Role of a generative AI model in enhancing clinical decision‐making in nursing

Abstract

We would like to share ideas on the publication 'A comparative vignette study: Evaluating the potential role of a generative AI model in enhancing clinical decision-making in nursing (Saban & Dubovi, 2024).' The clinical decision-making skills of nursing students, emergency room Registered Nurses and ChatGPT, an AI program, were compared in this cross-sectional study. Three clinical cases were given to the participants to evaluate and recommend. The findings demonstrated that ChatGPT had trouble with preliminary evaluations, suggested pointless tests and had trouble going back and reconsidering choices. Notwithstanding these drawbacks, ChatGPT maintained logical coherence and clarity while responding more quickly and verbally than human participants. ChatGPT's indecisiveness in preliminary evaluations and propensity to provide unsuitable recommendations are among its weaknesses. Additionally, the AI program demonstrated a lack of flexibility when it came to reassessing choices in light of fresh knowledge. Furthermore, ChatGPT's responses were noticeably verbose in comparison to those of human participants, which could be a symptom of inefficiency or impreciseness. These flaws point out places where ChatGPT might be strengthened to increase its efficacy and efficiency in future applications. Overall, the study demonstrates ChatGPT's advantages and disadvantages for use in clinical decision-making. Subsequent investigations may concentrate on enhancing AI algorithms to improve their efficacy in medical environments. Several significant changes could be taken into consideration to improve ChatGPT's performance. First and foremost, it must enhance its capacity to generate precise preliminary evaluations and suggestions. This can entail optimizing the algorithm to comprehend customer inquiries more fully and deliver pertinent and useful answers. Moreover, improving the AI programme's ability to reassess choices in light of fresh data can be advantageous. This would allow ChatGPT to adjust and deliver real-time recommendations that are more precise and current. Finally, looking at methods to improve ChatGPT's word usage efficiency to speed up responses could help to further enhance its functionality. Reduced superfluous words and repetitions could allow the AI programme to respond to consumers in a more succinct and efficient manner, therefore enhancing the user experience in general. Additional research into the factors influencing ChatGPT's and physicians' performance differences could reveal more about the limitations and potential applications of AI in healthcare. Respecting a code of behaviour is essential because people are the technology's ultimate users (Kleebayoon & Wiwanitkit, 2023). None declared. HD was equally contributed in ideas, writing, analysing and approval. VW was equally contributed in ideas, supervision and approval. None declared. Authors declare no conflict of interest. None declared.

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