Truss Health provides an AI-powered remote patient safety monitoring platform called Laso for post-surgical care. This system uses data from various devices and sensors to analyze patient health status and detect surgical site infections early. The platform delivers timely alerts to healthcare providers, enabling proactive intervention and improving patient outcomes across orthopedic, OB/GYN, abdominal, and cardiac surgery recovery.
Funding
Funding not disclosed
Founders
Product
Problem
Post-surgical complications, particularly surgical site infections (SSIs), lead to increased patient morbidity, extended hospital stays, and higher medical costs. Current methods for detecting SSIs often rely on in-person evaluations, potentially delaying intervention and worsening patient outcomes.
Solution
Truss Health offers an AI-powered remote patient safety monitoring platform, Laso, designed for the early detection of surgical site infections (SSIs). The platform uses various devices and sensors to collect patient data, which is then securely transmitted for real-time analysis. By applying machine learning and predictive analytics, the platform identifies early signs of infection, enabling healthcare providers to intervene swiftly and personalize treatment plans. This proactive approach aims to reduce hospital readmissions, minimize complications, and improve patient recovery.
Target Audience
The primary target audience includes healthcare providers, hospitals, and surgical teams seeking to enhance patient monitoring beyond the hospital setting and improve post-surgical recovery management.
Features
- AI-driven platform analyzes patient data in real-time for early and accurate detection of SSIs
- Remote patient monitoring through various devices and sensors
- Risk stratification system to identify patients at higher risk of SSIs
- Customizable alert settings based on doctor preferences and patient needs
- Real-time data visualization dashboard for doctors to monitor patient trends
- Integration with Electronic Health Records (EHR) for a comprehensive view of patient data
- Clinical decision support with evidence-based guidelines and recommendations
- Secure data transmission and storage