Full Cycle Denials Solution | RevProtect From Sift Healthcare
XSolis Denials Prevention Alternative
Full Cycle Denials Solution
A concurrent-review tool, like Xsolis, works at one moment of the claim’s life. But denials form before it and exist after it, and a point solution can’t see what it doesn’t touch.
RevProtect delivers denials solutions across pre-bill, concurrent, and post-bill and provides payments intelligence across the full cycle. One platform for the whole denial problem — not another tool to bolt on.
Full Cycle Denials Solution - Xsolis Alternative
From Insight to Intervention — Across the Revenue Cycle
RevProtect goes beyond utilization management. It predicts pre-bill and concurrent denials and prescribes role-based actions to prevent denials and adverse payment outcomes.
These recommendations are delivered directly within the workflows teams already use.
AI-Driven Prevention, A Full Cycle Denials Solution
For each at-risk case, RevProtect provides your teams clear guidance and actionable denial prevention recommendations on:
Documentation gaps that materially affect reimbursement
Additional clinical evidence required to support billed services
Tests, labs, or assessments needed
Diagnostic work to establish medical necessity
Details for provider queries
Specific questions to obtain missing or insufficient clinical detail
Supporting materials
Documentation to strengthen claim submissions and appeals
RevProtect ensures claims are supported by the right evidence before submission, reducing the likelihood of adverse payment outcomes. When denials or downgrades do occur, teams already have the documentation needed to win disputes and appeals.
Built for real roles — not generic tasks
RevProtect identifies why reimbursement risk exists and delivers role-specific interventions to prevent denials.
Recommendations are grounded in denial type, DRG context, and payer behavior.
Every recommendation is tied to what each role can influence, reducing noise and increasing follow-through.
Role-specific action, by design
Clinical Documentation Improvement (CDI)
- Surface missing MCC/CC specificity
- Guide targeted provider queries tied to payer expectations
Utilization Review (UR)
- Flag level-of-care risk
- Recommend escalation to physician advisor when warranted
Coding
- Highlight modifier and duplication risk
- Identify coding edits likely to trigger payer review
Patient Financial Services (PFS) / Denials Teams
- Focus effort on high-probability denial overturns
- Surface the exact evidence needed to support appeals
Delivering Actionable Recommendations That Prevent Denials
RevProtect combines multiple AI and analytical layers to move from risk identification to denial prevention action:
- Prediction layer surfaces reimbursement risk and root cause
- Look-alike modeling identifies statistically similar paid and denied cases
- Nearest-neighbor analysis highlights relevant clinical and documentation differences that matter
- Denial and persona playbooks translate risk into role-specific guidance
- System guardrails enforce confidence thresholds and escalation rules
- Plain-language outputs deliver clear actions and rationale via API or embedded workflows
This architecture ensures denial prevention recommendations are role-specific, precise, and defensible.
Smarter Denial Prevention With Every Outcome
As denial prevention actions are taken and outcomes are realized, RevProtect continuously learns and adapts. This learning loop ensures the system improves with use, while maintaining governance and control.
See how RevProtect recommendations are validated and measured
Aligned to Outcomes, Not Promises
RevProtect is available through a performance-based engagement model designed to align incentives and reduce risk. Sift partners directly with health systems to tie success to measured reductions in denials and adverse payment outcomes (not activity, licenses, or usage).
Talk with us about whether a performance-based model makes sense for your organization.
Explore a performance-based engagement
Justin Nicols
Founder & CEO
A leading industry expert in data analytics technology and has an extensive background in corporate finance and investment banking. Prior to founding Sift, Justin served on the executive team of venture backed ad technology company, and an e-commerce technology company.