Advantages and limitations of large language models for antibiotic prescribing and antimicrobial stewardship

Introduction

Imagine you are a hospital-based infectious diseases specialist receiving a consultation request from another ward. When you first read the request for consultation on your computer screen, an intelligent artificial assistant, leveraging large language models (LLMs) technology, has already prepared a coherent summary of the patient’s medical and microbiological history, relevant laboratory and instrumental test results, and the evolution of their acute phase conditions in the last few days^{1, 2–3}. This summary immediately provides you with an initial idea about what to do, without laboriously spending many minutes searching for information across clinical notes in the patient’s clinical chart.

Subsequently, you go to the other ward to visit the patient and gather additional information from the patient and their treating physicians. During the consultation, your intelligent artificial assistant can (i) directly register and summarize the additional information provided by the patient and their treating physicians and (ii) suggest additional relevant questions to be posed. After coherently merging the already known information from the patient’s history and tests results with the new information collected during the consultation, your artificial intelligent assistant can explicitly offer some suggestions for your revision (e.g., prescribing a given antibiotic at a certain dosage and for a certain duration), supported by reasonable, summarized explanations.

This is only a hypothetical example of how LLMs could aid physicians in the near future in prescribing antibiotics, likely not exhaustive of all potential applications of LLMs for this purpose^{3, 4, 5, 6, 7–8}. Since the advantages (above all, dramatic reduction of repetitive tasks for clinicians, thereby making time for more sophisticated clinical reasoning) of introducing LLMs in daily clinical practice could be transformative in healthcare, and considering that profound implementation of LLMs within electronic health records has already been announced⁹, a thorough understanding of both potential advantages and relevant limitations is essential for current and future clinicians who will very likely deal with this emerging technology in their daily clinical practice^1,10.

In this perspective, we focus on the potential advantages and limitations of introducing LLMs to support antibiotic prescribing, both in terms of improving the efficacy and safety of the therapeutic approach to the single patient and in terms of the appropriate use of antibiotics in line...