NCQA Creates Working Group on Natural Language Processing

Feb. 18, 2020
Working group will look at how to validate the accuracy of NLP output as part of an electronic clinical data system

The National Committee for Quality Assurance has created a natural language processing (NLP) working group to help NCQA explore how NLP may be suitable for use in quality measurement, and reporting.

NCQA invited a diverse group of NLP suppliers from across the country to apply for the NLP Working Group and chose Apixio, UPMC and Wave Health Technologies LLC.

 NLP refers to the process by which computer algorithms sift through unstructured, everyday language to translate and organize it into computer-friendly data.

NCQA notes that NLP has the potential to increase the efficiency, accuracy, and integrability of clinical data. That makes it valuable for organizations participating in pay-for-performance care delivery, but NCAQ has concerns that some NLP implementations can yield potentially flawed results. That flawed data could then make its way into pivotal data streams like the ones used for HEDIS reporting.

In its monthly conversations with the working group, NCQA wants to explore ways to avoid flawed data. The working group will look at how to validate the accuracy of an NLP output as part of an electronic clinical data system (ECDS). NCQA expects the working group’s participants to show how their NLP software converts unstructured clinical data into structured data and how they ensure quality for their customers and discuss what their customers expect from NLP solutions. All of this will inform development of a standard for validation of NLP data.

Lessons learned with the working group will be shared in parallel monthly meetings with an independent advisory panel of NLP experts—academicians, researchers and industry thought leaders—who will provide an impartial and independent perspective on the validation model NCQA expects to develop.

NCQA will evaluate its capability to develop a comprehensive approach to validate the integrity of NLP solutions.

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