Article

Medicare Advantage Plans Brace for Sweeping 2025 CMS Audit and Payment Rule Changes

  • June 11, 2025

CMS Tightens Oversight of Medicare Advantage Plans

In the coming year, the nation’s Medicare Advantage insurers – which cover over 31 million Americans – face an unprecedented wave of regulatory changes and scrutiny. The Centers for Medicare & Medicaid Services (CMS) has quietly ushered in a more aggressive audit regime for Medicare Advantage (MA) plans, alongside significant updates to how these plans are paid for the health risks of their enrollees.

Health plan CEOs, whose organizations collectively received about $455 billion in Medicare payments last year, are now grappling with what these changes mean operationally and financially. Many are preparing for a future in which annual federal audits become a routine part of doing business and risk adjustment rules are rewritten to curb excess payments.

Oversight Intensifies: RADV Audits Expand in 2025

Late this spring, CMS announced a dramatic expansion of its Risk Adjustment Data Validation (RADV) audits – the primary tool for verifying that MA plan payments are justified by members documented health status. Historically, CMS audited only a small sample (around 60) of MA contracts each year, targeting plans suspected of excessive billing. That is changing effective immediately: CMS will audit all eligible Medicare Advantage contracts annually (approximately 550 plans in total)1. In addition, the agency is fast-tracking a backlog of past years’ audits, pledging to complete all outstanding audits for payment years 2018 through 2024 by early 2026. This means health plans could be hit with multiple audit findings in short succession, condensing what might have been a decade of scrutiny into a much shorter window.

“We are committed to crushing fraud, waste and abuse across all federal healthcare programs,” Dr. Mehmet Oz, the CMS Administrator, said in a statement announcing the new audit strategy. While emphasizing the value of Medicare Advantage, Oz underscored that CMS must ensure [plans] are billing the government accurately2.

The RADV audits themselves will also become more intensive. CMS is increasing the sample size of medical records it reviews for each plan from about 35 records to as many as 200 records per plan annually1. By reviewing a larger slice of each plan’s claims, CMS aims to make any identified error rates more credible for extrapolation – a process of projecting the sample’s error rate onto the plan’s entire member population1. CMS finalized a rule in 2023 that, for the first time, allows auditors to extrapolate overpayment findings starting with audits of 2018 claims onward. In the past, if an audit uncovered (for example) $100,000 in improper payments in the sample, the plan would repay that amount; now CMS can multiply that figure across all similar cases in the year – a change that could turn modest audit findings into multimillion-dollar liabilities for plans.

To support this ambitious oversight agenda, CMS is bolstering its audit arsenal. The agency will deploy “enhanced technology” – including advanced data analytics, and potentially artificial intelligence, to flag suspect diagnoses in billing data1. It is also undertaking a massive workforce expansion, increasing its team of medical coders from just 40 to roughly 2,000 by September 2025 to manually review records and confirm unsupported codes2. This 50-foldstaffing surge underscores the scale of CMS’s commitment. All Medicare Advantage plans can now expect an audit each year, a stark departure from an era when many insurers never faced a RADV audit at all1.

For health plans, the immediate implication is a significant operational burden. Insurers will need to respond to ongoing documentation requests, often under tight deadlines, and may find themselves in perpetual audit preparation mode. Some plans are already ramping up their own internal audit teams and processes to mirror CMS’s efforts, aiming to catch and correct errors proactively before federal auditors arrive.

A Revamped Risk Adjustment Model and Policy Changes

Behind the audit crackdown is a broader effort to refine how risk adjustment – the system that pays more for sicker patients – is administered. In 2024, CMS began phasing in a new risk adjustment model (known as “V28”) for Medicare Advantage, the first major overhaul in years. This updated model recalibrates which diagnoses count toward a patient’s risk score and how much they raise payments. Notably, CMS removed over 2,000 diagnosis codes from the model that it deemed prone to being “up-coded” – the practice of documenting extra or more severe conditions to inflate payments3. The goal is to target codes most likely to be abused and ensure that payments better reflect genuine health status.

The transition to the new model is occurring gradually to mitigate disruption. For payment year 2024, risk scores were calculated with a blend (33% new model, 67% old model). By 2025, the balance flips to 67% new model (V28) and 33% old4, and by 2026 the new model will be fully in place. The V28 model introduces 115 condition categories (up from 86 in the previous model) but with a more selective set of diagnosis codes – 7,770 codes mapping to those categories, versus 9,797 codes in the old model4. In practical terms, some diagnoses that used to boost payments will no longer do so, or will do so to a lesser degree. Chronic conditions like diabetes, depression, or vascular disease are among those seeing coding criteria tightened or subdivided to prevent overstating a patient’s illness burden, according to policy analysts.

CMS argues these changes will improve payment accuracy and curb excess spending. Agency officials noted that Medicare Advantage plans have been paid billions more than similar patients in traditional Medicare, partly due to aggressive coding practices. Indeed, CMS now estimates MA plans overbill the government by about $17 billion a year through unsupported diagnoses, with some estimates as high as $43 billion. The new risk model, coupled with stepped-up audits, is designed to rein in this overspending. Med PAC, a congressional advisory body, has reported that payments to MA plans in 2024 were on track to be roughly $83 billion higher than they would have been in fee-for-service Medicare for the same enrollees – a gap these policies seek to narrow.

Health plans and providers, however, have voiced concern about the speed and impact of these changes. The industry pushed back hard when the new model was proposed, prompting CMS to adopt the three-year phase-in rather than an immediate switch3. Many insurers and health systems fear the model’s stricter coding could reduce payments for vulnerable patients, potentially affecting benefit offerings. CMS’s own projections suggested that despite the model changes, average plan payments per enrollee would still rise in 2024 and 2025, due to other adjustments. But those increases may be smaller than plans are used to, and impacts will vary byplans3.

