Epidemiologic trends of domestic violence-related ocular injuries among pediatric patients: data from the Nationwide Emergency Department Sample 2008-2017.

PURPOSE: To study the epidemiology of all domestic violence (DV)-related ocular injuries among pediatric emergency department (ED) patients in the United States. METHODS: This is a retrospective, cross-sectional study of isolated children (<18 years of age) with a diagnosis of DV and primary or secondary diagnosis of ocular injuries in the Nationwide Emergency Department Sample, 2008-2017. We calculated annual incidence of DV-related ocular injuries and prevalence by demographic variables, including age, sex, and income quartile. Median charges, median length of inpatient hospital stay, and factors associated with hospitalization were also measured. RESULTS: From 2008 to 2017, there were 4,125 ED encounters, with an average incidence of 0.56 per 100,000 population (males, 50.0%; mean age [SE], 9.2 [0.3]). Patients in the lowest income quartile (42.6%) and with Medicaid insurance (63.2%) were the most prevalent. The most common known perpetrator was a family member (29.4%). Most ED encounters took place at southern regional (28.6%), metropolitan teaching (67.1%) and designated trauma hospitals (57.8%). Contusion of the eye/adnexa and being struck by or against an object were the most common ocular diagnosis and known mechanism of injury, respectively. An estimated 12.4% of patients were admitted with a median hospital stay of 4 (IQR, 2-6). Median charges during the study period were $27,415.10 (IQR, $13,142.70-$54,454.90). CONCLUSIONS: DV-related ocular injuries were most prevalent among patients with a low socioeconomic status. Given the historical underreporting of DV, future studies are warranted to identify more specific social determinants of health that contribute to such presentations.

Factors Associated With Visual Impairment Among Adults With a History of Criminal Justice Involvement.

The purpose of this study was to investigate the prevalence of and factors associated with visual impairment among adults with a history of criminal justice involvement (CJI). This retrospective, cross-sectional study reviewed adult respondents from the 2015-2018 National Survey on Drug Use and Health. We analyzed sociodemographic and health characteristics to determine factors associated with visual impairment among adults with and without a history of CJI. In this national, population-based study, we found similar rates of visual impairment among adults with and without CJI (5.7% vs. 4.2%, p < .001). However, adults with CJI were more likely to report visual impairment at a younger age. Among adults with CJI, visual impairment was associated with female sex, older age, Black/African American race, less education, lower income, and chronic health conditions (including diabetes, heart disease, respiratory illness, mental health symptoms, and hearing impairment). CJI in the past year (probation [adjusted odds ratio, AOR, 0.70; 95% confidence interval, CI, 0.53-0.93]; one arrest [AOR, 1.47; 95% CI, 1.14-1.89]; two or more arrests [AOR, 1.73; 95% CI, 1.29-2.33]) was uniquely associated with visual impairment among adults with a CJI history (p < .05 for all relationships). Research, screening, and treatment for visual impairment should include those with justice involvement to improve health equity.

Domestic Violence-Related Ocular Injuries Among Adult Patients: Data from the Nationwide Emergency Department Sample, 2008-2017.

PURPOSE: To investigate domestic violence (DV)-related ocular injuries among adult emergency department (ED) patients in the US. METHODS: This was a retrospective, cross-sectional study of patients with a diagnosis of DV and diagnosis of ocular injury in the Nationwide Emergency Department Sample (NEDS) from 2008-2017. We identified patient- and hospital-level variables associated with DV-related ocular injuries. We calculated annual incidence rates using US Census data. Adjusting for inflation using the Consumer Price Index, we calculated mean and total charges. RESULTS: From 2008-2017, there were 26,215 ED visits for ocular injuries related to DV with an average incidence of 1.09 per 100,000 adult population (female patients, 84.5%; mean age [SE], 34.3 [0.2]). DV-related ocular injuries were most prevalent among patients in the lowest income quartile (39.1%) and on Medicaid (37.4%). Most ED visits presented to metropolitan teaching (55.4%), non-trauma (46.7%), and south regional (30.5%) hospitals. The most common ocular injury was contusion of eye/adnexa (61.1%). The hospital admission rate was 5.2% with a mean hospital stay of 2.9 [0.2]. The inflation-adjusted mean cost for medical services was $38,540 [2,310.8] per encounter with an average increase of $2,116 per encounter, annually. The likelihood of hospital admission increased for patients aged ≥60 years old, on Medicare, and with open globes or facial/orbital fractures (all p < .05). CONCLUSION: Contusion of the eye/adnexa was the most common ocular injury among patients with DV-related ED visits. To better facilitate referrals to social services, ophthalmologists should utilize DV screenings, especially towards women and patients of less privileged socioeconomic status.

