Diabetic retinopathy screening model in low and middle-income countries: a scoping review
Yeni Dwi Lestari1,2,3, Ratna Sitompul4,5, Indah Suci Widyahening6
1Doctoral Program in Medical Sciences, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia. yeni2lestari@yahoo.com.
Background:
Diabetic retinopathy (DR), a leading cause of blindness in working-age adults, disproportionately affects low- and middle-income countries (LMICs). While preventable through early intervention, DR screening programs are often lacking in these resource-constrained settings.
Objective:
This scoping review examines DR screening models implemented in LMICs, identifying evidence, research gaps, and potential improvement strategies.
Methods:
A literature search across multiple databases identified studies on DR screening in LMICs, limited to peer-reviewed articles from the past 20 years focusing on DR screening model effectiveness or implementation. Key data (study design, screening techniques, outcomes) were extracted and synthesized narratively.
Results:
This review synthesized 30 studies on DR screening in LMICs, mainly from India, South Africa, Pakistan, and Bangladesh. These studies explored diverse screening methods, from traditional techniques (ophthalmoscopy, funduscopy, slit lamp exams) to telemedicine and AI. Non-mydriatic fundus photography, often with AI-assisted grading, was common, as were remote grading and store-and-forward systems. Given the resource constraints in these settings, non-mydriatic methods were often preferred. Many studies optimized resources by training non-physicians for image acquisition, followed by specialist grading. The reviewed studies highlighted the effectiveness of community-based screening programs in expanding coverage and improving patient adherence. Furthermore, they demonstrated the cost-effectiveness of smartphone-based imaging devices and AI-driven systems. However, challenges remained, including limited infrastructure, inconsistent training, and follow-up difficulties.
Conclusions:
LMIC DR screening utilizes traditional and innovative technologies, with community-based approaches, telemedicine, and AI enhancing reach and accuracy. Transitioning from case-finding to population-based screening requires stronger diabetes surveillance and integration within primary care.
