Trends in Geographic Distribution of Visual Disability - United States, 2010-2019.

PURPOSE: We aimed to describe changes in the geographic distribution of self-reported visual impairment (VI) over the last decade (2010-2019) in the U.S. METHODS: Our study was an analysis of publicly available data collected between 2010 and 2019 from the Census Bureau American Community Survey. RESULTS: The mean overall prevalence of self-reported VI from 2010 to 2019 was 2.31% in the United States, and there was a significant increase in VI over the past decade from 2.25% in 2010-2014 to 2.37% in 2015-2019 (p < .001). VI was significantly higher in rural counties (3.58%), compared to urban (3.10%) or metropolitan counties (2.18%) (p < .001). In terms of geographic region, the South of the United States had the highest rate of VI (2.63%) (p < .001). For age groups > 17-years-old in the 2010-2019 data, women had higher rates of VI compared to men. CONCLUSIONS: Prevalence of self-reported visual impairment has risen and disproportionately affects certain communities. This includes individuals living in the South, in rural counties, and women.

Geographic and socioeconomic access disparities to Phase 3 clinical trials in ophthalmology in the United States.

BACKGROUND/OBJECTIVE: To identify geographic and socioeconomic variables associated with residential proximity to Phase 3 ophthalmology clinical trial sites. METHODS: The geographic location of clinical trial sites for Phase 3 clinical trials in ophthalmology was identified using ClinicalTrials.gov. Driving time from each United States (US) census tract centroid to nearest clinical trial site was calculated using real traffic patterns. Travel data were crosslinked to census-tract level public datasets from United States Census Bureau American Community Survey (ACS). Cross-sectional multivariable regression was used to identify associations between census-tract sociodemographic factors and driving time (>60 min) from each census tract centroid to the nearest clinical trial site. RESULTS: There were 2330 unique clinical trial sites and 71,897 census tracts. Shortest median time was to retina sites [33.7 min (18.7, 70.1 min)]. Longest median time was to neuro-ophthalmology sites [119.8 min (48.7, 240.4 min)]. Driving >60 min was associated with rural tracts [adjusted odds ratio (aOR) 7.60; 95% CI (5.66-10.20), p < 0.0001]; Midwest [aOR 1.84(1.15-2.96), p = 0.01], South [aOR 2.57 (1.38-4.79), p < 0.01], and West [aOR 2.52 (1.52-4.17), p < 0.001] v. Northeast; and tracts with higher visual impairment [aOR 1.07 (1.03-1.10), p < 0.001)]; higher poverty levels [4th v.1st Quartile of population below poverty, aOR 2.26 (1.72-2.98), p < 0.0001]; and lower education levels [high school v. Bachelor's degree or higher aOR 1.02 (1.00-1.03), p = 0.0072]. CONCLUSIONS: There are significant geographic and socioeconomic disparities in access to ophthalmology clinical trial sites for rural, non-Northeastern, poorer, and lower education level census tracts, and for census tracts with higher levels of self-reported visual impairment.

Patient Accessibility to Eye Care in the United States.

