Bespoke revenue cycle intelligence for your unique needs
Apply machine learning to payer behavior and denial trends to prioritize the right accounts, highlight next best actions, accelerate reimbursement, reduce screen fatigue, and drive performance.
Measured impact, rooted in revenue cycle realities
worklist complexity
cost-to-collect
in 60 days
How it works
We organize backlogged accounts, uncover denial patterns, and surface high-value accounts that must be addressed quickly to be paid, delivered directly into your existing tools.
- Compatible with existing RCM platforms
- No change management required
- Operates in the background or within existing workflows
- Drives faster payment without adding operational burden
RevRadar Account Prioritization
Score and rank accounts by predicted reimbursement and payment speed using machine learning trained on historical payer adjudication behavior.
- Predicts likelihood of denial, expected reimbursement amount, and days to payment
- Generates a dynamic score to prioritize high-yield, low-effort accounts
- Reduces time spent manually sorting or guessing account value
Denial Resolution Insights
Take the guesswork out of denial code interpretation with retrieval-augmented generation (RAG) that surfaces the next best action.
- Outlines claim details to understand why it was rejected
- Provides concise steps to resolve denials efficiently & recover revenue faster
- Pulls forward claims with similar patterns for minimal context switching
- Enables user editing to ensure the claim is handled the way the team needs
Comment Classification
Evaluate user actions with natural language processing to identify worklist bottlenecks, reveal user routing errors, and measure quality of follow-up activity against standards of work.
- Analyzes free-text notes to benchmark actions against expected workflows
- Surfaces routing errors and inconsistencies in user handling of accounts
- Improves oversight and accountability across revenue cycle staff
A/R Acceleration
Reduce your billed A/R and DNFB days by organizing backlogs, grouping similar issues, and surfacing high-risk accounts before they stall payment.
- Identifies and clusters hard-to-find, high-impact accounts
- Reduces aging by streamlining backlog review and sorting
- Supports faster reimbursement without increasing staff workload
Case Study
Quick Wins in Discharged Not Final Billed
4.0
DNFB day reduction in first 60 days
$21M
Cash acceleration in first 60 days
113+
Staff benefiting from improved workflow