Disparities in Eye Care Access and Utilization: A Narrative Review.

This narrative review summarizes the literature on factors related to eye care access and utilization in the United States. Using the Healthy People 2030 framework, this review investigates social determinants of health associated with general and follow-up engagement, screenings, diagnostic visits, treatment, technology, and teleophthalmology. We provide hypotheses for these documented eye care disparities, featuring qualitative, patient-centered research. Lastly, we provide recommendations in the hopes of appropriately eliminating these disparities and reimagining eye care.

Racial, Ethnic, and Socioeconomic Disparities Drive Appointment No-Show in Patients with Chronic Eye Disease.

BACKGROUND: Visit no-shows (NS) reduce clinic efficiency and effective resource allocation. Inadequate follow-up among patients with chronic eye disease increases risk of disease progression. Our study identifies demographic, medical, and socioeconomic characteristics that increase odds of NS among patients with chronic eye conditions at high risk of vision-threatening complications. METHODS: This is a retrospective case-control study of data abstracted over a 5-year period (January 2013-December 2018) in an urban academic ophthalmology practice. Follow-up appointments of patients ≥ 18 years of age with a diagnosis of glaucoma, diabetic retinopathy, or age-related macular degeneration were included. Age, sex, race, ethnicity, language preference, zip code, and relevant medical history were recorded. A multivariate mixed logistic regression model was utilized to determine any association between demographic factors and visit NS. RESULTS: A total of 106,652 visits for 4,598 unique patients were included in this study. Of these, 13,240 (12.4%) visits were NS. Patient characteristics that increased the odds of NS included Hispanic ethnicity (p < 0.0001), Black race (p < 0.0001), and a history of mental illness (p < 0.0001). Socioeconomic factors that increased the odds of NS included median household income < $40,000 (p = 0.002), Medicare insurance (p < 0.0001), and Medicaid insurance (p < 0.0001). CONCLUSIONS: Our results highlight the influence of ethnic, racial, medical, and socioeconomic characteristics on appointment NS among patients with chronic eye disease. Future interventions aimed at reducing appointment NS could channel resources to the at-risk populations identified in this analysis to improve access to care for those who need it most.

Data Sources for Evaluating Health Disparities in Ophthalmology: Where We Are and Where We Need to Go.

Data provide an opportunity to discover disparities and inequities that may otherwise be unrecognized. Within the American Academy of Ophthalmology (AAO) Task Force on Disparities in Eye Care, the Leveraging Data Sub-task Force was charged with identifying data sources to study health disparities in eye care and to leverage data to advance health equity. We evaluated large data sources to determine their strengths, deficiencies, and relative accessibility in relation to the likelihood of identifying eye care disparities. We highlight the current challenges with these data sources and review key recommendations for improving future sources for studying health disparities in eye care.

The Impact of Image Processing Algorithms on Optical Coherence Tomography Angiography Metrics and Study Conclusions in Diabetic Retinopathy.

Purpose: The purpose of this study was to evaluate the impact of image processing on quantitative metrics in optical coherence tomography angiography (OCTA) images and study conclusions in patients with diabetes. Methods: This was a single center, retrospective cross-sectional study. OCTA imaging with the Cirrus HD-OCT 5000 AngioPlex of patients with diabetes was performed. The 8 × 8 mm superficial slab images underwent 4 different preprocessing methods (none, background subtraction [BGS], foveal avascular zone brightness adjustment, and contrast limited adaptive histogram equalization [CLAHE]) followed by 4 different binarization algorithms (global Huang, global Otsu, local Niblack, and local Phansalkar) in ImageJ. Vessel density (VD), skeletonized VD (SVD), and fractal dimension (FD) were calculated. Mixed-effect multivariate linear regressions were performed. Results: Two hundred eleven scans from 104 patients were included. Of these scans, 67 (31.8%) had no diabetic retinopathy (DR), 99 (46.9%) had nonproliferative DR (NPDR), and 45 (21.3%) had proliferative DR (PDR). Forty-eight of 211 (22.7%) scans had diabetic macular edema (DME). The image processing method used significantly impacted values of VD, SVD, and FD (all P -values < 0.001). On multivariate analysis, the image processing method changed the clinical variables significantly associated with VD, SVD, and FD. However, BGS and CLAHE yielded more consistent significant covariates across multiple binarization algorithms. Conclusions: The image processing method can impact the conclusions of any given study analyzing quantitative OCTA metrics. Thus, caution is urged in the interpretation of such studies. Background subtraction or CLAHE may play a role in the standardization of image processing. Translational Relevance: This work proposes strategies to achieve robust and consistent analysis of OCTA imaging, which is especially important for clinical trials.

