Cost-effectiveness requirements for implementing artificial intelligence technology in the Women’s UK Breast Cancer Screening service

Armando Vargas-Palacios (), Nisha Sharma and Gurdeep S. Sagoo
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Armando Vargas-Palacios: University of Leeds
Nisha Sharma: Leeds Teaching Hospital NHS Trust
Gurdeep S. Sagoo: University of Leeds

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract The UK NHS Women’s National Breast Screening programme aims to detect breast cancer early. The reference standard approach requires mammograms to be independently double-read by qualified radiology staff. If two readers disagree, arbitration by an independent reader is undertaken. Whilst this process maximises accuracy and minimises recall rates, the procedure is labour-intensive, adding pressure to a system currently facing a workforce crisis. Artificial intelligence technology offers an alternative to human readers. While artificial intelligence has been shown to be non-inferior versus human second readers, the minimum requirements needed (effectiveness, set-up costs, maintenance, etc) for such technology to be cost-effective in the NHS have not been evaluated. We developed a simulation model replicating NHS screening services to evaluate the potential value of the technology. Our results indicate that if non-inferiority is maintained, the use of artificial intelligence technology as a second reader is a viable and potentially cost-effective use of NHS resources.

Date: 2023
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DOI: 10.1038/s41467-023-41754-0

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