Data Mining Tailwinds and Headwinds

Greg Dorn, President & Mark Johnson, SVP Product Management

March 05, 2024


Examining Key Drivers for Advancing Data Mining Efficacy and Addressing Obstacles for Enhanced Outcomes.


Historically, data mining efforts were largely manual and reactive. The evolution of data mining powered by technological advancements has continued to transform over the last decade into proactive, efficient, and automated processes. The integration of big data analytics, AI, machine learning, and advanced statistical methods have brought greater precision, speed and success to data mining efforts.  Modern data mining can manage complex algorithms capable of identifying past inaccuracies and predicting potential future issues.

This article provides an overview of headwinds and tailwinds related to data mining as it continues to evolve. It emphasizes the need for continuous innovation and adaptability in this transformative data mining era.

The 3 tailwinds we see accelerating success in payment integrity include:

  1. Rapid AI / Machine Learning Advancements
  2. Increased Digitization and Data Availability
  3. Shifting Focus to Prevention

The 3 headwinds we see that need governance and planning to optimize success include:

  1. Data Management
  2. Regulatory Challenges
  3. Growing Healthcare Claim Complexity

Additionally, in this article we share CERIS data mining findings to illustrate the types of patterns we have recently uncovered.  Our focus is to deliver information that drives enhanced payment integrity success in the market.

Let's partner to a clear path to greater accuracy and cost savings.

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