Local performance and fairness testing of an AI Scribe in a paediatric developmental assessment clinic in South Australia: a silent trial protocol.

introductionAny tool that can reduce the administrative burden on healthcare providers while preserving safe, accountable and high-quality medical documentation is of immense value both to healthcare institutions and consumers. The key question we need to answer is whether a prospective tool can reduce these burdens while maintaining (and, ideally METHODS AND ANALYSIS: Using an algorithmic audit framework developed specific to our context, we will compare clinician-written clinical notes to AI-generated notes produced in parallel to the standard of care (ie, a 'silent' or translational trial paradigm). We will compare the time required to review clinical documentation per the standard of care compared with the AI-supported workflow with consideration to the accuracy of the final documentation. Finally, we will qualitatively describe AI-generated notes and compare them to the current standard to identify specific areas where clinical guidelines (eg, performance information, risk mitigation) would support appropriate clinical use. ETHICS AND DISSEMINATION: Ethics approval has been obtained by the Women's and Children's Health Network Human Research Ethics Committee (HREC) (HRE00067) and the South Australian Aboriginal HREC (#04-25-1185). This protocol offers an accessible example for health institutions looking to apply an evidence-based approach to AI Scribe assessment that prioritises clinical documentation standards. We will publish our study results in an academic journal and include a publicly accessible summary for the general public on the Women's and Children's website. TRIAL REGISTRATION NUMBER: 10.17605/OSF.IO/P6TM5.