Technology
Heart failure remains a leading cause of mortality, with 20% of patients dying within one year of diagnosis and 50% within five years. Current treatment approaches are often generalized and fail to account for the complex interplay between heart and kidney function in patients, especially those with acute heart failure and kidney injury (cardio-renal syndrome).
This innovative solution leverages causal machine learning and hybrid models integrating continuous physiological signals and electronic medical records (EMR). It offers personalized therapy recommendations, enabling precise management of acute decompensated heart failure (ADHF) patients. Future applications include home-based decision support tools to improve chronic heart failure management and reduce hospital readmissions.
Advantages
- Personalized Treatment: Provides tailored therapeutic recommendations for patients with heart failure and kidney injury.
- Data-Driven Decisions: Integrates physiological signals and EMR for comprehensive clinical insights.
- Outcome Improvement: Aims to reduce length of hospital stays (LOS), hospital readmissions, and associated penalties.
- Remote Management Capability: Expands treatment to at-home settings for chronic care.
- Cost Efficiency: Supports reimbursement pathways, including CPT codes 99443 and 99454.
Applications and Opportunities
- Hospital-Based Acute Management: Decision support for in-hospital treatment of ADHF patients to optimize therapy and reduce complications.
- Remote Chronic Care: Home-based systems for managing chronic heart failure, enhancing patient outcomes and reducing hospital readmission rates.
Business Development Contacts