The American Medical Group Association, representing provider organizations, cautiously noted that the phase-in gives CMS “an opportunity to refine the plan” if unintended consequences emerge by 2026. In essence, while regulators see the new model as a needed course correction, the industry sees a potential budget cut in disguise, to be fought or at least closely watched.

Operational and Compliance Challenges for Health Plans

For health plan executives, the confluence of comprehensive audits and new risk scoring rules translates into a daunting compliance agenda. Operationally, plans must strengthen their documentation practices and IT systems immediately. Every diagnosis code submitted for payment must be backed by proper medical record evidence – not just to withstand a CMS audit, but to ensure the plan isn’t overstating its risk scores under the refined model. Many insurers are conducting internal RADV-style audits on 2018–2022 data right now, essentially red-flagging any diagnosis in their system that might not hold up to scrutiny. By performing these self-audits and deleting or correcting unsupported codes in CMS’s database, plans can mitigate future penalties4. This proactive approach, encouraged by consultants, aims to “reduce and manage RADV financial exposure” by addressing issues before the government does.

Provider engagement is another critical piece. Medicare Advantage insurers often rely on networks of physicians and hospitals to document diagnoses, and historically some have incentivized providers to code comprehensively. Now the dynamic is shifting: plans are implementing new provider training and education on the V28 coding changes, stressing accurate and only supported diagnoses. Some plans are also revisiting their contracts with providers. Those that share risk with providers (through value-based arrangements or bonus incentives) may insert clauses making providers financially liable for coding errors that lead to audit recoveries. If a CMS extrapolated audit claws back millions of dollars from a plan, the plan doesn’t want to shoulder that alone – it may seek to recover portions from the physician groups whose documentation was found lacking. This is a delicate conversation, but it reflects how seriously plans are treating the new audit risk.

Internally, compliance and audit departments at MA organizations are bracing for a heavier lift. Plan CEOs are evaluating whether their teams have the bandwidth and expertise to handle continuous audit requests, or if they need to enlist outside help (such as specialized auditing firms or consulting partners). The administrative load of responding to RADV audits – pulling hundreds of medical records from archives, coding them, and submitting rebuttal evidence – is significant, especially for smaller regional plans. Plans must also keep pace with evolving guidance: CMS recently issued updated RADV audit dispute and appeal instructions (effective January 2025), clarifying how plans can challenge audit findings through a reconsideration process2. Ensuring the legal team is ready to navigate these appeals, especially when extrapolated sums are on the line, will be crucial.

Finally, IT systems need updates to accommodate the 2025 risk model blend and forthcoming full model transition. Claims and billing software must incorporate the new HCC definitions so that as of January 1, 2025, incoming claims are evaluated under the correct risk adjustment logic. Misalignments here could directly affect revenue projections and compliance. Some plans have had to reconfigure analytics dashboards and retrain their coders and coding vendors on the model’s nuances – for example, which codes no longer map to an HCC (and thus no longer increase payments)4. This system work is technical, but vital to avoid errors in submissions that could trigger audits or payment shortfalls.

Financial Stakes and Industry Response

The financial implications of CMS’s 2025 changes are multifaceted. On one hand, Medicare Advantage insurers might see lower revenue growth per patient as risk scores level off under the tighter model. On the other hand, they face the possibility of paying back substantial sums if audits uncover past overpayments. Even a small error rate can translate into a large liability when extrapolated across tens or hundreds of thousands of members. Past RADV audits (2011–2013) found overpayments in the range of 5% to 8%2. If a similar error rate were found today and extrapolated, a mid-sized plan with $1 billion in annual revenue might have to refund $50–$80 million for a single year – a heavy hit to earnings.

Compounding the concern, CMS’s decision to finalize audits from 2018 through 2024 in one burst means some plans could be writing checks for multiple years’ worth of overpayments almost at once. Financial officers are reviewing reserves and worst-case scenarios now. “If CMS identifies and extrapolates overpayments for those years, financial losses due to recoupment will be concentrated over a much shorter time period than under the prior timetable,” the Ropes & Gray analysis cautioned1. In other words, what might have been staggered as a series of smaller repayments over a decade could become a tidal wave of obligations around 2025–2026. This has implications for plan budgeting, dividend plans, and even market valuations – indeed, stock analysts have begun asking public MA insurers about their audit exposures in earnings calls.

Preparing for Change: Mitigation Strategies for Plans

In response to these challenges, savvy health plans are taking a multi-pronged approach to mitigate risk. One key strategy is investing in advanced analytics to identify coding outliers. Plans are leveraging data algorithms to scan claims for patterns – for example, providers who code unusually high rates of certain lucrative diagnoses – and then conducting targeted chart reviews to verify those cases. By doing so, plans can either validate the codes with proper documentation or proactively “unlock” and remove unsupported diagnoses from their submissions, thereby inoculating against future audit findings. This kind of internal cleanup, though potentially reducing payments in the short term, can save a plan from a costly claw-back down the road. Several large insurers have created special RADV task forces for this purpose, blending expertise from compliance, IT, and clinical coding teams.

Education and training are also front and center. Health plan leaders are doubling down on provider education programs to reinforce documentation standards. For example, physicians are being reminded that every chronic condition must be explicitly documented each year in the medical record to count for risk adjustment – and if they add a diagnosis, it should be one actively managed or treated, not just noted in passing. Plans are updating provider handbooks to reflect diagnoses that no longer risk-adjust under the new model, so clinicians don’t waste effort coding conditions that won’t contribute to funding. Some plans are even offering or requiring “documentation integrity” training sessions for network providers, knowing that many audit issues can be prevented at the point of care through better record-keeping.

