Diabetes eye screening in urban settings serving minority populations: detection of diabetic retinopathy and other ocular findings using telemedicine

Feasibility and acceptance of artificial intelligence-based diabetic retinopathy screening in Rwanda

BACKGROUND

Evidence on the practical application of artificial intelligence (AI)-based diabetic retinopathy (DR) screening is needed.

METHODS

Consented participants were screened for DR using retinal imaging with AI interpretation from March 2021 to June 2021 at four diabetes clinics in Rwanda. Additionally, images were graded by a UK National Health System-certified retinal image grader. DR grades based on the International Classification of Diabetic Retinopathy with a grade of 2.0 or higher were considered referable. The AI system was designed to detect optic nerve and macular anomalies outside of DR. A vertical cup to disc ratio of 0.7 and higher and/or macular anomalies recognised at a cut-off of 60% and higher were also considered referable by AI.

RESULTS

Among 827 participants (59.6% women (n=493)) screened by AI, 33.2% (n=275) were referred for follow-up. Satisfaction with AI screening was high (99.5%, n=823), and 63.7% of participants (n=527) preferred AI over human grading. Compared with human grading, the sensitivity of the AI for referable DR was 92% (95% CI 0.863%, 0.968%), with a specificity of 85% (95% CI 0.751%, 0.882%). Of the participants referred by AI: 88 (32.0%) were for DR only, 109 (39.6%) for DR and an anomaly, 65 (23.6%) for an anomaly only and 13 (4.73%) for other reasons. Adherence to referrals was highest for those referred for DR at 53.4%.

CONCLUSION

DR screening using AI led to accurate referrals from diabetes clinics in Rwanda and high rates of participant satisfaction, suggesting AI screening for DR is practical and acceptable.

Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs

BACKGROUND/OBJECTIVES

Artificial intelligence can assist with ocular image analysis for screening and diagnosis, but it is not yet capable of autonomous full-spectrum screening. Hypothetically, false-positive results may have unrealized screening potential arising from signals persisting despite training and/or ambiguous signals such as from biomarker overlap or high comorbidity. The study aimed to explore the potential to detect clinically useful incidental ocular biomarkers by screening fundus photographs of hypertensive adults using diabetic deep learning algorithms.

SUBJECTS/METHODS

Patients referred for treatment-resistant hypertension were imaged at a hospital unit in Perth, Australia, between 2016 and 2022. The same 45° colour fundus photograph selected for each of the 433 participants imaged was processed by three deep learning algorithms. Two expert retinal specialists graded all false-positive results for diabetic retinopathy in non-diabetic participants.

RESULTS

Of the 29 non-diabetic participants misclassified as positive for diabetic retinopathy, 28 (97%) had clinically useful retinal biomarkers. The models designed to screen for fewer diseases captured more incidental disease. All three algorithms showed a positive correlation between severity of hypertensive retinopathy and misclassified diabetic retinopathy.

CONCLUSIONS

The results suggest that diabetic deep learning models may be responsive to hypertensive and other clinically useful retinal biomarkers within an at-risk, hypertensive cohort. Observing that models trained for fewer diseases captured more incidental pathology increases confidence in signalling hypotheses aligned with using self-supervised learning to develop autonomous comprehensive screening. Meanwhile, non-referable and false-positive outputs of other deep learning screening models could be explored for immediate clinical use in other populations.

Teleophthalmology provides earlier eye care access for patients with newly-diagnosed diabetes

Purpose

Timely diagnosis of diabetic retinopathy is important in preventing vision loss. This study aims to determine if remote retinal imaging enables earlier eye care access among newly-diagnosed diabetic patients.

Design

Retrospective cohort study.

Methods

Using the OptumLabs® Data Warehouse - a longitudinal, real-world dataset containing deidentified administrative claims and electronic health record (EHR) data, we included 968 846 adults with newly diagnosed type 2 diabetes and at least 1 year of continuous enrollment. We compared time from initial diabetes diagnosis to first eye exam by remote screening or in-person eye exam.

