Healthcare Analytics Dashboard
Healthcare
Project Overview
ICU medical staff waste precious time manually tracking patient delirium data across multiple spreadsheets and systems, preventing them from focusing on critical care decisions. This comprehensive analytics dashboard automatically aggregates patient data from various sources and uses predictive algorithms to identify patients at risk for delirium episodes before symptoms appear, enabling proactive intervention.
The Challenge
Critical patient data remains scattered across multiple hospital systems, electronic health records, and manual spreadsheets, making comprehensive analysis nearly impossible. Medical staff spend hours compiling reports instead of treating patients, while critical patterns that could predict delirium episodes get buried in data silos. The fragmented approach delays clinical decisions when timing is crucial for patient outcomes.
Solution
Created a unified healthcare analytics platform while at Riseapps that aggregates data from all hospital systems into a single real-time dashboard. Machine learning algorithms analyze patient patterns to predict delirium risk 6-12 hours before onset, triggering automated alerts to medical staff. The system eliminates manual report generation while providing instant insights that enable proactive patient care, significantly improving outcomes while reducing staff workload.