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1kalin

Medical Billing & Revenue Cycle

by 1kalin · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
539
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Install in OpenClaw
/install afrexai-medical-billing
Description
Analyze medical billing workflows, identify revenue leaks, optimize claims, reduce denials, and improve revenue cycle KPIs for healthcare practices and billi...
README (SKILL.md)

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 \x3C35 >50
Clean claim rate >95% \x3C90%
First-pass resolution >90% \x3C80%
Denial rate \x3C5% >10%
Collection rate >95% \x3C90%
Cost to collect \x3C4% >7%
Net collection rate >96% \x3C92%

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.

Usage Guidance
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.
Capability Analysis
Type: OpenClaw Skill Name: afrexai-medical-billing Version: 1.0.0 The skill bundle contains only metadata and markdown documentation. The SKILL.md and README.md files describe a medical billing and revenue cycle management tool, providing usage instructions and examples. There are no executable code files. Analysis of the markdown content reveals no prompt injection attempts, malicious commands, data exfiltration instructions, or any other indicators of harmful behavior. The external links provided are informational/marketing and do not instruct the agent to perform any malicious actions.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install afrexai-medical-billing
  3. After installation, invoke the skill by name or use /afrexai-medical-billing
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial public release of afrexai-medical-billing skill: - Provides end-to-end analysis of medical billing workflows, denial management, payer contracts, coding, compliance, and patient collections. - Includes specialty-specific guidance on CPT/ICD-10 coding accuracy and modifier usage. - Benchmarks practice KPIs and identifies revenue leaks with actionable recommendations. - Features payer contract comparison tools and underpayment detection. - Covers compliance checklists (OIG, Stark Law, No Surprises Act) and internal audit frameworks. - Supports customizable queries for denial analysis, appeal letters, and fee schedule comparisons.
Metadata
Slug afrexai-medical-billing
Version 1.0.0
License
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is 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... It is an AI Agent Skill for Claude Code / OpenClaw, with 539 downloads so far.

How do I install Medical Billing & Revenue Cycle?

Run "/install afrexai-medical-billing" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Medical Billing & Revenue Cycle free?

Yes, Medical Billing & Revenue Cycle is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Medical Billing & Revenue Cycle support?

Medical Billing & Revenue Cycle is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Medical Billing & Revenue Cycle?

It is built and maintained by 1kalin (@1kalin); the current version is v1.0.0.

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