Another defensive measure is incorporating more stringent audit clauses in vendor contracts. Many health plans use third-party vendors for chart reviews or in-home assessments to help identify additional diagnoses. In the wake of the RADV rule, plans are making sure those vendors attest to the accuracy of codes they submit on the plan’s behalf – and assume liability if codes don’t hold up in an audit. Similarly, plans in risk-sharing arrangements with providers are clarifying how any recovered payments will be handled, as noted earlier. The overarching aim is to align incentives so that everyone – plan, provider, vendor – has “skin in the game” to only report truthful, supportable diagnoses.

From a financial planning perspective, some insurers are bolstering reserves or reinsurance coverage to cushion against possible repayments. Just as importantly, they are scenario-testing the impact of lower risk scores. CFOs are running models on 2025 revenue under various coding intensity assumptions (for instance, if certain common diagnoses drop out of HCC scoring) to guide bids and benefit design for the upcoming plan year. In extreme cases, a few plans have hinted they might need to trim benefits or adjust premiums if the new model significantly undercuts their payments – a move that would likely invite member and political backlash. For now, most are taking a wait-and-see approach, hoping that improved documentation and coding accuracy can blunt the negative financial impacts.

Navigating the Changes with Technology and Support

As Medicare Advantage organizations brace for this new regulatory landscape, many are turning to technology and specialized support services to adapt more effectively. Digital operations platforms and analytics tools are emerging as essential aids in ensuring compliance without overwhelming internal teams. For example, some health plans are deploying AI-driven software to automatically review medical records for any discrepancies between documented conditions and submitted diagnosis codes. These tools can flag potential unsupported diagnoses in real time, allowing plans to correct errors before they are picked up in a CMS audit. Enhanced reporting systems also help plans continuously monitor their risk score trends under the new model and identify areas where scores are dropping due to the V28 changes – insight that can inform provider outreach and member care programs.

Mizzeto’s healthcare digital operations suite is designed to streamline back-office processes for payers, which now include the heavy compliance workloads. For instance, Mizzeto provides audit and compliance assistance, conducting transactional audits to ensure policy compliance and quality control. Such services can take on the labor-intensive task of reviewing claims and medical records for accuracy, effectively augmenting a health plan’s internal audit department. Mizzeto also specializes in claims processing automation and data management, which helps plans keep their billing accurate and up-to-date with the latest rules. By automating routine claims checks and integrating the new risk adjustment logic into claims workflows, these technologies reduce the chance of human error that could lead to audit findings.

Another area where external partners prove valuable is in financial reconciliation and provider recovery efforts. If a plan does end up owing money back to CMS or identifies overpayments made to providers, Mizzeto’s services include analyzing overpayment situations and even helping to recoup excess payments from providers in the plan’s network. This kind of support is critical when plans are processing the results of an audit or adjusting payments post-review. It ensures that once a compliance issue is identified, the plan can resolve it swiftly on the financial side – whether that means correcting claims, retrieving funds, or crediting CMS – all with minimal disruption to operations.

Crucially, these solutions are not about replacing human expertise but augmenting it. Health plan executives remain at the helm in setting strategy (such as how to respond to CMS rule changes or when to self-audit), but they are leveraging technology and trusted partners to execute those strategies at scale. The result can be a more resilient organization: one that can handle an uptick in audits and shifting payment formulas without sacrificing focus on member care.

Looking ahead, Medicare Advantage plans will continue to refine their approach as real-world data from 2025 rolls in. Early audit results and the first full year of the new risk score model will provide feedback, showing where coding patterns need improvement or which compliance investments yield the best returns. Health plan CEOs are keenly aware that the stakes are high – both in terms of dollar amounts and public trust. Yet, with thorough preparation, the right expertise, and strategic use of technology, plans can navigate these reforms. The overarching goal is aligning Medicare Advantage’s impressive growth with robust accountability. And while the 2025 CMS audit changes pose undeniable challenges, they also present an opportunity: for health plans to demonstrate their commitment to accuracy and quality, strengthening the partnership between the government and private insurers that millions of seniors rely on every day.

1CMS Announces Significant Changes to RADV Auditing Efforts: Considerations and Next Steps for the Medicare Advantage Industry

2CMS Rolls Out Aggressive Strategy to Enhance and Accelerate Medicare Advantage Audits

3Providers, payers press CMS to get rid of Medicare Advantage risk adjustment changes entirely

4Key Areas of Focus for Risk Adjustment as the Calendar Turns to 2025

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AI Data Governance - Mizzeto Collaborates with Fortune 25 Payer

AI Data Governance

The rapid acceleration of AI in healthcare has created an unprecedented challenge for payers. Many healthcare organizations are uncertain about how to deploy AI technologies effectively, often fearing unintended ripple effects across their ecosystems. Recognizing this, Mizzeto recently collaborated with a Fortune 25 payer to design comprehensive AI data governance frameworks—helping streamline internal systems and guide third-party vendor selection.

This urgency is backed by industry trends. According to a survey by Define Ventures, over 50% of health plan and health system executives identify AI as an immediate priority, and 73% have already established governance committees. 

Define Ventures, Payer and Provider Vision for AI Survey

However, many healthcare organizations struggle to establish clear ownership and accountability for their AI initiatives. Think about it, with different departments implementing AI solutions independently and without coordination, organizations are fragmented and leave themselves open to data breaches, compliance risks, and massive regulatory fines.  

Principles of AI Data Governance  

AI Data Governance in healthcare, at its core, is a structured approach to managing how AI systems interact with sensitive data, ensuring these powerful tools operate within regulatory boundaries while delivering value.  

