Medical.watch
Medical.watch provides a cloud‑based platform that consolidates real‑time vital sign data from wearables and bedside sensors into a single dashboard, applying customizable alerts and AI‑driven anomaly detection to flag critical changes. The system includes HIPAA‑compliant messaging, task assignment, and API integration with EMR/EHRs, enabling hospitals, clinics, and home health agencies to monitor patients remotely and coordinate rapid interventions.
- Artificial Intelligence
- Digital Health
- Healthcare Technology
- Internet of Things
Funding
Founders
Founder details are not available yet.
Product
Problem
Healthcare providers lack a centralized, real-time monitoring system for patient vital signs and clinical alerts, leading to delayed interventions and inefficient care coordination.
Solution
Medical.watch offers a cloud-based platform that aggregates continuous patient monitoring data from wearable devices and bedside sensors into a unified dashboard. The system applies configurable alert thresholds and AI-driven anomaly detection to notify clinicians of critical changes instantly. Integrated communication tools enable secure messaging and task assignment among care teams, while compliance‑focused data logging supports regulatory reporting. The platform is accessible via web and mobile applications, allowing providers to monitor patients remotely and prioritize interventions based on real‑time risk assessments.
Target Audience
Primary users are hospitals, outpatient clinics, and home health agencies that require continuous patient monitoring and rapid clinical response capabilities.
Features
- Real-time aggregation of vitals from multiple medical-grade wearables and IoT sensors
- Customizable alert rules with AI-powered predictive analytics for early deterioration detection
- Secure, HIPAA‑compliant messaging and task management for care team coordination
- Web and mobile dashboards with patient‑specific trend visualizations and drill‑down details
- API integrations for EMR/EHR systems to streamline data flow and documentation