Results

We found that at year 1 after diagnosis, 5459 (0.56%) patients underwent remote imaging and 208 023 (21.5%) underwent in-person exam. The mean (95% CI) time to eye exam was 3.48 (3.38-3.58) months for remote imaging and 4.22 (4.20-4.23) months for in-person visits (p < 0.0001). Interestingly, 27.5% of remote screenings were performed on the same day of diabetes diagnosis. Excluding same-day encounters, mean time to eye exam was 4.80 (4.68-4.91) months for remote imaging and 4.85 (4.83-4.86) months for in-person eyecare (p = 0.4).

Conclusions

Thus, teleophthalmology may enable earlier eye care access among patients with newly-diagnosed diabetes, primarily with same-day screenings. Increased adoption of teleretinal screening may enable earlier detection of diabetic retinopathy and prevent vision loss.

Oxidative Stress Mediates Epigenetic Modifications and the Expression of miRNAs and Genes Related to Apoptosis in Diabetic Retinopathy Patients

Knowledge on the underlying mechanisms and molecular targets for managing the ocular complications of type 2 diabetes mellitus (T2DM) remains incomplete. Diabetic retinopathy (DR) is a major cause of irreversible visual disability worldwide. By using ophthalmological and molecular-genetic approaches, we gathered specific information to build a data network for deciphering the crosslink of oxidative stress (OS) and apoptosis (AP) processes, as well as to identify potential epigenetic modifications related to noncoding RNAs in the eyes of patients with T2DM. A total of 120 participants were recruited, being classified into two groups: individuals with T2MD (T2MDG, n = 67), divided into a group of individuals with (+DR, n = 49) and without (-DR, n = 18) DR, and a control group (CG, n = 53). Analyses of compiled data reflected significantly higher plasma levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) and significantly lower total antioxidant capacity (TAC) in the +DR patients compared with the -DR and the CG groups. Furthermore, the plasma caspase-3 (CAS3), highly involved in apoptosis (AP), showed significantly higher values in the +DR group than in the -DR patients. The microRNAs (miR) hsa-miR 10a-5p and hsa-miR 15b-5p, as well as the genes BCL2L2 and TP53 involved in these pathways, were identified in relation to DR clinical changes. Our data suggest an interaction between OS and the above players in DR pathogenesis. Furthermore, potential miRNA-regulated target genes were identified in relation to DR. In this concern, we may raise new diagnostic and therapeutic challenges that hold the potential to significantly improve managing the diabetic eye.

Effect of Accessible Nonmydriatic Retinal Imaging on Diabetic Retinopathy Surveillance Rates

Purpose: To evaluate the impact on surveillance rates for diabetic retinopathy (DR) by providing nonmydriatic retinal imaging as part of comprehensive diabetes care at no cost to patients or insurers. Methods: A retrospective comparative cohort study was designed. Patients were imaged from April 1, 2016 to March 31, 2017 at a tertiary diabetes-specific academic medical center. Retinal imaging was provided without additional cost beginning October 16, 2016. Images were evaluated for DR and diabetic macular edema using standard protocol at a centralized reading center. Diabetes surveillance rates before and after no-cost imaging were compared. Results: A total of 759 and 2,080 patients respectively were imaged before and after offering no-cost retinal imaging. The difference represents a 274% increase in the number of patients screened. Furthermore, there was a 292% and 261% increase in the number of eyes with mild DR and referable DR, respectively. In the comparative 6-month period, 92 additional cases of proliferative DR were identified, estimated to prevent 6.7 cases of severe visual loss with annual cost savings of $180,230 (estimated yearly cost of severe vision loss per person: $26,900). In patients with referable DR, self-awareness was low, with no significant difference in the before and after groups (39.4% vs. 43.8%, p = 0.3725). Conclusions: Providing retinal imaging as part of comprehensive diabetes care substantially increased the number of patients identified by nearly threefold. The data suggest that the removal of out-of-pocket costs substantially increased patient surveillance rates, which may translate to improved long-term patient outcomes.

Ultra-Widefield Imaging as a Teleophthalmology Screening Tool for Ocular Pathology

Background

Prior studies have validated ultra-widefield imaging as a remote screening tool for diabetic retinopathy. The aim of this study was to determine its use in screening for any fundus pathology in a routine patient population.

