For decades, business process outsourcing - BPO - has been a vital support system for health plans and payers, absorbing back-office functions that insurers deemed too costly or inefficient to manage in-house. It delivered lower costs, extended coverage, and the ability to scale operations without expanding internal headcount. Whether offshore or onshore, BPO firms became essential partners, processing high volumes of repetitive tasks—claims, calls, data entry—with efficiency and speed.
But today, the complexity of healthcare administration is evolving. Member expectations are rising. Regulatory environments are shifting rapidly. And the volume of data flowing through payer systems has grown exponentially. BPO is no longer just about scale — it’s about intelligence, accuracy, and adaptability.
It’s no surprise, then, that payers and providers now spend nearly $500 billion annually on billing and insurance-related costs, much of it tied to workflows that haven’t kept pace with modern needs.1
At Mizzeto, we believe the future of BPO lies in pairing deep operational expertise with smart automation — not as a replacement, but as a powerful extension of the people doing the work.
Redefining BPO with AI Agents
Roughly 43% of tasks performed by payers, such as eligibility checks, claims status updates, and benefits verification, can already be automated using current technologies.2
AI agents aren’t here to replace human talent — they’re here to help them work better. When trained on payer-specific workflows, AI agents can reduce manual toggling, eliminate duplicate entries, and surface relevant information in real time. They’re tireless, consistent, and able to handle tier-one issues or route escalations more efficiently — all while learning and improving with every interaction.
The result? Fewer errors. Faster resolutions. And more time for human teams to focus on complex issues that require empathy, critical thinking, and judgment.
There’s a growing misconception that automation means the end of outsourcing. We see it differently. AI enables a more responsive, resilient, and intelligent form of BPO — one that doesn’t just deliver scale but continuously improves how operations are delivered.
Instead of moving work “out of sight, out of mind,” today’s BPO, powered by AI, brings new transparency and ownership back into the system. It enhances what teams can do. It reduces friction across handoffs. And it strengthens the relationship between health plans and their members.
Mizzeto’s Approach
At Mizzeto, we partner with payers to modernize operations — not by tearing down what works, but by building on it. We work with internal client teams to deploy innovative technologies that handle repetitive and rule-based tasks.
BPO is not dead. It’s transforming. And the future of claims processing, member and provider data management, contact center support and back-office operations lies in the partnership between humans and machines, working together to deliver smarter care.
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.
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:
Protect People –Ensuring member data privacy, security, and regulatory compliance (HIPAA, GDPR, etc.).
Prioritize Equity – Mitigating algorithmic bias and ensuring AI models serve diverse populations fairly.
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.
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.
For decades, prior authorization has been the blunt instrument of utilization management. Every MRI, infusion, or elective surgery required the same gatekeeping, regardless of whether the ordering physician had a spotless track record or a history of questionable requests. The result : clogged pipelines, overworked nurses, and exasperated providers who felt they were being second-guessed at every turn.
Now, momentum is building toward a different model. Under CMS reforms and state-level initiatives like Texas’s gold-card law, payers are experimenting with exemption programs that reduce or eliminate prior authorization requirements for high-performing providers.1 The idea is straightforward: if a provider’s approval rates are consistently north of 90 percent, why waste administrative energy on rubber-stamping? By shifting clinical oversight to where it’s most needed, payers can cut friction while maintaining safeguards against overuse.
But the simplicity of the pitch belies the complexity of execution. For payer CEOs, the key question is not whether to gold-card providers — it’s how to design programs that are defensible, fair, and scalable in an increasingly transparent regulatory environment.
The Policy Push Behind Gold-Carding
The concept of exempting low-risk providers is not new, but the regulatory winds have shifted. In 2023, CMS’s proposed WISeR (Work to Improve Standardization of Prior Authorization Requirements) framework explicitly encouraged payers to consider differential authorization pathways based on provider performance.2 At the same time, several states — led by Texas— passed laws requiring insurers to exempt physicians from prior authorization if they meet high approval thresholds.
