Improving patient outcomes with predictive analytics
Private hospital network | Healthcare | 6 months
The challenge
The hospital network struggled to identify patients at high risk of readmission and coordinate care effectively across multiple facilities. This led to poor patient outcomes and increased healthcare costs.
Our solution
We developed a predictive analytics platform that identifies high-risk patients using historical patient data, treatment patterns, and clinical indicators. The system provides care teams with actionable insights and recommendations.
Results
- ✓22% reduction in 30-day readmissions
- ✓35% improvement in care coordination
- ✓Better patient satisfaction scores
- ✓Significant cost savings from prevented readmissions
Technologies used
PythonAzure MLFHIR
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