Sift MD leverages artificial intelligence and predictive analytics to reduce insurance claim denials.
By applying machine learning to claims edits, Sift MD goes beyond data scrubbing and rules engines. Sift MD analyzes claims, proposes adjustments and learns from denials.
Based on more than 100 attributes, including procedure codes, provider information and payer information; our preditive algorithms holistically examine denials and rank recommended workflow activity based on the ROI potential of the individual claim.
The Sift MD claims denial toolkit learns from denials, employing AI and machine learning to accelerate collections and reduces human capital intervention.
Improved denial rates accelerate payments, reduces bad debt write-off and reduces human capital intervention — all improvements to your bottom line.
No system can erase denials completely, but Sift MD helps your teams work smarter on denials that need to be addressed. Sift MD’s denial analytics rank denials in estimated ROI so your teams touch the most valuable accounts first.
Sift MD continously learns and improves based on claims edits. Denied claims become powerful as they're used to dynamically optimize processes to decrease future denails.
Learn how Sift MD can improve your analytics, denials management on insurance claims and patient scoring.Schedule Demo