Laryngoscope Investigative Otolaryngology (Aug 2024)

TrachGPT: Appraisal of tracheostomy care recommendations from an artificial intelligent Chatbot

  • Oluwatobiloba Ayo‐Ajibola,
  • Ryan J. Davis,
  • Matthew E. Lin,
  • Neelaysh Vukkadala,
  • Karla O'Dell,
  • Mark S. Swanson,
  • Michael M. Johns III,
  • Elizabeth A. Shuman

DOI
https://doi.org/10.1002/lio2.1300
Journal volume & issue
Vol. 9, no. 4
pp. n/a – n/a

Abstract

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Abstract Objective Safe home tracheostomy care requires engagement and troubleshooting by patients, who may turn to online, AI‐generated information sources. This study assessed the quality of ChatGPT responses to such queries. Methods In this cross‐sectional study, ChatGPT was prompted with 10 hypothetical tracheostomy care questions in three domains (complication management, self‐care advice, and lifestyle adjustment). Responses were graded by four otolaryngologists for appropriateness, accuracy, and overall score. The readability of responses was evaluated using the Flesch Reading Ease (FRE) and Flesch–Kincaid Reading Grade Level (FKRGL). Descriptive statistics and ANOVA testing were performed with statistical significance set to p < .05. Results On a scale of 1–5, with 5 representing the greatest appropriateness or overall score and a 4‐point scale with 4 representing the highest accuracy, the responses exhibited moderately high appropriateness (mean = 4.10, SD = 0.90), high accuracy (mean = 3.55, SD = 0.50), and moderately high overall scores (mean = 4.02, SD = 0.86). Scoring between response categories (self‐care recommendations, complication recommendations, lifestyle adjustments, and special device considerations) revealed no significant scoring differences. Suboptimal responses lacked nuance and contained incorrect information and recommendations. Readability indicated college and advanced levels for FRE (Mean = 39.5, SD = 7.17) and FKRGL (Mean = 13.1, SD = 1.47), higher than the sixth‐grade level recommended for patient‐targeted resources by the NIH. Conclusion While ChatGPT‐generated tracheostomy care responses may exhibit acceptable appropriateness, incomplete or misleading information may have dire clinical consequences. Further, inappropriately high reading levels may limit patient comprehension and accessibility. At this point in its technological infancy, AI‐generated information should not be solely relied upon as a direct patient care resource.

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