Sepsis is a critical medical condition marked by a dysregulated response to infection, causing systemic inflammation and potential organ failure. It remains a leading cause of morbidity and mortality in healthcare. Early detection and timely intervention are essential for improving patient outcomes, yet current methods for identifying severe sepsis face major challenges.
Traditional approaches to identifying and diagnosing severe sepsis are not real-time, causing delays in clinician response. These delays can hinder timely intervention, which is vital for effective sepsis management. Recently, health systems have developed or implemented Sepsis AI/ML models for early detection. However, studies show that most AI-based sepsis models generate high false positive rates (flag rates), with some models incorrectly flagging as many as 25% of patients. These inaccuracies can lead to unnecessary treatments, increased healthcare costs, and missed opportunities to intervene for patients who are truly at risk. Additionally, repeated false alarms can erode clinician trust in these models.
NJII is introducing a comprehensive, peer-reviewed AI-based solution, powered by our partner Cognome, with the lowest flag rate (<2%) and highest accuracy compared to published studies of other models. The Sepsis Management Ensemble includes three components: two ML models and a sepsis-specific LLM. The Sepsis Early Warning Predictor (SEPSIS-EARLY) uses advanced machine learning to analyze live clinical data, enabling sepsis prediction up to 6 hours in advance. By combining metrics such as scoring systems, lab values, and demographic data, SEPSIS-EARLY enhances early sepsis recognition, critical for effective management. This model has achieved the lowest published false-positive rate in the industry (< 2%), demonstrating reliability and the ability to foster clinician trust.
The Sepsis Realtime Surveillance (SEPSIS-REALTIME) model is the second component. This automated phenotype model leverages clinical documentation and real-time data to accurately reflect sepsis prevalence across the hospital. Integrated with EHR systems like Epic, SEPSIS-REALTIME provides timely alerts within the clinician’s workflow. Accurate real-time detection can shorten time to intervention by approximately 30%, enabling faster clinical response in critical situations.
The third component is a sepsis-specific LLM that analyzes clinical notes and diverse data sources to identify severe sepsis in real-time. It provides a comprehensive view of patient progress and clinical conditions across multiple systems. This LLM eliminates the need for nurses to manually cross-reference notes within the patient’s chart. It also automates regulatory and registry reporting and delivers highly accurate coding for billing purposes.
The implications of this next-generation sepsis solution are profound. As the healthcare industry continues to confront the challenges of early and accurate sepsis detection, NJII’s Sepsis Management Ensemble—focused on real-time data and advanced predictive modeling—can significantly improve early detection, enhance overall patient care and reduce mortality.
For healthcare professionals and institutions aiming to implement effective sepsis detection solutions, NJII offers valuable insights and resources to support this critical area of patient care.
Need more information visit Healthcare AI Solutions – NJII