ChatGPT in hospital infection prevention and control – assessing knowledge of an AI model based on a validated questionnaire

• Authors: Ankita Jawanpuria , Aruna Rani Behera , Chinmaya Dash , Mohammad Hifz Ur Rahman

Abstracts

EN

Introduction and aim. An AI model like ChatGPT is a good source of knowledge. We can explore the potential of AI models to complement the expertise of healthcare professionals by providing real-time, evidence-based information in infection prevention and control (IPC). Material and methods. This study involved 110 queries related to IPC, validated by subject experts in IPC. The responses from ChatGPT were evaluated using Bloom’s taxonomy by experienced microbiologists. The scores were divided as <3 as being a poor response, 3–4 as an average response, and >4 as a good response. Statistical analysis was done by correlation coefficient and Cohen’s Kappa. Results. The overall score was 4.33 (95% CI, q1 3.65–q3 4.64) indicating ChatGPT’s substantial IPC knowledge. A good response (i.e.>4 score) was found in 70 (63.6%) questions, while in 10 (9%) questions, it showed a poor response. The poor response was seen in needle stick injury and personal protective equipment (PPE) doffing-related questions. The overall correlations were found to be significant. Cohen’s Kappa confirmed moderate to substantial agreement between evaluators. Conclusion. ChatGPT demonstrated a commendable understanding of IPC principles in various domains and the study identifies specific instances where the model may require further refinement especially in critical scenarios such as needlestick injuries and PPE doffing.

Keywords

EN

artificial intelligence; ChatGPT; infection control; large language model; medical education

• Publisher: Uniwersytet Rzeszowski. Wydawnictwo Uniwersytetu Rzeszowskiego
• Journal: European Journal of Clinical and Experimental Medicine
• Year: 2024
• Volume: 22
• Issue: 2
• Pages: 347-352

Dates

published

2024

Contributors

author

Ankita Jawanpuria

• Department of Microbiology, Manipal Tata Medical College, Manipal Academy of Higher Education, Manipal, India

author

Aruna Rani Behera

• Department of Microbiology, Manipal Tata Medical College, Manipal Academy of Higher Education, Manipal, India

author

Chinmaya Dash

• Department of Microbiology, Manipal Tata Medical College, Manipal Academy of Higher Education, Manipal, India

author

Mohammad Hifz Ur Rahman

• Department of Community Medicine, Manipal Tata Medical College, Manipal Academy of Higher Education, Manipal, India

Identifiers

DOI

10.15584/ejcem.2024.2.19

Biblioteka Nauki

40570861