Inside Muni Appeals: The MRI Prior Authorization Appeal That Scored 94/100

Why We're Showing You This

Most appeal automation tools are black boxes. You upload a denial, get a letter back, and have no idea if it's legally sound or just well-formatted nonsense.

We're doing something different: showing you exactly how Muni Appeals builds evidence-based arguments, using a real example from our testing pipeline.

What we're revealing:

• The exact denial scenario (prior authorization denial for contrast-enhanced brain MRI)
• The research sources our system found (15+ authoritative citations)
• How we structure evidence hierarchy (clinical guidelines → peer-reviewed evidence → federal benchmarks → insurer policies)
• Quality scoring methodology (5 dimensions scored)
• The final appeal letter output

What we're protecting:

• Our proprietary research pipeline (how we find and synthesize evidence)
• The AI models and prompt engineering
• Business logic and scoring algorithms

Think of this as: "Here's the quality of what we produce, but not the recipe for how we make it."

The Denial: UnitedHealthcare Prior Authorization for CPT 70553

Here's the exact denial letter our system processed:

The Legal Issue: This denial is procedural, not clinical. UHC applied population-level imaging guidelines to deny a medically necessary study without evaluating the specific clinical context. When a treating physician orders contrast-enhanced MRI for suspected intracranial pathology, national clinical guidelines (NCCN, peer-reviewed evidence) support this as standard of care—not optional screening.

What Makes This Complex:

Overturning this requires proving:

1. National clinical guidelines (NCCN) establish MRI with contrast as standard of care for suspected intracranial disease
2. Peer-reviewed evidence shows contrast-enhanced sequences are diagnostically superior and medically necessary
3. Federal coverage benchmarks (CMS) affirm CPT 70553 is a covered, standard diagnostic service
4. UHC's own policies allow exceptions and retroactive authorization when medically necessary

Manual research for this takes 60-75 minutes. Muni Appeals found 15+ authoritative sources in 90 seconds. Here's what it found and how it built the appeal.

What Our System Found: 4 Layers of Evidence

Layer 1: National Clinical Guidelines (NCCN - Highest Authority)

The system identified that multiple National Comprehensive Cancer Network (NCCN) guidelines establish MRI with contrast as the standard imaging modality for suspected intracranial pathology:

NCCN Primary CNS Lymphoma Guidelines:

"An MRI of the brain or spinal cord usually requires a contrast agent... Contrast highlights areas... to make them easier to see. MRI scans can reveal one or multiple tumors."

NCCN Nasopharyngeal Cancer Guidelines:

"MRI with contrast of collarbone to skull base. CT of skull base and neck may also be done."

Recommends contrast-enhanced MRI for skull base/intracranial involvement in staging and treatment planning.

NCCN Acute Myeloid Leukemia Guidelines:

"Brain MRI with contrast, if leukemic meningitis suspected."

Establishes that contrast-enhanced brain MRI is the standard imaging modality when CNS involvement is a concern, given its superior sensitivity.

Why this matters: NCCN guidelines are considered the gold standard in oncology and neuro-oncology care. When NCCN recommends MRI with contrast for multiple conditions in the differential diagnosis of intracranial disease, it's not experimental—it's standard of care. UHC's population-level imaging criteria cannot override condition-specific NCCN recommendations.

Layer 2: Peer-Reviewed Clinical Evidence (Level I Evidence)

Dynamic Contrast-Enhanced Perfusion MRI Meta-Analysis: Systematic review and meta-analysis demonstrating that DCE-perfusion MRI aids in discrimination between low-grade and high-grade gliomas and distinguishes recurrence from treatment effects. Source: PubMed - Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas

Glioblastoma Imaging Standards:

"The recommended minimum MRI examination includes both pre- and post-gadolinium T1-weighted imaging, with additional sequences (e.g., diffusion/perfusion) to improve diagnostic confidence and differentiation."

Source: PubMed - Critical Imaging for the Identification and Diagnosis of Glioblastoma

Contrast Clearance Analysis Study: Demonstrates high diagnostic accuracy in differentiating tumor progression from treatment-related changes, outperforming conventional techniques in systematic review/meta-analysis. Source: PubMed - Contrast clearance analysis in neuro-oncology

Brain Metastases Treatment Response Meta-Analysis:

"Treatment response assessment relies on contrast-enhanced T1-weighted MRI as foundational, with pooled accuracies for advanced techniques reported across studies."

