Exposing the Gaps: The Need for Claims Auditing

Breaking Bottlenecks in Utilization Management

Utilization Management (UM) remains a fundamental component of health plan operations—ensuring that care is medically necessary and delivered efficiently. However, legacy systems and manual processes continue to impede decision speed, inflate administrative costs, and undermine provider and member satisfaction. Health plan executives are under mounting pressure to modernize these workflows. This article examines two key chokepoints in UM and outlines how automation and artificial intelligence (AI) can reengineer the process for better outcomes.

Fragmented Intake Channels: An Unresolved Legacy

Despite significant investments in digital infrastructure, most prior authorization (PA) requests still arrive through outdated, unstructured channels—faxes, phone calls, emails, scanned PDFs, or even smartphone photographs. These formats demand manual transcription and interpretation, driving up labor costs and introducing errors.

According to the CAQH, only 31 percent of prior authorization transactions were processed fully electronically via ASC X12N278, while 37 percent remained fully manual—processed by phone, fax, mail, or email¹. Manual processing is considerably more expensive and time-consuming. The CAQH Index shows payer-side costs average $3.50 per manual PA, compared to just $0.05 for fully electronic transactions. On the provider side, each manual submission consumes approximately $10–11 in staff effort².

This fragmentation affects the downstream UM workflow. Staff must sort through entries, clarify ambiguities, and reconcile incomplete information—all of which extend turnaround times. Providers frequently complain of submitting faxes or emails only to receive phone calls requesting additional details days later. For health plans, this creates backlogs, missed performance targets, and strained provider relations.

Documentation Overload: Reviewing the Irrelevant Along with the Relevant

Once intake is complete, UM nurses face another critical challenge: the volume of clinical documentation submitted in support of authorization requests. Providers often send extensive electronic medical record printouts, diagnostic reports, test results, and specialist notes—sometimes totalling hundreds of pages per case.

Reviewers must manually scan these documents, identify relevant facts, cross-check coverage guidelines, and reach a clinical determination. The process varies significantly in duration, often ranging from 30 minutes to several hours per case. In workloads of 20+ cases per day, this becomes a considerable staff burden.

From the health plan perspective, these delays translate into higher appeal volumes and compliance risks. When documentation is inconsistent or unnecessarily voluminous, decision-making becomes harder to standardize, resulting in variance across reviewers and potential errors that attract regulatory attention.

Automation at Intake: Converting Chaos into Standardized Data

The advent of Intelligent Document Processing (IDP) and Natural Language Processing (NLP) transforms how unstructured intake is handled. These tools can extract structured data from faxes, PDFs, and images, identifying key fields—member demographics, diagnosis codes, CPT codes, dates of service—and automatically populating intake systems.

Phone-based submissions can be converted to text via speech-to-text and NLP solutions. The value is not in eliminating humans, but in creating a single, reliable digital intake stream.

Health plans that implement these tools report dramatic improvements. One regional insurer processed over 200,000 authorizations annually through automated systems, achieving 90 percent first-pass accuracy and reducing data-entry burden by 40 percent. These gains support compliance with evolving CMS mandates on electronic prior authorization standards³.

AI-Infused Clinical Review: Enabling Smarter Decision-Making

Automation’s benefits extend into the clinical review phase when AI-driven tools analyze and summarize documentation. Models trained on medical language and entitlement policies can identify prescribed treatments, prior interventions, labs, and imaging outcomes relevant to PA criteria.

This allows for a triaged review model: routine, low-complexity requests may be auto-approved; ambiguous or high-risk requests are flagged for clinical review. Clinicians are presented with summaries and highlighted evidence, eliminating the need to browse hundreds of pages manually.

Health plans deploying these tools report up to a 50 percent reduction in average case review time. AI-assisted systems enhance consistency and reduce cognitive overload for UM staff, while preserving human oversight for critical decisions.

