Healthcare Insurance Data Analysis System

A lightweight, optimized system for analyzing healthcare insurance data from Excel and PDF files. This system extracts, processes, and analyzes insurance claims data to identify trends, patterns, rejection rates, and provides actionable insights. Optimized for deployment on Cloudflare Workers.

Features

• Data Extraction: Import data from Excel files and tables from PDFs
• Data Processing: Clean and transform data for analysis
• Rejection Analysis: Analyze claim rejection patterns and trends
• Trend Analysis: Identify monthly and quarterly trends in claims
• Interactive Visualizations: View data through interactive charts and graphs
• Report Generation: Generate JSON and CSV reports
• AI-Powered Insights: Get AI-generated analysis and recommendations
• Cloudflare Workers Compatible: Optimized for edge deployment with minimal resource usage

JavaScript Implementation (Recommended)

The JavaScript implementation is optimized for deployment on Cloudflare Workers, providing fast, scalable performance.

Installation

# Clone the repository
git clone https://github.com/BrainSAIT-LTD/Healthcare-Insurance-Data-Analysis-System.git
cd Healthcare-Insurance-Data-Analysis-System/js-version

# Install dependencies
npm install

Development

# Install Wrangler CLI globally (if not already installed)
npm install -g wrangler

# Start local development server
npm run dev

Deployment to Cloudflare Workers

1. Login to Cloudflare

wrangler login

2. Update your KV namespace ID in wrangler.toml:

[[kv_namespaces]]
binding = "HEALTH_INSURANCE_DATA"
id = "your-kv-namespace-id"

3. Deploy to Cloudflare Workers

npm run deploy

Python Implementation (Legacy)

The original Python implementation uses Streamlit for the web interface.

Installation

# Clone the repository
git clone https://github.com/BrainSAIT-LTD/Healthcare-Insurance-Data-Analysis-System.git
cd Healthcare-Insurance-Data-Analysis-System

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# Windows
venv\Scripts\activate
# macOS/Linux
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Running the application

# Start the Streamlit app
streamlit run app.py

JavaScript vs Python Implementation

Advantages of JavaScript Implementation

• Lightweight: Optimized for edge computing with minimal dependencies
• Fast performance: Quick startup and response times
• Cloudflare Workers deployment: Global edge distribution
• Lower operational costs: Less resource intensive
• Simplified architecture: Single unified codebase

When to use Python Implementation

• Local development: When you need a quick local setup
• Complex data science tasks: When you need to use specific Python libraries
• Legacy compatibility: When integrating with other Python systems

API Documentation

Endpoints

• POST /api/upload: Upload Excel or PDF files for analysis
• POST /api/analyze/rejections: Analyze claim rejection patterns
• POST /api/analyze/trends: Analyze claim trends over time
• POST /api/report: Generate downloadable reports
• POST /api/insights: Generate AI-powered insights (requires OpenAI API key)

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.