Source: PubMed - Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis

Why this matters: These are Level I systematic reviews and meta-analyses—the highest quality of clinical evidence. They collectively establish that contrast-enhanced MRI sequences are integral to accurate diagnosis, staging, and management decisions in neuro-oncology and intracranial conditions. This isn't opinion—it's evidence-based medicine.

Layer 3: Federal Coverage Benchmarks (CMS Standards)

CMS Medicare Claims Processing Manual: Instructs payment for contrast material supplied under Q9952 when billed with CPT codes including 70553. Source: CMS Medicare Claims Processing Manual

CMS LCD Companion Guidance: Explicitly references payment for contrast agents when billed with 70553. Source: CMS LCD Billing and Coding Guidance

CMS National Coverage Determination - MRI (220.2): Affirms diagnostic MRI coverage when medically necessary; directs code-level details to related Billing & Coding Articles. Source: CMS NCD - Magnetic Resonance Imaging (220.2)

CMS Billing and Coding Article: Provides claims processing parameters for head/neck MRI procedures consistent with CPT 70553 when medically necessary. Source: CMS Billing and Coding: MRI and CT Scans of the Head and Neck

Why this matters: While Medicare policies don't directly govern commercial plans, they represent authoritative federal standards widely aligned with commercial coverage. CMS's explicit coverage of CPT 70553 with contrast establishes that this is a recognized, covered diagnostic service—not experimental or excludable.

Layer 4: UnitedHealthcare's Own Policies

UHC Notice of Utilization Review Procedures:

"Clinical Coverage Review evaluates requested services under applicable benefit documents and mandates using evidence-based medical policy and standardized clinical criteria."

Source: UnitedHealthcare Notice of utilization review and benefit determination procedures

UHC Appeals and Grievances Process: Discusses coverage exceptions where alternatives would not be as effective or would cause adverse effects. When non-contrast imaging is inadequate for safe and effective care, exception or retro-authorization is warranted. Source: UnitedHealthcare Appeals and Grievances Process

UHC Specialty Medical Injectable Drug Program: Published updates show use of prior authorization frameworks and exceptions for injectable agents, illustrating plan flexibility and clinical exception pathways when medically necessary. Source: UnitedHealthcare Specialty medical injectable drug program updates

Why this matters: UHC's own utilization review framework requires evidence-based criteria and allows exceptions when medically necessary. The appeal demonstrates that NCCN guidelines + Level I evidence = evidence-based medical necessity, triggering UHC's obligation to approve or provide retroactive authorization.

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The Complete Appeal Letter (94/100 Score)

Here's the actual appeal letter Muni Appeals generated in under 2 minutes. This scored 94/100 across our 5 quality dimensions. Every source cited below is real and clickable—verify for yourself.

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Why This Appeal Works: Strategic Breakdown

Now that you've seen the full letter, let's break down exactly why this approach is so effective against UnitedHealthcare prior authorization denials.

The Evidence Hierarchy Strategy

The system synthesized these sources into a 5-part argument, ordered by persuasive leverage:

1. Lead With UHC's Own Utilization Review Standards (Procedural Leverage)

What we did: Opened by citing UHC's published notice that coverage determinations must use "evidence-based medical policy and standardized clinical criteria."

Why this works: This immediately frames the appeal as a procedural correction, not a medical necessity debate. We're not arguing that the patient needs this MRI—we're showing that UHC's own evidence-based standards require approval once NCCN guidelines and Level I evidence are presented.

The smoking gun quote:

"Clinical Coverage Review evaluates requested services under applicable benefit documents and mandates using evidence-based medical policy and standardized clinical criteria" — UHC Notice of Utilization Review Procedures

This puts UHC in a position where denying the appeal means contradicting their own published utilization review framework.

2. Cite National Clinical Guidelines (NCCN - Highest Clinical Authority)

What we did: Referenced three separate NCCN patient guidelines that establish MRI with contrast as standard of care for suspected intracranial pathology.

Why this works: NCCN guidelines are the gold standard in oncology and neuro-oncology care. They're evidence-based, peer-reviewed, and updated continuously. When UHC's utilization review framework requires "evidence-based medical policy," NCCN guidelines are the authoritative source.

The key point:

"MRI with contrast is not optional but is the standard-of-care for multiple oncologic and neuro-oncologic presentations relevant to the differential diagnosis in suspected intracranial disease."