Regulatory Alignment: Meeting CMS Requirements Efficiently

The CMS Interoperability and Prior Authorization Final Rule (CMS‑0057‑F), effective January 1, 2026 (with APIs required by 2027), imposes strict requirements: seven‑calendar‑day turnaround for standard requests, 72‑hour turnaround for expedited requests, public reporting of authorization metrics, and standardized API-based communication⁴.

Automation is essential for compliance. Without it, health plans risk missing deadlines, misreporting metrics, and exposing themselves to regulatory sanctions. Automated intake and AI-supported review systems facilitate meeting timeliness standards, improve denial rationale transparency, and generate structured data required for public disclosures.

Operational and Strategic Returns

Adopting automation and AI in UM workflows delivers measurable operational and strategic advantages:

• Faster turnaround times, supporting regulatory compliance and enhanced provider/member experience
• Lower administrative costs, with per-case cost reductions from dollars to cents
• Improved decision consistency, reducing variability and appeal risk
• Better provider relationships, fostering collaboration and satisfaction
• Scalable operations, capable of handling volume without linear staffing growth

According to CAQH projections, universal adoption of electronic PA could save the healthcare system nearly $500 million annually.

Governance and Change Management

Implementing automation successfully requires more than technology. Integration with core UM systems such as QNXT or Facets is a prerequisite. Oversight mechanisms must be in place to audit automated decisions and ensure human review for denied cases. Clinician training is essential to shift from manual workflows to supervisory roles. Transparency—through AI outputs aligned to policy rationale—is critical for provider acceptance.

Monitoring key performance indicators—including intake accuracy, review time, first-pass approval rates, and provider satisfaction—is essential for evaluating ROI and guiding continuous improvement.

Conclusion

In today's healthcare environment, utilization management processes demand urgent modernization. Fragmented intake channels and documentation overload threaten decision efficiency, care quality, and compliance. Automation and AI offer pragmatic, scalable solutions that improve accuracy, reduce administrative friction, and enhance both provider and member experience—all while supporting regulatory alignment.

For health plan executives, investment in intelligent UM is not optional; it is a strategic imperative. At Mizzeto, we partner with plans to deploy integrated technology solutions that optimize intake, augment clinical review, and embed rigorous governance. To explore a tailored blueprint for digitally transforming your UM operations, contact us today.

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Sources Cited

¹2023 CAQH Index Report

²Administrative Transaction Costs by Provider Specialty

³Navigating The CMS Prior Authorization Final Rule: What Health Plans Need to Know

⁴CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F)

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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.

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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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Medicaid Cuts Could Reshape Health Plans

Medicaid, historically a stabilizing force in the health insurance industry, now faces growing uncertainty. Across several states, proposals to tighten eligibility, reduce reimbursement rates, and limit administrative funding are gaining momentum — moves driven by rising budget pressures and shifting priorities.

While these cuts remain proposals for now, health plans that administer Medicaid contracts are already bracing for a future that could look starkly different. If enacted, the changes would not merely trim around the edges; they would fundamentally alter the economics of Medicaid lines of business, posing deep risks to payer profitability, operational resilience, and member retention.

The Revenue Model Under Threat

For many plans — especially those heavily invested in government programs — Medicaid accounts for a significant portion of total revenue. However, Medicaid margins have always been slender, relying on scale and predictable membership to deliver sustainable returns. Proposed reductions in per-member-per-month (PMPM) payments, combined with renewed eligibility redeterminations, would tighten this margin even further.

Health plans are preparing for a scenario where healthier, lower-cost members fall off the rolls first, leaving behind a smaller, sicker population that is far more expensive to serve. This adverse selection effect would drive up medical loss ratios (MLRs) just as reimbursement dollars are drying up, creating a potentially untenable cost structure.

Operational and Strategic Fallout

The immediate financial impact is only part of the story. Operational disruption would be equally profound. Plans would need to manage increased churn, more reinstatement requests, and heavier call center volumes — all while under tighter administrative budgets. Provider networks, already strained in many Medicaid markets, could weaken further as reimbursement declines make participation less attractive for physicians and hospitals.