CMS has also signaled that “burden reduction” is now a formal policy objective. In fact, in the 2024 Interoperability and Prior Authorization Final Rule, the agency underscored its intent to reduce unnecessary PAs while strengthening transparency and data sharing.3 For payers, this is not just an option — it’s a compliance expectation wrapped in a market imperative.
Redefining Utilization Management as Risk Distribution
At its core, gold-carding reframes UM from a one-size-fits-all process into a system of risk distribution. High-performing providers are effectively “trusted” to order without friction, while oversight is concentrated on outliers. The potential benefits are significant:
Faster patient access to care.
Reduced provider abrasion and administrative cost.
Reallocation of clinical staff time toward complex, high-risk cases.
But with those benefits come risks. Exemptions, if poorly designed, can lead to unchecked overuse, uneven enforcement, and reputational blowback if patients or regulators perceive favoritism.
The Design Challenge: Fairness, Defensibility, Trackability
Building a gold-card program that stands up to scrutiny requires rigor on three fronts:
Fairness → Criteria for exemption must be objective, transparent, and consistently applied. Approval rate thresholds should be clearly defined, risk-adjusted for patient mix, and re-evaluated regularly. Otherwise, payers risk accusations of bias or anticompetitive behavior.
Defensibility → Every exemption policy must be anchored in data that can withstand audit. With CMS now requiring public reporting of prior authorization metrics, payers will need to demonstrate that exempted providers still meet quality and cost benchmarks.
Trackability → Exemptions cannot be “set and forget.” Payers need real-time dashboards to monitor ordering patterns, detect drift in provider behavior, and quickly revoke exemptions if abuse emerges.
This is where technology becomes central. Without robust analytics and interoperable data systems, exemption programs risk becoming unmanageable at scale.
Providers Welcome It — With Caveats
Unsurprisingly, provider groups have pushed hard for gold-carding. The American Medical Association has called excessive prior authorization a leading driver of physician burnout, with 86 percent of physicians reporting that PA delays care.4 From the provider’s perspective, exemption is overdue recognition of clinical expertise.
Yet even among clinicians, there are concerns. Some worry that tying exemptions strictly to approval percentages may penalize those who care for complex, high-risk populations, where denials are more common. Others point out that exemption does not reduce documentation burden unless paired with true interoperability — otherwise, the paperwork just shifts downstream.
The Strategic Choice for Payers
For payer executives, the decision is less about whether to gold-card and more about how to do it without destabilizing UM. Key choices include:
Scope: Which service categories are safe to exempt (e.g., advanced imaging) versus too costly or risky (e.g., oncology drugs)?
Frequency: How often should exemption eligibility be reassessed — annually, quarterly, or in real time?
Transparency: How much of the exemption logic should be shared with providers, regulators, or even members?
Handled well, gold-card programs can become a strategic differentiator — improving provider relationships, reducing administrative waste, and aligning with CMS’s burden-reduction agenda. Handled poorly, they risk accusations of lax oversight, cost overruns, and regulatory penalties.
The Bottom Line
Gold-carding is more than a provider-pleasing gesture. It is a rebalancing of clinical risk — away from the blanket suspicion of all orders and toward targeted oversight of outliers. For payers, the opportunity is clear: exemption programs can cut costs, ease provider friction, and demonstrate compliance with CMS’s call for smarter, less burdensome UM.
But success depends on execution. Exemptions must be grounded in transparent criteria, backed by auditable data, and monitored continuously. That requires more than policy — it requires technology.
At Mizzeto, we help payers build precisely these capabilities: advanced analytics for provider performance, interoperable dashboards to monitor exemptions in real time, and UM platforms that align compliance with efficiency. For payer CEOs navigating the shift, the choice is not whether to distribute clinical risk — it’s whether to do so with the infrastructure to make it sustainable.
