Enhancing Access to Orthopedic Education: Exploring the Potential of Generative Artificial Intelligence (AI) in Improving Health Literacy on Rotator Cuff Injuries
Generative AI is capable of rewriting PEMs about RCI at a reading comprehension level that conforms to the CDC and NIH guidelines, and hospital administrators and orthopedic surgeons should consider the findings of this study, and the potential utility of AI when crafting PEMs of their own.
Abstract
Introduction: Health literacy plays a vital role in determining one's health status, as studies have shown that poor health literacy is associated with negative health results. The Centers for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) advise that patient educational materials (PEMs) should be written at an eighth-grade reading level or lower, matching the average reading level of adult Americans. This study evaluated the ability of generative artificial intelligence (AI) to rewrite PEMs about rotator cuff injuries (RCIs) to align with the eighth-grade reading level recommendation of the CDC and NIH. Methods: Online PEMs about RCI from the 25 highest ranked orthopedic hospitals from the 2022 U.S. News and World Report Best Hospitals Specialty Ranking were collected. Chat Generative Pretrained Transformer Plus, version 4.0 (OpenAI, San Francisco, CA) was then instructed to rewrite the PEMs to adhere to CDC and NIH-recommended guidelines. Readability scores were calculated for the original and rewritten PEMs, and paired t-tests were used to determine statistical significance. Results: Analysis of the original and rewritten PEMs about RCI demonstrated significant reductions in reading-grade level and word count of 4.33 ± 1.50 (p < 0.001) and 442.68 ± 351.45 (p < 0.001), respectively. Discussion: Our study determined that generative AI is capable of rewriting PEMs about RCI at a reading comprehension level that conforms to the CDC and NIH guidelines. Hospital administrators and orthopedic surgeons should consider the findings of this study, and the potential utility of AI when crafting PEMs of their own.