The SIGHT Studies used recruitment materials, clinical protocols and manual of procedures approved by their Institutional Review Boards (IRBs) (University of Alabama at Birmingham IRB300004921; University of Michigan IRB00000244, and Columbia University IRB-AAAR9162). The IRBs at Columbia University and Westat approved their coordinating center function (Columbia University IRB-AAAT0194; Westat IRB/FWA #00005551) to collect and synthesize deidentified data. All aspects of the study were conducted in accordance with the Declaration of Helsinki and compliance with Health Insurance Portability and Accountability Act (HIPAA).

In order to reach high-risk individuals living at or below the poverty level, recruitment and eye health screenings were conducted from 2020 to 2023.¹⁹ The AL-SIGHT team partnered with three FQHCs in rural areas to recruit eligible participants and conducted screenings in these health centers.²⁰ The MI-SIGHT study team partnered with two community-based healthcare facilities, a free clinic, and a FQHC, and recruited eligible participants and conducted screenings in these clinics.²¹ The NYC-SIGHT study team partnered with the NYC Housing Authority and the NYC Department for the Aging to recruit and conduct eye health screenings in community centers and senior centers located where people live in Harlem and Washington Heights neighborhoods.^22,23

AL-SIGHT: Individuals who were (1) African American or Hispanic ≥40 years of age; (2) White ≥50 years of age; (3) anyone ≥18 years of age with diabetes, (4) anyone ≥18 years of age with a glaucoma-associated diagnosis, and (5) anyone ≥18 years of age with a family history of glaucoma.

MI-SIGHT: Individuals who were (1) ≥18 years of age with diabetes mellitus, (3) African-Americans ≥40 years of age, (4) Latinos ≥60 years of age, (5) Caucasians ≥65 years of age, and (6) persons from all ethnic backgrounds with a family history of glaucoma.

NYC-SIGHT: Individuals who were (1) ≥40 years of age, and (2) living independently in affordable housing developments or a member of the senior center.

Across all sites, those who met the study’s inclusion criteria were consented over the telephone or in person. Only enrolled participants age 40 and older were included in this analysis.

Participants completed a survey prior to the screening and reported their date of birth, sex, race/ethnicity, education level, health insurance, employment, marital status, and transportation methods to medical appointments.

Medical and ocular conditions, prescription eyeglasses use, and family history of glaucoma and blindness were asked. Participants were asked if they ever had a dilated eye exam and if so, approximately when was their last dilated eye exam. Participants who had not had a recent dilated eye exam were asked for the main reason for not attending.

Methods used to detect eye diseases across the SIGHT Studies are described below, including the similarities and differences Table 1 and have been previously published.^20–22

In AL-SIGHT Study, the FQHC staff was notified of participants needing follow-up eye exam referrals and they scheduled all appointments and communicated this to the participant; this information was also communicated to the study coordinator who kept in contact with the participant to facilitate making reminders to attend appointments. The coordinator tracked appointment adherence at the optometrist’s or ophthalmologist’s office. Participants who were “no-shows” to appointments were scheduled for new appointments for a period of up to six months. The coordinator documented the participant’s appointment adherence for a period of six months by remaining in contact with all clinics where participants were referred.

In MI-SIGHT Study, the ophthalmic technicians who conducted the remote telemedicine assessment also functioned as health educators and care navigators. After the remote ophthalmologist graded the data and gave follow-up recommendations, participants returned for a second visit with the ophthalmic technician. At that second visit, the ophthalmic technician dispensed the glasses from the on-line retailer and ensured a proper fit, educated the participants about the doctor’s findings and recommendations, and assisted the patient in making the appropriate follow-up appointment. In addition, if a patient needed assistance with transportation, interpretation, or insurance, if the ophthalmic technician could not provide the assistance they helped connect the participant with a social worker or a community resource to provide the assistance.

In NYC-SIGHT Study, all eye exam dates were documented in the Research Electronic Data Capture (REDCap) and study staff reviewed EPIC electronic medical records (EMR) each time a participant was scheduled to document appointment adherence over 10 months.

