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afrexai-medical-billingAfrexai 医疗账单

Agent Skill

afrexai-medical-billing 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

17,038

周安装

696

GitHub Stars

公开资料未说明

下载量

5,457
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:afrexai-medical-billing(Afrexai 医疗账单)
来源仓库:https://github.com/1kalin/afrexai-medical-billing
安装命令:
openclaw skills install afrexai-medical-billing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install afrexai-medical-billing

简介

afrexai-medical-billing 分析医疗计费流程,识别收入泄漏与索赔拒付原因。

  • 适用于医疗机构优化收入周期管理与合规性检查。afrexai-medical-billing 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 输出包括编码建议、审计清单与 KPI 改进方案。
  • 使用时需提供账单记录、医保政策与内部流程文档。
  • 涉及患者健康信息时必须符合 HIPAA 等隐私保护法规。

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

MetricTargetRed 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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

98.74%
按下载量换算5,388

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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