This establishes that UHC's population-level imaging criteria (designed to prevent inappropriate screening MRIs for simple headaches) cannot override condition-specific NCCN recommendations when there's clinical suspicion of intracranial pathology.

3. Support With Level I Peer-Reviewed Evidence (Medical Necessity)

What we did: Included 4 systematic reviews and meta-analyses from PubMed showing that contrast-enhanced MRI sequences are diagnostically superior and medically necessary.

Why this works: These are Level I studies—the highest quality of clinical evidence. They demonstrate that:

• Contrast distinguishes low-grade from high-grade gliomas
• Contrast differentiates tumor recurrence from treatment effects
• Contrast is foundational for treatment response assessment in brain metastases
• Pre- and post-contrast sequences are the recommended minimum standard for glioblastoma evaluation

The pressure point:

"Collectively, these Level I systematic reviews/meta-analyses support that contrast-enhanced MRI sequences are integral to accurate diagnosis, staging, and management decisions in neuro-oncology and related intracranial conditions—precisely the role of CPT 70553."

This prevents UHC from pivoting to a "not medically necessary" argument after their prior authorization barrier falls apart.

4. Invoke Federal Coverage Benchmarks (CMS Standards)

What we did: Cited 4 CMS policy documents that explicitly affirm coverage of CPT 70553 with contrast when medically necessary.

Why this works: While Medicare policies don't directly govern commercial plans, they represent authoritative federal standards that commercial insurers widely align with. CMS's explicit coverage of CPT 70553 with contrast establishes that this is a recognized, covered diagnostic service—not experimental or excludable.

The benchmark:

"Although Medicare policies do not directly govern a commercial plan, they represent authoritative federal standards widely aligned with commercial coverage and reinforce that contrast-enhanced brain MRI is a covered, standard diagnostic service."

This gives the appeal federal credibility and makes it harder for UHC to claim the service is investigational or not covered.

5. Reference UHC's Exception and Retroactive Authorization Policies

What we did: Cited UHC's own appeals process documentation showing that exceptions and retroactive authorizations are available "where alternatives would not be as effective or would cause adverse effects."

Why this works: This is where we close the loop. We've shown:

1. UHC requires evidence-based criteria (their policy)
2. NCCN guidelines establish contrast MRI as standard of care (evidence-based)
3. Level I studies prove diagnostic superiority (medical necessity)
4. CMS covers it (federal benchmark)
5. UHC allows exceptions when medically necessary (their flexibility)

The requested action:

"Approve coverage for CPT 70553 retroactively for the date(s) of service above, or issue expedited prior authorization if the study is pending."

This makes it explicit: we're asking for retroactive authorization based on medical necessity that meets UHC's own evidence-based standards.

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The Timeline: 90 Seconds of Research, 30 Seconds to Draft

Here's how Muni Appeals processed this denial in under 2 minutes:

0:00-0:15 — Denial letter uploaded and parsed

• Extracted: Procedure code (70553), insurer (UnitedHealthcare), denial reason (prior authorization required)
• Categorized denial type: Prior authorization / procedural denial

0:15-1:45 — AI research phase (90 seconds)

• Searched NCCN guidelines for brain MRI with contrast recommendations → Found 3 patient guidelines
• Queried PubMed for contrast-enhanced MRI evidence in neuro-oncology → Found 4 systematic reviews/meta-analyses
• Searched CMS database for CPT 70553 coverage policies → Found 4 applicable Medicare documents
• Searched UHC policy database for utilization review and exception policies → Found 3 official documents
• Total sources found: 15+ (all verified and linked)

1:45-2:00 — Letter generation and quality scoring (15 seconds)

• Structured argument using evidence hierarchy (UHC procedures → NCCN guidelines → peer-reviewed evidence → CMS benchmarks → UHC exceptions)
• Drafted opening paragraph establishing procedural framework
• Composed 5-part argument with direct quotes and source links
• Generated requested action with specific retroactive authorization language
• Scored across 5 dimensions (medical accuracy, evidence quality, legal soundness, hallucination risk, persuasiveness)
• Final score: 94/100 (threshold for approval: 85+)

Total time: 2 minutes

Compare this to manual research:

• Finding NCCN guidelines: 15-20 minutes
• PubMed literature review: 20-25 minutes
• Searching CMS policies: 10-15 minutes
• Finding UHC utilization review policies: 10-15 minutes
• Drafting and citing: 20-25 minutes
• Manual total: 75-100 minutes

That's a 35-50x time savings.

