TY - JOUR
T1 - Accuracy of information given by chatgpt for patients with inflammatory bowel disease in relation to ECCO Guidelines
AU - Sciberras, Martina
AU - Farrugia, Yvette
AU - Gordon, Hannah
AU - Furfaro, Federica
AU - Allocca, Mariangela
AU - Torres, Joana
AU - Arebi, Naila
AU - Fiorino, Gionata
AU - Iacucci, Marietta
AU - Verstockt, Bram
AU - Magro, Fernando
AU - Katsanos, Kostas
AU - Busuttil, Josef
AU - De Giovanni, Katya
AU - Fenech, Valerie Anne
AU - Zammit, Stefania Chetcuti
AU - Ellula, Pierre
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/8/1
Y1 - 2024/8/1
N2 - Background: As acceptance of artificial intelligence [AI] platforms increases, more patients will consider these tools as sources of information. The ChatGPT architecture utilizes a neural network to process natural language, thus generating responses based on the context of input text. The accuracy and completeness of ChatGPT3.5 in the context of inflammatory bowel disease [IBD] remains unclear. Methods: In this prospective study, 38 questions worded by IBD patients were inputted into ChatGPT3.5. The following topics were covered: [1] Crohn's disease [CD], ulcerative colitis [UC], and malignancy; [2] maternal medicine; [3] infection and vaccination; and [4] complementary medicine. Responses given by ChatGPT were assessed for accuracy [1-completely incorrect to 5-completely correct] and completeness [3-point Likert scale; range 1-incomplete to 3-complete] by 14 expert gastroenterologists, in comparison with relevant ECCO guidelines. Results: In terms of accuracy, most replies [84.2%] had a median score of ≥4 (interquartile range [IQR]: 2) and a mean score of 3.87 [SD: ±0.6]. For completeness, 34.2% of the replies had a median score of 3 and 55.3% had a median score of between 2 and 0.05]. However, statistical analysis for the different individual questions revealed a significant difference for both accuracy [p < 0.001] and completeness [p < 0.001]. The questions which rated the highest for both accuracy and completeness were related to smoking, while the lowest rating was related to screening for malignancy and vaccinations especially in the context of immunosuppression and family planning. Conclusion: This is the first study to demonstrate the capability of an AI-based system to provide accurate and comprehensive answers to real-world patient queries in IBD. AI systems may serve as a useful adjunct for patients, in addition to standard of care in clinics and validated patient information resources. However, responses in specialist areas may deviate from evidence-based guidance and the replies need to give more firm advice.
AB - Background: As acceptance of artificial intelligence [AI] platforms increases, more patients will consider these tools as sources of information. The ChatGPT architecture utilizes a neural network to process natural language, thus generating responses based on the context of input text. The accuracy and completeness of ChatGPT3.5 in the context of inflammatory bowel disease [IBD] remains unclear. Methods: In this prospective study, 38 questions worded by IBD patients were inputted into ChatGPT3.5. The following topics were covered: [1] Crohn's disease [CD], ulcerative colitis [UC], and malignancy; [2] maternal medicine; [3] infection and vaccination; and [4] complementary medicine. Responses given by ChatGPT were assessed for accuracy [1-completely incorrect to 5-completely correct] and completeness [3-point Likert scale; range 1-incomplete to 3-complete] by 14 expert gastroenterologists, in comparison with relevant ECCO guidelines. Results: In terms of accuracy, most replies [84.2%] had a median score of ≥4 (interquartile range [IQR]: 2) and a mean score of 3.87 [SD: ±0.6]. For completeness, 34.2% of the replies had a median score of 3 and 55.3% had a median score of between 2 and 0.05]. However, statistical analysis for the different individual questions revealed a significant difference for both accuracy [p < 0.001] and completeness [p < 0.001]. The questions which rated the highest for both accuracy and completeness were related to smoking, while the lowest rating was related to screening for malignancy and vaccinations especially in the context of immunosuppression and family planning. Conclusion: This is the first study to demonstrate the capability of an AI-based system to provide accurate and comprehensive answers to real-world patient queries in IBD. AI systems may serve as a useful adjunct for patients, in addition to standard of care in clinics and validated patient information resources. However, responses in specialist areas may deviate from evidence-based guidance and the replies need to give more firm advice.
KW - Artificial intelligence
KW - Health communication
KW - Inflammatory bowel disease
KW - Patient education
UR - https://www.scopus.com/pages/publications/85195223895
U2 - 10.1093/ecco-jcc/jjae040
DO - 10.1093/ecco-jcc/jjae040
M3 - Article
C2 - 38520394
AN - SCOPUS:85195223895
SN - 1873-9946
VL - 18
SP - 1215
EP - 1221
JO - Journal of Crohn's and Colitis
JF - Journal of Crohn's and Colitis
IS - 8
ER -