For more than a decade, the Affordable Care Act (ACA)marketplaces have been a proving ground for U.S. health coverage. Enrollment has grown steadily—reaching 21.4 million people in 2024, the highest ever recorded since the ACA’s passage in 2010, according to HHS data.1 But growth has also drawn scrutiny. Are networks sufficient? Are subsidies sustainable? And are consumers being steered into plans that fit their needs, or into products that maximize broker commissions?
In April 2024, the Centers for Medicare & Medicaid Services (CMS) finalized the 2025 Marketplace Integrity and Affordability Rule, a sweeping regulation designed to tighten oversight of ACA plans. For payers active in this space, the rule is far more than a compliance exercise. It is a stress test of operational discipline, affordability strategy, and long-term reputation.
Understanding the Rule: Guardrails for Growth
At its core, the rule establishes new guardrails to protect members and restore public trust in ACA coverage. Among its most notable provisions:
Network adequacy requirements are being strengthened, including time-and-distance standards for provider access.
Agent and broker oversight is expanded, with CMS cracking down on misleading marketing and enrollment practices.
Premium alignment and subsidy rules are clarified to prevent distortions from “silver loading” and other pricing maneuvers.
Risk adjustment methodology is refined to limit gaming and improve fairness across plans.
Special enrollment protections are broadened, particularly for vulnerable populations transitioning between coverage.
Together, these rules reflect a single objective: ensuring that ACA marketplaces are not only growing, but doing so in a way that is affordable, accessible, and trustworthy.
Implications for Payers
The immediate effect of the rule is to raise the baseline expectations for payers. Network adequacy, for instance, is no longer a matter of marketing claims—it will require demonstrable compliance with uniform national standards. That puts pressure on provider contracting, data accuracy, and real-time monitoring systems. Plans that have relied on narrow networks as a lever to control costs may find those models increasingly difficult to sustain.
Risk adjustment is another pressure point. The ACA marketplace has always depended on risk adjustment to stabilize competition and prevent cherry-picking of healthier members. CMS’s refinements signal that aggressive coding strategies—so familiar in Medicare Advantage—will not be tolerated in the same way here. Instead, payers will need to build risk adjustment approaches that are analytically rigorous, transparent, and audit-ready. That will require investment not just in analytics, but in governance and compliance infrastructure.
The new guardrails on agent and broker behaviour strike at the heart of distribution strategy. Complaints about misleading marketing have surged in recent years—more than 90,000 in 2023 alone, according to CMS data.2 The new rule makes clear that CMS will not tolerate abusive practices. For payers, this means doubling down on compliance programs, tightening oversight of third-party distribution, and potentially investing in direct-to-consumer channels that reduce reliance on brokers altogether.
And then there is affordability. Subsidies remain the lifeblood of marketplace enrollment—according to Kaiser Family Foundation(KFF), as of 2025, 92% of ACA Marketplace enrollees receive a subsidy (Advanced Premium Tax Credit).3 But CMS’s new scrutiny of premium alignment and silver loading is a signal that creative pricing strategies are reaching their limits. CFOs will need to model subsidy flows with greater precision, ensuring that premiums are sustainable while remaining compliant with evolving federal rules.
Strategic Connections: More Than Compliance
Stepping back, the through line of this regulation is trust. CMS is asking payers to run their ACA business with the same operational rigor already expected in Medicare Advantage and Medicaid managed care. For executives, this has three interrelated consequences.
First, reputation management becomes inseparable from compliance. Marketplace plans are highly visible, and violations—whether inadequate networks or aggressive broker tactics—can quickly draw media and regulatory scrutiny. A lapse here is not just a legal risk; it is a brand risk.
Second, operational scalability is no longer optional. Stricter adequacy standards, enrollment oversight, and risk adjustment rules require infrastructure that can flex with growth. Manual workarounds may suffice for a few thousand members, but they will not withstand enrollment at the scale the marketplaces now represent.
Third, regulatory convergence is accelerating. What happens in ACA will not stay in ACA. CMS is deliberately harmonizing standards across programs, and the lessons learned in marketplace compliance will almost certainly shape the expectations for Medicare Advantage, Medicaid managed care, and even commercial exchange products. In other words, this rule is not just a one-off correction; it is a preview of where payer regulation as a whole is heading.
