Evaluating ChatGPT’s efficacy in addressing common patient questions in plastic surgery consultations

Aim: This study aims to investigate the ability of ChatGPT to answer common patient questions related to the five most common aesthetic procedures. Methods: We asked three questions, two of which were the same across procedures, for each of the five most common plastic surgery procedures as determined by the 2022 American Society of Plastic Surgery (ASPS) Procedural Statistics Release. These were posed to ChatGPT on the same day, using the same account. Then, they were compared to the corresponding information on the ASPS website. Results: We found that ChatGPT provides accurate, organized, and grammatically correct responses to common patient questions. It was comparable to the ASPS website in terms of comprehensiveness of the complications listed across procedures. However, its responses regarding recovery time were less detailed than the corresponding ASPS articles. It included accurate information on recovery time that was unavailable on the ASPS site. For procedure-specific questions, ChatGPT was more detailed 2/5 times, less detailed 1/5 times, and provided a completely different answer than the ASPS website 2/5 times. Conclusion: This study provides support for ChatGPT’s utilization as a tool to improve the efficiency of consultations for aesthetic procedures. However, it is important to recognize ChatGPT’s limitations in answering questions in a patient/procedure-specific way. Therefore, it is not a substitute for an experienced surgeon consultation. Further research is needed to assess the reliability of ChatGPT before it can be fully recommended as an ultimate patient learning tool.

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Publication Details

Journal
Artificial Intelligence Surgery
Published
2024-12-10
DOI
https://doi.org/10.20517/ais.2024.61
Citations
7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.84
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article

Evaluating ChatGPT’s efficacy in addressing common patient questions in plastic surgery consultations

Nicholas A. Mirsky, Seth Ray Thaller, Baylee M. Brochu
7 citations
Artificial Intelligence Surgery
Artificial Intelligence in Healthcare and Education
0.84
article

Evaluating ChatGPT’s efficacy in addressing common patient questions in plastic surgery consultations

Nicholas A. Mirsky, Seth Ray Thaller, Baylee M. Brochu
article en
7 citations

Abstract

Aim: This study aims to investigate the ability of ChatGPT to answer common patient questions related to the five most common aesthetic procedures. Methods: We asked three questions, two of which were the same across procedures, for each of the five most common plastic surgery procedures as determined by the 2022 American Society of Plastic Surgery (ASPS) Procedural Statistics Release. These were posed to ChatGPT on the same day, using the same account. Then, they were compared to the corresponding information on the ASPS website. Results: We found that ChatGPT provides accurate, organized, and grammatically correct responses to common patient questions. It was comparable to the ASPS website in terms of comprehensiveness of the complications listed across procedures. However, its responses regarding recovery time were less detailed than the corresponding ASPS articles. It included accurate information on recovery time that was unavailable on the ASPS site. For procedure-specific questions, ChatGPT was more detailed 2/5 times, less detailed 1/5 times, and provided a completely different answer than the ASPS website 2/5 times. Conclusion: This study provides support for ChatGPT’s utilization as a tool to improve the efficiency of consultations for aesthetic procedures. However, it is important to recognize ChatGPT’s limitations in answering questions in a patient/procedure-specific way. Therefore, it is not a substitute for an experienced surgeon consultation. Further research is needed to assess the reliability of ChatGPT before it can be fully recommended as an ultimate patient learning tool.

Artificial Intelligence SurgeryVol. 4(4)
University of Miami (US)
Quality Education
Openalex Percentile: Top 24%
Artificial Intelligence in Healthcare and Education
0.84
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