The SIGHT Studies Coordinating Center received summarized data, including demographic, social determinants of health indicators, medical and ocular history, detection of eye diseases, and referred and not referred for in-office follow-up eye care from the three SIGHT Studies. The data were aggregated into a single database and analyzed separately by the coordinating center biostatistician. Only enrolled participants age 40 and older were included in this analysis.

Participant characteristics were compared between those referred and not referred for in-office eye care. A two-sample t-test and Fisher’s exact test and chi-square test were used to compare continuous and categorical variables, respectively, between those referred and not referred stratified by site. p values of ≤0.05 (two-sided) were considered statistically significant. The R 4.4.0 statistical software and IBM Statistical Package for Social Science Version 28 (IBM Corp. Armonk, NY) (IBM SPSS Statistics for Windows Version 28.0. 2021) were used for data analysis.

For consistent data analysis across the three sites, only enrolled participants over age 40 are described and presented in Tables 2–4. SIGHT Studies screened 4,516 participants over age 40 and each location detected a substantial amount of eye disease requiring referral for in-office eye care [total referred: AL: (47.3%); MI: (42.8%); NYC: (66.1%)] Table 2. The highest rates of uncorrected refractive error (76.8%) and cataracts (45.9%) were seen at the AL-SIGHT Study. Glaucoma/glaucoma suspects, including ocular hypertension detection rates, ranged from 18.6% at AL-SIGHT, 24% at MI-SIGHT, and 26.7% at NYC-SIGHT Table 2, including those with pre-existing glaucoma.

AL-SIGHT enrolled 838 participants for screening. A large percentage (76.8%) had uncorrected refractive error with 83 (9.9%) having vision impairment in the better seeing eye, 148 (18.6%) with glaucoma associated diagnoses, 52 (7.1%) with diabetic retinopathy, and 19 (2.4%) with macular degeneration. Almost half of participants had cataract (n = 375, 45.9%).

MI-SIGHT included 2970 participants age 40+ in this analysis. Of these participants, 711/2970 (24%) were referred for glaucoma/suspected glaucoma, 160/2970 (5%) for diabetic retinopathy, 64/2970 (2%) for macular degeneration, 215/2970 (7%) for surgical cataract evaluation, and 471/2970 (16%) for other eye conditions (e.g. retinal abnormalities, corneal abnormalities, etc.); participants could have more than one reason for referral. Those with a screening result for glaucoma (n = 2965), 119 self-reported a previous diagnosis of glaucoma, 484 reported no prior glaucoma diagnosis, and 108 didn’t answer the question; thus, the incident rate of glaucoma could be between 16.3% (484/2965) if we include only those who reported no prior history of glaucoma and 20.0% (484 + 108/2965) if we include both those who did not report a prior history of glaucoma and those who did not answer the question.

NYC-SIGHT: Of the 308 participants who had completed the eye exam, 218 were referred to ophthalmology and 257 were diagnosed with refractive error. Reasons for referral included: glaucoma/glaucoma suspect (n = 51), cataracts (n = 74), retinal abnormalities (n = 17), other ocular diagnosis (n = 22), and no dilated eye exam in at least 2 years, could not remember their last eye exam, or never had an eye exam (n = 103). Based on telemedicine image data from the worse eye of those referred to ophthalmology, 250 participants had an abnormal image, 138 were referred for an in-office glaucoma evaluation due to an abnormal optic disc image, and those with pre-existing glaucoma were excluded.

Although the referral criteria varied between the three SIGHT Studies, as shown in Table 1, all sites used visual acuity, IOP measurements, and fundus/optic nerve photography as criteria for referrals. AL-SIGHT and MI-SIGHT also used OCT results. Participants across all sites with an IOP ≥23 mmHg, and/or an abnormal fundus image, read and confirmed by an ophthalmologist, were referred. The NYC-SIGHT Study optometrist also referred participants who failed the eye health screening and had not had an eye exam within 2 years for an in-office eye exam, as recommended by the Data Safety and Monitoring Board.

