Jamal, Aleena

The increasing use of digital applications in healthcare has led to a greater need for patient education materials. These materials, often in the form of pamphlets, booklets, and handouts, are designed to supplement physician–patient communication and aim to improve patient outcomes. However, the effectiveness of these materials can be hindered by variations in patient health literacy. Readability, a measure of text comprehension, is a key factor influencing how well patients understand these educational materials. While there has been growing interest in readability assessment in medicine, many studies have demonstrated that digital texts do not frequently meet the recommended sixth-to-eighth grade reading level. The purpose of this opinion article is to review readability from the perspective of studies in pediatric medicine, internal medicine, preventative medicine, and surgery. This article aims to communicate that while readability is important, it tends to not fully capture the complexity of health literacy or effective patient communication. Moreover, a promising avenue to improve readability may be in generative artificial intelligence, as there are currently limited tools with similar effectiveness.

Introduction: Therapeutic nutrition plays an imperative role during a patient’s hospital course. There is a tremendous body of literature that emphasizes the systematic delivery of information regarding hospital nutrition diets. A major component of delivering healthcare information is the principle of providing quality healthcare information, but this has not yet been investigated on hospital nutrition diets. This study aimed to evaluate the comprehension and readability of patient education materials regarding therapeutic hospital diets. Methodology: The methodology employed the use of publicly available questions regarding hospital nutrition diets and categorized them per Rothwell’s Classification of Questions. Additionally, the questions were extracted online and have an associated digital article linked to the question. These articles underwent analysis for readability scores. Results: This study’s findings reveal that most hospital diets do not meet the recommended grade-reading levels. Conclusions: This underscores the need for healthcare providers to enhance patient education regarding hospital diets. The prevalence of “Fact” questions showcases the importance of clearly explaining diets and dietary restrictions to patients.

Background: Inferior Vena Cava (IVC) filters have become an advantageous treatment modality for patients with venous thromboembolism. As the use of these filters continues to grow, it is imperative for providers to appropriately educate patients in a comprehensive yet understandable manner. Likewise, generative artificial intelligence models are a growing tool in patient education, but there is little understanding of the readability of these tools on IVC filters. Methods: This study aimed to determine the Flesch Reading Ease (FRE), Flesch–Kincaid, and Gunning Fog readability of IVC Filter patient educational materials generated by these artificial intelligence models. Results: The ChatGPT cohort had the highest mean Gunning Fog score at 17.76 ± 1.62 and the lowest at 11.58 ± 1.55 among the Copilot cohort. The difference between groups for Flesch Reading Ease scores (p = 8.70408 × 10−8) was found to be statistically significant albeit with priori power found to be low at 0.392. Conclusions: The results of this study indicate that the answers generated by the Microsoft Copilot cohort offers a greater degree of readability compared to ChatGPT cohort regarding IVC filters. Nevertheless, the mean Flesch–Kincaid readability for both cohorts does not meet the recommended U.S. grade reading levels.