Methods

In this prospective randomized study, patients underwent both slit lamp indirect ophthalmoscopy and ultra-widefield imaging. Ultra-widefield images were independently reviewed by two optometrists, and discrepancies were adjudicated by a retina specialist. Clinical findings from slit-lamp examiners and image-reviewers were coded into themes and clinically meaningful findings were extracted. Cohen's kappa was used to estimate agreement for these findings between the two image-reviewers and between the image-reviewers and slit-lamp examiners.

Results

Nine-hundred eyes of 450 patients were examined and imaged, of which 616 eyes were analyzed. At least one abnormal fundus finding was present on ophthalmoscopy in 71 eyes (11%) and on adjudicated image interpretation in 166 eyes (27%). Agreement between the two image-reviewers was moderate to substantial for most clinically meaningful findings, including optic disc hemorrhage (κ = 0.8), macular exudates (κ = 0.7), and macular pigmentary changes (κ = 0.7). Agreement between examiners and image-reviewers was moderate to substantial for optic disc hemorrhage (κ = 1), indistinct optic disc margins (κ = 0.5), drusen (κ = 0.4), pigmentary changes (κ = 0.4), and hemorrhage (κ = 0.8). A total of 187 findings were detected by imaging but not examination, compared with 42 that were detected on examination but not imaging.

Conclusion

In a routine patient population, ultra-widefield imaging agreed with standard-of-care slit-lamp examinations and detected more fundus findings.

Health Care Disparities in Diabetes and Diabetic Retinopathy

PURPOSE

To investigate prevalence of diabetes (DM), diabetic retinopathy (DR), and areas with highest rates of undetected DR. To quantify and map locations of disparities as they relate to poverty and minority populations.

METHODS

Retrospective cohort study from large regional health data repository (HealthLNK). Geographic Information System (GIS) analysis mapped rates of DM and DR in Chicago area ZIP Codes.

RESULTS

Of 1,086,921 adults who met the inclusion criteria, 143,790 with DM were identified. ZIP Codes with higher poverty rates were correlated with higher prevalence of DM and DR (Pearson's correlation coefficient 0.614, p < .05, 0.333, p < .05). Poverty was negatively correlated with likelihood of DR diagnosis (-0.638, p < .05). Relative risks of DM and DR were calculated in each ZIP Code and compared to actual rates. 36 high-risk ZIP Codes had both high-risk of DM and low DR detection. In high-risk ZIP Codes 85.4% of households self-identified as ethnic minority and 33.0% were below the Federal Poverty Level (FPL). Both percentages were significantly higher than the Chicago average of 50.5% minority and 19.9% below FPL (p < .05). 67 ideal ZIP Codes had both low risk of DM and high DR detection. In ideal ZIP Codes 32.6% of households self-identified as minority, and 10.2% were below the FPL (p < .05).

CONCLUSIONS

A health care disparity exists with regards to DM and DR. High-risk ZIP Codes are associated with higher poverty and higher minority population, and they are highly concentrated in just 17% of the ZIP codes in the Chicago area.

Factors Associated with Utilization of Teleretinal Imaging in a Hospital-Based Primary Care Setting

Regular eye examinations to screen for the initial signs of diabetic retinopathy (DR) are crucial for preventing vision loss. Teleretinal imaging (TRI) offered in a primary care setting provides a means to improve adherence to DR screening, particularly for patients who face challenges in visiting eye care providers regularly. The present study evaluates the utilization of TRI to screen for DR in an outpatient, hospital-based primary care clinic. Patients with diabetes mellitus (DM) but without DR were eligible for point-of-care screening facilitated by their primary care provider, utilizing a non-mydriatic, handheld fundus camera. Patient demographics and clinical characteristics were extracted from the electronic medical record. Patients who underwent TRI were more likely to be male, non-White, and have up-to-date monitoring and treatment measures, including hemoglobin A1c (HbA1c), microalbumin, and low-density lipoprotein (LDL) levels, in accordance with Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. Our findings demonstrate that TRI can reduce screening costs compared to a strategy where all patients are referred for in-person eye examinations. A net present value (NPV) analysis indicates that a screening site reaches the break-even point of operation within one year if an average of two patients are screened per workday.

