Stellation Care provides health insurers and risk‑bearing organizations with AI‑augmented analytics on the full Medicare and Medicaid claims universe, delivering provider performance scores that adjust for patient complexity and phenotype. The platform lets users benchmark providers, visualize referral flows and utilization patterns, and automate network‑building and engagement campaigns to optimize provider networks and improve outcomes.
Funding
Funding not disclosed
Founders
Product
Problem
Health plans and risk‑bearing organizations often lack granular, outcome‑based insights into individual provider performance across Medicare and Medicaid populations, making it difficult to design efficient networks, manage utilization, and engage providers effectively.
Solution
Stellation Care aggregates the complete nationwide Medicare and Medicaid claims dataset and applies AI‑augmented analytics that control for patient complexity. The platform generates provider performance scores and detailed outcome data for specific patient phenotypes, procedures, and conditions. Users can benchmark providers against peers, identify high‑performing specialists and primary care physicians, and visualize referral flows, utilization patterns, and quality outcomes through heat maps and network diagrams. Built‑in workflow automation enables the creation of provider scorecards, evidence‑based recommendations, and targeted engagement campaigns without altering existing network contracts. This data‑driven approach helps organizations build or optimize networks, improve care coordination, and achieve cost savings while maintaining or enhancing patient outcomes.
Target Audience
Primary customers are health insurers, accountable care organizations, and other risk‑bearing entities that manage provider networks and seek data‑driven strategies for cost reduction and outcome improvement.
Features
- AI‑enhanced analytics on the full Medicare and Medicaid claims universe, adjusting for patient complexity and phenotype
- Provider performance scorecards with raw outcome metrics and comparative benchmarks across specialties and conditions
- Interactive visualizations (heat maps, journey charts, network diagrams) showing referral volumes, patient flows, and care coordination patterns
- Automation tools for network building, provider tiering, and engagement campaign execution
- Statistical outlier detection that surfaces performance variations and underlying data drivers
- Integration of quality, utilization, and population health measures to support both network optimization and member intervention strategies