Mednition provides a machine learning-based decision support platform, KATE, that enhances emergency department triage by automatically identifying and prioritizing high-risk patients. This solution enables nurses to improve patient outcomes without altering existing workflows, significantly increasing the efficiency of critical care delivery.
Funding
$10M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
CHFounders
Product
Problem
Emergency departments (EDs) face challenges in quickly identifying and prioritizing high-risk patients, leading to potential delays in critical care and negatively impacting patient outcomes. Traditional triage methods can be subjective and may not effectively leverage all available patient data to accurately assess risk. This can result in some patients "slipping through the cracks" and not receiving timely intervention.
Solution
Mednition's KATE is a machine learning-based clinical decision support system designed to enhance emergency department triage. KATE analyzes real-time patient data to automatically identify and prioritize high-risk patients, enabling nurses to make more informed decisions at the point of care. The platform seamlessly integrates into existing ED workflows and EMR systems, requiring no changes to current processes. By providing nurses with AI-powered risk intelligence, KATE helps improve patient outcomes, optimize ED performance, and reduce the risk of overlooking critical cases. The system leverages a nurse-first approach, ensuring that the technology supports and augments clinical judgment.
Target Audience
The primary target audience includes emergency department nurses, physicians, and hospital administrators seeking to improve patient outcomes, optimize triage efficiency, and reduce the risk of overlooking critical cases.
Features
- Real-time, AI-powered risk assessment using machine learning algorithms
- Seamless integration with existing EMR systems and ED workflows
- Automated identification and prioritization of high-risk patients at triage
- Clinical Data Engine to turn data into action
- Customizable alerts and notifications for timely intervention
- Support for early sepsis detection with KATE Sepsis module
- Clinical validation and expert-backed algorithms