Maximize the PY2020 Submission Deadline Extension & Improve RAF Accuracy

With CMS’ extension of the PY2020 submission deadline, now is the time to capitalize on this extension and perform an end-to-end encounter data quality assessment to improve risk score accuracy. 

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60%-85% OF DATA QUALITY ISSUES EXIST PRIOR TO SUBMISSION

Pareto’s Revenue Integrity suite of solutions assesses the complete end-to-end encounter data process to pinpoint the data quality issues impacting your revenue and compliance. Our solution works by applying advanced analytic models and root cause clustering algorithms to identify where data quality issues occur and prioritize remediation based on materiality.

Achieving financial success in any risk adjusted market also requires complete and compliant risk documentation. Our solution applies market-specific suspecting algorithms to identify undocumented risk gaps for remediation through both prospective and retrospective campaigns.

ENSURE ACCURATE & COMPLIANT RISK SCORES
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OUR EXPERIENCE ACROSS ALL MARKETS

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Complexities of the Encounter Data Process

From encounter to regulatory submission, the flow of health data through various systems and organizations creates many potential areas of data degradation, resulting in data quality issues that negatively impact revenue. These issues can lead to as much as 1%-3% of premium lost due to unreported risk, requiring a holistic approach to data integrity evaluation.

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Pareto Data Integrity Assessment & Performance Evaluation

Our data quality assessment is designed to recover lost data, improve processes by reducing errors, and identify instances of incorrectly captured and submitted encounter information that pose a compliance risk to help you achieve complete and accurate encounter submissions and improve risk score accuracy.

As part of this one-time assessment, your plan will receive:

  • Encounter-Level Data Evaluation to identify and prioritize where data quality issues exist. 
  • Root Cause Investigation through defined root causes to help prioritize improvement efforts for 2021 and beyond.
  • Financial Exposure Quantification to determine the value of data discrepancies and focus remediation.  
  • Compliance Evaluation by identifying potential under- and over-reported  encounter submissions. 
  • Independent Risk Score Calculation for each dataset evaluated.
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Ken Mikesh

Ken Mikesh

ph. 773.354.1087

kmikesh@paretointel.com

Contact us to request a Data Quality Assessment and Performance Evaluation