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RACS ASC 2025
AI-Driven Pre-Consultations for Elevated PSA: Streamlining Urology Workflows and Boosting Patient Outcomes—A Pilot Study
Poster
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Poster

Disciplines

Urology Surgery

Talk Description

Institution: Royal Prince Alfred Hospital - NSW, Australia

Purpose This pilot study aims to evaluate the feasibility, acceptability, and preliminary clinical utility of an AI-driven pre-consultation process in an outpatient urology setting for patients presenting with elevated prostate-specific antigen (PSA) levels. The study will assess both patient experience and clinician-reported outcomes. Methodology A prospective observational design will be employed with approximately 30–40 patients attending their first outpatient consultation for elevated PSA. The AI tool will gather patient information, generate consultation and post-consultation documentation, facilitate risk stratification, and provide decision-making support. Both clinicians and patients will complete interviews and validated questionnaires to evaluate efficacy, barriers and satisfaction with the AI-enhanced workflow. Quantitative measures will capture time efficiency and diagnostic outcomes compared to standard care. Results It is anticipated that the AI tool will reduce administrative burden by streamlining data collection and documentation processes. Improved efficiency in clinician–patient consultations is expected, alongside favourable patient-reported satisfaction and acceptance of the AI-enabled workflow. Preliminary diagnostic outcomes, although exploratory in nature, will help refine the protocol for a larger study. Conclusion Findings from this pilot study will offer critical insights into the practical integration of AI technology in outpatient urological care. By assessing feasibility, acceptability, and initial clinical utility, the project will guide the design of a larger-scale investigation aimed at improving patient outcomes, enhancing clinician workflow, and reducing administrative burden.
Presenters
Authors
Authors

Dr Damien Gibson - , Dr Scott Leslie - , Dr Kun Yu - , A/Prof Ruban Thanigasalam - , Dr Kate Alexander - , A/Prof Daniel Steffens -