Referral uptake after diabetic retinopathy screening with artificial intelligence-assisted care pathways: a systematic review and meta-analysis

Journal article

Artificial intelligence (AI) is an accurate screening tool for diabetic retinopathy (DR), the leading cause of blindness among working-aged adults. However, its impact on referral uptake is uncertain. We searched Embase, MEDLINE, Scopus, Web of Science and Cochrane Library databases from year 2000 to February 17, 2025. Randomised and non-randomised studies comparing referral uptake after AI-assisted DR screening versus standard of care were included. 2644 articles were identified, and six included for analysis. The relative risk of DR referral uptake with AI-assisted screening compared with the status quo was 1.89 (95% CI, 1.18, 3.03, I2 = 91.9%). Settings which underwent referral pathway transformation from routine to targeted referrals for DR demonstrated the greatest effect size. Most (n = 4) studies also utilised behavioural change interventions enabled by immediate results acquisition of AI to enhance health-seeking behaviour. Our findings suggest the effectiveness of DR screening is derived not only from diagnostic technology, but from AI-enabled care pathway redesign encompassing both health system transformation and coordinated patient-facing interventions which improve referral uptake.

Authors: Leigh, JA; Sherrington, A; Barber, ARJ; Turner, AW; Kidd, M

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: npj Digital Medicine
• Publication date: 2026-04-17
• Acceptance date: 2026-03-30
• DOI: 10.1038/s41746-026-02616-3
• EISSN: 2398-6352
• ISSN: 2398-6352
• Language: English
• Keywords: Diabetic retinopathy; Primary care; MEDLINE; Psychological intervention; Health care; Referral; Blindness