547 Investigating the Role of Artificial Intelligence Aids in Enhancing Communication and Shared Decision-Making in Urological Care: A Systematic Review

Abstract

Abstract Aim Effective communication and shared decision-making are essential for optimising urological care, making informed decisions, and improving patient outcomes. The integration of Artificial Intelligence (AI) in urology has the potential to act as a supportive tool in this process. This systematic review aims to investigate how AI may aid and enhance communication and shared decision-making, emphasising patient-centred care. Method Following PRISMA guidelines, a systematic search was performed using Cochrane, EMBASE, MEDLINE, and Scopus for literature published between 2019 and 2024. Search terms included "Artificial Intelligence," "Urology," "Shared Decision-Making," and "Communication." Studies were screened using our predefined inclusion and exclusion criteria. Results Of 807 identified studies, 27 were appropriate for inclusion. AI-driven tools, particularly Large Language Models (LLMs), show the potential to reduce knowledge gaps for diverse literacy levels and improve patient comprehension. These aids may improve the readability of complex medical content and translate information with cultural sensitivity. AI may also enhance electronic communication between patients and physicians, assisting in frequently asked questions, follow-ups, and discharge letters of equivalent quality to those written by junior clinicians. However, AI has limitations, with different LLMs displaying variable levels of effectiveness and accuracy across urological conditions. Conclusions The integration of AI has the potential to enhance communication and promote shared decision-making in urology. However, patients should use AI as a complement to physicians rather than a replacement. To confidently determine their role and ensure AI output accuracy, further studies, validation, and the refinement of AI in clinical settings are required.

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