Deep learning for quality assessment of optical coherence tomography angiography images.

Optical coherence tomography angiography (OCTA) is an emerging non-invasive technique for imaging the retinal vasculature. While there are many promising clinical applications for OCTA, determination of image quality remains a challenge. We developed a deep learning-based system using a ResNet152 neural network classifier, pretrained using ImageNet, to classify images of the superficial capillary plexus in 347 scans from 134 patients. Images were also manually graded by two independent graders as a ground truth for the supervised learning models. Because requirements for image quality may vary depending on the clinical or research setting, two models were trained-one to identify high-quality images and one to identify low-quality images. Our neural network models demonstrated outstanding area under the curve (AUC) metrics for both low quality image identification (AUC = 0.99, 95%CI 0.98-1.00, [Formula: see text] = 0.90) and high quality image identification (AUC = 0.97, 95%CI 0.96-0.99, [Formula: see text] = 0.81), significantly outperforming machine-reported signal strength (AUC = 0.82, 95%CI 0.77-0.86, [Formula: see text]= 0.52 and AUC = 0.78, 95%CI 0.73-0.83, [Formula: see text] = 0.27 respectively). Our study demonstrates that techniques from machine learning may be used to develop flexible and robust methods for quality control of OCTA images.

Socioeconomic and Demographic Disparities in the Use of Telemedicine for Ophthalmic Care during the COVID-19 Pandemic.

PURPOSE: To identify disparities in the use of telemedicine during the coronavirus disease 2019 (COVID-19) pandemic. DESIGN: A cross-sectional study of completed clinical encounters in an academic ophthalmology center from March 2020 through August 2020. PARTICIPANTS: A total of 5023 patients comprising 8116 ophthalmic clinical encounters. METHODS: Medical charts were abstracted for demographic information. We identified zip code-level socioeconomic characteristics, which were drawn from the 2019 American Community Survey 5-year estimates. MAIN OUTCOME MEASURES: The completion of a synchronous video encounter, the completion of a telephone (audio-only) encounter in the absence of any video encounters, or the completion of in-person encounters only. RESULTS: During the study period, 8116 total clinical encounters were completed for 5023 unique patients. Of these patients, 446 (8.9%) participated in a video encounter, 642 (12.8%) completed a telephone encounter, and 3935 (78.3%) attended clinical appointments in person only. In adjusted analysis, patients who were Black (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.52-0.80; P < 0.001) or Hispanic/Latino (OR, 0.65; 95% CI, 0.49-0.85; P = 0.002) were significantly less likely to complete a video or telephone appointment. Older patients (OR, 0.99; 95% CI, 0.98-0.99; P < 0.001), patients whose primary language was not English (OR, 0.49; 95% CI, 0.28-0.82; P = 0.01), Black patients (OR, 0.45; 95% CI, 0.32-0.62; P < 0.001), and Hispanic/Latino patients (OR, 0.56; 95% CI, 0.37-0.83; P = 0.005) were significantly less likely to complete a video encounter. Finally, among patients completing any type of telemedicine encounter, older age, (OR, 1.02; 95% CI, 1.01-1.03; P < 0.001), Medicare insurance (OR, 1.55; 95% CI, 1.11-2.17; P = 0.01), and Black race (OR, 1.97; 95% CI, 1.33-2.94; P < 0.001) were associated with using only phone visits. CONCLUSIONS: Ethnic/racial minorities, older patients, and non-English-speaking individuals were significantly less likely to complete a video telehealth encounter. With the expansion of telemedicine and the need to reduce the disparate impact of COVID-19 on minorities, it will be increasingly important to identify barriers to telehealth use and opportunities to improve access.

Awareness of Diabetic Retinopathy: Insight From the National Health and Nutrition Examination Survey.