Quality Scoring: How We Validate Output

Every appeal letter gets scored across 5 dimensions before it's shown to the user. Here's what this example scored:

| Quality Dimension | Score | What We're Measuring | |---|---|---| | Medical Accuracy | 96/100 | Correct CPT codes, proper medical terminology, aligns with clinical standards | | Evidence Quality | 95/100 | Source authority (prioritizes clinical guidelines > peer-reviewed evidence > govt > insurer policies), proper citation format | | Legal Soundness | 92/100 | Argument structure, regulatory citations, avoids unsupported legal claims | | Hallucination Risk | 98/100 | No fabricated statistics, all sources verified with URLs, no made-up policy numbers | | Persuasiveness | 94/100 | Logical flow, leads with strongest evidence, clear requested action |

Overall Score: 94/100 (threshold for approval: 85+)

What the Scores Mean

Medical Accuracy (96): The appeal uses CPT 70553 correctly, references appropriate clinical indications for contrast-enhanced brain MRI, and employs terminology consistent with neuro-oncology and neuroimaging practice standards. Near-perfect score reflects accurate clinical context.

Evidence Quality (95): Sources are ranked by authority—NCCN clinical guidelines (gold standard), Level I systematic reviews/meta-analyses, federal CMS policies, and UHC's own utilization review documents. All 15+ citations include URLs and document names. Exceptional source quality.

Legal Soundness (92): The procedural framing is strong—establishing UHC's evidence-based criteria requirement and then meeting it. CMS policies cited appropriately as federal benchmarks. Retroactive authorization request is legally appropriate. High score reflects solid legal structure.

Hallucination Risk (98): Near-perfect score means no fabricated data. Every NCCN guideline is real and quoted accurately. Every PubMed study exists and is correctly cited. Every CMS policy number is valid. This is critical—some AI tools make up NCCN recommendations or fake study conclusions.

Persuasiveness (94): The letter leads with UHC's own procedural requirements (strongest leverage for a prior auth denial), then builds through NCCN guidelines → peer-reviewed evidence → federal benchmarks → UHC exceptions. Clear structure with explicit requested action (retroactive authorization).

What Makes This Approach Different

1. We Show the Actual Letter, Not Just the Theory

Most appeal automation tools show you:

• "Our AI finds relevant guidelines" (but won't show which ones)
• "We cite clinical evidence" (but won't show the actual citations)
• "Trust us, it works" (but won't show the letter)

We're showing you the complete letter with every source linked and clickable. This is what 94/100 quality looks like in practice.

2. We Find the Right Evidence Hierarchy for Each Denial Type

For this prior authorization denial, the strongest leverage is:

1. UHC's own procedural requirements (they must use evidence-based criteria)
2. NCCN clinical guidelines (the authoritative evidence-based standard)
3. Level I peer-reviewed studies (prove medical necessity)
4. Federal coverage benchmarks (show it's standard, covered care)
5. UHC's exception policies (request retroactive authorization)

Compare this to the Aetna mental health case study (frequency limitation denial):

1. Insurer's own policy contradictions (strongest for coverage exclusions)
2. Professional standards (AMA/APA)
3. Federal parity law (MHPAEA - legal leverage)
4. Clinical literature (medical necessity)

Same strategic framework, different evidence hierarchy based on denial type and insurer. Muni Appeals automatically adapts.

3. We Prioritize NCCN Guidelines for Cancer/Neuro Cases

For suspected intracranial pathology, NCCN guidelines carry more weight than general imaging criteria because:

• They're condition-specific (not population-level screening guidelines)
• They're evidence-based and peer-reviewed
• They're updated continuously
• They're considered the gold standard in oncology/neuro-oncology care

Muni Appeals found 3 separate NCCN guidelines in 90 seconds that all recommend MRI with contrast for different conditions in the differential diagnosis. Manual research would take 20-30 minutes to find even one.

4. We Don't Fabricate Data (98% Hallucination-Free)

This appeal scored 98/100 on hallucination risk, meaning:

• No made-up "studies show" claims without sources
• No fake NCCN guideline quotes
• No invented CMS policy numbers
• No fictional UHC policy references
• Every URL was verified before being cited

If our system can't find a source, it doesn't include the claim. Many AI tools will confidently cite nonexistent NCCN recommendations—we don't.

5. We Frame Prior Auth Denials as Procedural Corrections, Not Clinical Disputes

The MRI appeal demonstrates a critical strategic advantage for prior authorization denials: we frame them as procedural failures, not medical necessity debates.

