The startup develops an artificial intelligence platform that utilizes risk modeling methodologies to analyze health data and generate accurate healthcare predictions. This enables health systems, physician groups, and life sciences companies to create targeted treatments and deliver appropriate services to specific populations.
Funding
$61.5M 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.
Founders
Product
Problem
Healthcare systems and organizations often struggle to efficiently manage patient populations due to the complexity of health data and the difficulty in identifying high-risk individuals. Clinicians face challenges in synthesizing patient information and predicting potential adverse events, leading to reactive rather than proactive care. This can result in increased costs, strain on resources, and suboptimal patient outcomes.
Solution
HDAI's HealthVision platform is an intelligent health management solution that leverages AI/ML and generative AI technologies to transform healthcare data into actionable insights. The platform integrates with existing EHR systems and normalizes structured and unstructured data to create personalized care profiles and predictive analytics. By using digital twins and AI-optimized workflows, HealthVision enables healthcare providers to proactively identify high-risk patients, optimize resource allocation, and improve patient outcomes. The platform's responsible AI approach ensures transparency and explainability, allowing clinicians to drill down to the source documents used for AI-generated summaries and predictions.
Target Audience
The primary target audience includes hospitals, health systems, ACOs, independent physician groups, and Medicare Advantage or commercial payers seeking to improve patient outcomes, reduce costs, and optimize resource allocation through AI-driven insights.
Features
- AI-powered predictive models for identifying high-risk patients and predicting adverse events
- Generative AI tools for querying, reading, and summarizing patient charts
- Integration with EHR systems to normalize structured and unstructured data
- Digital twins for comparing performance against clinically-matched control groups
- AI-optimized workflows for care coordination and resource allocation
- Personalized patient-level risk profiles with quantified probabilities and risk drivers
- Population-level views of provider and network performance
- Configurable reports developed by data scientists, analysts, and clinicians
- HIPAA, SOC2, and HITRUST certifications