For payers wrestling with multiple AI implementations across claims processing, member services, and provider data management, proper governance provides the guardrails needed to safely deploy AI. Without it, organizations risk not only regulatory exposure but also the potential for PHI data leakage—leading to hefty fines, reputational damage, and a loss of trust that can take years to rebuild. 

Healthcare AI Governance can be boiled down into 3 key principles:  

  1. Protect People Ensuring member data privacy, security, and regulatory compliance (HIPAA, GDPR, etc.). 
  1. Prioritize Equity – Mitigating algorithmic bias and ensuring AI models serve diverse populations fairly. 
  1. Promote Health Value - Aligning AI-driven decisions with better member outcomes and cost efficiencies. 

Protect People – Safeguarding Member Data 

For payers, protecting member data isn’t just about ticking compliance boxes—it’s about earning trust, keeping it, and staying ahead of costly breaches. When AI systems handle Protected Health Information (PHI), security needs to be baked into every layer, leaving no room for gaps.

To start, payers can double down on essentials like end-to-end encryption and role-based access controls (RBAC) to keep unauthorized users at bay. But that’s just the foundation. Real-time anomaly detection and automated audit logs are game-changers, flagging suspicious access patterns before they spiral into full-blown breaches. Meanwhile, differential privacy techniques ensure AI models generate valuable insights without ever exposing individual member identities.

Enter risk tiering—a strategy that categorizes data based on its sensitivity and potential fallout if compromised. This laser-focused approach allows payers to channel their security efforts where they’ll have the biggest impact, tightening defenses where it matters most.

On top of that, data minimization strategies work to reduce unnecessary PHI usage, and automated consent management tools put members in the driver’s seat, letting them control how their data is used in AI-powered processes. Without these layers of protection, payers risk not only regulatory crackdowns but also a devastating hit to their reputation—and worse, a loss of member trust they may never recover.

Prioritize Equity – Building Fair and Unbiased AI Models 

AI should break down barriers to care, not build new ones. Yet, biased datasets can quietly drive inequities in claims processing, prior authorizations, and risk stratification, leaving certain member groups at a disadvantage. To address this, payers must start with diverse, representative datasets and implement bias detection algorithms that monitor outcomes across all demographics. Synthetic data augmentation can fill demographic gaps, while explainable AI (XAI) tools ensure transparency by showing how decisions are made.

But technology alone isn’t enough. AI Ethics Committees should oversee model development to ensure fairness is embedded from day one. Adversarial testing—where diverse teams push AI systems to their limits—can uncover hidden biases before they become systemic issues. By prioritizing equity, payers can transform AI from a potential liability into a force for inclusion, ensuring decisions support all members fairly. This approach doesn’t just reduce compliance risks—it strengthens trust, improves engagement, and reaffirms the commitment to accessible care for everyone.

Promote Health Value – Aligning AI with Better Member Outcomes 

AI should go beyond automating workflows—it should reshape healthcare by improving outcomes and optimizing costs. To achieve this, payers must integrate real-time clinical data feeds into AI models, ensuring decisions account for current member needs rather than outdated claims data. Furthermore, predictive analytics can identify at-risk members earlier, paving the way for proactive interventions that enhance health and reduce expenses.

Equally important are closed-loop feedback systems, which validate AI recommendations against real-world results, continuously refining accuracy and effectiveness. At the same time, FHIR-based interoperability enables AI to seamlessly access EHR and provider data, offering a more comprehensive view of member health.

To measure the full impact, payers need robust dashboards tracking key metrics such as cost savings, operational efficiency, and member outcomes. When implemented thoughtfully, AI becomes much more than a tool for automation—it transforms into a driver of personalized, smarter, and more transparent care.

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Importance of an AI Governance Committee

An AI Governance Committee is a necessity for payers focused on deploying AI technologies in their organization. As artificial intelligence becomes embedded in critical functions like claims adjudication, prior authorizations, and member engagement, its influence touches nearly every corner of the organization. Without a central body to oversee these efforts, payers risk a patchwork of disconnected AI initiatives, where decisions made in one department can have unintended ripple effects across others. The stakes are high: fragmented implementation doesn’t just open the door to compliance violations—it undermines member trust, operational efficiency, and the very purpose of deploying AI in healthcare.

To be effective, the committee must bring together expertise from across the organization. Compliance officers ensure alignment with HIPAA and other regulations, while IT and data leaders manage technical integration and security. Clinical and operational stakeholders ensure AI supports better member outcomes, and legal advisors address regulatory risks and vendor agreements. This collective expertise serves as a compass, helping payers harness AI’s transformative potential while protecting their broader healthcare ecosystem.

Mizzeto’s Collaboration with a Fortune 25 Payer

At Mizzeto, we’ve partnered with a Fortune 25 payer to design and implement advanced AI Data Governance frameworks, addressing both internal systems and third-party vendor selection. Throughout this journey, we’ve found that the key to unlocking the full potential of AI lies in three core principles: Protect People, Prioritize Equity, and Promote Health Value. These principles aren’t just aspirational—they’re the bedrock for creating impactful AI solutions while maintaining the trust of your members.

If your organization is looking to harness the power of AI while ensuring safety, compliance, and meaningful results, let’s connect. At Mizzeto, we’re committed to helping payers navigate the complexities of AI with smarter, safer, and more transformative strategies. Reach out today to see how we can support your journey.

February 14, 2025

5

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Feb 21, 20242 min read

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Modernizing UM Intake

Modernizing UM Intake

For health plans seeking to modernize utilization management (UM), streamline operations, and meet the evolving expectations of regulators and providers alike, one core issue remains persistently overlooked: the absence of integrated, real-time validation within the UM intake process.

Each day, thousands of prior authorization (PA) requests arrive via fax, web portals, and clearinghouses. Before a nurse or decision engine can determine whether a service is medically necessary, the system must first answer a more fundamental question: Is this member eligible for coverage — right now, for this service, from this provider?

