A Rapid Diagnostic of Risk in Hospitalized Patients Using Machine Learning (NCT05893420)
A Rapid Diagnostic of Risk in Hospitalized Patients With COVID-19, Sepsis, and Other High-Risk Conditions to Improve Outcomes and Critical Resource Allocation Using Machine Learning
🩺 Plain-English Summary (8th-Grade Level)
In this study, the investigators will deploy a software-based clinical decision support tool (eCARTv5) into the electronic health record (EHR) workflow of multiple hospital wards. eCART's algorithm is designed to analyze real-time EHR data, such as vitals and laboratory results, to identify which patients are at increased risk for clinical deterioration. The algorithm specifically predicts imminent death or the need for intensive care unit (ICU) transfer. Within the eCART interface, clinical teams are then directed toward standardized guidance to determine next steps in care for elevated-risk patients. The investigators hypothesize that implementing such a tool will be associated with a decrease in ventilator utilization, length of stay, and mortality for high-risk hospitalized adults.
Who can join: Review the eligibility criteria below.
Location: Yale New Haven Health System — New Haven, Connecticut
Age range: 18 Years
🧪 Interventions in This Study
📋 "Do I Qualify?" — 1-Minute Self Screener
Instant ChecklistFull eligibility criteria are available on the official NIH protocol. View the criteria ↗
📍 All Participating Trial Locations (3 Sites)
- Yale New Haven Health System — New Haven, Connecticut
- BayCare Health System — Clearwater, Florida
- University of Wisconsin Health — Madison, Wisconsin
💰 Cost, Insurance & Patient Rights
- 100% Free Items: The investigational treatment and protocol-required procedures are supplied at zero cost by the sponsor.
- Routine Patient Care: Under federal law (ACA § 2709) and many state statutes, routine care costs are covered during participation.
- Voluntary Participation: You may withdraw at any time without affecting your standard medical care.
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💡 How to Participate
- Check the checklist above to see if you may qualify.
- Review the official NIH record below to find the coordinating site.
- Ask about the visit schedule, what is covered at no cost, and any travel support.
- Confirm with your own doctor before making a decision.