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Our articles share field experience, findings, evaluated models and practical tools to help you build a screening programme of your own.
A non-mydriatic fundus camera can reduce friction in retinal capture and enable decentralized care models, as long as it is embedded in a workflow for quality, reading, and referral.
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Building a diabetic retinopathy screening program in primary care requires a clear cohort, capture model, reading pathway, referral rules, and simple metrics so coverage does not depend on isolated actions.
Teleophthalmology with AI should not be treated as a standalone app. It works best as an operational layer that expands coverage, supports prioritization, and preserves traceability with human review.
Implementing diabetic retinopathy screening is not about buying a camera. It is about designing a clinical-operational workflow that can capture, prioritize, refer, and close the loop.
Improving diabetes eye exam coverage requires more than reminders. It requires embedding retinal assessment into the routine care pathway.
In retinal screening, an ungradable image is not a technical detail: it is a missed clinical opportunity. Here is how to design a workflow that captures usable images the first time.
Diabetic retinopathy is one of the leading causes of preventable vision loss. Detecting it early is key to avoiding complications.
Operational guide to improve attendance, reduce loss to follow-up, and measure referral-loop closure in retina programs for people with diabetes.
Implementing teleophthalmology is not "doing video consults": it is about designing a clinical-operational workflow. These three models show how to bring it to production.
Three layers (image, result, workflow) and a practical checklist to integrate fundus imaging into the EHR without endless projects.
Human-in-the-loop is not 'having a physician look at it at the end': it is operational design with thresholds, roles, and evidence.
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