Intelligent Revenue Cycle Management (RCM) Automation Engine
An AI-Powered Framework for Automated Medical Claim Parsing & Workflow Automation
mediParse AI is an enterprise-grade platform designed to bridge the gap between unstructured medical documentation and structured healthcare operations. By leveraging state-of-the-art Large Language Models (LLMs) and advanced Vision OCR, MediParse AI transforms messy PDFs, scanned bills, and handwritten prescriptions into validated, actionable data.
The platform provides a complete end-to-end solution for hospitals and insurance providers (TPAs) to manage the entire Revenue Cycle Lifecycle—from pre-authorization and admission to discharge settlement and financial reconciliation.
- Multi-Modal AI Extraction: Ingests digital and scanned PDFs, extracting 30+ clinical parameters (ICD codes, medicines, billing amounts) with high confidence.
- Full RCM Lifecycle: Orchestrates the 8-stage journey: Pre-Auth → Admission → Enhancement → Discharge → Payment → Settlement → Case Closure.
- Financial Analytics & Revenue Gap Tracking: Automated reconciliation to identify revenue leakage, TDS calculations, and hospital-payer mismatch.
- Role-Based Portals: Dedicated, synchronized interfaces for clinical teams (Hospital Portal) and claims auditors (TPA Portal).
- Export & Integration: One-click exports to FHIR-compliant JSON and standardized CSV for seamless EMR/HIS integration.
- Human-in-the-Loop Validation: Built-in logic engine for cross-verifying billing calculations with manual feedback synchronization.
- Frontend: React (Vite) with a premium SaaS design system and dynamic dark-mode aesthetics.
- Backend: FastAPI (Python) for ultra-low latency API responses and asynchronous processing.
- AI / ML Engine: Advanced LLM inference (Gemini 2.0 / Llama-3) coupled with PyMuPDF for document vision.
- Database: Supabase (PostgreSQL) for real-time synchronization and secure cloud storage.
mediparse/
├── backend/
│ ├── main.py # API routing & service orchestration
│ ├── ai_pipeline.py # AI logic & structured extraction
│ ├── rcm_engine.py # Business logic for revenue reconciliation
│ ├── storage.py # Database integration (Supabase)
│ └── extractor.py # Vision OCR & PDF processing
├── frontend/
│ ├── src/
│ │ ├── api.js # Global API client
│ │ ├── components/ # Modular UI architecture
│ │ └── pages/ # Dashboard, Analytics, Case Management
│ └── package.json
└── README.md # Project documentation
- Navigate to the
backenddirectory. - Install dependencies:
pip install -r requirements.txt. - Configure your
.envwithSUPABASE_URL,SUPABASE_KEY, andGEMINI_API_KEY. - Start the server:
python main.py.
- Navigate to the
frontenddirectory. - Install dependencies:
npm install. - Start the development server:
npm run dev.
MediParse AI reduces manual data entry time by 90%, eliminates human error in billing reconciliation, and provides healthcare administrators with real-time visibility into their revenue health, ensuring faster claim settlements and better patient care delivery.
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