INTRODUCTION: This study determines the prevalence and associated correlates of people unaware of their diabetic retinopathy diagnosis in the U.S. METHODS: Participants unaware of diabetic retinopathy from the National Health and Nutrition Examination Survey from 2005 to 2008 were identified. The prevalence of those unaware of their diabetic retinopathy diagnosis was determined. Descriptive statistics and logistic regression were used to determine correlates associated with being unaware of one's diabetic retinopathy diagnosis (completed in 2018‒2020). RESULTS: Among 5,563 participants aged ≥40 years who underwent fundus photography, the prevalence of those unaware of their diabetic retinopathy diagnosis was 10.6% (9.8 million). This included 23.1% of those with self-reported diabetes (2.9 million) and 6.8% of those who reported not having diabetes (6.9 million). Among participants reporting diabetes with photographic evidence of retinopathy, 70.1% were unaware. Among individuals with self-reported diabetes, correlates of being unaware of one's diabetic retinopathy diagnosis included diabetes diaganosis for ≥10 years (OR=3.15, 95% CI=1.78, 5.56), HbA1c ≥6.5% (OR=2.92, 95% CI=1.65, 5.18), and treatment with insulin only (OR=4.04, 95% CI=1.43, 11.39). Self-reported hypertension was associated with decreased odds of undiagnosed diabetic retinopathy (OR=0.48, 95% CI=0.28, 0.82). Among those without self-reported diabetes, correlates of being unaware of diabetic retinopathy included older age (OR=1.02, 95% CI=1.01, 1.04), male sex (OR=1.83, 95% CI=1.31, 2.56), Black race (OR=1.81, 95% CI=1.12, 2.92), Hispanic race/ethnicity (OR=1.60, 95% CI=1.14, 2.25), elevated blood pressure (OR=1.54, 95% CI=1.23, 1.93), current smoking (OR=1.74, 95% CI=1.21, 2.51), and history of stroke (OR=2.20, 95% CI=1.06, 4.58). CONCLUSIONS: A substantial proportion of individuals with diabetic retinopathy are unaware of the diagnosis. These data provide a path toward refining efforts to diagnose and treat diabetic retinopathy to decrease the burden of preventable blindness.

Ophthalmology Departments Remain Among the Least Diverse Clinical Departments at United States Medical Schools.

PURPOSE: The current demographics of the ophthalmology workforce do not reflect the diverse United States population, which has implications for addressing health disparities. The demographics of ophthalmology department faculty may influence the recruitment of underrepresented students into the field. This study sought to determine how the racial and ethnic demographics of ophthalmology department faculty compare with those of other clinical departments at United States medical schools. DESIGN: Secondary data analysis of medical school faculty demographic data from the 2019 American Association of Medical Colleges (AAMC) Faculty Roster. PARTICIPANTS: Clinical faculty and department chairs at United States medical schools. METHODS: We analyzed the racial and ethnic demographics of clinical department faculty and department chairpersons using data from the 2019 AAMC Faculty Roster. We calculated the proportion of underrepresented minority (URM) faculty in ophthalmology and in 17 other clinical departments. We analyzed these data for statistically significant differences between ophthalmology and other clinical departments. In addition, we compared the percentage of URM ophthalmology faculty with the proportion of URM persons among graduating United States medical students and in the United States population using data from the Medical School Graduation Questionnaire and the United States census, respectively. MAIN OUTCOME MEASURES: The proportion of URM persons, defined as Black, Hispanic or Latino, Native American, or Native Hawaiian or Pacific Islander among clinical faculty and department chairs. RESULTS: Ophthalmology faculty are less racially and ethnically diverse than graduating medical students and the general United States population. When compared with 17 other clinical departments, ophthalmology has the third-lowest proportion of URM faculty, with only radiology and orthopedic surgery having a smaller proportion of URM faculty. These differences were statistically significant in most departments (12 of 18). No statistically significant difference was found in the proportion of URM department chairs in ophthalmology compared with most other clinical departments, although the absolute number of URM chairs in ophthalmology is low at only 8 chairpersons. CONCLUSIONS: More work must be done to increase the recruitment of URM physicians into ophthalmology faculty positions to obtain parity with other clinical departments and with the diverse patient populations that physicians serve.

Ophthalmic Emergency Department Visits: Factors Associated With Loss to Follow-up.

PURPOSE: To describe follow-up rates for patients referred for outpatient ophthalmic care after emergency department (ED) discharge and identify patient and visit characteristics associated with loss to follow-up (LTFU). DESIGN: Single-institution retrospective cohort study. METHODS: We analyzed the medical records of 2,206 patients seen in the ED for an eye-related issue who were subsequently scheduled for ophthalmology follow-up between 2013 and 2019 at a single tertiary health system. The main outcome measures were the frequency of and risk factors for LTFU and ED revisits. RESULTS: In total, 1,649 (74.8%) patients completed follow-up within 2 months of an index ED visit. In multivariable analysis, younger age (P < .001), a nonurgent ophthalmic condition or nonophthalmic primary diagnosis (P < .001), scheduled follow-up >5 days after the ED visit (P < .001), additional follow-up appointments (<.001), no prior history of ophthalmology appointments (P = .045), a visual acuity of 20/40 or better (P = .027), and having Medicaid or being uninsured (P < .001) were significantly associated with LTFU. The presence of an interpreter significantly increased the likelihood of follow-up among non-English speaking patients (P < .001). LTFU was significantly associated with an ED revisit within 4 months of an index visit, and the ED revisit rate was significantly higher for patients LTFU vs those who completed follow-up (5.7% vs 1.1%; P < .001). CONCLUSIONS: A quarter of patients referred for ophthalmic care after an ED presentation were LTFU. We identified numerous factors associated with LTFU that could be used to develop interventions to enhance follow-up. In addition, patients who were LTFU were more likely to revisit the ED for the same ophthalmic condition.

