NCT06996626

Real-time NOMA Evaluation

Real-time Evaluation of an Outlier-based Alerting System

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 3,000 (estimated)
• Sponsor: David T Huang · Academic / Other
• Sex: All
• Age: 18 Years – 100 Years
• Healthy volunteers: Not accepted

Summary

Alerts related to outlier clinician behavior are generated in real-time by an intelligent system continuously scraping EHR (electronic health record) data. These alerts are passed to the bedside and their potential impact on bedside clinical behavior is evaluated.

Detailed description

A clinician-informed AI model will generate outlier alerts from real-time review of the EHR (electronic health record) of UPMC Presbyterian/Montefiore ICU patients. These alerts will first be reviewed by an ICU clinician, along with the patients' EHR, for clinical relevance. For those alerts deemed potentially relevant, the ICU clinician will contact the treating ICU clinician (eg, an ICU pharmacist, physician, advanced practice provider) and discuss the alert. The treating ICU clinician will take whatever action, including no action, they deem best.

Conditions

• Critical Illness

Interventions

Type	Name	Description
DEVICE	Revealed Alerts	Bedside reveal of alerts generated by the alerting system
DEVICE	Unrevealed Alerts	Alerts will be generated but not revealed.

Timeline

• Start date: 2025-06-23
• Primary completion: 2026-06-30
• Completion: 2027-06-30
• First posted: 2025-05-30
• Last updated: 2025-07-09

Locations

2 sites across 1 country: United States

Regulatory

• FDA-regulated device study