This project analyzes hospital readmission rates using data from the Centers for Medicare & Medicaid Services (CMS) Hospital Readmissions Reduction Program, integrating it with Google Reviews to explore potential relationships between patient experiences and hospital performance.
Key areas of focus include:
✅ State-by-State Readmission Trends – Identifying variations in hospital performance across different regions.
✅ Hospital Review Insights – Examining Google Reviews to assess patient satisfaction and hospital ratings.
✅ Readmission vs. Patient Ratings – Exploring whether higher-rated hospitals tend to have lower readmission rates.
✅ Data Cleaning & Integration – Using SQL for data transformation and Python for web scraping hospital reviews.
This project highlights data-driven insights into healthcare quality and demonstrates practical applications of SQL, Python, and Tableau in analyzing real-world datasets.
You can view the presentation here:
To interact with all of the visuals you can do so by viewing directly from Tableua here:
To view my the Python script I created for webscraping google reviews you can download it here:
To view the SQL script that I created to clean my dataset you can download it here:
Citation: Centers for Medicare & Medicaid Services (CMS). (Year). Hospital Readmissions Reduction Program (HRRP) dataset. Retrieved from https://data.cms.gov
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