Theme

Innovation, AI and the Future of Quality

Full Session Description

Advances in artificial intelligence (AI) and natural language processing (NLP) are happening at a startling rate, with new capabilities reported nearly every week. As the hybrid methodology becomes de-emphasized and eventually retired, AI and NLP will provide important tools for ensuring that we are correctly recording compliance across populations, and to enable quality improvement initiatives.

In the future, AI and NLP may help us create and use new measures that are not currently possible with only claims and structured electronic health record data. Our two payer organizations, Capital District Provider Health Plan (CDPHP) and the University of Pittsburgh Medical Center (UPMC) Health Plan, are among the most experienced in applying these technologies broadly to quality measurement and quality improvement.

This presentation will provide a summary of a range of initiatives and use cases at our health plans. They include (1) moving to year-round HEDIS medical record review, (2) implementing programs for measure surveillance (e.g. Osteoporosis Measurement in Women) and quality improvement, (3) addressing challenging areas such as member complaints and member experience and (4) delivering information directly to the point of care. Some initiatives are overlapping among both organizations while others are specific to one organization.

Each health plan presenter will share their organization’s journey from inception to program deployment, the goals of each program, recent results (efficiency, impact on rates) as well as visions for how they hope to use this technology in the future. Throughout the presentation, we will focus on real world obstacles and how to overcome them, including: aggregating the right kind of data from providers, developing leadership buy-in, creating programs that are acceptable within the current regulatory and auditing landscape, and preparing our teams for the workforce changes that these technologies inevitably produce.

Promotional Description

The rapid evolution of artificial intelligence (AI) and natural language processing (NLP) is transforming healthcare at an unprecedented pace. As hybrid HEDIS® methodologies are phased out, AI and NLP offer powerful tools to improve compliance tracking, quality measurement and the development of new measures that go beyond traditional claims and structured EHR data.

This session features real-world insights from two leading health plans—Capital District Provider Health Plan (CDPHP) and UPMC Health Plan—who are at the forefront of applying AI and NLP to quality improvement and measurement. Together, they’ll share their experiences deploying innovative programs, including:

• Moving to year-round HEDIS® medical record review
• Implementing measure surveillance and quality improvement initiatives (e.g., Osteoporosis Measurement in Women)
• Addressing member complaints and experience challenges
• Delivering real-time information directly to the point of care

Healthcare leaders, data and analytics teams, quality improvement professionals and anyone interested in the practical application of AI and NLP in HEDIS® operations and quality management are encouraged to attend this session to hear each health plan discuss their journey from concept to rollout. 

Learning Objectives

1. Enumerate the broad range of uses of natural language processing (NLP) inquality measurement and quality improvement.​

2. Identify common challenges to use of these technologies in qualitymeasurement and improvement, as well as how to overcome them.​

3. Summarize approaches to developing and sustaining digital quality programswithin a payer organization.​

Key Takeaways

1. NLP unlocks essential insights from unstructured clinical data, enabling more accurate, scalable Prospective HEDIS® reviews.
2. Year‑round HEDIS improves performance, allowing health plans to close gaps earlier and enhance quality outcomes through timely interventions.
3. Real‑world results show measurable impact, including higher accuracy, improved efficiency, and significant gains in HEDIS compliance across multiple health plans.

Speaker Organizations