A Regional Healthcare Payor with High Denial Rates Leverages Deep Learning-Driven Claims Submission to Reduce CSAT Loss and Streamlining Account Payable Cycles​

Challenges

  • The average denials rate was up 23% in the previous 3 years. Up to 65% of rejected claims were never resubmitted​
  • 20% claims either had missing mandatory information for payment or incorrect medical coding​
  • Claim Submissions overloaded with irrelevant attachments and dynamic complex layouts of document structure that resulted in SLA non-compliance​

Solution

Intelligent

Data Engineering to pre-process each case for intelligent document indexing, classification and OCR conversion​

Deep Learning​

Models to intelligently extract and interpret data from complex and varied layout documents​

3-way

among claims form, supporting documents and system records, to verify the submissions for duplicity, fraud and payment leakage​

Impact

20%

Denial Rate Reduction​

50%

Reduction in Average Claims Processing

50%

Efficacy gain with intelligent document processing

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