Achieved a 50% Reduction in Time & Costs by Using Machine Learning to Pay the Right Provider

This national healthcare payer manages a data warehouse consisting of 50 million claims - and growing. Like many other payers, the client was challenged to correctly pay claims due to missing provider data. In theory, providers should be identified by their unique National Provider ID (NPI) but in reality, missing NPIs commonly challenge a payer’s claims adjudication processes and its ability to pay the right providers.

Read the case study to learn how xScion developed a solution that leveraged Advanced Data Science tools and techniques, including Machine Learning and Predictive Analysis, to reduce the need for manual review and enable the client to spend time on high value activities such as claims audits.

Results include:

  • Resolved missing provider data for 1% of daily claims batch (~50,000 daily).
  • Reduced time and cost to remediate missing IDs by 50%.
  • Achieved 98% accuracy in auto resolving missing IDs.
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