How to Use AI to Appeal a Denied Health Insurance Claim

How to Use AI to Help Fight a Health Insurance Denial: Step-by-Step Guide

A denied claim is a problem, not a dead end. With the right prompts and a clear process, AI can help you decode the denial, draft a strong appeal, and keep the case moving.

This guide is built for insurance professionals and writers who turn messy records into clean, persuasive arguments. Keep it tight, verifiable, and on deadline.

What AI can do (and what it can't)

• Summarize denial letters, policies, and charts into the key facts.
• Extract policy language tied to the denial reason and map it to your evidence.
• Draft letters, call scripts, and checklists you can refine and approve.
• Spot coding and authorization gaps that are fixable.

• AI can't give legal advice, make calls, or guarantee outcomes.
• De-identify all documents before using public AI tools. Confirm citations and figures manually.

Step 1: Build your evidence pack

Collect the denial letter, Explanation of Benefits (EOB), plan's certificate of coverage, prior authorization records, clinical notes, coding sheets (ICD/CPT/HCPCS), and any provider letters. Add dates, IDs, and contact info.

Prompt:
"Review this denial letter, EOB, and plan document. List every item missing from my evidence pack for a first-level appeal. Output: checklist with doc name, where to source it, and why it matters."

Step 2: Decode the denial reason precisely

Ask AI to extract the denial rationale in the payer's own terms and the exact policy clauses cited. This frames your argument.

Prompt:
"From this denial letter and plan document, extract: 1) denial reason as written, 2) relevant policy sections verbatim with page/section, 3) the standard needed to approve (e.g., 'medically necessary,' 'prior auth required'), 4) evidence I must prove."

Step 3: Confirm the appeal path and deadlines

Use AI to outline internal levels of appeal, deadlines, required forms, and external review rights, then verify in the plan document. Keep a single-page timeline.

For ACA-compliant plans and external review basics, see the official consumer guidance at HealthCare.gov. For ERISA plans, see the U.S. Department of Labor overview of claim and appeal rules at dol.gov.

Step 4: Build the medical necessity story

Summarize the patient's condition, prior treatments, outcomes, and risks if care is delayed. Tie each point to clinical notes, test results, and guideline citations your clinician approves.

Prompt:
"Using these clinic notes and labs, draft a medical necessity summary (150-250 words) that links symptoms, failed alternatives, risks of delay, and expected benefits. Include in-text references to the source page or note date. No invented citations."

Step 5: Fix coding, auth, and admin gaps

Many denials are coding or paperwork issues. Ask AI to flag mismatches between clinical notes, CPT/ICD codes, modifiers, site of service, and prior auth records. Confirm changes with the provider's billing team before resubmission.

Prompt:
"Compare these notes to these codes (ICD/CPT/HCPCS). List likely mismatches, missing modifiers, or site-of-service conflicts. Suggest compliant options to discuss with billing. Cite the specific text that supports each suggestion."

Step 6: Draft a clean appeal letter

Keep it short: issue, facts, policy, evidence, request. One page for first-level appeals is often enough; attach exhibits with a clear index.

Prompt:
"Draft a first-level appeal letter for Claim #[ID]. Structure: 1) denial reason in payer's language, 2) policy citations that support approval, 3) medical necessity summary (linked to exhibits), 4) any coding/auth corrections, 5) explicit request: overturn denial and pay per contract. Tone: professional, factual, concise. Include an exhibit list."

Step 7: Package and submit

• Exhibit index with labels (A, B, C…), titles, and dates.
• Appeal letter, cover sheet with contact details, and required forms.
• One PDF if possible, filename: "MemberID_ClaimID_AppealLevel_Date.pdf."

Prompt:
"Create a one-page exhibit index from these files. Columns: Label, Title, Date of Service, Source, Relevance. Keep titles under 80 characters."

Step 8: Track follow-up and escalate

Log every touchpoint: date sent, receipt, reference number, rep name, promised response date, and next action. Use AI to generate reminders and call scripts.

Prompt (call role-play):
"Act as a payer rep. I'll state the claim details. Ask realistic follow-up questions and request documentation. After the call, produce a call summary and next steps with deadlines."

Prompts you can copy

• Policy extractor: "From this plan document, pull every clause that governs [service], preauth, medical necessity, and timelines. Return citations with page/section numbers."
• Gap analysis: "Compare policy requirements to my evidence pack. List what satisfies each requirement and what's missing."
• Appeal variants: "Rewrite the letter for: 1) medical necessity, 2) prior auth obtained, 3) coding correction, 4) timely filing exception. Keep core facts identical."
• External review readiness: "Create a summary suitable for independent review: issue, policy, evidence table, and conclusion. No rhetorical language, just facts."

Workflow tips for insurance pros and writers

• Standardize templates: intake form, evidence checklist, medical necessity summary, letter, exhibit index, call log.
• Version control: date-stamp every draft; store source PDFs next to the letter.
• De-identify PHI before using public AI. Use enterprise or local tools for full PHI work.
• Measure win rate by denial type (medical necessity, coding, auth), turnaround time, and rework rate.

Ethics, privacy, and accuracy

• Never paste full PHI into unsecured tools. Redact names, member IDs, dates of birth, addresses.
• Verify all citations, codes, and figures. Treat AI output as a draft, not a decision.
• If the plan is ERISA-governed, align with the plan's claims and appeals procedures.

Sources and expert perspectives

This guide is informed by professionals working across clinical, legal, payer, and AI operations:

• Heather Bassett, MD - Chief Medical Officer, Xsolis
• Scott Bennett, Esq. - Attorney and EVP of Provider Relations, The Phia Group
• Christine Smith Stetler, RN - Director of Product Consulting, MedeAnalytics
• Ariella VanHara, LCSW - Clinical Assistant Professor, Florida Gulf Coast University
• Zach Veigulis - Chief AI Officer and Cofounder, Claimable

Keep sharpening your prompts

If you want deeper practice with prompt patterns for compliance-heavy writing, explore training on prompt design and workflow building: Prompt Engineering Resources.

This content is for information only and does not replace legal, medical, or billing advice. Verify requirements in the actual plan documents and with the payer.