AI Tool Cuts Neuroscience ICU Stay by Nearly 8 Hours Without Increasing Readmission Risk

A real-time artificial intelligence (AI) tool integrated into ICU workflows reduced length of stay (LOS) in a neuroscience intensive care unit (NSICU) by 7%—approximately eight hours—without raising unplanned ICU readmission rates.

The study, published in the Journal of Healthcare Management(March/April 2025; Vol. 70, Issue 2; pp. 126–136), was conducted at Tampa General Hospital(TGH), a large academic tertiary care and safety-net center in the United States with over 50,000 discharges and 30,000 surgical procedures annually. As part of a multidisciplinary ICU performance improvement initiative, researchers collaborated with GE HealthCare’s Command Center to develop a Downgrade Readiness Tile (DRT) aimed at streamlining patient transitions out of the NSICU. The goal was to alleviate ICU bed capacity strain—averaging above 90%—by enabling earlier identification of patients clinically appropriate for downgrade to lower-acuity units.

The DRT utilized over 76 real-time clinical variables extracted from the electronic medical records and displayed AI-generated assessments of downgrade eligibility with a target accuracy exceeding 95%. Instead of merely identifying indicators of clinical stability, the model flagged patients based on the absence or presence of clinical barriers to transfer. If no active criteria were met and no transfer order was initiated, the system automatically suggested downgrade readiness; if three or more barriers were present, it signaled ineligibility.