From Regulation to Strategy
For payer CEOs, the task now is not to build a compliance checklist but to seize the opportunity for long-term advantage. That means investing in provider data infrastructure to ensure that network adequacy can be demonstrated in real time, not after the fact. It means designing risk adjustment programs that can withstand audit without undermining competitive positioning. It means deploying analytics to model premium and subsidy interactions with precision, building pricing strategies that are resilient to regulatory change. And it means rethinking distribution oversight—not simply to police brokers, but to redesign member acquisition in ways that emphasize transparency and trust.
This is not just an operational mandate; it is a strategic one. The payers that embrace these changes will differentiate themselves not only in the ACA marketplace but across all lines of business. They will be seen as organizations that can scale growth while maintaining affordability, access, and compliance—qualities that regulators, providers, and members all increasingly demand.
The Bottom Line
The 2025 Marketplace Integrity and Affordability Final Rule is about more than patching gaps in oversight. It is CMS’s blueprint for a more consumer-centered insurance market—one where affordability, access, and transparency are non-negotiable. For payers, compliance is necessary, but it is not sufficient. The real opportunity lies in treating the rule as a catalyst: to clean up distribution, strengthen networks, and align pricing strategies with sustainable growth.
Payers who approach the rule narrowly, as a burden, will face mounting costs, reputational risk, and potential market exit. But those who meet it with vision will not only pass the integrity test; they will emerge stronger, with the infrastructure, credibility, and agility to lead in a converging regulatory environment.
At Mizzeto, we specialize in helping payers make that leap—from compliance to leadership. Our solutions in provider data management, risk adjustment analytics, and enrollment oversight are designed to help plans not just meet CMS requirements, but reimagine their core operations for resilience and growth.
The test of integrity is here. The question is not whether payers can comply, but whether they can transform.
Prior authorization has long been a symbol of administrative drag in U.S. healthcare—delaying care, frustrating providers, and increasing costs. Over 90 percent of U.S. physicians report that prior authorization causes delays in patient care—and nearly 90 percent say it contributes to professional burnout.1 Now, a sweeping CMS rule finalized in 2024 is set to upend the status quo. The Interoperability and Prior Authorization Final Rule (CMS-0057-F)2 doesn’t just mandate API adoption—it compels payers to reengineer how they handle requests, data, and transparency across the board.
The End of Manual Prior Authorization
For decades, prior authorization (PA) has relied on outdated methods—fax machines, phone calls, email threads—resulting in administrative waste and delayed care. In fact, nearly a quarter of U.S. physicians report that prior authorization has led to serious adverse events, including hospitalizations or life-threatening delays.3 The CMS rule marks the beginning of the end for these practices.
Announced in January 2024, CMS-0057-F mandates the adoption of modern, API-driven infrastructure to automate and streamline PA and health data exchange. The rule applies to:
Medicare Advantage organizations
Medicaid and CHIP (both FFS and managed care)
Qualified Health Plans (QHPs) on the Federally Facilitated Exchanges
Commercial plans are not currently included; however, the rule is expected to influence broader industry standards over time.
What the Rule Requires: From Compliance to Capability
By January 1, 2027, payers must move from fragmented systems to a unified, API-driven infrastructure as required by CMS’s final rule. At the heart of this transition is the adoption of FHIR-based APIs, which will transform prior authorization from a manual, siloed process into an interoperable, fully digital workflow.
The rule mandates several APIs designed to create seamless data exchange across the healthcare ecosystem. Providers will be able to electronically submit prior authorization requests, check documentation requirements, and receive real-time updates or decisions—eliminating the need for faxes, phone calls, and disconnected portals. To further streamline care delivery, in-network providers must also be granted digital access to a patient’s claims, encounter, clinical, and prior authorization history—empowering them to make informed decisions at the point of care.
