Investigative data journalism: quantifying fixable waste in US healthcare, one issue at a time. Open-source analysis of CMS, OECD, and federal datasets. $428.6B in savings identified so far across 8 published issues.
XGBoost pipeline predicting hospital Excess Readmission Ratios on FY2024 CMS HRRP data. SHAP explainability, 5-fold CV (R² 0.938), and a live Streamlit dashboard for per-hospital risk assessment.
SQL + Power BI + Excel analytics system built on public CMS hospital data. Tracks 30-day readmission rates, HCAHPS patient satisfaction, and clinical quality indicators across 4,800+ U.S. hospitals — with benchmarking, trend analysis, and operational efficiency reporting across three dashboard pages.
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Anomaly detection and overcharge prediction in Medicare Part-B claims using unsupervised outlier detection and supervised ML (XGBoost, Random Forest, logit regression). Analyzes 800K+ Illinois claims from CMS 2015 data.
Healthcare analytics system identifying hospitals at risk for CMS readmission penalties. Analyzes $5.96B in financial exposure, predicts intervention opportunities, saves $1.46B. Python • scikit-learn • CMS data • Healthcare policy
Analyzing CMS hospital readmission data — SQL + Python + statistical testing + predictive modeling
End‑to‑end healthcare analytics case study using CMS Hospital Quality data. SQL for data cleaning, R for predictive modeling, and Tableau for hospital readmission performance insights.
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