Surprisingly, this foundational step is still often handled manually, inconsistently, or retroactively. The result? Delays, denials, and widespread frustration across the healthcare ecosystem.

Intake is not a back-office task. It is the gateway to care. Without embedding real-time validation at this crucial entry point, the rest of the UM process — no matter how advanced — remains inefficient, error-prone, and reactive.

Why This Remains a Problem in 2025

On paper, eligibility verification should be simple. Health plans maintain detailed member rosters and benefit files. Providers know their patients and the services they’re requesting. Yet in practice, the data submitted — often via scanned faxes or portal uploads — frequently doesn’t match what’s on file.

Typos, outdated coverage, incomplete fields, and mismatched provider information are routine. When a request arrives with a missing member ID or an out-of-network provider, the workflow stalls. Intake staff are forced to search across multiple systems or call provider offices for clarification. What should take seconds can drag into days.

The problem is compounded by the fact that many health plans treat eligibility and provider validation as a downstream function — something checked only after clinical review has begun. This leads to wasted clinical resources, avoidable denials, and costly rework that strains provider relationships.

The impact is significant. Delays in eligibility confirmation are a leading cause of pended or returned prior authorization requests. When plans can’t confirm who the member is, what their benefits include, or whether the provider is in-network, decisions are delayed or denied entirely. This drives up call center volume, inflates administrative costs, and erodes trust with both providers and members.

With prior authorization already under scrutiny for creating access barriers, these avoidable intake failures represent a growing risk — operationally, financially, and reputationally.

A Modern Solution: Embedded, Automated Validation at Intake

The solution begins by reimagining intake as more than just document collection. It must become a real-time eligibility engine.

As faxes, PDFs, and form submissions are received, their data should be immediately digitized, validated, and cross-referenced against the plan’s enrollment and provider systems — before clinical review begins.

The first step is intelligent data capture. Using tools like optical character recognition (OCR), AI-powered form parsers, or integrated EDI feeds, intake systems can now reliably extract key fields such as member name, ID, date of birth, service requested, and provider NPI. Any uncertainty or inconsistency should automatically trigger flagging or human review.

Once extracted, real-time eligibility and provider validation can occur. The system checks whether the member is active for the requested date of service, whether the provider is in-network, whether the benefit covers the requested service, and whether prior authorization is required at all.

Done well, this validation happens in seconds. Clean, accurate requests are routed directly to clinical review — or even automatically approved based on rules. Errors are flagged for correction or returned to the provider with clear guidance, eliminating long-cycle rework.

Leading health plans are beginning to treat these validations not as post-intake audits, but as real-time filters. This ensures that only actionable, member-matched requests move forward. Intake teams and nurses spend less time correcting data, and more time making decisions. Turnaround times improve, and providers experience fewer frustrating delays.

The business value is clear. Plans that have implemented real-time validation of member, provider, and benefit information report a 30–50% reduction in pended requests due to data errors, a 25% improvement in turnaround times, and significantly lower call center burden. These changes directly improve provider satisfaction and help meet regulatory expectations — especially in states adopting prior authorization transparency laws.

Strategically, embedding validation checks at intake reduces the total cost of ownership for UM systems. With fewer unnecessary clinical reviews and resubmissions, plans can achieve more with leaner staffing while maintaining or increasing throughput. That’s not just operational efficiency — it’s defensible ROI.

Why Now Is the Time to Act

For health plan executives, the takeaway is simple: validating member, provider, and benefit data is no longer a task for the call center. It’s a critical enabler of modern utilization management and should be treated as such.

The technology is ready. OCR and AI can accurately digitize most intake documents. APIs can perform real-time queries to enrollment and provider databases. Provider directories are becoming increasingly standardized and accessible. The obstacle isn’t technical — it’s organizational focus.

As health plans invest in broader digital transformation — from automated decision engines to generative AI support tools — they must not neglect the foundation. A truly intelligent UM process begins with intelligent intake.

That means ensuring the request is clean from the start: the right member, the right benefits, the right provider. Once that’s established, every subsequent step — clinical review, approval, communication — can proceed faster, with greater confidence.

Plans that prioritize this foundational step today will be better positioned to reduce administrative costs, meet regulatory mandates, and deliver faster, safer care. In an environment where delays can have real clinical consequences, getting the first step right has never been more important.

It’s time to modernize eligibility and validation checks — and unlock the full potential of utilization management.

Jan 30, 20246 min read

August 1, 2025

2

min read

2026 Prior Authorization Mandates

Navigating CMS’s 2026 Prior Authorization Turnaround Time Mandates

Health plan leaders are approaching a pivotal deadline in utilization management. Beginning on January 1, 2026, new federal regulations from the Centers for Medicare & Medicaid Services (CMS) will significantly reduce the turnaround times for prior authorization decisions. These changes stem from the CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F), which aims to streamline approval processes and improve timely access to care. Under this rule, Medicare Advantage plans, state Medicaid agencies, managed care plans, CHIP programs, and exchange-based Qualified Health Plans must respond to expedited prior authorization requests within 72 hours and standard requests within seven calendar days.

Historically, prior authorization processes could extend up to 14 days, making this change particularly impactful for health plans. CMS projects these accelerated decisions and electronic processing will save approximately $15 billion over ten years by reducing administrative inefficiencies. Given the magnitude of this regulatory shift, utilization management (UM) directors and chief medical officers need to rapidly adjust their operations, technology infrastructure, staffing, and reporting mechanisms to ensure compliance.

Background and Rationale of the New Requirements

Prior authorization delays have long hindered patient care by postponing necessary treatments. Acknowledging these persistent issues, CMS finalized the 2024 Interoperability and Prior Authorization Rule to promote quicker, more transparent decisions. The rule standardizes response times, sets clear expectations for denial explanations, and mandates annual public reporting of key authorization metrics, including volumes and average decision times.

