How AI/ML is Driving Transparency in Healthcare Quality Improvement Programs

Date: Dec 7, 2020 | Time: 11:00 AM - 12:00 PM ET

In an effort to create a member-centric healthcare ecosystem, CMS and NCQA’s announcement of multiple policy changes has made health plans reorganize their daily operational focus areas including quality measures, timelines, interoperability, digitized quality, network fulfillment, and MLR compliance, among others.

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Our Speakers


Jeffrey Springer,
Sr. Vice President,
Healthcare Solutions,


Shitang Patel,
Asst. Vice President,
Health Plans,


Suman Giri
Data Science



Our webinar will showcase examples and case snippets on how to bridge transparency across the value chain while demonstrating disruptive technology adoptions to orchestrate an outcome and experience driven quality improvement approach

Key Learnings

  • Identify factors driving the need for transparency with respect to quality operations and traits of successful health plans
  • Understand the role of Data Science and analytics in structuring health plan operations, with the aim of driving transparency across the quality enterprise – e.g., chart retrieval, Star rating improvement, provider network management, etc.
  • Derive actionable steps to leverage AI/ML and NLP to embed transparency across data, analytics, workflow, and engagement, to streamline quality management initiatives

Payers need to further modernize their quality improvement initiatives by using approaches that showcase strong analytics capabilities which will pave the way in building a delightful and transparent member experience.