In addition, payers must support secure, automated data sharing both with other payers and with patients. When members switch plans, their clinical and prior authorization data must move with them, ensuring continuity of care without administrative delays. Patients themselves will benefit from expanded access to their own health and prior authorization data, promoting transparency and enabling them to engage more actively in their care decisions.
New Timelines. New Pressures.
The rule does not just digitize prior authorization—it accelerates it. Urgent requests must be resolved in 72 hours, standard requests within 7 calendar days. Every denial must include a specific, actionable reason. Additionally, beginning in 2026, payers must publicly post prior authorization metrics on their websites, such as approval/denial rates and average turnaround times. This means internal inefficiencies will soon be externally visible, putting reputational pressure on payers to perform.
These are not just technical deadlines; they are operational mandates that affect staffing, workflows, and long-term scalability.
A Mandate for Real Interoperability
Under the hood, this rule is about much more than prior auth. It is part of a larger federal push to tear down data silos and create a healthcare ecosystem that behaves more like a modern, digital industry.
Payers must not only modernize systems but also:
Align with USCDI (U.S. Core Data for Interoperability)
Integrate with provider EHR systems using SMART on FHIR
Track and document clinical decision logic in structured, shareable formats
Enable secure, permissioned data sharing with third-party apps and provider organizations
This is not plug-and-play IT. It is a strategic replatforming of how payers operate at their core.
The Risk of Falling Behind
Payers who approach this rule as a checkbox exercise—focusing only on minimum compliance—risk more than regulatory penalties. They risk damaging provider relationships due to slow or unreliable PA workflows as well as public reputational harm via poor performance metrics. Further risks include losing market share to more tech-forward competitors; and an increased operational cost due to inefficient legacy systems and manual workarounds
In contrast, those who embrace the shift stand to gain significant advantages—lower administrative burden, faster service turnaround, and stronger provider alignment.
Turning Regulation into Transformation
To meet the demands of CMS-0057-F and thrive in an increasingly digital healthcare ecosystem, payers must rethink how their systems handle prior authorization and data interoperability—from the ground up. This means building scalable, standards-based APIs that support automated prior authorization submissions, payer-to-payer data exchange, and real-time access for both providers and patients. These APIs must be secure, modular, and capable of integrating with existing platforms—without introducing unnecessary complexity.
Modernizing prior authorization also requires full end-to-end workflow automation. From intake and clinical review to adjudication and provider notification, each step must be digitized and streamlined to meet strict CMS timelines without increasing administrative burden. This is especially critical in achieving the mandated turnaround times—72 hours for urgent requests and seven calendar days for standard cases—while maintaining accuracy and consistency.
Equally important is seamless provider integration. By connecting directly with provider EHRs and enabling SMART on FHIR capabilities, payers can reduce manual follow-ups and foster real-time, context-aware collaboration with clinical teams. This not only improves efficiency but also strengthens provider relationships, which will be critical as performance metrics become public and increasingly scrutinized.
Transparency must also extend to how decisions are communicated. Payers need systems that can generate clear, standardized denial reasons—structured in a way that supports both compliance and clinician understanding. Meanwhile, CMS’s public reporting requirements demand real-time visibility into operational performance. Intuitive dashboards, aligned with federal standards, can help internal teams monitor key metrics while also meeting external transparency obligations.
Finally, the underlying architecture must be built for more than today’s rule—it should lay the foundation for future regulatory shifts, data sharing innovations, and scalable interoperability across the healthcare continuum.
The Bottom Line
CMS-0057-F marks a pivotal shift in how payers must operate. Prior authorization can no longer remain a manual, reactive process. It must become real-time, interoperable, and patient-centred.
Mizzeto specializes in delivering precisely these kinds of solutions—combining automation, streamlined prior authorization, clinical care review capabilities, and a unified utilization management intake process. We help payers not only meet regulatory requirements, but also reimagine their core operations for greater efficiency, scalability, and long-term impact.
The payers who act now, those who build modern infrastructure, streamline workflows, and enable intelligent automation, will not just comply with the rule. They will gain a lasting advantage in an industry that is rapidly evolving.
