AI Productivity Analysis for Medical Fees in Japan
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# MCP-Health Python Package     **AI Productivity Analysis for Medical Fees in Japan** A comprehensive Python package for analyzing the economic impact of AI implementation in Japan's healthcare system, focusing on administrative efficiency and clinical productivity improvements. ## 🌟 Features - **📊 Healthcare Productivity Analysis**: Calculate baseline metrics and AI impact projections - **💰 Economic Impact Assessment**: ROI analysis and cost savings calculations - **📈 Advanced Visualizations**: Professional charts and dashboards - **🏥 Japanese Healthcare Focus**: Specialized for Japan's aging society challenges - **🤖 AI Implementation Modeling**: Evidence-based improvement factors - **📋 Sample Datasets**: Representative Japanese healthcare data for testing ## 🚀 Quick Start ### Installation ```bash # Install from PyPI pip install mcp-health # Install with optional dependencies pip install mcp-health[interactive] # Jupyter + Plotly support pip install mcp-health[all] # All optional dependencies ``` ### Basic Usage ```python from mcp_health import HealthcareProductivityAnalyzer, HealthcareDataGenerator # Generate sample data generator = HealthcareDataGenerator() datasets = generator.generate_all_datasets() # Run analysis analyzer = HealthcareProductivityAnalyzer() analyzer.data = datasets report = analyzer.generate_analysis_report() # Print key results summary = report['summary'] print(f"Annual Savings: ¥{summary['total_annual_savings_trillion_yen']:.1f} Trillion") print(f"5-Year ROI: {summary['five_year_roi_percentage']:.0f}%") print(f"Payback Period: {summary['payback_period_years']} years") ``` ### Crea…
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