Skip to main content
EH

Elarin Health

Elarin Health offers an AI platform that predicts patient falls in healthcare settings 24-48 hours in advance. By integrating vital signs, mobility, and environmental data, it generates personalized risk assessments and actionable alerts for proactive intervention.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Falls in healthcare settings lead to significant financial costs, increased medical care, regulatory penalties, and reduced quality of life for residents. Existing fall prevention technologies often rely on reactive measures like video or motion detection, alerting staff only after risk factors are already present. This reactive approach limits the ability to intervene proactively and prevent incidents before they occur.

Solution

Elarin Health provides a predictive AI platform designed to proactively prevent falls in healthcare facilities. The system integrates vital sign data, mobility patterns, and environmental context to create continuously updated, individualized patient profiles. This enables the generation of personalized, explainable risk predictions that forecast potential fall events 24-48 hours in advance. Care teams receive real-time, early alerts and transparent reasoning behind the predictions, allowing for timely, targeted interventions. By shifting from reactive monitoring to proactive prediction, Elarin aims to reduce falls, enhance patient safety, and optimize operational efficiency.

Target Audience

Elarin Health targets healthcare providers, including skilled nursing facilities, assisted living communities, and home-based care settings, that are seeking to improve patient safety and reduce the incidence of falls.

Features

  • **Personalized Predictive Modeling:** Utilizes a deep learning model that analyzes temporal health patterns from integrated vital signs, mobility behavior, and environmental data to generate individualized fall risk predictions.
  • **Explainable AI Interface:** Features a natural language interface that provides transparent, clinically interpretable explanations for risk predictions, supporting clinical decision-making.
  • **Adaptive Learning Engine:** Continuously updates patient profiles every six hours and learns from real-world outcomes and clinician decisions to improve prediction accuracy and reduce bias.
  • **Proactive Risk Forecasting:** Detects risk windows hours or days in advance, enabling anticipatory interventions rather than reactive responses.
  • **Data Integration Capabilities:** Seamlessly integrates multiple data streams, including clinical data and environmental context, for a comprehensive understanding of patient risk.
  • **Workflow Integration:** Designed to integrate with existing clinical workflows and EHR systems for efficient data management and reporting.
  • **Customizable Alerts and Dashboards:** Provides visual, actionable insights tailored to facility needs and patient profiles, with customizable alert thresholds.
This profile is AI-generated and may contain inaccuracies.