Perhaps most concerning for health plan leadership is the risk to long-term growth. Many plans have used Medicaid as a feeder into Medicare Advantage or ACA exchange products, cultivating member loyalty over time. Membership disruption at the Medicaid level could weaken these pipelines, undermining future revenue streams across the enterprise.

A Narrow Window to Act

While the policy landscape remains fluid, waiting for final decisions would be a strategic mistake. Forward-looking health plans are already taking steps to shore up their Medicaid operations and hedge against potential cuts.

Some are investing heavily in member navigation programs to assist individuals through the redetermination process, hoping to maintain eligibility where possible or transition members to subsidized exchange products. Others are accelerating automation initiatives across eligibility and claims operations to bring down administrative costs without sacrificing service quality.

Meanwhile, payer-provider alignment is becoming a critical area of focus. Plans are pursuing value-based contracts more aggressively, tying reimbursement to outcomes and total cost of care rather than volume. The goal is clear: to better manage the higher-acuity populations that are likely to remain covered even if Medicaid rolls shrink.

At the policy level, sophisticated payers are not remaining silent. They are working closely with state regulators and policymakers to highlight the risks of blunt cuts — and to advocate for reforms that preserve managed care's role in delivering coordinated, cost-effective care for vulnerable populations.

The Stakes for the Industry

The proposed Medicaid cuts are not just another reimbursement adjustment. They represent a fundamental challenge to a core pillar of many health plans' business models. Those that fail to adapt may find themselves locked into unprofitable contracts, unable to absorb the rising costs of care. Those that move early — investing in operational efficiency, member retention, and policy advocacy — may not only survive the cuts but emerge stronger and more competitive.

For C-suite leaders, the question is not whether Medicaid will change — but whether their organizations are prepared to change fast enough with it.

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Poor Data Integration in Utilization Management

In an industry increasingly defined by transformation, few areas of healthcare remain as inefficient and opaque as utilization management (UM). Originally designed as a gatekeeping function to ensure medical necessity and cost control, UM today often functions as a fragmented, manual process that creates more friction than value. Behind this dysfunction lies a core issue: poor data integration.

For payers, the result isn’t just operational waste. Fragmented UM workflows drive downstream denials, inflate appeals volume, and delay care decisions—hurting both the bottom line and member experience.

But it doesn't have to be this way. By reengineering how data flows through the UM process—particularly clinical, eligibility, and prior authorization data—health plans can unlock measurable gains in turnaround times, medical loss ratios, and member satisfaction.

The Current State: Friction at Every Turn

To understand the magnitude of the problem, consider a typical UM request. A provider faxes or uploads a prior authorization form to the payer. The clinical review team must manually check for eligibility, hunt down documentation in external systems, and review notes that often arrive in image or PDF format. Many plans lack direct access to relevant clinical history unless integrated with the provider’s EHR or a health information exchange. Even when data is available, systems often don’t talk to each other, requiring copy-paste workarounds and swivel-chair decision-making.

This isn't just inefficient—it’s dangerous. 78% of physicians reported that prior authorization often or sometimes results in their patients abandoning a recommended course of treatment, according to the American Medical Association (AMA)^1. Behind many of these delays is the simple fact that UM reviewers don’t have the right data at the right time.

The Ripple Effect: Denials, Appeals, and Member Disruption

When data isn’t integrated, authorization requests are often incomplete. This leads to higher initial denial rates, often due to missing information, mismatched eligibility status, or failure to match clinical criteria—despite the service being medically necessary.

These denials create downstream work. Members are notified late. Providers resubmit documentation. Operations teams scramble to re-review the same cases. In some cases, services are delayed or denied altogether, forcing members into out-of-network options or emergency care.

The volume adds up. For a mid-size regional health plan processing over 500,000 UM requests annually, even a 5% increase in avoidable denials can translate to tens of thousands of rework cases—each one a cost center and a complaint waiting to happen.

What’s Missing: A Data Backbone for UM

UM doesn’t exist in isolation—it intersects with claims, member eligibility, provider networks, and clinical data. But most payer systems treat these as silos, not a unified operating model.