The Definition of Glaucomatous Optic Neuropathy in Artificial Intelligence Research and Clinical Applications

OBJECTIVE

Although artificial intelligence (AI) models may offer innovative and powerful ways to use the wealth of data generated by diagnostic tools, there are important challenges related to their development and validation. Most notable is the lack of a perfect reference standard for glaucomatous optic neuropathy (GON). Because AI models are trained to predict presence of glaucoma or its progression, they generally rely on a reference standard that is used to train the model and assess its validity. If an improper reference standard is used, the model may be trained to detect or predict something that has little or no clinical value. This article summarizes the issues and discussions related to the definition of GON in AI applications as presented by the Glaucoma Workgroup from the Collaborative Community for Ophthalmic Imaging (CCOI) US Food and Drug Administration Virtual Workshop, on September 3 and 4, 2020, and on January 28, 2022.

DESIGN

Review and conference proceedings.

SUBJECTS

No human or animal subjects or data therefrom were used in the production of this article.

METHODS

A summary of the Workshop was produced with input and approval from all participants.

MAIN OUTCOME MEASURES

Consensus position of the CCOI Workgroup on the challenges in defining GON and possible solutions.

RESULTS

The Workshop reviewed existing challenges that arise from the use of subjective definitions of GON and highlighted the need for a more objective approach to characterize GON that could facilitate replication and comparability of AI studies and allow for better clinical validation of proposed AI tools. Different tests and combination of parameters for defining a reference standard for GON have been proposed. Different reference standards may need to be considered depending on the scenario in which the AI models are going to be applied, such as community-based or opportunistic screening versus detection or monitoring of glaucoma in tertiary care.

CONCLUSIONS

The development and validation of new AI-based diagnostic tests should be based on rigorous methodology with clear determination of how the reference standards for glaucomatous damage are constructed and the settings where the tests are going to be applied.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Review of Visualization Approaches in Deep Learning Models of Glaucoma

Glaucoma is a major cause of irreversible blindness worldwide. As glaucoma often presents without symptoms, early detection and intervention are important in delaying progression. Deep learning (DL) has emerged as a rapidly advancing tool to help achieve these objectives. In this narrative review, data types and visualization approaches for presenting model predictions, including models based on tabular data, functional data, and/or structural data, are summarized, and the importance of data source diversity for improving the utility and generalizability of DL models is explored. Examples of innovative approaches to understanding predictions of artificial intelligence (AI) models and alignment with clinicians are provided. In addition, methods to enhance the interpretability of clinical features from tabular data used to train AI models are investigated. Examples of published DL models that include interfaces to facilitate end-user engagement and minimize cognitive and time burdens are highlighted. The stages of integrating AI models into existing clinical workflows are reviewed, and challenges are discussed. Reviewing these approaches may help inform the generation of user-friendly interfaces that are successfully integrated into clinical information systems. This review details key principles regarding visualization approaches in DL models of glaucoma. The articles reviewed here focused on usability, explainability, and promotion of clinician trust to encourage wider adoption for clinical use. These studies demonstrate important progress in addressing visualization and explainability issues required for successful real-world implementation of DL models in glaucoma.

Effectiveness of Glaucoma Screening and Factors Associated with Follow-up Adherence among Glaucoma Suspects in a Safety-Net Teleretinal Screening Program

PURPOSE

To evaluate rates and risk factors associated with follow-up adherence to in-person glaucoma evaluations and confirmed glaucoma diagnosis in glaucoma suspects identified through teleretinal diabetic retinopathy screening (TDRS).

DESIGN

Retrospective cohort study SUBJECTS: Patients with diabetes identified through teleretinal screening to have large or asymmetric cup-to-disc ratios in a Los Angeles County safety-net primary care-based TDRS program.

METHODS

Retrospective chart review was performed to obtain demographic and clinical information for patients with cup-to-disc ratios concerning for glaucoma on TDRS. Patients who completed an in-person follow-up appointment within 1 year of teleretinal screening were adherent. Factors associated with follow-up adherence and diagnosis of glaucoma were analyzed with chi-square and independent t tests along with multivariable logistic regressions.

MAIN OUTCOME MEASURES

The proportion of patients with suspected glaucoma who adhered with in-person follow-up examination, proportion of patients with confirmed glaucoma diagnosis, and factors associated with follow-up adherence and glaucoma diagnosis.

