Healthcare Simulation Case Generator

An AI-powered healthcare simulation case generator built with Next.js 14, TypeScript, and Claude AI. This application helps medical educators create realistic, educational simulation cases for healthcare training with advanced AI-generated progression scenarios.

🚀 Features

🤖 AI-Powered Progression Scenarios ⭐ NEW

• Conditional Branching: Create decision-based scenarios with multiple pathways
• Time-Based Evolution: Generate natural disease progression without intervention
• Complication Scenarios: Build unexpected clinical events and crisis management training
• Context-Aware Generation: Uses existing patient data for personalized scenarios
• Real-time Progress Tracking: Visual feedback during AI generation process

🏥 Core Case Generation

• AI-Powered Case Generation: Leverage Claude AI to create realistic medical simulation cases
• Multi-Step Form Interface: Intuitive case creation workflow
• Tab-Based Case Display: Organized presentation of patient information, scenarios, and learning objectives
• Timeline Visualization: Interactive timeline with expandable details and branch pathways

🎨 User Experience

• Modern UI/UX: Clean, responsive design built with Tailwind CSS
• Inline Timeline System: Toggle timelines without modal interruptions
• State Management: Efficient state handling with Zustand
• Form Validation: Robust form handling with React Hook Form
• Real-time Notifications: User feedback with React Hot Toast
• TypeScript: Full type safety throughout the application

🎯 AI Progression Scenarios

Three Scenario Types Available:

1. 🔀 Conditional Branching Scenarios

• Decision points with multiple pathways (positive/negative/neutral outcomes)
• Realistic vital sign progressions based on patient data
• Critical decision windows with clinical timing
• Patient-specific risk factors and physiological responses

2. ⏰ Time-Based Evolution Scenarios

• Natural disease progression modeling without intervention
• Pathophysiology-based progression patterns
• Compensatory mechanism progression and decompensation points
• Patient-specific timing variations (age, comorbidities, medications)

3. ⚠️ Complication Scenarios

• Unexpected clinical events and crisis management
• Risk factor-based complications with early warning signs
• Multiple management pathway options
• Realistic complication timing and recognition challenges

🎓 Educational Benefits:

• Clinical Accuracy: Evidence-based timing and pathophysiology
• Personalization: Patient-specific factors (age, medications, conditions)
• Assessment Ready: Built-in instructor notes and teaching points
• Progressive Complexity: Multiple difficulty levels available

🛠️ Tech Stack

• Framework: Next.js 14 with App Router
• Language: TypeScript
• Styling: Tailwind CSS
• State Management: Zustand
• Form Handling: React Hook Form
• AI Integration: Anthropic Claude API
• Icons: Lucide React
• Notifications: React Hot Toast
• Development: ESLint, Prettier

📋 Prerequisites

• Node.js 18.0.0 or higher
• npm 8.0.0 or higher
• Anthropic API key

🚀 Getting Started

1. Clone the repository

git clone <repository-url>
cd healthcare-sim

2. Install dependencies

npm install

3. Environment Setup

Create a .env.local file in the root directory:

cp .env.local.example .env.local

Update the .env.local file with your actual values:

# Anthropic Claude API Configuration
ANTHROPIC_API_KEY=your_anthropic_api_key_here

# NextAuth Configuration (for future authentication)
NEXTAUTH_SECRET=your_nextauth_secret_here
NEXTAUTH_URL=http://localhost:3000

# Application Settings
NODE_ENV=development
APP_NAME="Healthcare Simulation Case Generator"
APP_VERSION=1.2.0

4. Run the development server

npm run dev

Open http://localhost:3000 in your browser to see the application.

