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KATE was designed by clinicians for clinicians, providing ED Nurses AI-powered decision support at triage, where important clinical decisions impact patient flow and risk. With native Cerner integration, KATE listens to the stream of clinical EHR data and when appropriate provides clinicians a second opinion, helping avoid preventable errors on high risk patients and route lower acuity patients to the right care. KATE has demonstrated in real-world ED use:
- More accurate triage acuity assignment
- Better detection of high-risk clinical conditions
- Earlier sepsis detection and antibiotic treatment
- Reduced ED Length of Stay
- Improved interdisciplinary communication
Use Cases
- Accurate Triage Acuity Assignment
KATE is an AI-powered triage decision support solution that enhances Emergency Nurses ability to provide accurate triage acuity assignment intended to get your patients the right care at the right time. This is especially critical for the identification of high risk presentations at the point of care, where KATE empowers clinicians to improve clinical decision making by 93.2%. - Early Sepsis Detection at ED Triage
The advanced early sepsis detection model enables Emergency Nurses to identify patients with sepsis faster and more accurately at triage, and does so without requiring lab tests. Clinicians using KATE have improved 1-hour sepsis detection and bundle compliance by 87%. - Real-time ED Nurse Triage Training
KATE improves critical reasoning by providing Emergency Nurses real-time notifications on patient assessments and reassessments at triage. Clinicians' interaction with KATE helps ensure EHR documentation reflects the clinical state of each patient and helps put patients on the right clinical pathway within your ED. KATE achieved a 93.2% higher accuracy on high acuity patients vs. Nurses in this published clinical research.
Available in These Countries
- United States
Supported Devices
- Desktop
Version Details
Compatible with Cerner FirstNet (HL7 and FHIR Service)
Testimonial
"Mednition got it right. They've applied proven machine learning technology to one of medicine's most vexing problems [early sepsis detection] and they are delivering it in real time."
Stephen Liu, MD, FACEP, Emergency Department Medical Director, Adventist Health White Memorial
Key Features
Artificial Intelligence on Demand
KATE is designed to listen to and monitor EHR data, including free-text notes, existing within the nurse's Cerner FirstNet workflow. By leveraging KATE's out-of-the-box Machine Learning and Clinical Natural Language Processing, Emergency Department teams can immediately tap into the rich, historical medical records within their EHR to drive accurate, real-time clinical decision making at ED Triage.
Identify & Prioritize High Risk Presentations
KATE understands high risk patients, and can empower your nurse's with AI that can improve clinical decision making by 93.2% at ED triage. Stratify patients based on risk to improve throughput, reduce length of stay, and route patients to the appropriate level of care at the right time.
Early Sepsis Detection at ED Triage
Sepsis is the #1 cause of in-hospital mortality with greater than 80% of sepsis cases originating outside of the hospital, ED Triage is the best place to identify patients with Sepsis. KATE can identify 8 of 10 patients with sepsis at ED triage - without labs.
Train & Support Nurses in Real-time
KATE provides real-time, on-the-job training for ED nurses, improving their clinical reasoning, interdisciplinary communication, and triage accuracy.
Gain Actionable Insights on Performance
With KATE Reports, leadership teams can gain access to critical information and identify areas of strength or improvement at the department and individual level.