Real-world effectiveness of artificial-intelligence-assisted lesion triage on cancer waiting times

Abstract

Urgent skin cancer referrals are increasing, and artificial intelligence (AI) tools have been proposed as a solution to the considerable pressure on dermatology services. Using publicly available cancer waiting time data from 24 National Health Service trusts, this real-world interrupted time series and meta-analysis showed no consistent pooled improvement in Faster Diagnosis Standard breaches (the proportion of patients referred with suspected cancer waiting more than 28 days from referral to diagnosis) following deployment of an AI-assisted lesion triage system, with marked heterogeneity across trusts ranging from benefit to deterioration. These findings demonstrate that the impact of diagnostic AI is highly context-dependent and underscore the need for robust local evaluation and cost–benefit analysis prior to widespread adoption.

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