RESULTS

Eight-hundred seventeen patients with optic discs suspicious for glaucoma were included. Five-hundred thirty-four (65.4%) patients successfully completed an in-person glaucoma evaluation. Among these patients, 62.9% and 24.5% received a diagnosis of glaucoma suspect and glaucomatous optic neuropathy, respectively. Compared with patients aged < 50 years, patients aged 50 to 64 years had 1.57 times higher odds of being adherent with in-person visits (P = 0.036), whereas no difference was seen in those aged ≥ 65 years. For every $10 000 increase in the zip code median income, patients had 11% lower odds of being adherent (P = 0.031). Compared with Latino patients, Black patients had 3.52 times (P < 0.001) higher odds of having confirmed glaucoma.

CONCLUSION

The majority of patients referred as glaucoma suspects on TDRS completed a follow-up examination, and nearly a quarter of those examined received a confirmed glaucoma diagnosis. Patients aged ≥ 50 and < 65 years along with those from lower-income neighborhoods were more likely to follow up for an in-person evaluation. Compared with Latino patients, Black patients had a higher risk for a confirmed glaucoma diagnosis. This demonstrates the effectiveness of glaucoma detection in a large-scale TDRS program for a safety-net patient population.

FINANCIAL DISCLOSURE(S)

The authors have no proprietary or commercial interest in any materials discussed in this article.

Diabetic retinopathy screenings in West Virginia: an assessment of teleophthalmology implementation

BACKGROUND

The prevalence of diabetes in the state of West Virginia (WV) is amongst the highest in the United States, making diabetic retinopathy (DR) and diabetic macular edema (DME) a major epidemiological concern within the state. Several challenges exist regarding access to eye care specialists for DR screening in this rural population. A statewide teleophthalmology program has been implemented. We analyzed real-world data acquired via these systems to explore the concordance between image findings and subsequent comprehensive eye exams and explore the impact of age on image gradeability and patient distance from the West Virginia University (WVU) Eye Institute on follow-up.

METHODS

Nonmydriatic fundus images of diabetic eyes acquired at primary care clinics throughout WV were reviewed by retina specialists at the WVU Eye Institute. Analysis included the concordance between image interpretations and dilated examination findings, hemoglobin A1c (HbA1c) levels and DR presence, image gradeability and patient age, and distance from the WVU Eye Institute and follow-up compliance.

RESULTS

From the 5,512 fundus images attempted, we found that 4,267 (77.41%) were deemed gradable.  Out of the 289 patients whose image results suggested DR, 152 patients (52.6%) followed up with comprehensive eye exams-finding 101 of these patients to truly have DR/DME and allowing us to determine a positive predictive value of 66.4%. Patients within the HbA1c range of 9.1-14.0% demonstrated significantly greater prevalence of DR/DME (p < 0.01).  We also found a statistically significant decrease in image gradeability with increased age.  When considering distance from the WVU Eye Institute, it was found that patients who resided within 25 miles demonstrated significantly greater compliance to follow-up (60% versus 43%, p < 0.01).

CONCLUSIONS

The statewide implementation of a telemedicine program intended to tackle the growing burden of DR in WV appears to successfully bring concerning patient cases to the forefront of provider attention.  Teleophthalmology addresses the unique rural challenges of WV, but there is suboptimal compliance to essential follow-up with comprehensive eye exams. Obstacles remain to be addressed if these systems are to effectively improve outcomes in DR/DME patients and diabetic patients at risk of developing these sight-threatening pathologies.

Eight years' experience in mobile teleophthalmology for diabetic retinopathy screening

Background

Screening for diabetic retinopathy in the community without compromising the routine work of ophthalmologists at hospitals is the essence of teleophthalmology. This study was aimed at investigating the efficacy of teleophthalmology practice for screening diabetic retinopathy from 2012 to 2020. It was also aimed at comparing the 2-year prevalence of camps organized by a district hospital in South India, as well as the footfall, reporting, follow-up, patient response, and diagnostic efficacy at these camps.

Methods

All patients with diabetes and unexplained vision deterioration attending the mobile camp units underwent non-dilated fundus photography. Patients underwent teleconsultation with the ophthalmologist at the district hospital, and those requiring intervention were called to the district hospital. Trends were studied for the number of patients reporting to the hospital. Patient satisfaction was recorded based on a questionnaire.