Simultaneously, CMS is pushing health plans towards broader adoption of electronic prior authorization and interoperability standards, specifically through FHIR-based APIs to be fully implemented by 2027. This digital transformation seeks to eliminate outdated practices like faxed or phone-based authorizations, dramatically modernizing utilization management processes.

Operational Changes in Utilization Management

The new turnaround requirements compel health plans to thoroughly reengineer their prior authorization workflows. Health plans must now swiftly triage incoming authorization requests, classify them as urgent or routine, and ensure rapid, proactive outreach to providers if necessary information is missing. Many health plans are proactively reassessing the necessity of prior authorizations for lower-risk services, thus reducing the total number of requests requiring manual intervention.

Automation has become critical. Leveraging rules-based decision-making tools, health plans can automatically approve routine, evidence-based requests, significantly reducing turnaround times. This digital integration also supports real-time processing, reducing the administrative burden and allowing clinical teams to concentrate on complex or ambiguous cases.

Technology Infrastructure Improvements

Meeting these new CMS requirements is as much a technology challenge as it is operational. Transitioning from legacy systems to fully digital, API-driven solutions is essential. Health plans are rapidly adopting HL7 FHIR standards, enabling electronic submissions and automated responses directly integrated within providers' electronic health records (EHRs).

Implementing these advanced technologies requires significant investments in IT infrastructure and data management capabilities. Health plans must ensure accurate data mapping, consistent clinical documentation, and robust privacy and security controls. Successful technological transitions not only meet compliance but also offer considerable long-term operational efficiencies.

Workforce Implications

These tighter turnaround requirements directly affect staffing strategies within utilization management departments. Health plans may need to increase staffing levels, cross-train employees, or introduce additional shifts, including weekend or holiday coverage, to manage expedited cases effectively. Moreover, clinical staff will need to clearly document and communicate reasons for denials, enhancing transparency and reducing confusion for providers.

Enhanced Reporting and Accountability

Increased transparency is a central aspect of the new regulations. Beginning in 2026, health plans must publicly report comprehensive prior authorization metrics. This unprecedented level of public accountability is expected to drive continuous performance improvement and foster competitive differentiation among health plans based on their efficiency and responsiveness.

Internally, enhanced data reporting capabilities will be crucial. Health plans are developing automated systems to track, report, and analyze prior authorization metrics. Regular analysis of these metrics will help identify performance bottlenecks, inform process adjustments, and improve provider interactions.

Impact on Member and Provider Experience

The anticipated improvements from these regulatory changes promise substantial benefits for patients and providers alike. Faster decisions will reduce delays in essential treatments, and clear explanations for authorization denials will enable more effective clinical decision-making. Providers, integrating authorization processes into their EHR workflows, will find the prior authorization process less burdensome, enhancing overall provider satisfaction and clinical efficiency.

Members will experience improved transparency and predictability, positively influencing their overall healthcare experience. As health plans continue to refine these processes, consumer trust and satisfaction are expected to increase significantly.

Preparing for Successful Implementation

Health plan leaders should:

  • Conduct comprehensive assessments of current authorization workflows.
  • Accelerate adoption of advanced interoperability and API technologies.
  • Invest in adequate staffing and robust training programs.
  • Establish strong internal reporting and analytics infrastructure.
  • Proactively engage and educate providers about new processes and expectations.

By embracing these strategies, health plans will not only comply with CMS mandates but also position themselves as industry leaders in utilization management.

Conclusion

The CMS 2026 prior authorization regulations mark a substantial shift towards quicker, more transparent, and patient-centered healthcare processes. While the transition poses challenges, the long-term benefits—enhanced efficiency, improved patient care, and stronger provider relationships—make the effort worthwhile. Health plan leaders who proactively adapt and innovate will set new standards in utilization management, ultimately benefiting providers, members, and the broader healthcare community.

Sources

  1. CMS Interoperability & Prior Authorization Final Rule (CMS0057F) – details on turnaround timelines, denial rationale requirement, API deadlines CMADocs+15Centers for Medicare & Medicaid Services+15K&L Gates+15MCG Health+6Epstein Becker Green+6CMADocs+6Leavitt Partners An HMA Company+1Centers for Medicare & Medicaid Services+1The Guardian
  1. AMA insights and industry pledges – scope reduction, transparency goals, continuity of care commitments American Medical Association+4American Medical Association+4The Guardian+4

Jan 30, 20246 min read

July 22, 2025

2

min read

Strategic Impact of Federal Medicaid Cuts

Strategic Impact of Federal Medicaid Cuts

Congress recently passed significant Medicaid cuts as part of the "Big Beautiful Bill," reshaping the financial landscape for healthcare providers and health plans nationwide. These funding reductions profoundly impact healthcare stakeholders, affecting Medicaid eligibility, provider reimbursements, and overall healthcare access. This article examines these cuts in detail, highlighting strategic insights for health plan executives.

Breakdown of the Medicaid Cuts

The Congressional Budget Office (CBO), analyzed extensively by KFF, forecasts substantial federal Medicaid spending reductions over the next decade, estimating a nationwide reduction of approximately $500 billion over ten years. Most states will experience an average decrease of about 13%, with some states facing cuts ranging from 7% to as high as 18%. These funding reductions specifically target expansion populations, managed care rates, and provider reimbursement structures.

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Impact on Health Plans

Health plans will experience both immediate and long-term effects from these Medicaid cuts. Increased member churn and enrollment volatility are likely outcomes, given that tightened eligibility criteria will cause individuals to frequently cycle in and out of Medicaid. This scenario increases administrative burdens, eligibility verification costs, and outreach expenses aimed at retaining eligible members. Furthermore, maintaining continuity of care and managing member health outcomes amid these disruptions will pose additional challenges.

