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Adi Weintraub

Senior Academic

The future of patient education

A study on AI-driven responses to urinary incontinence inquiries

Reut Rotem, Omri Zamstein, Misgav Rottenstreich, Orfhlaith E. O'Sullivan, Barry A. O'reilly, Adi Y. Weintraub

OBJECTIVE: To evaluate the effectiveness of ChatGPT in providing insights into common urinary incontinence concerns within urogynecology. By analyzing the model's responses against established benchmarks of accuracy, completeness, and safety, the study aimed to quantify its usefulness for informing patients and aiding healthcare providers. METHODS: An expert-driven questionnaire was developed, inviting urogynecologists worldwide to assess ChatGPT's answers to 10 carefully selected questions on urinary incontinence (UI). These assessments focused on the accuracy of the responses, their comprehensiveness, and whether they raised any safety issues. Subsequent statistical analyses determined the average consensus among experts and identified the proportion of responses receiving favorable evaluations (a score of 4 or higher). RESULTS: Of 50 urogynecologists that were approached worldwide, 37 responded, offering insights into ChatGPT's responses on UI. The overall feedback averaged a score of 4.0, indicating a positive acceptance. Accuracy scores averaged 3.9 with 71% rated favorably, whereas comprehensiveness scored slightly higher at 4 with 74% favorable ratings. Safety assessments also averaged 4 with 74% favorable responses. CONCLUSION: This investigation underlines ChatGPT's favorable performance across the evaluated domains of accuracy, comprehensiveness, and safety within the context of UI queries. However, despite this broadly positive reception, the study also signals a clear avenue for improvement, particularly in the precision of the provided information. Refining ChatGPT's accuracy and ensuring the delivery of more pinpointed responses are essential steps forward, aiming to bolster its utility as a comprehensive educational resource for patients and a supportive tool for healthcare practitioners.

Publication language English
Pages 1004-1009
Journal International Journal of Gynecology and Obstetrics
Volume 167
Issue number 3
Publication status Published - 01.12.2024

Keywords

ChatGPT
Urogynecology
artificial intelligence‐generated responses
expert opinions
quality evaluation
urinary incontinence

ASJC Scopus subject areas

Obstetrics and Gynecology
Access to Document
10.1002/ijgo.15751
Other files and links
Link to publication in Scopus