Taking the Garbage Out: Addressing AI Bias in Quality Measurement

Use of artificial intelligence (AI) in health care quality measurement can enhance the precision and efficiency of performance assessment. However, the use of AI in measurement also raises concerns about biases that could perpetuate disparities and affect vulnerable individuals. There have been recent national discussions that emphasize the need for ethical, transparent, and equi­table AI applications in health care quality measurement, such as the US Centers for Medicare & Medicaid Services’ (CMS) information session titled “AI in Quality Measurement” and the Biden-Harris Administration’s Executive Order on AI. Addressing bias is crucial to ensuring that AI tools do not exacerbate existing inequalities, but instead contribute to fair quality assessment and high-quality outcomes. This article explores the use of AI in health care quality measurement and tactics to mitigate bias in AI-enhanced measurement.