Financial forecasting and risk management will become even more critical. Health plans must adjust their actuarial assumptions, premium rate-setting, and risk adjustment methodologies to account for potential revenue fluctuations and changing risk profiles. Contingency planning will be essential to navigate financial uncertainties resulting from decreases in enrollment.

Operational efficiencies will also become imperative as budgets tighten. Health plans will need to strategically invest in automation and advanced analytics to reduce administrative overhead and streamline core processes like utilization management (UM) and claims processing. Emphasizing preventive care and chronic disease management programs will also help lower costs associated with emergency and acute care services.

Provider-Side Implications

Providers will encounter significant reimbursement pressures due to reduced Medicaid funding, impacting care delivery and financial stability. Health plans will need to proactively manage potential narrowing of provider networks as reimbursement rates decline, which may increase provider contract negotiations. To mitigate these pressures, innovative value-based payment models and alternative reimbursement structures can incentivize quality outcomes and help stabilize provider networks.

Network adequacy and provider stability will become central concerns, as reimbursement cuts could lead to provider attrition from Medicaid networks, jeopardizing access to care for Medicaid members. The increased demand for essential providers, such as behavioral health specialists and primary care physicians, will further complicate network adequacy. Collaborating closely with providers on shared-risk arrangements can help stabilize networks and ensure continuity of care.

State-by-State Variability

The Medicaid cuts vary significantly across states. High-impact states such as California, Texas, and New York face larger proportional reductions, intensifying pressures on local health systems and requiring more strategic adjustments. In contrast, lower-impact states like Wyoming, Florida, and Alabama may have greater flexibility in transitioning their Medicaid operations. Health plan executives must closely analyze state-specific data to accurately project regional impacts and tailor responses accordingly.

Forward-Looking Strategic InsightsTo effectively respond to these Medicaid cuts, health plans should consider several strategic actions. Embracing value-based care models can stabilize revenue streams and improve patient outcomes by reducing reliance on fee-for-service reimbursement structures. Investing in digital transformation, including advanced analytics, automation, and artificial intelligence (AI), will enhance operational efficiencies, streamline UM processes, prior authorization, and claims processing.

Enhancing provider partnerships is another critical strategy. Health plans should explore shared-risk arrangements and provide resources to support providers in navigating financial pressures and improving operational efficiencies. Additionally, implementing robust member engagement and outreach strategies can help mitigate churn by proactively communicating eligibility criteria, renewal processes, and preventive care resources. Enhanced digital tools can further simplify member interactions and improve overall satisfaction.

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Conclusion

The Medicaid cuts implemented under the "Big Beautiful Bill" represent a significant shift in the Medicaid landscape, requiring health plan executives to make critical strategic decisions. By proactively addressing enrollment volatility, reimbursement pressures, operational efficiencies, and provider stability, health plans can navigate these reductions effectively and maintain the quality of care delivery.

Health plans that embrace innovation, strengthen provider partnerships, and enhance operational agility will be well-positioned to manage the impact of these Medicaid cuts and emerge stronger in an evolving healthcare market. At Mizzeto, we specialize in helping health plans adapt to market disruptions through smart automation, AI-powered operational tools, and expert staffing solutions. Whether you're reevaluating your UM workflows, navigating reimbursement shifts, or planning for churn-driven outreach, our team is here to help you build resilient, cost-efficient systems.

Sources:

https://www.kff.org/medicaid/issue-brief/allocating-cbos-estimates-of-federal-medicaid-spending-reductions-and-enrollment-loss-across-the-states/?utm_source=chatgpt.com

https://www.investors.com/politics/one-big-beautiful-bill-act-president-trump-tax-cuts-medicaid-spending/?utm_source=chatgpt.com

https://www.wsj.com/health/healthcare/medicaid-cuts-healthcare-trump-bill-7236d5e6?utm_source=chatgpt.com

https://healthjournalism.org/blog/2025/07/trumps-budget-bill-could-cost-lives-put-5-million-in-debt-how-to-cover-the-story/?utm_source=chatgpt.com

https://www.americanprogress.org/article/the-truth-about-the-one-big-beautiful-bill-acts-cuts-to-medicaid-and-medicare/?utm_source=chatgpt.com

https://www.cbo.gov/publication/61469?utm_source=chatgpt.com

Jan 30, 20246 min read

July 22, 2025

2

min read

Modernizing UM Intake with OCR Excellence

Modernizing UM Intake with OCR Excellence

In healthcare payer operations, utilization management (UM) intake is a mission-critical function—tasked with ingesting, interpreting, and processing prior authorization requests, clinical review documentation, and care determination materials submitted by providers. Yet despite widespread digital transformation across other parts of the healthcare ecosystem, UM intake remains heavily manual. Faxed forms, PDFs, and scanned medical records often arrive via fragmented workflows, requiring health plan staff to manually extract, transcribe, and route essential data to the correct systems and reviewers. This inefficiency adds significant friction to operations, delaying determinations and increasing labor costs. According to the 2023 CAHQ Index1 only 31% of prior authorization transactions are fully electronic, while 35% still rely on manual submission methods—a persistent mismatch that creates avoidable delays and administrative burden for health plans.

AI-driven OCR and NLP systems in payer settings have achieved very high accuracy in extracting and interpreting data from clinical and administrative documents. For example, a U.S. federal health agency (likely the VA) modernized its claims intake with an AI-based OCR platform: the legacy system’s ~77% accuracy was boosted to over 96% accuracy, while automating 99% of the form processing2. These results indicate that modern OCR/NLP solutions can surpass the 95%+ accuracy mark, often corresponding to extremely high classification AUCs. Such accuracy dramatically reduces human error – insurers have seen up to 90% error reduction in document processing when adopting OCR automation3. High precision in data extraction means payers can trust AI outputs for critical processes, minimizing misclassifications or overlooked information.

