Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Aug 14;18(8):1215-1221.
doi: 10.1093/ecco-jcc/jjae040.

Accuracy of Information given by ChatGPT for Patients with Inflammatory Bowel Disease in Relation to ECCO Guidelines

Martina Sciberras  1 , Yvette Farrugia  1 , Hannah Gordon  2   3 , Federica Furfaro  4 , Mariangela Allocca  4 , Joana Torres  5   6   7 , Naila Arebi  8   9 , Gionata Fiorino  4   10 , Marietta Iacucci  11 , Bram Verstockt  12   13 , Fernando Magro  14 , Kostas Katsanos  15 , Josef Busuttil  16 , Katya De Giovanni  16 , Valerie Anne Fenech  1 , Stefania Chetcuti Zammit  1 , Pierre Ellul  1
Affiliations

Accuracy of Information given by ChatGPT for Patients with Inflammatory Bowel Disease in Relation to ECCO Guidelines

Martina Sciberras et al. J Crohns Colitis. .

Abstract

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 <3. Overall, the mean rating was 2.24 [SD: ±0.4, median: 2, IQR: 1]. Though groups 3 and 4 had a higher mean for both accuracy and completeness, there was no significant scoring variation between the four question groups [Kruskal-Wallis test p > 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.

Keywords: Artificial intelligence; health communication; inflammatory bowel disease; patient education.

PubMed Disclaimer