NQF report provides guidance on quality measures using AI methods

The National Quality Forum released a report offering guidance on the responsible development, selection, implementation and monitoring of quality measures that use artificial intelligence methods for use in accreditation, pay-for-performance, public reporting, value-based payment and other accountability purposes. Developed by a national, multi-stakeholder technical expert panel, the consensus-based report says achieving trust in AI-enabled quality measures is dependent upon transparency, rigorous testing, clear performance standards, attention to equity, feasible implementation, ongoing monitoring and shared responsibility across all major participants using accountability measures. It recommends six strategies to advance trustworthy AI-enabled quality measures and provides an actionable roadmap for measure developers, program leaders, measured entities and measure implementation vendors to collaborate to achieve the promise of AI while maintaining trust in measurement and accountability.