Development of a target product profile for artificial intelligence in diabetic eye screening in England: a modified Delphi consensus study

Macdonald, Trystan B., Dinnes, Jacqueline, Maniatopoulos, Gregory, Solebo, Ameenat L., Hogg, H. D. Jeffry and Owens, David 2026. Development of a target product profile for artificial intelligence in diabetic eye screening in England: a modified Delphi consensus study. The Lancet Digital Health , 101033. 10.1016/j.landig.2026.101033

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Abstract

Artificial intelligence (AI) health-care technologies offer a means of addressing the growing gap between health-care capacity and demand. However, few technologies have met the complex requirements of health-care systems for adoption. Diabetic eye screening (DES) in England exemplifies the difficulty of understanding these requirements and translating them into real-world implementation decisions. This Review responds to a recognised policy need to develop a target product profile (TPP) for a DES AI system for use in England. The TPP outlines the requirements of the English health-care system for such a device and was developed using a modified Delphi consensus process involving interviews, surveys, and a consensus meeting. Participants included people living with diabetes, health-care professionals, health-care managers and leaders, regulators and policy makers, and developers. Thirty-five product specifications were agreed upon, covering areas such as clinical validity, utility, and environmental sustainability. Our TPP establishes clear criteria for DES AI development and deployment in England, and this TPP development process can serve as a template for initiatives to create TPPs for other AI health technologies and settings.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Medicine
Additional Information:	For full author list please see article webpage https://doi.org/10.1016/j.landig.2026.101033
Publisher:	Elsevier
ISSN:	2589-7500
Date of First Compliant Deposit:	15 July 2026
Last Modified:	16 Jul 2026 14:16
URI:	https://orca.cardiff.ac.uk/id/eprint/188249

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