Building Disruptive Data & Analytics for Quality Improvement

As the healthcare industry moves towards a member-centric healthcare ecosystem, both NCQA and CMS have made some critical regulatory and policy changes which have forced health plans to focus on enhancing the overall member experience and improving interoperability with providers.

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About the Speakers


Jeffrey Springer,
Sr. Vice President,
Healthcare Solutions,


Shitang Patel,
Asst. Vice President,
Health Plans,



In this on-demand webinar our speakers covered key characteristics of high-performing payers and discussed the role of advanced analytics and data science while answering all key questions pertaining to the recent quality program changes affecting health plans.

Key Learnings

  • Factors driving the need for efficiencies with regards to quality operations and traits of successful health plans
  • Role of data & analytics in structuring health plan operations for delivering efficiencies across the quality improvement programs
  • Actionable steps health plans can take to leverage AI, ML and NLP to maximize ROI and streamline quality management initiatives

Health Plans will need to streamline their operations to gain efficiencies, while delivering on quality improvement goals as higher Star ratings continue to be a key motivation. Data science and augmented capabilities such as NLP, RPA, and AI/ML will allow payers to design intelligent automated and optimized workflows with significant savings on wastage.


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