Abstract: PUB237
Exploring the Educational Implications of Declining Nephrology Fellowship Interest: A Comparative Analysis of Internal Medicine Specialties Using GPT-4
Session Information
Category: Educational Research
- 1000 Educational Research
Authors
- Garcia Valencia, Oscar Alejandro, Mayo Clinic Minnesota, Rochester, Minnesota, United States
- Thongprayoon, Charat, Mayo Clinic Minnesota, Rochester, Minnesota, United States
- Craici, Iasmina, Mayo Clinic Minnesota, Rochester, Minnesota, United States
- Cheungpasitporn, Wisit, Mayo Clinic Minnesota, Rochester, Minnesota, United States
- Miao, Jing, Mayo Clinic Minnesota, Rochester, Minnesota, United States
Background
The 2024 US fellowship match shows a concerning decline in interest in Nephrology with an 11% drop in candidates and only 66% of positions filled. We used Chat GPT to discern the factors affecting this trend and devise educational strategies to attract more trainees.
Methods
Using GPT-4, we compared Nephrology to 13 Internal Medicine specialties based on factors such as intellectual complexity, work-life balance, procedures, research, patient interactions, career demand, and remuneration. The model assigned scores (1-10) based on how well each specialty performed. The cumulative score determined ranking. To mitigate bias, we instructed GPT-4 to prioritize other specialties over Nephrology in hypothetical reverse scenarios.
Results
In GPT-4's evaluations Nephrology ranked only above Sleep Medicine. It lagged in crucial aspects such as a healthy work-life balance, strong patient relationships, and meeting career demands. While the match fill rate was 66%, slightly higher than Geriatric Medicine's 45%, there was a decline ranging from 4% to 14% across five critical criteria, encompassing intellectual challenge, procedural engagement, career prospects, research and academic opportunities, and financial compensation.
Conclusion
Nephrology's attractiveness is declining compared to other Internal Medicine specialties. This trend is concerning and calls for a reassessment of the factors influencing specialty choices among medical residents. The insights provided by AI can be used to redesign nephrology training programs, curriculum, and mentorship initiatives and apply them to improve medical education and career guidance. Further educational research and interventions are needed to comprehensively reassess nephrology education and training, and specific areas for future research and educational initiatives should be proposed to address the declining interest in the specialty.