Quantifying Emergency Medicine Residency Learning Curves Using Natural Language Processing: Retrospective Cohort Study
NLP analysis of clinical documentation provides a scalable, detailed method for tracking EM residents' clinical exposure and progression. Many residents continue to gain new experiences into their fourth year, particularly in higher-acuity cases. These findings suggest that a 4-year training model may offer meaningful additional educational value, while also highlighting the importance of individualized assessment given the variability in learning trajectories.
Authors
- J. M. Hughes
- Christian Rose (ORCID: https://orcid.org/0000-0002-5115-649X)
- William Dixon (ORCID: https://orcid.org/0000-0002-4944-7132)
- Rana Kabeer (ORCID: https://orcid.org/0000-0002-6780-2740)
- Carl Preiksaitis (ORCID: https://orcid.org/0000-0002-3856-0068)
Institutions
- Stanford University (US)
Publication Details
- Journal
- JMIR Medical Education
- Published
- 2025-11-09
- DOI
- https://doi.org/10.2196/82326
- Citations
- 2
- Primary Topic
- Innovations in Medical Education
- Type
- article
- Field-Weighted Citation Impact
- 3.76