DOI: 10.4103/jfmpc.jfmpc_272_26 ISSN: 2249-4863

eVisio®: A new visual screening app for primary care

Adrián Nieto-Ortiz, Esther Aguilera-Majoral, Oriol Turró-Garriga, Jordi Juvanet-Ribot, Aurora Fontova-Almató, Pere Plaja-Román

A
BSTRACT

Background:

eVisio® is a newly developed digital application designed to provide reliable visual screening through standardized visual acuity tests and to generate an automated recommendation regarding the level of clinical care required. Given the increasing demand for ophthalmology services and the need for efficient triage tools in primary care, validating the reliability of this app is essential.

Methods:

A cross-sectional comparative study was conducted with 543 patients attending a hospital ophthalmology unit over 6 months. Participants underwent visual acuity testing using both the traditional clinical method (gold standard) and the eVisio® app. The app’s recommendations—“Visit the ophthalmologist,” “Visit the optometrist,” or “No need of visit”—were compared with clinician-based recommendations. Concordance, sensitivity, specificity, and weighted kappa were calculated. Visual acuity differences were analyzed using Bland–Altman plots and non-parametric tests. Subgroup analyses were performed by age group and platform (iOS, Android, Web).

Results:

After exclusions, 512 cases were analyzed. Overall concordance between the app and the traditional method was 78.77%, with a sensitivity of 89.78% and a specificity of 82.61%. Weighted kappa indicated substantial agreement (0.73; 95% confidence interval: 0.68–0.78). Far acuity differences were not statistically significant, and 83.59% of values differed by ≤0.05 logMAR. Performance was consistent across platforms, and the highest concordance was observed in the 15–40 age group. A primary care subgroup assessed by a nonophthalmologic assistant showed lower specificity but maintained high sensitivity.

Conclusions:

eVisio® is a reliable tool for visual screening without expert supervision and demonstrates substantial agreement with standard clinical methods. Its implementation in primary care could improve referral efficiency, reduce unnecessary ophthalmology visits, and support early detection of visual problems. Further research should explore unsupervised home use and integration into teleophthalmology workflows.

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