The opening establishes:

"This letter appeals the prior authorization denial... and requests retroactive authorization consistent with UHC's utilization review standards requiring evidence-based criteria."

This framing creates leverage:

• The issue isn't "should this be covered?" (clinical dispute)
• The issue is "UHC's process failed to apply their own evidence-based standards" (procedural error)
• We're not asking them to change policy—we're asking them to follow it

When you cite NCCN guidelines + UHC's requirement to use evidence-based criteria, you convert a subjective "medical necessity" debate into an objective "you didn't follow your process" argument. This is much harder for insurers to defend and often results in faster overturns.

This procedural framing strategy also works for step therapy denials when insurers contradict their preferred drug lists—turning policy contradictions into procedural errors rather than clinical disputes.

6. We Make It Verifiable

Click any link in the appeal letter above. They all work. You can verify:

• NCCN Primary CNS Lymphoma guideline really does recommend MRI with contrast
• PubMed systematic review exists and says what we quoted
• CMS LCD guidance explicitly covers CPT 70553 with contrast
• UHC utilization review notice requires evidence-based criteria

Transparency builds trust. If we're citing it, you can check it.

Transparency: What You're Seeing vs. What We Protect

What This Case Study Shows ✅

The Denial Input:

• Denial reason (prior authorization denial for CPT 70553)
• Insurance company (UnitedHealthcare)
• Basic clinical context (suspected intracranial pathology, headaches for 3 weeks)

The Research Sources:

• 15+ citations across 4 evidence types
• Specific NCCN patient guidelines (Primary CNS Lymphoma, Nasopharyngeal Cancer, AML)
• Peer-reviewed systematic reviews/meta-analyses (PubMed)
• Federal regulations (CMS NCDs, LCDs, billing guidance)
• UHC policies (utilization review procedures, appeals process, exception pathways)

The Output Quality:

• Scoring methodology (5 dimensions)
• Actual scores (94/100 overall)
• Feedback on strengths and weaknesses
• Final appeal letter structure

Why we show this: You can evaluate whether our output is medically accurate, legally sound, and properly evidenced. Transparency builds trust.

What We're Not Showing ❌

Our Research Pipeline:

• How we search for and retrieve NCCN guidelines so quickly
• Which AI models we use for evidence synthesis
• How we rank source authority automatically (NCCN > PubMed > CMS > insurer)
• The prompts that guide evidence compilation

Our Scoring Algorithms:

• Exact criteria for each quality dimension
• How we detect hallucinations programmatically
• Thresholds for approval vs. rejection
• Multi-agent validation process

Our Business Logic:

• Proprietary knowledge of which evidence hierarchy works for which denial types
• Denial-to-evidence mapping strategies
• Appeal structure optimization based on insurer
• NCCN guideline indexing and retrieval methods

Why we protect this: This is our competitive advantage—the encoded knowledge of appeal strategies, clinical guideline frameworks, and quality validation that took years to build. You see the output quality without being able to replicate the system.

The Bottom Line: Professional-Grade Appeals, Transparently Scored

This example demonstrates what Muni Appeals delivers:

Speed: 2 minutes vs 75-100 minutes manual research (35-50x faster)

Rigor: 15+ authoritative sources across 4 evidence layers

Quality: 94/100 score with validated dimensions (medical accuracy, evidence quality, legal soundness, no hallucinations)

Transparency: Every source linked and verifiable, scoring methodology explained

Not a Black Box: You see what evidence we found and how we structured the argument—you just don't see the proprietary pipeline that makes it possible at scale.

Real-World Application

While this example uses a test scenario, the methodology applies to actual prior authorization denials:

Radiology practices facing UHC prior auth denials can see exactly how we'd build a retroactive authorization argument with NCCN guidelines and Level I evidence.

Oncology practices can understand how we elevate cancer-related imaging from "doesn't meet criteria" to "NCCN-recommended standard of care."

Any specialty facing prior auth barriers can see our procedural framing: cite insurer's evidence-based requirement, then meet it with authoritative guidelines.

Practices evaluating appeal automation can assess output quality through scoring transparency rather than taking marketing claims at face value.

Try the System Yourself

Upload a real denial letter. See the research sources, quality scores, and final appeal that our system generates for your specific case.

3 free appeals. No credit card required.

Start Your Free Appeals

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Frequently Asked Questions

Is this a real patient case?

