Qatalyst Health's ROSA platform uses AI to automate revenue cycle management for long-term care facilities. It streamlines admissions by triaging referrals and ensures accurate reimbursement by automatically populating forms with data from patient charts and progress notes.
Funding
Funding not disclosed
Founders
Product
Problem
Long-term care facilities face challenges in optimizing patient census and ensuring accurate reimbursement for all provided services. Manual review of referrals and fragmented data across systems leads to missed billable opportunities and administrative inefficiencies.
Solution
Qatalyst Health's ROSA platform is an AI-driven solution designed to enhance revenue cycle management for long-term care facilities. It automates the triaging of hospital referrals, prioritizing candidates based on clinical and financial indicators to streamline the admissions process. ROSA integrates with existing EHR systems to automatically populate reimbursement forms by analyzing patient charts, progress notes, and discharge summaries, ensuring all billable services are captured. The platform also provides intelligent notifications for changes in patient care, triggering instant updates to reimbursement forms. This comprehensive approach aims to maximize captured revenue and reduce administrative overhead for reimbursement teams.
Target Audience
The primary customers are long-term care facilities seeking to optimize their admissions process and maximize revenue capture through improved reimbursement accuracy and efficiency.
Features
- AI-powered referral triaging and ranking based on medication costs, behavioral risk, and other clinical factors.
- Automated scrubbing of EHR data (discharge summaries, care charts, progress notes) for reimbursement form population.
- Intelligent notifications for patient care updates, triggering automatic reimbursement form adjustments.
- Centralized repository for Medicaid and Medicare reimbursement forms with an audit log for every item.
- Medication analysis to identify billable services and flag discrepancies with diagnoses.
- Dictation functionality for progress notes with high accuracy and reference to historical documentation.
- EHR integration for seamless data flow and automated form completion.
- AI model accuracy rate of 99.3% for identifying diagnoses, billable services, behavioral markers, and medications.