Smarter risk capture starts here.

CMS’s V28 model and the expanded RADV program have raised the stakes for accurate, timely, and fully supported documentation. Retrospective reviews alone are no longer enough. The future is a combined strategy: retrospective error capture + prospective error prevention.

Our platform brings both together with AI, advanced NLP, and compliance intelligence so you can strengthen RAF scores, reduce audit exposure, and drive better patient outcomes.

Retrospective Risk Adjustment

Retrospective reviews remain critical to capture what gets missed after the fact. But with CMS’s shift to contract-level RADV extrapolation, every missed or unsupported diagnosis carries greater financial impact.

Today’s retrospective essentials:

• AI/NLP powered chart review across structured + unstructured data

• Detection of coding errors, unsupported conditions, and missing documentation

• Targeted reports by member, provider, or condition

• Preparation for retrospective RADV reviews covering PY 2018-2024

Prospective & Concurrent Risk Adjustment

Prospective reviews are now the real safeguard against CMS audits and revenue clawbacks. Capturing conditions at the point of care ensures specificity, compliance, and accurate payment before audits ever occur.

Today’s prospective essentials:

• Pre-visit suspect lists surfaced directly in EHRs

• Real-time documentation prompts based on MEAT (Monitor, Evaluate, Assess, Treat)

• Provider education and CDI (Clinical Documentation Improvement) workflows

• Continuous monitoring of coding specificity (e.g. HFpEF vs HFrEF, CKD staging)

RADV Audit Readiness

CMS has expanded RADV sampling from ~60 plans per year to over 550, with sample sizes up to 200 records and extrapolated contract-level findings. Plans can no longer afford to ignore documentation gaps.

RADV readiness with our platform:

• Audit simulation reports to flag likely disallowed diagnoses

• Centralized repository for record retrieval & compliance review

• Documentation validation tools to confirm provider signature and MEAT criteria

• Configurable dashboards to track “at-risk” conditions and audit trends

RAF Score Analytics

Your RAF score is no longer static—it’s dynamic, influenced by missed conditions, coding accuracy, and CMS’s updated V28 coefficients.

Our RAF score analytics provide:

• Predictive modeling for revenue impacts under V28

• Member/provider-level drill downs to target high-impact gaps

• Trend dashboards comparing retrospective vs prospective capture rates

• Financial projections to plan for audits and revenue shifts

PROSPECTIVE RISK ADJUSTMENT

ENSURE HCC REPORTING ACCURACY

By applying clinical AI with rules-based HCC analytics to claims data, you unlock powerful insights into your Medicare members’ prospective RAF scores—pinpointing chronic conditions that need timely intervention and driving measurable improvements in quality of care.

RADV Audit READINESS

RESOLUTION & CORRECTION

With our advanced, rules-based clinical AI, you can unlock deep insights into your Medicare members’ prospective RAF scores—identifying chronic conditions that need timely attention to improve outcomes and quality of care. At the same time, our analytics help protect your RAF score revenue by audit-proofing your Risk Adjustment Data Validation (RADV) process, ensuring you’re prepared to confidently pass audits when they arrive.

RAF SCORE ANALYTICS

TOTAL FINANCIAL IMPACT

Gain a clear view of financial impact—at both the member and provider level—by quantifying expected risk revenue gains or losses over any defined period.