Medical Billing & Revenue Cycle

Analyze medical billing workflows, identify revenue leaks, optimize claims, reduce denials, and improve revenue cycle KPIs for healthcare practices and billi...

Security Scan

The skill's requirements and runtime instructions align with its stated purpose (medical billing and revenue-cycle analysis); it is an instruction-only skill with no installs or credential requests, but you should confirm the publisher and avoid sharing protected health information (PHI).

Purpose & Capability

The name/description (medical billing & revenue cycle) match the SKILL.md content: coding checks, denial analysis, KPIs, payer contract analysis, compliance, and charge-capture guidance. The README and SKILL.md reference AfrexAI resources which are relevant to the stated purpose. Minor inconsistency: registry metadata lists no homepage/source while the README/SKILL.md include AfrexAI links; this is a provenance gap but not a functional mismatch.

Instruction Scope

SKILL.md instructions are scoped to receiving practice-level inputs (specialty, payer mix, KPIs, problem area) and returning analyses and recommendations. It does not instruct the agent to read local files, environment variables, or call external endpoints beyond the documented AfrexAI links. However, the guidance can involve sensitive billing data; the skill does not include explicit instructions or warnings about PHI handling — users could be tempted to paste patient-level data into prompts, which would be inappropriate.

Install Mechanism

No install spec and no code files — this is an instruction-only skill, so nothing is downloaded or written to disk. This minimizes installation risk.

Credentials

The skill does not request any environment variables, credentials, or config paths. The declared requirements are minimal and proportional to the stated functionality.

Persistence & Privilege

always:false and default model-invocation behavior. The skill does not request elevated or persistent privileges, nor does it attempt to modify other skills or system settings.

Assessment

This skill is internally coherent for medical billing advice and is low-risk from a technical/install perspective. Before installing or using it: 1) Verify the publisher (follow the AfrexAI links and confirm the vendor identity) since registry metadata lacks a homepage; 2) Never paste PHI (patient identifiers, full claims with patient info) into prompts — test with de-identified or synthetic data only; 3) Treat clinical, legal, and compliance recommendations as advisory: have billing, compliance, or legal experts review any operational changes (Stark Law, False Claims Act, payer contract negotiations); 4) If you plan to run the skill autonomously or integrate it into workflows, document and audit what data you send and consider enabling usage restrictions; 5) If you need stronger assurance about provenance or accuracy, ask the publisher for a privacy/data-handling statement and references for the benchmarks and CARC/RARC mappings used.

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 — AI agent context packs for regulated industries. Get the full Healthcare AI Context Pack with 50+ frameworks at our storefront.