In Utilization Management (UM), nurses often spend hours reviewing lengthy clinical records to identify the small subset of information needed for a medical necessity determination. These files—sometimes exceeding dozens or even hundreds of pages—contain physician notes, lab results, imaging reports, and discharge summaries scattered throughout, with no standardized structure or clear prioritization of relevance. Extracting the critical details requires reading line-by-line, cross-referencing across sections, and manually piecing together the patient’s clinical story.
This process is not only labor-intensive but also misaligned with the role of skilled clinicians. Instead of applying their expertise to complex medical decision-making, UM nurses are forced into the role of document synthesizers. Across thousands of cases, this leads to slower review cycles, increased administrative costs, elevated burnout risk, and unnecessary delays in care. According to the American Journal of Managed Care, prior authorization processes already contribute billions in wasted administrative time annually1 — inefficient record summarization is a major driver of that burden.2
As case volumes rise and the complexity of medical documentation grows, the challenge is accelerating. Without tools that can rapidly distill large records into clear, accurate summaries, UM operations will remain constrained by a bottleneck that limits both efficiency and clinical focus.
In addition to navigating lengthy records, UM nurses must also manually cross-check clinical details against InterQual, MCG, or CMS criteria to determine medical necessity. This process often requires flipping between multiple systems or documents—matching diagnosis codes, lab values, imaging findings, and treatment history against guideline requirements. It is a time-consuming and error-prone task that diverts focus from clinical judgment to administrative box-checking. Without automated assistance to align extracted data with the appropriate guidelines, even straightforward cases can take far longer than necessary, delaying care and increasing the risk of inconsistencies in determinations.
AI-Powered Tools That Empower Clinical Reviewers
The next generation of AI offers a powerful set of tools designed to address the core inefficiencies in Utilization Management. Rather than replacing the nurse’s clinical judgment, these technologies support it—streamlining routine tasks, improving information access, and accelerating decision-making while maintaining compliance and auditability. Some examples of how health plans can harness AI in their clinical review workflows are:
Automatically summarize complex clinical records, distilling hundreds of pages into structured briefs that highlight only the clinically relevant information tied to medical necessity criteria.
Contextualize clinical details within InterQual, MCG, or CMS guidelines, using large language models (LLMs) trained to understand and map patient data directly to the applicable authorization framework—eliminating the need for constant manual reference.
Intelligently route cases based on urgency, flagging high-priority or time-sensitive cases for immediate review, while categorizing lower-risk cases accordingly to optimize nurse workload distribution.
Enable real-time support through clinical chat assistants, which can answer reviewer questions about documentation, summarize patient history on request, or locate specific data points in the medical record—saving time and reducing cognitive load.
Standardize case outputs across reviewers and case types, ensuring consistency in how data is presented, interpreted, and acted upon.
The impact is immediate and measurable. Nurses begin reviews with the essential information already organized, supported by tools that minimize administrative overhead and reinforce clinical accuracy. What once took hours now takes minutes. Teams can handle higher case volumes without increasing staffing—and nurses are empowered to focus on clinical determinations, not paperwork.
A Call to Action for Health Plan Leaders
The reality is clear: manual summarization of complex medical records is one of the most persistent inefficiencies in UM. It consumes valuable clinical resources, slows authorizations, and increases the risk of burnout among nurses. The cost—both operational and human—will only rise as case volumes increase and medical documentation grows in length and complexity.
Health plan leaders have a choice: continue absorbing the costs of manual summarization or adopt AI solutions that deliver ready-to-review summaries while preserving full compliance and audit integrity. The technology is ready, the ROI is clear, and the benefits extend beyond efficiency to workforce well-being and member satisfaction.
It is time to remove the bottleneck that forces nurses to act as document compilers. Let AI handle the paperwork, intake complexity, and information retrieval. Let nurses focus on what they do best—making informed clinical determinations that ensure appropriate care and efficient use of healthcare resources.
Reach out to discover how Mizzeto is helping plans modernize their UM workflows – book time with our team here!
