Disabilities and Generative Artificial Intelligence Education in Rheumatology Fellowship: Educational Module and...

Area of Science:

• Medical Education
• Rheumatology
• Artificial Intelligence

Background:

• Rheumatic and musculoskeletal diseases (RMDs) can lead to disabilities impacting work and school participation.
• Generative artificial intelligence (genAI) offers potential to streamline documentation for disability advocacy.
• Training fellows-in-training (FITs) in genAI and disability advocacy is crucial for effective patient support.

Purpose of the Study:

• To assess the impact of an online module and simulation on FITs' confidence and skills in using genAI for accommodation letters.
• To identify areas for further instruction in genAI application for disability advocacy.

Main Methods:

• FITs completed an online module and simulation focused on engineering genAI prompts for accommodation letters.
• Skills were evaluated using a rubric, and confidence was measured via pre-post Likert scales.
• Statistical analysis using Wilcoxon signed-rank tests compared pre- and post-training confidence levels.

Main Results:

• Eighty-three percent of FITs scored proficiently on average, with prompt engineering being the strongest skill (95.45%).
• The lowest scoring area was differentiating provider roles (74.55%).
• FITs reported significant confidence improvements across all objectives, particularly in prompt engineering and finalizing genAI-drafted letters (p<0.0001).

Conclusions:

• Educational interventions effectively teach FITs to integrate genAI into writing accommodation letters.
• This training enhances FITs' ability to address disparities for patients with RMD-related disabilities.
• Developing these skills prepares FITs for confident practice in rheumatology, integrating genAI in clinical care for people with disabilities.