Enter Optical Character Recognition (OCR), now enhanced by natural language processing (NLP) to transform unstructured documentation into structured, actionable data. Unlike legacy OCR tools that merely digitize text, today’s AI-augmented OCR systems can parse scanned clinical forms and extract key fields—such as diagnosis codes, provider names, dates of service, and member identifiers—with high accuracy. For health plans, this advancement allows manual intake to be replaced—or significantly augmented—by automated workflows that feed critical data directly into UM systems, reducing processing time, ensuring auditability, and accelerating clinical review timelines.

From Bottlenecks to Breakthroughs: Time and Cost Savings

The operational impact of OCR is significant. Manual UM intake can take 10–15 minutes per case; OCR-capable automation handles them in seconds. When multiplied across thousands of prior authorizations, the downstream effect is profound—faster processing, reduced labor cost, fewer transcription errors, and a more agile payer workflow.

Faster, cleaner intake dramatically improves care delivery velocity. Staff can redirect from data entry to higher-value tasks like complex case review or provider outreach. Moreover, structured intake data enables robust analytics. Health plans can identify bottlenecks, monitor denial rates, and drill into clinical trends—all made possible by reliable, automated data capture.

Safeguarding Accuracy, Compliance, and Privacy

Speed means little without accuracy and control. To ensure trusted OCR deployment, health plans must couple systems with domain-specific training—covering medical terminology, diagnostic codes, and typical UM document formats. Validation layers should automatically flag low-confidence extracts for human review—kept deliberately low, often at under 5% of cases.

From a compliance standpoint, logging every step—from document ingestion to final approval—is non-negotiable. These logs support HIPAA mandates and audit readiness. Strong encryption, access controls, and document tracing help meet CMS and OCR privacy guidelines. OCR accuracy has also been rigorously tested in federally funded studies, where performance varies by layout, font, and data quality, reinforcing the need for process-specific oversight4.

The Tangible Benefits of OCR-Enabled UM Intake

Evidence from clinical and administrative implementations highlights the growing maturity of OCR/NLP in healthcare environments. For example, in a federally funded study, hybrid OCR/NLP systems achieved over 99% accuracy when extracting colonoscopy and pathology data across varied clinical report formats (PMC). 

Automating UM intake dramatically accelerates processing and decision times. By digitizing incoming requests and using AI to pre-populate or even auto-adjudicate cases, health plans have cut throughput times by as much as half. Real-world deployments back this up: one regional Medicare contractor implemented an intelligent document processing solution and cut document handling times by over 50% for 35 million Medicare appeal pages, speeding up prior authorization case reviews accordingly5. In short, OCR/NLP intake automation enables payers to process UM requests in a fraction of the time previously required.

A Roadmap for Implementation

Deploying OCR at scale begins with Document Profiling. This first step involves identifying the highest-impact document types—typically those that are high-volume and low in variability. Prior authorization forms, structured provider notes, and standardized intake formats are ideal candidates, as they offer consistency that allows OCR engines to perform with optimal accuracy from the outset.

Next comes Pilot Deployment, where a focused OCR/NLP solution is tested on a specific document category. During this phase, health plans should measure throughput, accuracy rates, error types, and the percentage of cases requiring manual review. This controlled environment helps teams fine-tune extraction logic, validate system performance, and establish key performance indicators for scaling.

System Integration follows, ensuring the extracted data flows securely and traceably into utilization management platforms or case management systems. This includes configuring APIs or file-based ingestion pipelines, verifying that data fields map correctly, and implementing audit trails to support traceability and compliance with HIPAA and CMS requirements.

The fourth phase, Scale Strategically, involves expanding OCR capability across a broader range of document types. This may include more complex or unstructured documents such as handwritten physician notes, scanned lab forms, or multi-page clinical summaries. As use cases broaden, it’s critical to continuously refine OCR models and adjust workflows to account for new formats or data variability.

Finally, Governance and Monitoring underpin the long-term success of OCR implementation. Health plans should maintain live dashboards to monitor system accuracy, processing times, and manual intervention rates. Regular audits must be conducted to validate performance, uncover biases or drift, and ensure that all data handling practices meet HIPAA, HITRUST, and other applicable standards. This ensures not only operational excellence but also defensible compliance in a highly regulated industry.

Conclusion: OCR as the Cornerstone of Modern UM

OCR is no longer optional in modern UM workflows—it’s essential. When properly deployed and governed, OCR enables profound improvements: faster decisions, fewer errors, reduced costs, and liberated staff. The shift from bottlenecked intake to seamless, automated data capture represents a measurable leap forward for payer operations.

For health plans facing cost pressures, regulatory scrutiny, and rising expectations, OCR-powered UM intake is one of the most accessible tools for transformation. With accuracy rates routinely exceeding 95%, and ROI often reaching 30%+ in the first year, the business case is compelling.

Mizzeto brings deep healthcare domain knowledge, process design expertise, and governance frameworks tailored for payer use. If your organization is ready to eliminate intake inefficiencies, improve accuracy, and secure your UM pipeline, reach out to Mizzeto. Let us help you deploy AI-enhanced OCR responsibly, effectively, and with demonstrable results.

Sources Cited

1 CAHQ Index

2 SPEEDING UP CLAIMS PROCESSING

3 Top Benefits of OCR in Insurance

4 Extracting Medical Information from Paper COVID-19 Assessment Forms

5 Amazon Web Services

Jan 30, 20246 min read

July 22, 2025

2

min read