Using Public Datasets to Identify Priority Areas for Ocular Telehealth

Abstract

Purpose: Telemedicine can expand access to ocular services, but barriers include restrictive policies and poor reimbursement. A tool to identify priority regions for interventions is needed. Methods: Eye care provider (ECP) density, self-reported visual disability, and demographics were calculated using census data and professional registries. The relationship between visual disability and ECP density was explored in fractional regression models. These data were compared with state telemedicine policy favorability. Results: For each additional ECP per 100,000 population, there was 0.0111% less disability in the county (95% confidence interval -0.0150% to -0.00719%) in an adjusted model. Of 3,142 counties, 1,078 (34%) were in the worst population-weighted quartile for ECP density and visual disability. Conclusions: Low ECP density is associated with higher visual disability, suggesting an opportunity for ocular telehealth. Counties with favorable policy climates should be prioritized for telemedicine implementation. Public datasets can be used to survey wide geographic areas to identify areas worthy of detailed needs assessments.

Keywords: diabetic retinopathy; ocular telehealth; telehealth; telehealth policy; telemedicine; visual disability.

Fig. 1.

Map of the continental United States with shaded opportunity counties. These counties were in the highest population-weighted quartile for visual disability and lowest population-weighted quartile for eye care provider density.