1kalin/afrexai-medical-billing/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 - Eval
npx skillsauth add openclaw/skills 1kalin/afrexai-medical-billingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Analyze medical billing workflows, identify revenue leaks, optimize claim submissions, and reduce denial rates. Built for healthcare practices, billing companies, and revenue cycle teams.
| 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% |
Give the agent your:
The agent will analyze against benchmarks and give specific, actionable recommendations.
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.
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