We are grateful for Artsi et al’s thoughtful letter highlighting crucial challenges and considerations in using large language models (LLMs) to simplify radiology reports and enhance patient understanding.

Our national radiologist shortage in the United States is a health care crisis that affects all radiology groups, from private practice to academia, and from urban to rural settings. Imaging demands have skyrocketed due to our aging population with increased medical complexity. However, the number of radiology residency training positions has not kept up with the growing demand. As of March 2024, the ACR Career Center lists more than 1,700 radiology jobs for 1,150 radiology residency graduates [1].

Many practices face staffing challenges stemming from expanding clinical volumes and recruitment difficulties. This study aims to evaluate the use of supplemental surge staffing along with scheduled shift redistribution as a bridge to needed staffing increases.