Ophthalmic Medication Expenditures and Out-of-Pocket Spending: An Analysis of United States Prescriptions from 2007 through 2016.

PURPOSE: To estimate temporal trends in total and out-of-pocket (OOP) expenditures for ophthalmic prescription medications among adults in the United States. DESIGN: Retrospective, longitudinal cohort study. PARTICIPANTS: Participants in the 2007 through 2016 Medical Expenditure Panel Survey (MEPS) 18 years of age or older. The MEPS is a nationally representative survey of the noninstitutionalized, civilian United States population. METHODS: We estimated trends in national and per capita annual ophthalmic prescription expenditures by pooling data into 2-year cycles and using weighted linear regressions. We also identified characteristics associated with greater total or OOP expenditures with multivariate weighted linear regression. Costs were adjusted to 2016 United States dollars using the gross domestic product price index. MAIN OUTCOME MEASURES: Trends in total and OOP annual expenditures for ophthalmic medications from 2007 through 2016 as well as factors associated with greater expenditures. RESULTS: From 2007 through 2016, 9989 MEPS participants (4.2%) reported ophthalmic medication prescription use. Annual ophthalmic medication use increased from 10.0 to 12.2 million individuals from 2007 and 2008 through 2015 and 2016. In this same period, national expenditures for ophthalmic medications increased from $3.39 billion to $6.08 billion and OOP expenditures decreased from $1.34 to $1.18 billion. Per capita expenditure increased from $338.72 to $499.42 (P < 0.001), and per capita OOP expenditure decreased from $133.48 to $96.67 (P < 0.001) from 2007 and 2008 through 2015 and 2016, respectively. From 2015 through 2016, dry eye (29.5%) and glaucoma (42.7%) medications accounted for 72.2% of all ophthalmic medication expenditures. Patients who were older than 65 years (P < 0.001), uninsured (P < 0.001), and visually impaired (P < 0.001) were significantly more likely to have greater OOP spending on ophthalmic medications. CONCLUSIONS: Total ophthalmic medication expenditure in the United States increased significantly over the last decade, whereas OOP expenses decreased. Increases in coverage, copayment assistance, and use of expensive brand drugs may be contributing to these trends. Policy makers and physicians should be aware that rising overall drug expenditures ultimately may increase indirect costs to the patient and offset a decline in OOP prescription drug spending.

Barriers to and Facilitators of Diabetic Retinopathy Screening Utilization in a High-Risk Population.

BACKGROUND: Diabetic retinopathy (DR) is among the leading causes of vision loss in the USA, yet an estimated 50% of patients with diabetes do not receive recommended annual screening eye exams. Patients with diabetes and low socioeconomic status or who are racial/ethnic minorities are at increased risk for vision loss. METHODS: Qualitative interviews were conducted with 24 patients with diabetes at a federally qualified community health center in an urban area regarding factors influencing their use of screening. The interviews were recorded, transcribed, and analyzed line by line to identify themes. The themes were organized in a theoretical framework of factors influencing receipt of screening. RESULTS: The median age of participants was 57.5 (range 44-73). Ten participants identified as female and 14 as male. Participants identified as Black (14), White (4), Hispanic (3), and other/no answer (3). Twenty-three had health insurance. Twenty-three had received an eye exam within in the past year, and 17 reported that they receive eye exams at least yearly. Four hundred fifteen comments were analyzed, and 22 concepts were identified under 7 broader themes and two overarching categories of individual and structural factors. Themes included vision status, competing concerns, emotional context, resource availability, in-clinic experience, cues to action, and knowledge about diabetes. CONCLUSIONS: The factors that influence diabetic retinopathy screening utilization are complex. Visual symptoms and the need for glasses are important facilitators of screening. Many patients lack knowledge about diabetic retinopathy and the utility of preventative eye care. New strategies for engaging high-risk populations are necessary.