RAAPID is a Novel Clinical AI Platform that utilizes proprietary Neuro-Symbolic AI and Natural Language Processing (NLP) to provide a transparent, evidence-backed audit trail for every Hierarchical Condition Category (HCC) code, linking codes directly to MEAT-based documentation in clinical notes. The platform is purpose-built for Health Plans, Health Systems, Providers, and Tech & Service Partners to maximize coding accuracy, enhance clinical decisions, and achieve compliance.
It offers a unified suite for the end-to-end value-based care journey, including:
- Prospective Risk Adjustment: Patient prioritization, pre-visit planning, and gap closure to improve care quality.
- Retrospective Risk Adjustment: Autonomous chart review, HCC identification, and MEAT validation workflow to reduce project timelines from months to days.
- RADV Audit Solution: Runs MEAT evidence-first checks, generates export files, and manages responses with clear audit trails for extrapolation protection.
Key technologies include DocumentAI, Knowledge Graph, Machine Learning, and Deep Learning, which process unstructured clinical notes at scale. RAAPID claims industry-leading performance with 92%+ out-of-the-box accuracy (rising to over 98% with final coder validation), productivity gains of 60-80% for coding teams, and a 10:1 guaranteed ROI. It is a secure, cloud-based SaaS solution with API availability for seamless integration into existing systems.
