# Mapping disparities in diabetic eye exam adherence using geographic information systems

**Authors:** Neil Sai Dogra, Michael Patrick Geiss, Talia Gearinger, Alan Delmerico, Rajeev S. Ramchandran

PMC · DOI: 10.1371/journal.pone.0340804 · PLOS One · 2026-02-13

## TL;DR

This study uses maps to show that people in certain areas, especially those with high poverty and minority populations, are less likely to get eye exams for diabetes, which can lead to preventable blindness.

## Contribution

The novel use of GIS to map disparities in diabetic eye exam adherence reveals geographic and demographic patterns linked to non-adherence.

## Key findings

- 31.5% of patients with diabetes were non-adherent to recommended eye exams.
- Non-adherence was strongly linked to poverty, unemployment, and lower education levels.
- GIS maps identified urban and rural clusters with high non-adherence and distinct demographic profiles.

## Abstract

Diabetic retinopathy is a leading cause of preventable vision loss in adults, and timely retinal screening is essential for early detection and intervention. However, adherence to diabetic eye exam guidelines remains suboptimal, particularly in underserved populations. Geographic Information Systems (GIS) offer a novel approach to visualizing disparities in eye care access and adherence.

We conducted a retrospective, cross-sectional study of 15,656 patients with diabetes mellitus (aged 18–75) receiving care in a university-based health system in Monroe County, NY, from November 2020 to November 2021. Eye exam adherence was determined using Healthcare Effectiveness Data and Information Set (HEDIS) criteria. Patient-level demographics and ZIP-code-level socioeconomic data were analyzed using ordinary least squares (OLS) regression. GIS choropleth maps were used to visualize regional variations in eye exam adherence and associated demographic and socioeconomic indicators.

Overall, 31.5% of patients were non-adherent to HEDIS eye exam standards. Non-adherence rates varied significantly by ZIP code (range: 13–50%) and were strongly associated with higher poverty (R² = 0.50, p < 0.0001), unemployment (R² = 0.17, p = 0.008), and lower educational attainment (R² = 0.50, p < 0.0001). Non-adherence also increased with higher proportions of Hispanic (R² = 0.24, p = 0.001) and non-Hispanic Black residents (R² = 0.45, p < 0.0001), and decreased with higher proportions of non-Hispanic White residents (R² = 0.45, p < 0.0001). GIS mapping identified an urban cluster of ZIP codes with consistently high non-adherence and socioeconomic risk profiles, as well as a rural outlier with high non-adherence but differing demographic characteristics.

Our findings highlight geographic, socioeconomic, and racial disparities in diabetic eye exam adherence. GIS can serve as a powerful tool to identify high-risk populations and inform targeted outreach strategies aimed at reducing vision loss in vulnerable communities.

## Linked entities

- **Diseases:** diabetic retinopathy (MONDO:0005266), diabetes mellitus (MONDO:0005015)

## Full-text entities

- **Diseases:** diabetes mellitus (MESH:D003920), Diabetic retinopathy (MESH:D003930), vision loss (MESH:D014786)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12904463/full.md

## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC12904463/full.md

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Source: https://tomesphere.com/paper/PMC12904463