PURPOSE: The United States (US) federal government uses health provider shortage areas (HPSAs) to define patient accessibility to primary care physicians. It is unclear whether HPSAs can be applied to eye care providers (ECPs). Our study determined the applicability of federal HPSA designations to ECP availability in the US. DESIGN: Cross-sectional study. PARTICIPANTS: US general population and ophthalmologists/optometrists in the Medicare database. METHODS: The primary care HPSA score, visual impairment prevalence, and ECP location were determined for each census tract or county using data from the US Department of Health and Human Services, the Centers for Disease Control and Prevention, and Centers for Medicare and Medicaid Services. MAIN OUTCOME MEASURES: Association of HPSA with vision loss and ECP density was examined. The 2-step floating catchment area approach was used to newly define eye care shortage areas (patient accessibility score [PAS], higher being worse accessibility) for every county in the US, by weighting the 2-step FCA scores by prevalence of vision loss and ECP density. Multivariable logistic regression was used to identify sociodemographic variables associated with areas of ECP shortage. RESULTS: Among 72 735 census tracts included, statistically significant but weak correlations of HPSA score with visual impairment (VI) (r = 0.38; P < 0.0001) and ECP density per county population (r = -0.18; P < 0.0001) were found. Only 54.0% of census tracts with < 25th percentile ECP density per county were HPSAs (P < 0.0001). Of census tracts > than 75th percentile for VI only 58.0% were HPSAs (P < 0.0001). Multivariable regression found a higher odds of ECP PAS ≥ 75th percentile (worse accessibility) in rural counties (adjusted odds ratio [aOR], 2.47; 95% confidence interval [CI], 1.93-3.67; P < 0.001) and counties with a greater prevalence of residents with less than a high school education (aOR, 1.21; 95% CI, 1.19-1.25; P < 0.001), residents ≥ 65 years of age (aOR, 1.10; 95% CI, 1.07-1.13; P < 0.001), and uninsured residents (aOR, 1.04; 95% CI, 1.01-1.06; P < 0.001). Counties with a greater proportion of men (aOR, 0.93; 95% CI, 0.89-0.967; P < 0.001) or White residents (aOR, 0.99; 95% CI, 0.98-0.99) had a lower odds of ECP PAS ≥ 75th percentile. CONCLUSIONS: Current HPSAs only weakly correlate with ECP supply. We propose a new approach to identify counties with high need but limited access to eye care. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Association of Socioeconomic, Demographic, and Health Care Access Disparities With Severe Visual Impairment in the US.

Importance: Approximately 13% of US adults are affected by visual disability, with disproportionately higher rates in groups impacted by certain social determinants of health (SDOH). Objective: To evaluate SDOH associated with severe visual impairment (SVI) to ultimately guide targeted interventions to improve ophthalmic health. Design, Setting, and Participants: This quality improvement study used cross-sectional data from a telephone survey from the Behavioral Risk Factor Surveillance System (BRFSS) that was conducted in the US from January 2019 to December 2020. Participants were noninstitutionalized adult civilians who were randomly selected and interviewed and self-identified as "blind or having serious difficulty seeing, even while wearing glasses." Exposures: Demographic and health care access factors. Main Outcomes and Measures: The main outcome was risk of SVI associated with various factors as measured by odds ratios (ORs) and 95% CIs. Descriptive and logistic regression analyses were performed using the Web Enabled Analysis Tool in the BRFFS. Results: During the study period, 820 226 people (53.07% female) participated in the BRFSS survey, of whom 42 412 (5.17%) self-identified as "blind or having serious difficulty seeing, even while wearing glasses." Compared with White, non-Hispanic individuals, risk of SVI was increased among American Indian/Alaska Native (OR, 1.63; 95% CI, 1.38-1.91), Black/African American (OR, 1.50; 95% CI, 1.39-1.62), Hispanic (OR, 1.65; 95% CI, 1.53-1.79), and multiracial (OR, 1.33; 95% CI, 1.15-1.53) individuals. Lower annual household income and educational level (eg, not completing high school) were associated with greater risk of SVI. Individuals who were out of work for 1 year or longer (OR, 1.78; 95% CI, 1.54-2.07) or who reported being unable to work (OR, 2.90; 95% CI, 2.66-3.16) had higher odds of SVI compared with the other variables studied. Mental health diagnoses and 14 or more days per month with poor mental health were associated with increased risk of SVI (OR, 1.87; 95% CI, 1.73-2.02). Health care access factors associated with increased visual impairment risk included lack of health care coverage and inability to afford to see a physician. Conclusions and Relevance: In this study, various SDOH were associated with SVI, including self-identification as being from a racial or ethnic minority group; low socioeconomic status and educational level; long-term unemployment and inability to work; divorced, separated, or widowed marital status; poor mental health; and lack of health care coverage. These disparities in care and barriers to health care access should guide targeted interventions.

A Geographic Analysis of Google Characterizations of Who Is an "Eye Doctor" Across the US.

