Claims anomaly benchmark
Find unusual billing patterns before they cost you.
PatternIQ benchmarks medical claims against millions of historical adjudicated claims and surfaces unusual modifiers, places of service, quantities, charges and diagnosis patterns worth reviewing before submission.
Built for billing teams, RCM platforms, EHRs, practice-management systems and clearinghouses. API-first; no LLM in the analysis path.
Is this modifier uncommon for comparable claims?
Do similar claims usually bill from a different POS?
Is this billed quantity typical for the procedure?
Where does the submitted charge sit in the historical range?
Is this procedure / primary-diagnosis pairing uncommon?
Benchmark, not a rule
A claim is compared with the most specific reliable cohort of historically similar claims — same procedure, place of service, insurance category and, where available, primary diagnosis. PatternIQ reports how common the submitted configuration is and how it compares with the typical one.
Evidence, not a verdict
Every flag carries the historical frequency, the comparison count, the historical outcome difference and an evidence level. There is no risk score: a billing professional can see exactly why something stood out and decide what to do.
Patterns, not just claims
When many claims in a batch share the same unusual configuration, PatternIQ groups them and compares the batch frequency with the historical benchmark. That reveals a billing workflow repeatedly producing the same configuration.
What PatternIQ does not do
It does not decide whether a claim is correct, recommend or change a code or modifier, predict denial, estimate recoverable revenue, or infer an allowed amount. It does not use a black-box model, embeddings or an LLM. It surfaces a historical benchmark; a human decides whether anything should change.