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Health Report Analysis Dashboard

A web-based dashboard for analyzing and visualizing health report data. This dashboard allows healthcare professionals to quickly search for patient records, view detailed information, and gain insights through interactive visualizations.

Features

  • Interactive Patient Search: Search for patients by name, ID, medical condition, doctor, or hospital.
  • Detailed Patient Information: View comprehensive patient details including personal information, medical history, hospitalization data, and billing information.
  • Risk Alert System: Highlight patients with high-risk conditions.
  • Billing Comparison Visualization: Compare billing amounts for patients with similar conditions.
  • Custom Styling and Layout: Clean and modern design with custom CSS for improved user experience.

Getting Started

Prerequisites

  • Python 3.8 or higher
  • Streamlit
  • Plotly
  • Pandas

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/health-report-dashboard.git

  2. Install the required packages:

    pip install streamlit plotly pandas

  3. Run the dashboard:

    streamlit run health_dashboard.py

Usage

  1. Open your web browser and navigate to the local Streamlit URL (usually http://localhost:8501).
  2. Use the search bar to find patients by name, ID, condition, doctor, or hospital.
  3. Select a patient from the search results to view detailed information.
  4. Explore the interactive visualizations to gain insights into patient data.

Screenshots

Dashboard View 1 Dashboard View 2

Contributing

Feel free to contribute to this project by submitting pull requests or opening issues. Any contributions are welcome!

License

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

Contact

For any questions or feedback, please contact your-email@example.com.

Acknowledgments

  • Streamlit for providing a powerful and easy-to-use framework for creating web applications.
  • Plotly for enabling interactive data visualizations.
  • Pandas for efficient data manipulation and analysis.

Adding Images to Your GitHub Repository

To include the images in your GitHub repository, follow these steps:

  1. Upload the Images: Place the images (Web_page-0001.jpg and Web_page-0002.jpg) in the root directory of your repository or in a specific folder (e.g., images/).

  2. Update the README File: Ensure the paths to the images in the README file match the actual paths in your repository. If you place the images in an images/ folder, update the paths accordingly:

    ![Dashboard View 1](images/Web_page-0001.jpg)
![Dashboard View 2](images/Web_page-0002.jpg)

  3. Commit and Push: Commit the changes to your repository and push them to GitHub.

    git add README.md Web_page-0001.jpg Web_page-0002.jpg
git commit -m "Add README and dashboard screenshots"
git push origin main