Healthcare
Predicting Patient Readmissions
SparkAirflowSnowflakePython
The Challenge
A regional hospital network was losing $12M annually to unplanned 30-day readmissions. Patient data was siloed across EMR systems, billing platforms, and lab databases with no unified view.
The Approach
Built a real-time data pipeline unifying 14 source systems into a single patient data warehouse. Developed predictive models on top of the integrated data that flagged high-risk patients at discharge, enabling care teams to intervene with targeted follow-up programs.
The Impact
27% reduction in 30-day readmissions
3.2M records unified across 14 source systems
$8.4M in annual cost savings
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