Three key gaps stand out:

1. Eligibility and Benefits Data Not Embedded in UM Systems
   UM reviewers often lack real-time visibility into a member’s active eligibility, benefits coverage, and network status—forcing them to toggle between systems or wait on back-office verification.
2. Clinical Data Unstructured or Inaccessible
   Even when plans request clinical documentation, it often arrives as scanned images or PDF attachments that require manual review. Without structured clinical data—diagnoses, labs, medication history—automated triage and approval are nearly impossible.
3. Lack of Integration with Prior Auth Systems
   Many plans rely on legacy prior auth platforms that don’t integrate with their case management, provider portals, or claims adjudication systems. This disconnect leads to mismatches in decisions versus payments.

Fixing the Flow: What Integrated UM Should Look Like

The fix is not about layering another portal on top. It’s about re-architecting the UM workflow around data integration, with a focus on real-time, bidirectional information exchange. Here’s what that looks like:

1. Real-Time Eligibility Integration: UM platforms must have API-based access to core member data, pulling real-time eligibility, coverage, and benefit details directly into the authorization review workflow. This eliminates errors from outdated eligibility files and speeds up determinations.
2. Structured Clinical Data Access: Rather than waiting for static faxes, plans should integrate with HIEs, EHRs, and data aggregators to receive structured clinical summaries. With proper NLP tools and smart forms, this data can be mapped into decision support tools that flag approvals or route complex cases to clinicians.
3. Automated Triage and Rule Engines: Integrated workflows allow for low-complexity cases (e.g., recurring DME, imaging) to be auto-approved based on clinical criteria, reducing manual review volume. These rule engines must be dynamic and updated with CMS or plan-specific guidelines.
4. Closed-Loop Communication with Providers: Integrated platforms should allow providers to receive immediate feedback on missing information and upload documents within the same system. This reduces rework and eliminates the “black box” effect of UM decisions.
5. Post-Decision Data Sync: Authorization decisions must sync with claims systems in real-time, ensuring downstream claims are processed accurately against UM determinations—reducing post-payment denials and provider abrasion.

The Payoff: Efficiency, Experience, and Compliance

Plans that invest in integrated UM workflows aren’t just modernizing—they’re reaping returns.

• Reduced Denial Rates: Integrated eligibility and clinical data reduces avoidable denials by 15–30%.
• Shorter Turnaround Times: Real-time data eliminates delays from manual validation, cutting review times from days to hours.
• Lower Appeals Volume: Fewer preventable denials reduce administrative strain and provider frustration.
• Improved Audit Readiness: A single source of truth for decision rationale and documentation simplifies CMS compliance.
• Better Member Outcomes: Timely decisions enable timely care—reducing preventable ER visits, hospitalizations, and member grievances.

The global utilization management software market was valued at $15.21 billion in 2023 and is projected to reach $44.25 billion by 2031, growing at a compound annual growth rate (CAGR) of 18.25% from 2024 to 2031 ². This rapid growth underscores the increasing reliance on technology to address UM inefficiencies.

Additionally, in the U.S., the drug utilization management market is expected to reach $60.68 billion by 2030, with a CAGR of 7.3% from 2024 to 2030. Physicians handle an average of 19.7 prior authorizations per week, highlighting the significant administrative burden these tools create in clinical practice³.

The Road Ahead: Don’t Wait for the Perfect Platform

Some payers hesitate to overhaul their UM systems, fearing the cost or disruption of a full platform migration. But full transformation isn't required to make progress. Many integrations—especially eligibility, clinical document parsing, and provider feedback loops—can be layered onto existing systems through middleware, APIs, and smart automation tools.

The key is to stop treating UM as a static function and start treating it as a dynamic, data-enabled workflow. Because at its core, utilization management is not about saying "no." It's about saying "yes"—to the right care, at the right time, backed by the right data.

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¹ Exhausted by prior auth, many patients abandon care: AMA survey

² Straits Research, 2024

³ Precedence Research, 2024; AMA, 2022