Medical Students' Perception of Automated Note Feedback After Simulated Encounters.

ABSTRACT:

Background

Grading medical student patient notes (PNs) is resource-intensive. Natural language processing (NLP) offers a promising solution to automatically grade PNs. We deployed an automated grading system that uses NLP and explored the perceived value of PN feedback.

Approach

The automated system graded written notes after two standardized patient encounters by third-year medical students. The system generated an individualized report on 'items found' and 'items not found' in the history, physical examination, and diagnosis sections, which was shared with students for feedback via a web-based interface. By rotation, block students received either the automated case feedback first or the faculty-written model note feedback first (the pre-intervention baseline).

Evaluati

SUBMITTER: Bansal SK 

PROVIDER: S-EPMC12624243 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature