Introduction: Glaucoma is one of the leading causes of irreversible blindness around the world. Black individuals are two times more likely to be diagnosed with glaucoma compared to White individuals. In 2019, the prevalence of glaucoma in Monroe County was highest amongst older individuals aged 85 and non-Hispanic Blacks. This study seeks to explore differences in glaucoma treatment rates that may be exacerbating disease severity and prognosis for individuals most acutely affected by glaucoma in Monroe County, NY. Methods: We used data from the Center for Disease Control’s National Vision and Eye Health Surveillance System (VEHSS) to assess the rates of glaucoma treatment for different racial, gender, and age demographic groups in Monroe County, NY. The source data were from individuals enrolled in Medicare who filed a claim. We stratified the data based on the glaucoma treatment type: laser glaucoma surgery, glaucoma drainage devices, other glaucoma surgery, or glaucoma prescription drugs. The main outcome variable was the prevalence rate of various types of glaucoma treatment in Monroe County, NY. The data were analyzed by potential risk covariates such as race/ethnicity, age, and gender. A descriptive data analysis was performed to assess for demographic trends. Results: The most common form of glaucoma treatment in Monroe County, NY was prescription drug therapy (36.82%), which was predominant across all racial, gender, and age groups. This was followed by laser surgery (3.26%), glaucoma drain (1.47%), and other forms of glaucoma surgery (0.58%). Women displayed a higher incidence of laser surgery, glaucoma drainage, and other glaucoma surgeries (3.58%, 1.77%, and 0.69%, respectively) with a lower incidence of prescription drug usage (36.14%) compared to men. Black non-Hispanic patients had a higher incidence of laser surgery and prescription drug usage (3.39% and 47.20%, respectively), but a lower incidence of glaucoma drainage and other glaucoma surgeries (1% and 0%, respectively) compared to other racial groups. Conclusions: This study elucidates the differences in glaucoma treatment types across different racial, gender, and age groups in Monroe County, NY. The results underscore the disparities in treatment rates for Medicare patients diagnosed with glaucoma in Monroe County. The results justify the need for increased interventions to increase access to a variety of glaucoma treatment options to mitigate disparities in glaucoma outcomes.

Background/Objectives: As the world becomes more connected, it is becoming critical for clinicians to understand other cultures, races, and ethnicities to provide the most effective therapy. A comprehensive understanding of all communities necessitates an examination of the social determinants of health (SDH). Eye diseases and many other conditions are influenced by SDH. To elucidate the impact of SDH on eye health, a comparative ecological analysis of Monroe and Erie Counties in New York State was conducted to identify any differences in SDH and glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy prevalence. Methods: The CDC Vision and Eye Health Surveillance System (VEHSS) was utilized to collect glaucoma, AMD, and diabetic retinopathy data in Monroe and Erie Counties, New York State, and the USA for 2019. The American Community Survey, County Health Rankings, and Neighborhood Atlas data portals were used to collect the county socioeconomic demographics, along with other health statistics. Results: Overall, Erie County had a higher prevalence of AMD (9.56% vs. 6.61%, p < 0.0001) and glaucoma (13.05% vs. 11.71%, p < 0.0001) compared to Monroe County. Erie County also had a higher prevalence of AMD and glaucoma across all races, aside from North American Natives. Erie County also had a greater primary care shortage, with only 1 primary care physician for every 1230 individuals. Although income inequality and poverty were similar between Erie and Monroe Counties, Erie County also has more racial segregation regarding the residential layout (ranked 74 on a scale of 0 to 100, with 100 being the most segregated). Conclusions: The results indicate that Erie County had an increased prevalence of AMD and glaucoma compared to Monroe County in 2019, along with a greater primary care shortage. Although this analysis targeted Western New York, disparities such as lack of primary care access and segregation are prevalent across the US, necessitating widespread action to address these problems.

Purpose: Visual impairment in children is a significant public health issue, especially for those from disadvantaged backgrounds. Vision screening by schools and pediatricians have had limited success in resolving this concern. This study examined the outcomes, challenges, and demographics of the MobilEyes program, a school-based mobile eye care initiative in Rochester, New York. Methods: During the 2022-2023 academic year, students in PreK, K, 1st, 3rd, 5th, and 7th grade underwent visual acuity screening per New York State Guidelines. A positive screen was visual acuity <20/40 for kindergarteners or younger and <20/30 for 1st graders or older. Children who failed vision screening and whose parents provided consent for school-based eye examination subsequently underwent cycloplegic refraction and dilated fundus examination by a pediatric ophthalmologist. Demographics subgroups were analyzed by school, school region, and grade level. Results: 1399 students from six schools underwent vision screening, of which 387 (27.7%) failed the initial screening. From those, 125 (32.3%) returned signed parental consent forms and 108 (27.9%) underwent full eye examinations. Of this group, 68 (63.0%) were prescribed glasses, and 40 (37.0%) did not require glasses prescription and were considered false positives. Significantly more urban students failed their vision screening than suburban students, 32.8% vs 22.5% (p<0.001), and urban students had a lower false positive vision screening result (meaning that they failed their vision screening but were found to have a normal exam) than suburban students 27.6% vs 48% (p=0.047). Across all schools we found statistically significant differences between grade levels in the number failing vision screening (p<0.001) and returning consent forms (p=0.021). Conclusion: Our data highlights the need for additional support of school screening and full eye examinations, especially in urban regions. Future studies should address the challenges of high vision screening false positivity percentages and obtaining parental consents to perform eye examinations.