Burn Patient Education in the Modern Age: A Comparative Analysis of ChatGPT and Google Performance Answering Common Questions on Burn Injury and Management.

Journal: Journal of burn care & research : official publication of the American Burn Association
Published Date:

Abstract

Patients often use Google for their medical questions. With the emergence of artificial intelligence large language models, such as ChatGPT, patients may turn to such technologies as an alternative source of medical information. This study investigates the safety, accuracy, and comprehensiveness of medical responses provided by ChatGPT in comparison to Google for common questions about burn injuries and their management. A Google search was performed using the term "burn," and the top 10 frequently searched questions along with their answers were documented. These questions were then prompted into ChatGPT. The quality of responses from both Google and ChatGPT was evaluated by 3 burn and trauma surgeons using the Global Quality Score scale, rating from 1 (poor quality) to 5 (excellent quality). A Wilcoxon paired t-test evaluated the difference in scores between Google and ChatGPT answers. Google answers scored an average of 2.80 ± 1.03, indicating that some information was present, but important topics were missing. Conversely, ChatGPT-generated answers scored an average of 4.57 ± 0.73, indicating excellent quality responses with high utility to patients. For half of the questions, the surgeons unanimously preferred their patients receive information from ChatGPT. This study presents an initial comparison of Google and ChatGPT responses to commonly asked burn injury questions. ChatGPT outperforms Google in responding to commonly asked questions on burn injury and management based on the evaluations of 3 experienced burn surgeons. These results highlight the potential of ChatGPT as a source of patient education.

Authors

  • Sumaarg Pandya
    Department of Plastic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, United States.
  • Mario Alessandri Bonetti
    Department of Plastic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, United States.
  • Hilary Y Liu
    Department of Plastic Surgery, University of Pittsburgh Medical Center, 1350 Locust Street, Pittsburgh, PA, G10315219, USA.
  • Tiffany Jeong
    Department of Plastic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, United States.
  • Jenny A Ziembicki
    Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, United States.
  • Francesco M Egro
    Department of Plastic Surgery, University of Pittsburgh Medical Center, 1350 Locust Street, Pittsburgh, PA, G10315219, USA. francescoegro@gmail.com.

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