OPDPS Planning MVP

Project Description

OPDPS (Outpatient Department Planning System) is a Python-based application for resource allocation and scheduling in hospital outpatient departments. This MVP demonstrates the core functionality of resource allocation, scheduling, workload distribution, and reinforcement learning-based optimization using a Streamlit app.

Features

• Resource allocation
• Daily schedule generation
• Workload distribution
• Reinforcement learning model for optimization
• Interactive Streamlit interface for viewing results

Installation

1. Clone the repository
2. Create a virtual environment:

   python3 -m venv venv
   

3. Activate the virtual environment:
   • On Windows:

     venv\Scripts\activate
     

   • On macOS and Linux:

     source venv/bin/activate
     

4. Install dependencies:

   pip install -r requirements.txt
   

Usage

1. Make sure you're in the project root directory (opdps_planning_mvp)
2. Run the Streamlit app:

   streamlit run main.py
   

3. Your default web browser should open automatically. If it doesn't, open a web browser and navigate to the URL displayed in the terminal (usually http://localhost:8501)

Project Structure

• main.py: Contains the entire Streamlit app, including core models and simulation logic
• requirements.txt: List of Python dependencies
• README.md: Project documentation

Components

1. ResourceAllocator: Assigns staff and equipment to patients
2. Scheduler: Generates daily schedules based on allocations
3. WorkloadDistributor: Distributes tasks among available staff
4. RLModel: Simple reinforcement learning model for optimization (placeholder for future development)

Future Improvements

• Implement more sophisticated resource allocation and scheduling algorithms
• Enhance the reinforcement learning model with more complex state and action spaces
• Integrate with real hospital data systems
• Add more interactive features to the Streamlit app, such as custom input for staff, patients, and equipment
• Implement data persistence and historical analysis
• Add visualization of resource utilization and efficiency metrics

License

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Contributors

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