronically), an AI system at the provider’s office or a patient’s smartphone automatically drafts an appeal letter and submits it. What is now an arduous task taking days could be done in seconds. Even denials for small-dollar claims or technical reasons will be appealed, whereas today many of those are simply written off due to cost of follow-up. In effect, “no denial goes unchallenged.”

• Explosion in Appeal Volume: If appeal rates jump from <1% to nearly 100%, the number of appeals filed annually would increase hundreds-fold. Instead of only a few hundred thousand formal appeals (as seen today), we could see on the order of hundreds of millions of appeals each year, corresponding to the ~450 million denials issued yearlytargetedonc.com. Every hospital and large clinic might be auto-filing thousands of appeals per day via their revenue cycle AI systems. This flood of appeals ensures that insurers must review (or at least respond to) almost every denial decision.

• High Success Rates and Rapid Resolutions: If historical patterns hold, a large share of these appealed claims will be overturned in favor of the provider/patient. Currently about 50–60% of appealed denials get reversed upon internal or external appeal review premierinc.com targetedonc.com. In a future state where appeals are ubiquitous, one might expect similar success rates – meaning hundreds of millions of additional claims paid that would otherwise have been lost. Patients would experience far fewer dead-end denials; nearly every denied treatment would at least have a second chance. The turnaround time for appeals could also shorten: AI can draft the letters instantly, and insurers themselves may adopt AI to expedite appeal adjudication. It’s conceivable that many disputes could be resolved in days instead of months.

• Minimal Cost per Appeal: Crucially, the cost to generate each appeal will be tiny (pennies or a few dollars of cloud computing time) compared to the ~$44 in staff labor today premierinc.com. The marginal cost of appealing every denial approaches zero with full automation. This means providers have nothing to lose by appealing everything – even if an appeal has a low chance or is for a small reimbursement, the AI will file it anyway. In the aggregate, providers would no longer be constrained by limited billing staff; an AI assistant can handle virtually unlimited volume. A large hospital system, for example, could have an autonomous “denial appeals bot” working 24/7, ensuring no denial slips through without a fight.

• Patient Advocacy as the Norm: On the patient side, imagine most consumers (or their doctors on their behalf) using easy apps to appeal any denial from their insurance. The knowledge that an AI agent is available might encourage more patients to pursue needed care because they know any initial denial can and will be contested. The daunting paperwork that used to discourage patients will be handled behind the scenes by AI. In three years, it might be routine for an insured patient to get a denial letter in the mail and immediately respond by uploading it to a chatbot or snapping a photo in an app that generates the appeal letter to send back.

Overall, the next few years could bring a paradigm shift: denial management moving from a low-volume, manual exception process to a high-volume, largely automated process. Essentially, appeals might become an expected “second stage” of claims, with AI systems on both sides negotiating payment after an initial denial. This future is supported by current trends – the last 1–2 years have already seen mainstream acceptance of generative AI in medicine, and many providers reporting successful pilot results and ROI from AI-assisted appeals. As one healthcare CEO quipped, until broader fixes come, “this might be the solution” for the denial problem cthosp.orgcthosp.org.

Financial and Operational Implications of Industry-Wide AI Appeals

If nearly all denials are appealed via AI, the impact on healthcare finances and operations will be significant. This industry-wide shift would affect insurance companies, healthcare providers, and potentially patients’ costs. Below we analyze the possible implications:

Impact on Healthcare Providers (Doctors & Hospitals)

For providers, ubiquitous AI-generated appeals promise major revenue recovery and efficiency gains. Hospitals currently forfeit substantial income from unappealed denials – often writing off smaller claims or lacking resources to pursue every case. In a future with automated appeals, providers could recover a large share of revenue that is rightfully owed for services. Waystar estimates about 63% of denied dollars are recoverable with proper appeal effort targetedonc.com, so providers stand to recoup potentially tens of billions of dollars that today are lost. This improves hospitals’ financial stability and reduces the bad debt that can ultimately get passed to patients.

Operationally, providers could dramatically cut administrative costs related to denials. Instead of employing large staffs for denial management, much of the work would be handled by AI. The ~$19.7 billion/year that providers spend fighting denials premierinc.com can be reduced or reallocated. Routine drafting of appeal letters, assembling medical evidence, and tracking appeal status can be offloaded to software. This could allow provider organizations to redeploy billing specialists to more complex cases or other revenue cycle tasks. Physicians, too, benefit by reclaiming time – an appeal letter that might have taken an hour of dictating and editing can be done with a simple prompt, reducing clerical burden and burnout. In essence, provider workflow becomes more efficient: denied claims move through an automated second-pass process (appeal) without requiring the same level of human intervention as before.

It’s worth noting that while providers will save on labor, they may incur new costs for AI tools (licensing software like SmarterDenials or paying per-use fees). However, these costs are likely far lower per claim than the current manual process. Many startups charge on a contingency or subscription model that aligns with recovered revenue cthosp.org, so the ROI for providers is attractive. Larger hospital systems might invest in their own AI infrastructure, trading some upfront cost for long-term savings. Overall, providers who embrace AI appeals should see improved cash flow (more claims paid on first or second submission) and lower overhead per claim. This could especially benefit smaller clinics or physician practices that historically couldn’t afford intensive denial follow-up – now an AI service can do it for them, potentially improving their reimbursement rates to levels big health systems enjoy cityviewnc.com.