🏗️ Project Structure

healthcare-sim/
├── src/
│   ├── app/                 # Next.js App Router pages
│   │   ├── api/            # API routes
│   │   │   └── progression/ # AI progression generation endpoint
│   │   ├── globals.css     # Global styles
│   │   ├── layout.tsx      # Root layout
│   │   └── page.tsx        # Home page
│   ├── components/         # React components
│   │   ├── ui/            # Reusable UI components
│   │   ├── forms/         # Form components
│   │   ├── progression/   # AI progression scenario components
│   │   └── layout/        # Layout components
│   ├── lib/               # Library configurations
│   │   └── anthropic.ts   # Claude AI integration
│   ├── stores/            # Zustand stores
│   │   └── useAppStore.ts # Main application store
│   ├── types/             # TypeScript type definitions
│   │   ├── index.ts       # Main types
│   │   └── progression.ts # Progression scenario types
│   └── utils/             # Utility functions
│       ├── constants.ts   # Application constants
│       └── helpers.ts     # Helper functions
├── public/                # Static assets
├── AI_GENERATION_PROMPTS.md # Expert AI prompts for scenario generation
├── PROGRESSION_TAB_README.md # Detailed progression system documentation
├── CHANGELOG.md          # Version history and updates
├── .env.local           # Environment variables
├── package.json         # Dependencies and scripts
├── tailwind.config.js   # Tailwind CSS configuration
├── tsconfig.json        # TypeScript configuration
└── README.md           # Project documentation

🎮 Using AI Progression Scenarios

Creating a New Progression Scenario:

1. Navigate to Progression Tab in any case
2. Click "Create New Progression Scenario"
3. Choose scenario type: Conditional Branching, Time-Based Evolution, or Complication
4. Select "Generate with AI"
5. Configure parameters:
   • Duration (15-120 minutes)
   • Complexity level (Simple/Moderate/Complex)
   • Specific settings per scenario type
6. AI generates complete scenario with realistic clinical timing
7. View timeline inline with expandable details

Timeline Interaction:

• Click "Timeline" button to toggle inline display
• View Timeline Summary for quick overview (event counts, severity stats)
• Expand sections individually (Main Timeline, Branch Details)
• Clinical accuracy with evidence-based progressions

🔧 Available Scripts

• npm run dev - Start development server with Turbopack
• npm run build - Build the application for production
• npm run start - Start the production server
• npm run lint - Run ESLint
• npm run lint:fix - Fix ESLint errors automatically
• npm run type-check - Run TypeScript type checking
• npm run format - Format code with Prettier
• npm run format:check - Check code formatting
• npm run clean - Clean build artifacts

🌐 Deployment

Vercel (Recommended)

1. Push your code to a Git repository
2. Connect your repository to Vercel
3. Add environment variables in Vercel dashboard:
   • ANTHROPIC_API_KEY
   • NEXTAUTH_SECRET
   • NEXTAUTH_URL (set to your production URL)
4. Deploy

Other Platforms

The application can be deployed to any platform that supports Next.js:

• Netlify
• AWS Amplify
• Railway
• Render

🔐 Environment Variables

Variable	Description	Required
ANTHROPIC_API_KEY	Your Anthropic Claude API key	Yes
NEXTAUTH_SECRET	Secret for NextAuth.js (future use)	No
NEXTAUTH_URL	Base URL for authentication	No
NODE_ENV	Environment (development/production)	No

🧪 Confirmed Working Features

Recent successful testing (June 2025):

✅ AI generated: "Time-Based Evolution: Early Sepsis from UTI - Elderly Diabetic"
✅ API endpoint responding correctly (/api/progression/generate)
✅ Case data integration working (hasContextData: true)
✅ Real-time generation logging active
✅ Complete scenario created with timeline data

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

If you encounter any issues or have questions:

1. Check the Issues page
2. Create a new issue with detailed information
3. Contact the development team

🔮 Future Enhancements

• User authentication and authorization
• Advanced scenario analytics and usage tracking
• Scenario sharing between instructors
• Integration with Learning Management Systems (LMS)
• Mobile application
• Multi-language support
• Enhanced AI prompts with specialty-specific templates
• Peer review system
• Assessment integration with automatic scoring

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🎯 Production Ready: Complete AI generation integration functional with all three scenario types working, dev server running successfully, and real-time AI scenario generation operational using expertly crafted medical education prompts.

Built with ❤️ for healthcare education