The Opportunity 

The use of artificial intelligence (AI) has the potential to accelerate progress toward quality measures that are low burden to implement, have high reliability, focus on what matters to patients, and provide real-time feedback that can inform improvement.  

As organizations administering accountability programs begin to incorporate quality measures that use AI methods for accreditation, pay-for-performance, public reporting, value-based payment, and other accountability purposes, there is a need to further consensus on the selection and implementation of these measures. While there are several governance and guidance frameworks for the use of AI in healthcare more broadly, there is a lack of guidance for selecting and implementing AI-enabled quality measures. Without this guidance, users may be uncertain about the accuracy and trustworthiness of measure results. 

Cultivating trust is particularly important for measures intended for use in accountability programs. Providers, patients, and payers must be confident that publicly reported measure scores and measures used in payment decisions fairly and accurately reflect the aspect of quality they are intended to measure.

About the Project 

Funded by the Gordon and Betty Moore Foundation, NQF has convened a national panel, the AI in Quality Measures Technical Expert Panel (AI TEP), representing a variety of critical perspectives to drive insights and forge consensus on guidance consensus on guidance and recommendations for selecting and implementing quality measures that use AI methods. 

The proposed guidance will identify the information and actions needed to support the selection and ongoing implementation of quality measures incorporating AI methods to leverage the benefits of AI while maintaining accuracy and trust. The guidance will interpret broad consensus-based frameworks on the use of AI in healthcare for the use case of quality measurement. 

The AI TEP has held several virtual convenings, beginning in January 2024, and will hold a series of virtual and in-person meetings in 2025. NQF will post the draft guidance for public comment in fall 2025 and plans to publish the final guidance in spring 2026. For questions about the project, please contact AIinqualitymeasures@qualityforum.org.