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Purpose: To develop a method to identify preschools with the greatest need for vision screening, correlations between socioeconomic status, preschool capacity, and rates of pediatric vision screenings performed by a community vision screening program were investigated. Geoinformatics mapping software was used to visually display the areas of greatest need. Methods: Vision screening data from a community vision screening program, child care facility data from California Department of Social Services, and income data from the U.S. Census Bureau through ArcGIS software (Esri) were collected. When possible, data were consolidated at the ZIP code level. Kolmogorov-Smirnov analysis was used to determine correlations between data elements. Licensed child care facilities were scored on a scale (from 1 to 5) based on the socioeconomic status of the ZIP code and the facility capacity. The scoring system prioritized larger facilities in lower income communities to most efficiently use vision screening program resources. Results: There was a positive correlation between the capacity of the child care facility and the median household income ( P = .005). Second, we found a positive correlation between child care capacity and the median household income ( P = .005). Licensed child care facilities were mapped and colored using GIS software according to their cumulative score. Conclusions: Challenges to vision screening in under-served communities include the lack of child care facilities and smaller facility size. The use of a scoring system and mapping software can direct vision screening programs to reach a greater number of children with the most efficient use of resources. [ J Pediatr Ophthalmol Strabismus . 2022;59(6):375–379.] |
