Providers and venues, mapped against the portfolio's own severity patterns.BETA
Provider and venue outlier mapping software, in beta, surfaces which providers, venues, and treatment patterns correlate with higher severity or cost across your claim portfolio. Every pattern is benchmarked against your own portfolio, cited back to the underlying claims, and shown only once it clears a minimum sample size.
Severity and cost patterns, mapped by provider and venue.
The map aggregates claim outcomes by provider, venue, and treatment pattern across the portfolio you route through Medrecords AI, then benchmarks each one against the portfolio's own norms, with the sample size shown next to every pattern.
A signal that routes to a human, never a verdict.
Patterns below the minimum sample size aren't shown at all. Patterns that clear it route to your SIU or review queue as a signal, cited back to the specific claims that produced it, for a person to open and investigate.
A pattern signal, never a fraud label.
The map never labels a provider or venue as fraudulent. It surfaces a statistical pattern, cost or severity that sits outside the portfolio's normal range, and nothing more. Correlation shown here is not an accusation.
Every pattern requires a minimum sample size before it's shown, so a single unusual case never triggers a flag. When a pattern clears that bar, it routes to your SIU or review queue as a signal for a human to investigate, never as an automated determination.
From portfolio to signal, in three steps.
Aggregate, benchmark, and route, with a human deciding what happens next.
Claim outcomes are aggregated by provider, venue, and treatment pattern across the book you route through Medrecords AI.
Each pattern is measured against the severity and cost range typical for the portfolio, with the sample size shown alongside it.
Patterns that clear the minimum sample size route to your SIU or review queue as a signal, cited back to the claims behind it.
Built for the teams that manage a claim portfolio.
A portfolio-wide view for the organizations that route large volumes of claims.
Provider & Venue Outlier Map, answered.
It surfaces which providers, venues, and treatment patterns correlate with higher severity or cost across a claim portfolio, benchmarked against the portfolio itself and cited back to the claims behind each pattern.
No. It never labels a provider or venue as fraudulent. It shows a statistical pattern relative to the portfolio; what happens next is entirely a human decision.
It routes to your SIU or review queue as a signal for a person to investigate, cited to the specific claims behind the pattern. It's not an automated determination.
Yes. A pattern has to clear a minimum sample size before it's shown at all, so a single unusual claim never triggers a flag.
Yes, in beta. The Provider & Venue Outlier Map is live and testable now on your own portfolio; we're refining it hands-on with early customers, and if your use case is a good fit we'll work with you directly.
See the outlier map on your own portfolio.
Join the beta and run it against a real book of claims, or book a demo first.