Automated auditing of emergency department documentation using large language models

This study investigates the effectiveness of four large language models (LLMs) in automating the auditing of emergency department (ED) documentation to reduce errors that can harm patients and increase medicolegal risks. The results indicate that these LLMs achieved high accuracy and precision in detecting documentation errors, suggesting their potential as quality assurance tools in emergency care. The authors advocate for further research on integrating these models into clinical workflows.