Importance: In order to continue to clarify and maintain their role as eye physicians and surgeons, ophthalmologists may want to understand how they are viewed in the public eye and online. Objective: To determine the representation of ophthalmologists (OMD) and optometrists (ODs) when a Google search for "eye doctor near me" is made from each county in the US. Design, Setting, and Participants: This population-based cross-sectional study used publicly available data on OMDs and ODs and a Google search application programming interface (API) to search the phrase "eye doctor near me" from the geographic coordinates of each county centroid in the US (searched June 30, 2021). The top 10 sites and 3 Google map links, excluding physician ratings sites, were recorded. Data from the US Centers for Medicare and Medicaid Services were used to estimate the real number of OMDs and ODs per county. Main Outcome and Measures: The primary outcome was the mean proportion of OMDs listed by Google search as compared with the real proportion of OMDs for the US overall and for each state and county. Results: A total of 2955 counties from 52 states and territories were included. The overall mean proportion of OMDs (OMDs with ODs) from the Google search of all counties was 4726.97 of 16 345.93 (28.91%), which was also less than the real proportion of ODs (15 778 of 41 975 [37.58%], a difference of 8.67%; 95% CI, 37.13-38.05%; P < .001). OMDs were underrepresented by Google in 35 of 52 states and territories (67.3%). Conclusions and Relevance: In most counties in the US, Google search of the phrase "eye doctor near me" may underrepresent ophthalmologists. Ophthalmologists may want to pursue search engine optimization to try to achieve balanced representation online.

Persistent Opioid Use after Ophthalmic Surgery in Opioid-Naive Patients and Associated Risk Factors.

PURPOSE: To determine the rate and risk factors for new persistent opioid use after ophthalmic surgery in the United States. DESIGN: Retrospective claims-based cohort analysis. PARTICIPANTS: Opioid-naive patients 13 years of age and older who underwent incisional ophthalmic surgery between January 1, 2012, and June 30, 2017, and were included in Optum's de-identified Clinformatics Data Mart database. METHODS: New persistent opioid use was defined as filling an opioid prescription in the 90-day and the 91- to 180-day periods after the surgical procedure. The outcome variable was an initial perioperative opioid prescription fill. Rates of new persistent opioid use were calculated, and multivariate logistic regression models were used to identify variables increasing the risk of new persistent use and refill of an opioid prescription after the initial perioperative prescription in first 30 days. MAIN OUTCOME MEASURES: New persistent opioid use and refill. RESULTS: A total of 327 379 opioid-naive patients (mean age, 67 years [standard deviation, 16 years]; 178 067 women [54.4%]) who underwent ophthalmic surgery were examined. Among these patients, 14 841 (4.5%) had an initial perioperative opioid fill. The rate of new persistent opioid use was 3.4% (498 of 14 841 patients) compared with 0.6% (1833 of 312 538 patients) in patients who did not have an initial perioperative opioid fill. After adjusting for patient characteristics, initial perioperative opioid fill was associated independently with increased odds of new persistent use (adjusted odds ratio [OR], 6.21; 95% confidence interval [CI], 5.57-6.91; P < 0.001). Among patients who had filled an initial perioperative prescription, a prescription size of 150 morphine milligram equivalents or more was associated with an increased odds of refill (adjusted OR, 1.87; 95% CI, 1.58-2.22; P < 0.001). CONCLUSIONS: Exposure to opioids in the perioperative period is associated with new persistent use in patients who were previously opioid-naive. This suggests that exposure to opioids is an independent risk factor for persistent use in patients undergoing incisional ophthalmic surgery. Surgeons should be aware of those risks to identify at-risk patients given the current national opioid crisis and to minimize prescribing opioids when possible.

Epidemiology and management of uveal melanoma.

Uveal melanoma is the most common primary intraocular malignancy in adults. The disease overwhelmingly affects white populations. Other risk factors include fair skin, light iris color, ancestry from northern latitudes, and ocular/oculodermal melanocytosis. Historically, enucleation was the definitive treatment of uveal melanoma, but brachytherapy and proton beam irradiation are now the most commonly used treatment methods. However, there are still no effective therapies against metastatic uveal melanoma, which is almost always fatal. Continued advances in understanding of the molecular mechanisms of uveal melanoma will facilitate the identification of prognostic markers and therapeutic targets.