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Don't waste your time working claims that won't be paid.
Sift's used machine learning to identify your most valuable claim denials, prioritizing denials around their likelihood of being paid. Sift's recommendations are integrated into your current revenue cycle workflows, making it easy to work smarter. Sift’s ROI-based work order lists reduce days payable outstanding, increase payments, reduce your cost to collect and accelerate cash flow.
Stop chasing dollars and focus on the denials that will get paid. Sift’s predictive models score denials based on their likelihood of being overturned and paid. Sift's rank-ordered work lists are based on ROI potential and are integrated directly into your current revenue cycle workflow. Sift AI-based denials tools help you apply your resources to the most promising denials, better track outcomes and accelerate your cash flow.
Sift provides ongoing payer-specific claim edit recommendations as payers continually change their rules. Using historical payments data and model-based monitoring, Sift identifies claim billing patterns that require payer-specific claim edits to avoid future denials.
By recommending edits based on historical denials and payments Sift helps you prevent claims edit leakage and prevent future denials.
Sift enhances your current denials management systems. Contact us today to learn more our data science applications for the revenue cycle.