Our Solution: RevBlox™


Revblox analyzes historical claim and payment data and applies proprietary machine learning algorithms to identify patterns of claims denials, as well as their causes. In addition to machine learning, rules-based edits, such as incorrect or missing codes and Medically Unlikely Edits (MUEs) or payer-specific edits, are also incorporated. Once the causes have been identified, providers can use this information to remediate issues at the source.