No. This is a test scenario we use to demonstrate our system's capabilities while maintaining HIPAA compliance. The denial letter, patient details, and clinical context are fictional. However:

• The appeal letter is real (generated by our actual system)
• The research sources are real (all 15+ links work and were found by our AI)
• The scoring is real (this letter genuinely scored 94/100)
• The methodology is real (this is exactly how we process prior auth denials)

We use test cases like this for product demos and quality assurance. Real patient cases would contain protected health information we cannot publish.

Why show the complete appeal letter?

Because seeing is believing. Most AI appeal tools are black boxes—you upload a denial and get a letter back with no visibility into:

• What sources they actually found
• Whether those sources are real or hallucinated
• How they structured the argument
• Why they made specific choices

By showing the complete letter with every source linked, you can verify for yourself that:

• The NCCN citations are real (click them)
• The argument structure is sound (see the 5-layer hierarchy)
• The quality scoring is accurate (compare to the letter content)

This is transparency in action.

How do you prevent AI hallucinations?

Every appeal undergoes automated validation before scoring:

1. Clinical Guideline Verification

• NCCN guideline references cross-checked against official NCCN database
• Quotes verified against source PDFs
• Ensures we're citing guidelines that actually exist and say what we claim

2. Code Verification

• CPT codes checked against official AMA databases
• ICD-10 codes validated
• Ensures we're citing codes that actually exist

3. Policy Citation Validation

• All insurer and CMS policy documents verified against official repositories
• URLs tested for validity (dead links fail validation)
• Policy numbers cross-referenced with official indexes

4. Statistical Fact-Checking

• Any statistic must have a source URL
• PubMed citations verified against NCBI database
• No unsourced assertions allowed

5. Source Authority Ranking

• Clinical guidelines (NCCN, specialty societies) scored highest (0.90-0.95)
• Peer-reviewed systematic reviews/meta-analyses scored 0.85-0.90
• Government sources (CMS, FDA) scored 0.80-0.85
• Insurer policies scored based on relevance and authority

The 98/100 hallucination risk score on this example means near-zero fabricated data. If we can't verify it, we don't cite it.

Does showing your methodology help competitors?

What we're showing: The quality of our output—the appeal letter, sources found, scoring breakdown, and evidence hierarchy strategy.

What we're protecting: The proprietary systems that make this possible:

• Our research pipeline (how we search and rank NCCN guidelines in seconds)
• The AI models and prompt engineering
• Our clinical guideline database architecture
• The scoring algorithms and validation logic
• Our NCCN indexing and retrieval methods

Think of it like a restaurant showing you a dish vs. the recipe. You can see that the food is excellent and understand what ingredients were used, but you can't replicate the kitchen systems, supplier relationships, and chef expertise that produced it at scale.

A competitor seeing this case study still doesn't know:

• How we access NCCN guidelines so quickly
• Which AI models we use for different denial types
• How we automatically match clinical scenarios to relevant NCCN guidelines
• How our multi-agent validation process works

Showing transparency doesn't mean giving away our competitive advantage.

What if my denial is different from this MRI example?

Muni Appeals adapts to different denial types and insurers. The evidence hierarchy changes based on the denial reason:

Prior Authorization Denials (like this example):

• Cite insurer's evidence-based utilization review requirements
• Pull NCCN guidelines or specialty society recommendations
• Reference CMS coverage policies as federal benchmarks
• Include Level I peer-reviewed evidence

Medical Necessity Denials:

• Cite clinical practice guidelines from specialty societies
• Pull insurer medical policies for the specific CPT code
• Reference Medicare NCDs/LCDs as federal benchmarks
• Include peer-reviewed outcomes studies

Experimental/Investigational Exclusions:

• Prove FDA approval status
• Cite professional society endorsements (NCCN, ASCO, etc.)
• Show Medicare coverage as federal validation
• Include clinical trial evidence

Frequency Limitations (mental health):

• Cite MHPAEA parity requirements
• Reference insurer's own coverage policies
• Show professional standards (AMA, APA)
• Include clinical efficacy evidence

Different Insurers:

• UHC appeals cite UHC utilization review standards
• Aetna appeals cite Aetna CPBs and provider manuals
• BCBS appeals cite BCBS Medical Policy Reference Manuals
• Medicare appeals cite NCDs/LCDs and MLN Matters articles

Same strategic framework, different sources and evidence hierarchies based on your specific situation.

How accurate is the 2-minute claim?