Mean age was significantly higher across all sites for those referred to in-office eye care compared to those who were not referred and ranged from age 62 (AL) to age 70 years (NYC) Table 3. Significantly higher referral rates were noted for participants age 60–79 years and ≥80 years at NYC-SIGHT (p < 0.001) and >80 years at MI-SIGHT (p < 0.001) compared to those age 40–59 years Table 3. There were no significant differences in referral rates seen between men and women across the sites. In NYC-SIGHT, participants who were employed, unemployed, retired, or unable to work (p < 0.030) or had Medicare insurance had higher referral rates for in-office eye care compared to those who were not referred (p = 0.002). The majority of participants across all sites had health insurance Table 3. No other statistically significant differences were seen between those referred and not referred with regard to SDOH.

Higher referral rates were seen in participants who self-reported diabetes across all locations (AL: 50.4%; MI: 53.8%; NYC: 73.3%) Table 4. In both MI-SIGHT (p < 0.001) and NYC-SIGHT (p < 0.027), self-reported hypertension rates were higher among those referred compared to those not-referred. Referral rates for participants who self-reported having glaucoma were higher in MI-SIGHT and NYC-SIGHT (p < 0.001). At AL-SIGHT, participants who reported their last dilated eye exam more than 2 years ago (p < 0.001) and at MI-SIGHT, those who had a dilated eye exam within the past year (p < 0.001) were more likely to be referred. Main reasons stated by participants across the three sites for no dilated eye exam in the past 2 years for both referred and non-referred participants are shown in Table 4, with the majority stating they had no reason to go to the eye exam, not thought about the eye exam, no vision insurance, the cost of the eye exam, and other non-specific reasons.

AL-SIGHT: A total of 396 participants (47.3%) were referred for in-office follow-up eye examinations.

MI-SIGHT: At the end of study period, 72% of participants who were high-risk referrals and 40+ years old (927of 1271) had 1 year elapse since follow-up recommendations were given. Information on attendance at recommended follow-up with an ophthalmologist within that year was obtained on 577 of these participants, of whom 481 (83%) attended follow-up. If we assume that those who we were unable to obtain follow-up information on were non-adherent, the rate of attending recommended follow-up could be as low as 52% (481 of 927).

NYC-SIGHT: Of 468 referred participants in NYC-SIGHT, 47% (n = 220/468) attended the initial in-office eye exam. Adherence rates: Navigator Intervention (71.8%) versus Usual Care (28.2%).²⁹

In order to understand how the SIGHT Studies data related to national prevalence data, only enrolled participants age 40 and older were included in this comparison. Eye disease detection rates across the SIGHT Studies were compared with national crude prevalence rates for individuals 40 years and older served by Medicaid and Medicare insurance and reported in CDC’s Vision and Eye Health Surveillance System (VEHSS).³⁰ The CDC’s 2019 annual prevalence estimates using Medicare data were 8.0% for glaucoma and 5.27% for glaucoma suspect (combined 13.27%); Medicaid data rates were 3.9% for glaucoma and 2.13% for glaucoma suspect (combined 6.03%).³⁰ The glaucoma/glaucoma suspect findings of 18.6% in Alabama, 24% in Michigan, 26.7% in NYC detected across the three SIGHT Studies is higher than these national averages. While Medicare and Medicaid rates for glaucoma and glaucoma suspect by race and ethnicity, are higher for Black adults (18.97% Medicare/8.76% Medicaid) and Hispanic/Latino adults (13.64% Medicare/6.42% Medicaid), compared to non-Hispanic White adults, our study findings remain higher than all of these data from 2019.³⁰ This difference is likely due to the SIGHT Studies being conducted in high-risk, underserved populations with lack of access to eye care and poor in-office eye care utilization rates.¹² Heterogeneity, or the degree of variation in the screening and referral criteria used across the three SIGHT Studies could impact the interpretation of comparative findings across different settings. We acknowledge that what worked in one setting may not be generalizable or apply in other settings.

