Clinic Performance Tracker is a data-driven solution designed to streamline employee performance management at clinics. This project includes two main deliverables:

1. An interactive dashboard built in Metabase to track and visualize employee performance metrics.
2. A target generator tool built in Streamlit using Python to efficiently set employee performance targets.

Efficient employee performance management is critical for healthcare facilities to ensure quality service delivery and resource optimization. To address this, the Clinic Performance Tracker project was developed to empower clinic managers with real-time insights into staff performance and provide tools to set performance goals effectively.

This project was initiated to solve key challenges faced by clinic managers, such as:

• Tracking employee performance across various metrics.
• Setting and managing weekly-monthly-yearly target hours for staff members.
• Streamlining data visualization and analysis processes.

The dashboard, built using Metabase, provides clinic managers with a comprehensive view of employee performance. Key features include:

• Real-time performance tracking by location, manager, and staff.
• Aggregated performance metrics (actual working hours vs. target hours).
• Interactive filters for customization (e.g., date, location, and manager).

Click the image below to watch the demo on YouTube:

The target generator, built in Streamlit, enables clinics to set performance targets for employees. This tool simplifies the annual target cloning process by:

• Cloning target hours from the previous year to the upcoming year.
• Allowing adjustments to target hours (ranging from 4–7 hours per day per person).
• Exporting updated targets to integrate with the performance dashboard seamlessly.

Check out the video demo of the tool here:

For detailed setup and usage instructions, please visit the Documentation folder.

• Metabase: For dashboard creation and data visualization.
• Streamlit: For building the target generator tool.
• PostgreSQL: As the primary database for data storage.
• Python: For backend scripting and data manipulation.

• Huan LV - Project Lead
• Anthony Nguyen - Target Generator Development / Bug Fixes
• Divyanshu Fialok - Target Generator Development / Bug Fixes
• Dawn Dang - Dashboard Development / Design
• Andy Nguyen - Dashboard Development / Design