Using Natural Language Processing to Advance your Quality Measurement and Quality Improvement programs

Description

Moving to prospective, measurement-year HEDIS is an important strategy to better managing members and achieving higher quality rates and associated incentive payments. Provider-sponsored health plans are uniquely positioned to excel at this strategy because of better access to clinical data for their members. However, data alone is not sufficient to move the needle for plans moving to prospective, measurement-year HEDIS. Scaling to populations is difficult because of the substantial labor costs of medical record review (MRR). Health plans are turning to natural language processing (NLP) to minimize the additional work of reviewing entire populations. NLP is already used extensively in Risk Adjustment and is gaining momentum for Quality MRR. NLP is also a technology that is rapidly evolving and improving, with new applications and approaches that are transforming multiple industries (think chatGPT). In this program, Dr. Rebecca Jacobson, President of Astrata will explain natural language processing, how it is being used at Health Plans to improve quality measurement and quality improvement, and how it aligns with the transformation to digital quality measurement.

Topics

Attendees will gain valuable insights into:

• The use of NLP in health plan quality operations

• How to move to prospective, measurement-year HEDIS as part of the digital quality transformation

• How to assess the quality of technologies that uses NLP.

Intended Audience

Chief Quality Officer | Chief Medical Officer | Quality Improvement Director | Quality Measurement Director | Medicare, Medicaid, Value-Based Care Leaders