WISDOM: Using AI to Prioritise Surgical Wound Review

Artificial intelligence has enormous potential in healthcare, but where can it genuinely improve infection prevention without replacing clinical judgement? In this episode, Phil Russo and Martin Kiernan are joined by Professor Judith Tanner (University of Nottingham) and Melissa Rochon (Guy's and St Thomas' NHS Foundation Trust) to discuss a recent paper about the WISDOM study, a randomised feasibility trial evaluating AI-assisted digital surveillance for surgical wounds after hospital discharge.

Following on from a previous podcast in which patients submit wound photographs from home (https://infectioncontrolmatters.podbean.com/e/surgical-site-infection-surveillance-by-patient-generated-images/), this paper describes how AI can prioritise images that need urgent clinical review, and why this approach could transform surgical site infection surveillance while reducing unnecessary hospital visits. The guests discuss developing an AI model from almost 40,000 wound images, ensuring equitable performance across different skin tones, patient acceptance of digital follow-up, workforce redesign, and how remote monitoring could evolve into supported self-care. Rather than replacing clinicians, AI is shown to be a practical tool for helping healthcare teams focus on the patients who need them most.

Rochon M, Tanner J, Cariaga K, Jurkiewicz J, Beckhelling J, Harris R, et al. AI-enabled digital wound monitoring after cardiac surgery: a randomised controlled feasibility, safety, and acceptability trial. J Hosp Infect 2026. https://doi.org/10.1016/j.jhin.2026.04.020.

https://www.journalofhospitalinfection.com/action/showPdf?pii=S0195-6701%2826%2900159-3

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