Skill: 1kalin/afrexai-medical-billing (version 1.0.0)

# Medical Billing & Revenue Cycle Management Analyze medical billing workflows, identify revenue leaks, optimize claim submissions, and reduce denial rates. Built for healthcare practices, billing companies, and revenue cycle teams. ## What This Covers ### CPT/ICD-10 Coding Accuracy - Common coding errors by specialty (top 10 per specialty) - Modifier usage: 25, 59, 76, 77, AI, AS — when required vs when it triggers audit - E/M level selection (2021 guidelines): time-based vs MDM-based - Evaluation matrix: does documentation support the code billed? ### Claim Denial Analysis - Denial reason code lookup (CARC/RARC codes) - Top 20 denial reasons across commercial + Medicare + Medicaid - Root cause mapping: front-desk error, coding error, clinical documentation, payer policy - Appeal letter framework by denial type (with timelines) - Clean claim rate benchmark: 95%+ target ### Revenue Cycle KPIs | Metric | Target | Red Flag | |--------|--------|----------| | Days in A/R | <35 | >50 | | Clean claim rate | >95% | <90% | | First-pass resolution | >90% | <80% | | Denial rate | <5% | >10% | | Collection rate | >95% | <90% | | Cost to collect | <4% | >7% | | Net collection rate | >96% | <92% | ### Payer Contract Analysis - Fee schedule comparison: Medicare vs commercial rates by CPT - Allowed amount benchmarking (what you should be getting paid) - Underpayment detection: compare ERA/835 to contracted rates - Rate negotiation prep: volume data, market rates, quality metrics ### Compliance & Audit Readiness - OIG Work Plan items relevant to your specialty - Stark Law / Anti-Kickback safe harbors checklist - False Claims Act risk factors - Internal audit sampling methodology (statistically valid) - Documentation improvement programs (CDI) ### Charge Capture Optimization - Missed charge identification by department - Charge lag analysis (days from service to charge entry) - Superbill/encounter form design best practices - Common missed revenue: vaccines, injections, supplies, time-based codes ### Patient Financial Responsibility - Eligibility verification workflow (real-time vs batch) - Prior authorization tracking and requirements by payer - Patient estimate generation (good faith estimate compliance) - Collections strategy: statements → calls → agency threshold - No Surprises Act compliance checklist ## Usage Give the agent your: - **Specialty** (orthopedics, cardiology, primary care, etc.) - **Payer mix** (% Medicare, Medicaid, commercial, self-pay) - **Current KPIs** (denial rate, days in A/R, collection rate) - **Problem area** (denials, underpayments, coding, compliance) The agent will analyze against benchmarks and give specific, actionable recommendations. ## Example Prompts - "Our orthopedic practice has a 12% denial rate. Top reasons are CO-4 and CO-16. Analyze root causes." - "Compare our cardiology fee schedule to Medicare rates for our top 20 CPTs." - "Build an appeal letter for a CO-197 denial on CPT 99214 with modifier 25." - "Audit our E/M coding distribution — we're billing 80% level 3. Is that normal for family medicine?" - "Our days in A/R jumped from 32 to 48 in two months. What should we investigate?" ## Industry Context Medical billing errors cost US healthcare $935 million per week. The average practice loses 5-10% of revenue to preventable billing issues. Denial management alone can recover 2-5% of net revenue when done right. --- Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI agent context packs for regulated industries. Get the full Healthcare AI Context Pack with 50+ frameworks at our [storefront](https://afrexai-cto.github.io/context-packs/).


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