CHICAGO, Sept. 18, 2018 /PRNewswire/ -- Pareto Intelligence, a leading analytics solution provider for healthcare organizations, today announced successful outcomes for its Data Integrity solution for 2017. This proven solution analyzed the encounter data completeness and accuracy of over 4 million lives across all government markets (Medicare Advantage [MA], Medicaid, Affordable Care Act [ACA]) last year, including over 12% of the MA population. From this evaluation, Pareto identified several data quality issues with a total financial impact of over $150 million. With 2018 regulatory submissions for encounter data well underway in all regulated markets, health insurers should begin evaluating their end-to-end data processes now to ensure they are not experiencing issues suppressing revenues or presenting compliance risks.

"All issuers know if what they've submitted is accepted or not by the government, but many are unable to say with confidence whether or not they submitted everything completely and accurately," said Brandon Solomon, Vice President of Client Advisory and Business Development with Pareto Intelligence. "Our Data Integrity solution continues to uncover new issues throughout the end-to-end encounter process that are posing financial and compliance risk to issuers. After a very successful 2017, we have one of the most effective solutions in the market."

Pareto's Data Integrity solution works by obtaining data extracts from each point of data process from encounter through to regulatory submission. Advanced analytics are then applied to pinpoint specific areas of data degradation. Once discrepancies have been identified, Pareto's clustering algorithms determine the root cause of data quality issues, enabling focused remediation and resolution at the source. This process is built to achieve complete and accurate outcomes by improving processes and proactively identifying instances of incorrectly captured and submitted encounter information, resulting in lost revenue and/or compliance issues.

This solution enables health plans in all markets to close gaps in reported risk, ensuring that final risk scores match the acuity of the population managed.

Plus, Pareto's experience has shown that even small data quality issues can have a material financial impact. Typically, a 1-3% data quality issue translates into $5-$15 million in premium shortfall for a 50,000-member health plan. With an average of 65-80% of data quality issues occurring prior to submission, an end-to-end assessment ensures that all information received (e.g., billing 837s, supplemental records from chart reviews, etc.) is making it through to submission and acceptance without any degradation.

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