Sepsis Early Warning System

Challenge – Missed Early Warning Signs
Manual monitoring and delayed sepsis detection increased mortality and length of stay across three ICUs. Clinicians missed nearly 15% of early warning signs due to data fragmentation across vital systems, resulting in late interventions and higher clinical risks.

Solution – Real-Time Predictive Sepsis Model
NucleusTeq deployed a predictive AI engine using Nova (NuoData) to calculate real-time sepsis risk scores based on vital trends, lab results, and patient history. Integrated via FHIR APIs, the system triggered automated alerts directly in EHR dashboards, ensuring clinicians could act promptly on deteriorating conditions. Continuous retraining improved accuracy and model robustness over time.

Impact – From Reactive Care to Predictive Response
• AUROC of 0.9 for high-accuracy risk detection
• 15% reduction in adverse sepsis events
• 25% improvement in clinical alert adherence
• 10% reduction in ICU length of stay

The solution transformed sepsis management from reactive detection to proactive prevention — improving survival rates and optimizing critical care resources.