Detect FW&A patterns, validate risk adjustment coding, and protect your MIPS performance—whether you're an ACO, medical group, health plan, or even a private practice.
The Challenge
Your members see providers across networks and geographies. Every claim carries compliance risk. Fraudulent DME suppliers bill for equipment patients never received. Providers exceed MUE limits or MIPS expectations. Coding gaps put risk adjustment revenue in jeopardy.
Most organizations discover these problems during an audit. By then, it's too late.
Our Approach
Pamastay normalizes claims data from any source—CCLF files from CMS, EDI 837 feeds, direct extracts—into a unified compliance intelligence layer. Our detection engine surfaces fraud indicators, coding risks, and cost outliers before they impact your performance.
How It Works
Upload CCLF files, connect EDI feeds, or integrate directly. Pamastay normalizes and deduplicates automatically.
Our detection engine applies MUE edits, orphan DME rules, and cost outliers. Claims tagged with severity levels.
Drill into providers, compare against peers, use audit tools. Export for compliance committees and regulators.
Book a demo and we'll show you Pamastay with sample data—or connect your own claims feeds.
Schedule a Demo