Lay summary
This research aims to improve the diagnosis of ear disease in children by introducing artificial intelligence (AI) technology into primary healthcare. Ear infections are common, but accurate diagnosis can be difficult. GPs rely on visual examination and patient history, which can lead to over-treatment with antibiotics or under-treatment, delaying specialist referral. This project will first gather feedback from primary care teams to understand how an AI-assisted diagnostic tool can be integrated into practice and to evaluate useability and acceptability. The AI tool will then be trialled in a high-need urban general practice to assess its feasibility to integrate into normal clinical workflows, and its impact on diagnosis accuracy, referral patterns, and patient experiences. By supporting more accurate diagnosis of ear disease, this approach aims to reduce unnecessary treatments, and address long-standing health inequities - particularly for Māori and Pacific children - while offering a cost-effective, scalable solution for the wider health system.