SQL analysis of hospital readmission rates using patient data
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Updated
Apr 21, 2026
SQL analysis of hospital readmission rates using patient data
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Analyzing and predicting 30-day readmission to help hospitals intervene and prevent readmission to reduce costs
Machine-learning model that predicts hospital readmission risk from structured clinical data (Python, Jupyter, Docker).
Blake's Haas Capstone Project - Patient Readmissions Prediction
COVID-19 30-day readmission risk pipeline — EHR cohort construction, ML scoring, Streamlit care manager dashboard
Power BI: ML-scored hospital readmission predictor — targeting $26B in preventable readmissions
Predicting the readmission of Diabetic patients using Machine Learning based on various factors.
Healthcare Analytics project using MySQL and Power BI to identify factors driving hospital readmissions.
"SQL analysis of 30-day hospital readmission patterns using the UCI Diabetes 130-US Hospitals dataset (MySQL, joins, CTEs, window functions)"
Analysed 10 years of diabetic patient hospital records using MySQL and Tableau to identify the primary risk factors driving 30-day readmissions, age, diagnosis type, and discharge disposition.
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