Exploring the Potential of an AI Chatbot as a Supplementary Tool for Nutritional Prescription Hospital Discharge: A Preliminary Study

Abstract

AI-based chatbots are increasingly used to automate clinical documentation, but their efficacy in generating specialized nutritional prescriptions for hospital discharge remains underexplored. This preliminary study evaluated the performance of a prominent AI chatbot in producing clinically valid nutritional guidelines. A specialist committee of registered dietitians selected 16 common medical and surgical pathologies. Standardized prompts were used to generate nutritional discharge guidelines from the chatbot. The same committee then evaluated the AI-generated texts for technical accuracy and content presentation on a 0-10 scale (approval score ≥ 7.0). Inter-rater reliability was assessed using the intraclass correlation coefficient (ICC) and Cohen's Kappa. Overall, 50% (8/16) of the AI-generated prescriptions met the predefined approval threshold. Performance was higher for medical pathologies (mean score: 7.1 ± 1.2) compared to surgical pathologies (6.6 ± 1.4), although this difference was not statistically significant (<i>p</i> > 0.05). Inter-rater reliability was substantial (ICC > 0.72; Kappa > 0.62). The findings indicate that AI chatbots hold promise as supplementary tools for drafting nutritional discharge summaries, potentially reducing administrative workload. However, their variable performance underscores the indispensable need for rigorous review and validation by qualified healthcare professionals before any clinical application.

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