This specific example: 90 seconds for research, 2 minutes total including letter generation and scoring.

Time varies based on:

• Denial complexity: Simple prior auth denial (like this example) vs. multi-layered experimental treatment determination
• Insurance company: UHC has indexed utilization review policies (fast). Some regional insurers have scattered policies (slower).
• Procedure code: Common codes like 70553 have abundant NCCN/CMS sources. Rare experimental procedures require deeper searches.

Average times across all denial types:

• Simple denials (prior auth, coverage exclusion): 1-3 minutes
• Moderate complexity (medical necessity for common procedures): 3-5 minutes
• High complexity (experimental procedures, rare conditions): 5-8 minutes

Still faster than manual: Even our slowest cases (8 minutes) beat the 75-100 minutes required for manual NCCN guideline searches, PubMed literature reviews, CMS policy searches, and drafting. That's a 9-50x time savings depending on complexity.

Can I edit the appeal before submitting?

Yes. Muni Appeals generates the letter, but you retain full control:

Review Process:

1. System generates appeal with research sources and scoring
2. You review the letter for accuracy and completeness
3. You can request regeneration with different emphasis
4. You can edit the letter directly before downloading
5. You approve the final version for submission

You're still the clinician/provider. We automate the tedious research and documentation work, but:

• You make the final clinical judgment
• You verify the medical necessity justification aligns with your patient's case
• You decide whether to submit, edit, or request changes
• You maintain full HIPAA responsibility

Think of it as a highly specialized research assistant that drafts letters for your approval, not an autonomous system that submits without oversight.

Can I try this exact case in your demo?

Yes. This UnitedHealthcare MRI prior authorization case is available in our demo mode. You can:

• Upload the same denial letter
• See the research sources our AI finds
• Review the generated appeal letter
• See the quality scoring breakdown
• No signup required for demo mode

We stock demo mode with multiple case studies covering different denial types (prior auth, medical necessity, frequency limitations, experimental exclusions) so you can see how Muni Appeals handles scenarios similar to your practice's denials.

Try the demo with this case

How do you find NCCN guidelines and insurer policies so quickly?

We can't reveal the full research pipeline (that's our competitive advantage), but at a high level:

• We maintain indexed databases of NCCN clinical guidelines across all cancer types and conditions
• Our system knows where to search across multiple UHC policy portals (utilization review, medical policies, clinical rationale pages)
• We use specialized search algorithms to match clinical scenarios to relevant NCCN recommendations automatically
• We cross-reference patient guidelines, provider guidelines, and clinical evidence summaries

Manual research requires:

• Navigating NCCN's extensive guideline library (50+ cancer types)
• Reading through 100+ page clinical guidelines to find imaging recommendations
• Searching UHC's fragmented policy documentation across multiple systems
• Cross-referencing insurer utilization review criteria with NCCN standards

That's 25-40 minutes even for experienced clinicians. Our system does it in 90 seconds.

What about state prompt payment laws for prior authorization delays?

Excellent additional leverage. Many states have prompt payment laws that require timely prior authorization decisions:

• California - Insurers must respond to prior auth requests within 5 business days for urgent care, 14 days for non-urgent
• New York - 3 business days for urgent, 15 days for non-urgent prior authorization reviews
• Texas - 3 business days for urgent, 15 days for non-urgent (Texas Insurance Code § 1301.137)
• Illinois - Similar timelines with penalties for delays

If your state has prompt payment laws and the insurer delayed their denial, you can argue for retroactive authorization based on administrative failure to meet statutory timelines.

Muni Appeals will automatically search for and cite applicable state prompt payment laws when processing prior authorization denials with delayed reviews.

Why did this score 94/100?

This high score reflects:

1. Sophisticated 5-Layer Evidence Hierarchy: The appeal closes the loop by starting and ending with UHC's own utilization review requirements, creating an airtight procedural argument.

2. NCCN Guideline Authority: NCCN guidelines are the gold standard in oncology/neuro-oncology. Citing 3 separate NCCN patient guidelines for different conditions in the differential diagnosis provides unassailable clinical authority.

3. Level I Evidence Quality: 4 systematic reviews and meta-analyses from PubMed demonstrating diagnostic superiority of contrast-enhanced sequences, all with precise statistical findings.

4. Near-Perfect Hallucination Score (98): Every NCCN guideline quote is real and verifiable. Every PubMed study exists and supports the claims made.

