Ever wish you had a crystal ball to help your organization avoid denials? Good news: Data science can provide that predictive insight. Machine-learning combined with historical data holds the key to helping hospitals preempt denials and identify the patterns and underlying causes of them – so you can avoid denials rather than simply managing them.
To learn more, join ZirMed Product Manager Ryan Feldt for a high-level overview of ZirMed’s powerful predictive-analytics solution that leverages your organization’s historical data to predict and help you avoid denials. In this webinar, Ryan will demonstrate how predictive analytics technology can:
- Identify and flag claims that are likely (>98%) to be denied—and route them to the right staff at the right time, before the claim goes out the door.
- Provide robust exception-based workflows to automatically keep staff focused on the highest-value claims.
- Measure appeal effectiveness and collection rates.
- Identify root-causes and previously hidden denial-related patterns in your data – both the most common and meaningful high-impact outliers.