Case study: Data mining for errors yields more accurate pharmacy payments

With the U.S. healthcare system spending more than $600 billion on prescription drugs annually, it’s critical for health plans to ensure proper payment for claims for pharmacy services and medications covered under the plan’s medical benefit.

But this can be challenging for payers. Identifying and recovering billing and payment errors in medical pharmacy takes time and administrative resources. Read our new case study to see how Cotiviti’s Data Mining pharmacy solution uncovered millions in inaccurate payments for two health plans using predictive analytics and specialist validation.

In this case study, you’ll learn:

  • How Cotiviti’s diversified team of experts monitor industry changes to build a unique content library
  • How a large Blue Plan identified >$10M in potential savings with data mining
  • How a community health plan identified a large overpayment trend in unclassified drugs

Read the case study

Tailor the data mining process to your needs through collaboration with auditing experts to identify and validate overpaid claims. Discover the value of data mining in payment integrity to help ensure thorough medical pharmacy claim review and increase payment accuracy for your organization.

To learn more about Cotiviti’s Payment Accuracy and data mining solutions, set up a conversation with our team. For a deep dive into how health plans can improve pharmacy payment integrity, watch our on-demand webinar,  Beyond prior authorization: Ensuring accuracy of specialty drug claims.


Matthew Herbein
As director of audit operations, Matthew is responsible for managing and overseeing all pharmaceutical audit activities including overpayment recoveries, contract commitments, and customer satisfaction measure scores. With almost a decade in the healthcare services industry, he applies his information technology and data science expertise to improve the payment integrity space. Matthew's strategic leadership yields significant financial recoveries, enhances operational efficiency, and nurtures client engagement.

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Case study: Data mining for errors yields more accurate pharmacy payments

Matthew Herbein

Nov 16, 2023

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