Impact on Insurance Companies (Payers)

For insurers, a world of near-automatic appeals poses challenges and likely requires adaptation. In the short term, health insurance companies would face a massive increase in appeals to review. Currently, because such a tiny fraction of denials are appealed, insurers save money – on both payouts and administrative work – when patients/providers don’t contest denials. If suddenly nearly every denial triggers an appeal letter, insurers must allocate resources to handle them. This could mean higher administrative costs for payers, at least initially: more staff to process appeals, or investments in their own AI to triage and respond to appeals. Some insurers might follow the same playbook as providers by deploying AI agents on their side to quickly analyze appeals and draft response letters or decisions. We could see an “AI arms race” between provider bots and insurer bots.

Financially, insurers are likely to end up paying more claims. Because a high proportion of appealed denials are overturned (often because the initial denial was unjustified or additional info is provided), nearly universal appeals mean insurers can no longer count on denials as a pure cost-saving mechanism. Many denials that would have quietly gone unresolved will now result in payments. For example, if an insurer initially denies 100,000 claims worth $100 million, in today’s world maybe only 1,000 are appealed and 500 overturned (paying a small amount). In a future scenario, 100,000 appeals might be filed and ~50,000 overturned, forcing payment on a large chunk of that $100 million. In effect, insurers’ medical loss ratios (the share of premiums paid out in claims) could rise if they must honor more claims upon appeal.

To compensate, insurers might adjust their strategies. One potential response is reducing initial denial rates for borderline cases, knowing that an automatic appeal will come anyway. If an insurer’s algorithm currently auto-denies certain claims expecting few appeals, that calculus changes when every denial becomes an extra cycle of work with a good chance of reversal. Insurers might become more selective, denying only when they have strong grounds or required documentation is truly missing. In theory, this could actually improve fairness – fewer inappropriate denials – as payers realize it’s not worth denying claims that won’t hold up under appeal. We might see insurers preemptively request more information (or use AI to gather it) on the first submission to make correct decisions and avoid the appeal loop.

On the flip side, insurers could also try new tactics to uphold denials. They might employ advanced AI to generate counter-arguments to appeals, or even automatically trigger secondary reviews. They may also invest in faster appeals resolution units to keep up with volume, possibly even automating approval of appeals that meet certain criteria (to avoid backlog). Another likely impact is on insurance premiums and plan design: if insurers end up paying out more in claims (because fewer denials “stick”), they could raise premiums or tighten coverage policies to maintain their profit margins. Some industry observers worry that insurers might respond to rising payout rates by introducing stricter prior authorization rules or narrower networks to control costs – though regulators are watching closely and have pushed back on excessive barriers to carecthosp.orgcthosp.org. In summary, insurers will need to balance the increased short-term administrative burden and payout with longer-term adjustments in pricing and utilization management. The dynamic between providers and payers could become more collaborative in some cases (e.g. shared data to avoid denials) or more contentious in others (each side’s AI trying to out-negotiate the other).

Impacts on Overall Healthcare Costs and Patient Experience

At the system level, near-universal appeals driven by AI could have mixed effects on healthcare costs. On one hand, administrative waste could decrease. As noted, the U.S. healthcare system loses an estimated $350 billion annually to administrative complexity and wastetargetedonc.com. Automating denial resolution addresses a slice of this problem by eliminating manual paperwork and repeated back-and-forth. The process of resolving payment disputes becomes more efficient, potentially reducing cost per claim for both providers and payers in the long run (once systems are in place). There is also a possibility that with AI handling routine denials, human experts can focus on the truly difficult cases, improving overall quality of decisions. Moreover, if insurers become more accurate upfront (to avoid unnecessary denials) and providers improve documentation (knowing AI will check it), the initial claim submission process might improve, resulting in fewer denials to begin with.

On the other hand, if many more claims are paid that previously would have been denied (and never paid), the total medical expenditures by insurers will rise. This money was always owed for covered services, but insurers often held onto it when patients didn’t appeal. When that changes, the payout increase could be substantial – potentially tens or hundreds of billions of dollars more paid claims across the industry per year. Those costs don’t vanish; they will be distributed via higher premiums, or absorbed partly through insurer profit margins. However, note that patients were paying many of those denied costs out-of-pocket or foregoing care. In a future with ubiquitous appeals, more of those costs get covered by insurance as intended, which could reduce the financial burden on patients and improve health outcomes (patients won’t abandon treatment due to a denial as often getcoai.com getcoai.com). So, while insurance companies might pass some costs along, the value delivered to patients and providers (in terms of covered care) increases.