Compared to similar scores (Infliximab 94/100): Both use multi-source policy contradictions effectively. MRI adds the "procedural correction" framing that's particularly powerful for prior auth denials specifically.

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How to Use This Knowledge for Your Practice

Even if you're not ready to try Muni Appeals, this case study teaches you what makes prior authorization appeals succeed:

The Strategy You Can Apply Manually

1. Frame It as Procedural, Not Medical Necessity (When Possible)

For prior auth denials, check if the insurer's utilization review policies require evidence-based criteria:

• Search "[Insurance Company] utilization review procedures"
• Look for language about "evidence-based" or "clinical guidelines"
• If found, cite it in your opening paragraph

Why this works: You're not asking them to reconsider medical necessity—you're showing they're violating their own procedural standards by not applying evidence-based criteria.

2. Lead With Clinical Guidelines (NCCN for Cancer, Specialty Societies for Others)

For any diagnosis-specific denial:

• Search "NCCN [condition] guidelines" for cancer/oncology cases
• Search "[Specialty Society] [condition] guidelines" for other cases (e.g., "AHA heart failure guidelines")
• Look for specific imaging/treatment recommendations

Why this works: Clinical guidelines are the authoritative "evidence-based" standard that insurers claim to follow. When NCCN says "MRI with contrast recommended," that trumps population-level utilization management criteria.

3. Support With Level I Evidence (Systematic Reviews/Meta-Analyses)

For any clinical intervention:

• Search PubMed for "[procedure] systematic review"
• Filter for meta-analyses and systematic reviews (Level I evidence)
• Include 2-3 studies showing efficacy and standard-of-care status

Why this works: High-level evidence proves the requested service is medically necessary and evidence-based, not experimental or inappropriate.

4. Cite Federal Coverage Benchmarks (CMS)

For any CPT code denial:

• Search "CMS [CPT code] NCD" (National Coverage Determination)
• Search "CMS [CPT code] LCD" (Local Coverage Determination)
• Reference Medicare coverage as federal benchmark

Why this works: Even for commercial plans, CMS coverage establishes that the service is recognized, standard care—not excludable or investigational.

5. Request Retroactive Authorization for Prior Auth Denials

For denials based solely on "prior auth required":

• Explicitly request retroactive authorization
• Cite medical urgency/necessity that justified proceeding
• Reference insurer's exception policies if available

Why this works: Many insurers have retroactive auth pathways for medically necessary care that couldn't wait for prior approval.

This is exactly what Muni Appeals automates—but you can do it manually if you have 75-100 minutes per appeal.

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Why Radiology and Oncology Practices Should Pay Special Attention

This UHC CPT 70553 denial demonstrates a systemic problem in imaging prior authorization:

Population-level imaging criteria applied inappropriately to individual cases where clinical guidelines (NCCN) recommend the study. Insurers deny these because:

1. Most practices don't have time to research NCCN guidelines
2. Few providers know to cite Level I evidence in appeals
3. Insurers bet on administrative attrition

The result: Patients experience delayed diagnosis because medically necessary imaging is denied based on screening guidelines that don't apply to their clinical situation.

If you order advanced imaging for cancer or neuro cases, you should be appealing these denials systematically. Each successful appeal:

• Recovers revenue for your practice ($1,800-2,500 for brain MRI with contrast authorization)
• Establishes precedent with that insurer for similar NCCN-guideline-driven imaging
• Helps patients get timely, appropriate diagnostic workup, avoiding delayed diagnosis and treatment

This case study shows it's clinically and legally feasible—the challenge is finding time to research NCCN guidelines, search PubMed, and write the appeals.

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Ready to See It Work on Your Denials?

Stop spending 75-100 minutes per appeal researching NCCN guidelines, CMS policies, and medical literature. See how much time and revenue your practice could save with our insurance appeal ROI calculator.

What happens when you try Muni Appeals:

1. Upload your denial letter (30 seconds)
2. Our system researches 15+ sources and drafts the appeal (1-3 minutes)
3. Review the sources, quality scores, and complete letter
4. Edit if needed, download, and submit to the insurer

The appeal letter you saw above? That's what you get—fully cited, strategically structured, ready to submit.

3 free appeals. No credit card required.

Start Your First Free Appeal

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This example case study demonstrates Muni Appeals methodology using a test scenario (UnitedHealthcare MRI prior authorization denial). Not based on real patient data. All sources cited are authentic and verifiable. Product methodology and scoring approach shown here apply to actual denial processing. Updated October 2025.