The use of telemedicine in ophthalmology has risen gradually over the last decade, with an exponential increase after the onset of the COVID-19 pandemic.^31,32Telehealth offers a paradigm-shifting opportunity in detecting glaucoma and retina-related eye conditions in underserved populations as a potential solution to ensure that even those with limited resources who could have remained undiagnosed, receive optimal eye care.^33,34 Prior practice-based telehealth programs for glaucoma and retina have shown utility of screening when compared to in-office eye exams.^35,,36 Other studies have reported that telehealth for glaucoma detection reduces the amount of time spent attending in-person clinic visits and decreases travel time and costs for each patient.^34–36 The Food and Drug Administration (FDA) has approved several devices for primary care screening of diabetic retinopathy, with implementation of these devices in many sectors.^34,35 With growing advances in technology and the incorporation of artificial intelligence, telehealth programs for glaucoma are expected to become even more cost-effective; however, effectiveness of telehealth-based screening programs has been limited by lack of follow-up between screening events and in-office eye exams.³⁷ Teleophthalmology data from the SIGHT Studies has found a significant amount of abnormal images and with support from navigators, many of these study participants have attended in-office eye exams confirming an eye disease diagnosis.^38,39

Though there was substantial variation across the sites in terms of screening tools and referral criteria leading to different referral rates and particularly different rates of uncorrected refractive error, rates of glaucoma/suspected glaucoma detected were similar across the three sites. One reason why the referral rates varied was that those with refractive error in NYC-SIGHT and AL-SIGHT were referred to optometry, while refractive error was treated as part of the screening program in MI-SIGHT. Therefore, this paper adds to the body of evidence that underserved communities benefit from the tele-ophthalmology interventions described in the SIGHT Studies. Showcasing the results side-by-side enables readers to understand that even though each study had different methodology, there were numerous findings that were shared. Placing eye disease screening in community locations with high rates of poverty was an effective approach in identifying referrable eye disease across three very different geographic locations. Understanding the success of this overarching approach despite the differences between the approaches is key to informing policy.

In addition, all SIGHT Studies considered social determinants of health indicators and demographic factors to address eye health disparities by bringing eye health screenings into the communities where people live and improved access to eye care in the community and referrals for in-office eye care for study participants who needed follow-up ocular treatment, management, and potential surgery. In AL-SIGHT a strength was that the coordinator tracked all participants referred for follow-up eye care for six months following the date of the referral. This allowed for tracking of persons who may have missed their initial appointment or had trouble getting an appointment that suited their schedule at an early date post referral.

In the MI-SIGHT Study, the ophthalmic technicians who conducted the remote telemedicine assessment also functioned as health educators and care navigators. After the remote ophthalmologist graded the data and gave follow-up recommendations, participants returned for a second visit with the ophthalmic technician. At that second visit, the ophthalmic technician dispensed the glasses from the on-line retailer and ensured a proper fit, educated the participants about the doctor’s findings and recommendations, and assisted the patient in making the appropriate follow-up appointment. In addition, if a patient needed assistance with transportation, interpretation, or insurance, if the ophthalmic technician could not provide the assistance, they helped connect the participant with a social worker or a community resource to provide the assistance.

The NYC-SIGHT used a bilingual (Spanish) patient navigator to ensure that referrals were completed, incuding confirming and rescheduling in-office eye exam appointments. The patient navigator utilized EPIC to keep track of referrals to Columbia or Harlem Ophthalmology and to ensure patients completed and received necessary care. Those with their own doctor signed a medical release form, and only a few patients’ medical records were received.

Recruitment was limited to adults who self-selected to participate, which may not be reflective of populations at higher risk for glaucoma in other urban and rural settings and therefore may have overestimated referral rates and results in selection bias. Individuals with pre-existing ocular conditions were not excluded, which may also contribute to higher referral rates seen for participants who self-reported glaucoma compared to those not referred. On the other hand, the majority of these individuals with pre-existing glaucoma had poor access to eye care, undiagnosed ocular conditions, poor IOP lowering medication adherence, and were therefore at risk of blindness. Although slightly different screening methods and screening failure criteria definitions were used at each site, referral criteria for in-office eye care was based on AAO Practice Pattern Guidelines^® and their Data and Safety Monitoring Committees. Additional factors, such as income and the presence of physical disabilities were not investigated and could influence results. Regarding referral criteria, standardized grading protocols or inter-grader reliability measures were used within each site for diagnosing “glaucoma” or “glaucoma suspect” but not across the sites, which we acknowledge does impact detection rate comparison.