There are also policy and regulatory implications. Regulators may need to monitor how both sides use AI – for example, ensuring that AI-generated denial letters or appeal letters remain accurate and fair. The Centers for Medicare & Medicaid Services (CMS) has already finalized rules to make insurers respond faster to appeals and publicly report denial metrics cthosp.org. If nearly all denials are appealed, those metrics will draw even more attention (e.g. if an insurer is shown to deny a high volume and frequently lose on appeal, regulators could intervene). This transparency could incentivize insurers to improve their initial decisions. Additionally, widespread use of AI in this domain raises questions about accuracy and errors: generative AI must be carefully validated to avoid hallucinations or misstatements in letters, which could otherwise add work if insurers reject appeals due to mistakes. Leading organizations like the AMA caution that AI outputs need oversight cthosp.org cthosp.org. It will be crucial that providers treat AI drafts as a starting point and verify critical details (e.g. patient identifiers, clinical facts) before submission – a task that can be streamlined with better training of models on healthcare-specific data (as some startups are doing cityviewnc.com cityviewnc.com).

From a patient’s perspective, an era of nearly all denials being appealed could vastly improve patient satisfaction and access to care. Today, many patients give up when a claim is denied, sometimes avoiding future treatment for fear of cost. In the future, patients may feel empowered knowing an appeal will likely fix the issue, which encourages them to stick with prescribed treatments. The financial toxicity of denied claims (a contributor to medical debt) would diminish if most valid claims eventually get paid. Patients will also become accustomed to digital tools handling their insurance battles – much like how tax software handles the complexity of the tax code for consumers. That said, there could be downsides if not managed: for instance, if insurers start fighting appeals with their own automated form letters, patients might get deluged with confusing correspondence. The hope, however, is that automation will streamline and shorten the overall denial-resolution process, so that what used to take multiple phone calls and letters might be resolved with a couple of automated exchanges of information.

Conclusion

The advent of generative AI in medical claim appeals is poised to transform a corner of healthcare that has long been a source of frustration, wasted cost, and inequity. By making it easy and inexpensive to contest insurance denials, AI appeal writers are ensuring that no claim is simply ignored or dropped due to paperwork burdens. In the immediate term, pioneering startups (like Claimable, Counterforce Health, and SmarterDx) and innovative health tech companies (like Doximity and Waystar) are already showing tangible results – overturning denials and recouping payments with remarkable efficiency. U.S. healthcare providers are beginning to embrace these tools to reduce administrative overhead and improve their revenue cycle, while patients are gaining new avenues to advocate for themselves using AI.

If current trends continue, the next few years will see an acceleration toward near-universal appeals of denied claims. Such a future stands to benefit providers and patients through higher reimbursement and coverage of needed care, though it will require insurers to adapt and possibly recalibrate their denial practices. The financial implications are immense: hundreds of millions of currently unpaid claims could be funded, shifting some costs back onto payers but also eliminating the hidden “tax” of undue denials on vulnerable patients. Operationally, an AI-driven appeals process will streamline healthcare administration – turning lengthy manual workflows into automated transactions – but it will also test the resilience of insurer systems and the integrity of AI decision-making.

In an ideal scenario, widespread AI appeals might actually lead to a more fair and transparent system: insurers might focus on legitimate denials (since frivolous ones will be routinely challenged), and providers can ensure no valid claim is left on the table. The “denial and appeal” loop may become just another standardized step in claims processing, handled largely by algorithms, with human experts intervening only in complex disputes. Of course, achieving this vision will require careful implementation, ongoing oversight, and collaboration between stakeholders to avoid simply escalating an arms race of automation.

Nonetheless, the trajectory is clear – generative AI is changing how insurance denials are managed. As one healthcare leader noted, this technology “unlocks a new era of productivity and precision” in an area that desperately needs it targetedonc.com. Nearly every denied claim could soon get a second look, and when that happens, the balance of power shifts slightly back toward doctors and patients. In a healthcare system notorious for its paperwork and paralysis, the deployment of AI appeal agents offers a promising remedy: ensuring that “no” is not the final answer when care is on the line.

Sources

1. AHA Center for Health Innovation – “Will a Chatbot Be Just What the Doctor Ordered for Reimbursement Appeals?” (Feb 2023)aha.orgaha.org

2. Business Insider – “The CEO using AI to fight insurance-claim denials…” (Dec 2024)businessinsider.combusinessinsider.com

3. Kaiser Family Foundation (KFF) – “Claims Denials and Appeals in ACA Marketplace Plans” (2023 & 2025 data)kff.orgkff.org

4. Premier Inc. – “Trend Alert: Private Payers Retain Profits by Denying Claims” (Mar 2023)premierinc.compremierinc.com

5. TechStartups/CNBC – “Waystar launches generative AI tool to help hospitals fight denials” (Jan 2025)techstartups.comtechstartups.com

6. Modern Healthcare – “Providers lean on AI startups to challenge denials” (Jan 2025)cthosp.orgcthosp.org

7. CO/AI (getcoai.com) – “Meet the entrepreneurs using AI to fight claim denials” (Dec 2024)getcoai.comgetcoai.com

8. CityView (Fayetteville) – “How a N.C.-based company uses AI to appeal claim denials” (Apr 2025)cityviewnc.comcityviewnc.com

9. Targeted Oncology – “AI Writes Appeal Letters for Denied Claims...and Wins” (Mar 2025)targetedonc.comtargetedonc.com