Surgeon Performance Analysis

Gemma Analytics – Analytics Engineer Task

This project analyzes EQ-5D-5L patient surveys to identify the most and least skilful surgeons for hip replacement operations, based on how much their patients improved after surgery.

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Objective

Measure patient improvement and rank surgeons by performance using a metric that combines:

• Average improvement
• Number of patients treated
• Consistency (via standard deviation)

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Approach

• Filtered for hip surgeries
• Mapped answers to numeric scores
• Calculated patient improvement (post - pre)
• Aggregated by surgeon
• Ranked using a weighted score: > avg_improvement × log(1 + num_patients)

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Highlights

Top Surgeons: Obi-Wan Kenobi, Luke Skywalker, Mon Mothma
Lowest Ranked: Padme Amidala, Princess Leia, Darth Maul

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Visuals

• Bar chart: Top 10 surgeons vs average improvements

• Bubble chart: Volume vs. improvement

• Box plot: Outcome consistency ( surgeon vs improvement score)

• Heatmap: Surgeon performance metric correlations

• BarChart: Patient Volume Vs Surgeons

• BarChart: Surgeon Ranking based on weighted score

Note: GitHub does not render interactive Plotly charts in Jupyter notebooks.

To view all visualizations, please refer to the static images in the plots/ folder.

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Tools

• Python, Pandas, NumPy
• pandasql (SQL in Python)
• Plotly (interactive charts)

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How to Run

This project was built using Python 3.9+.

Make sure you're using Python 3.9 or higher. Then install the required packages and launch the notebook:

pip install -r requirements.txt
jupyter notebook

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Final Note

Thank you for the opportunity to work on this challenge. I really enjoyed combining SQL, Python, and clear storytelling, especially knowing that Gemma values turning data into meaningful, actionable insights. I admire Gemma Analytics's mission to make analytics accessible and would be excited to contribute to that kind of work