Results

A total of 682 camps were held over 8 years, and 30 230 patients were examined. Teleconsultation was done for 12 157 (40.21%) patients. Patients requiring further investigations, intervention for diabetic retinopathy, or further management of other ocular pathologies were urgently referred to the district hospital (n= 3293 [10.89%] of 30 230 examined patients). The severity and presence of clinically significant macular edema increased significantly with an increased duration of diabetes mellitus (P < 0.001). The percentage of teleconsultations showed an increasing trend over the years (P = 0.001). Similarly, considering trends of patients reporting to the hospital, the attrition rate decreased over the years (P < 0.05). A total of 10 974 of 12 157 (90.27%) patients who underwent teleophthalmic consultation were satisfied with the service.

Conclusions

Teleconsultations over the years showed an increasing trend, and the attrition rate decreased over the years. Teleophthalmology is achieving success in providing high-quality service, easy access to care, and in increasing patient satisfaction. Future studies on the role of teleophthalmology for other leading preventable causes of blindness seem possible and necessary.

Effectiveness of a telemedicine program for triage and diagnosis of emergent ophthalmic conditions

BACKGROUND

To study the utility of a teleophthalmology program to diagnose and triage common ophthalmic complaints presenting to an ophthalmic emergency room.

METHODS

Prospective, observational study of 258 eyes of 129 patients presenting to the Massachusetts Eye and Ear Infirmary Emergency Ward (MEE EW) who completed a questionnaire to gather chief complaint (CC), history of present illness, and medical history. Anterior and posterior segment photographs were collected via iPhone 5 C camera and a Canon non-mydriatic fundus camera, respectively. Ophthalmic vital signs were collected. All information was reviewed remotely by three ophthalmologists; a diagnosis and urgency designation were recorded. The remote assessment was compared to gold standard in-person assessment.

RESULTS

The 129 recruited patients collectively contributed 220 visual complaints, of which 121 (55%) were from females with mean age 56.5 years (range 24-89). Sensitivities and specificities for telemedical triage were as follows: eye pain (n = 56; sensitivity: 0.58, CI [0.41, 0.74]; specificity: 0.91, CI [0.80, 1]), eye redness (n = 54; 0.68, CI [0.50, 0.86]; 0.93, CI [0.84, 1]), blurry vision (n = 68; 0.73, CI [0.60, 0.86]; 0.91, CI [0.80, 1]), and eyelid complaints (n = 42; 0.67, CI [0.43, 0.91]; 0.96, CI [0.89, 1]). The remote diagnostic accuracies, as stratified by CC, were eye pain (27/56; 48.21%), eye redness: (32/54; 59.26%), blurry vision: (30/68; 44.11%), eyelid (24/42; 57.14%).

CONCLUSIONS

Telemedical examination of emergent ophthalmic complaints consisting of a patient questionnaire, anterior segment and fundus photos, and ophthalmic vital signs, may be useful to reliably triage eye disease based on presenting complaint.

Teleophthalmology Using Remote Retinal Imaging During the COVID-19 Pandemic

Introduction: Lower insurance reimbursements have limited the financial sustainability of remote eye screening programs. Greater utilization and insurance coverage for teleophthalmology screening during the coronavirus disease 2019 (COVID-19) pandemic in 2020 may enhance awareness and expand remote retinal imaging services. This retrospective cross-sectional study evaluates utilization and insurance coverage for remote retinal imaging in the United States in 2020. Methods: We analyzed teleretinal imaging utilization and insurance payments from January 1 to December 31, 2020, using the Optum Labs Data Warehouse, a comprehensive national database of deidentified administrative claims for commercial and Medicare Advantage enrollees in the United States. We evaluated frequency of claims and insurance payment for services using the Current Procedural Terminology codes 92227 and 92228 for remote eye imaging by any provider, and 92250 for fundus photography by non-eye care providers. Results: The use of remote retinal imaging in the United States declined rapidly during the initial COVID-19 lockdown from 3,627 claims in February 2020 to 1,414 claims in April 2020, but returned to 3,133 claims by December 2020, similar to mean prepandemic levels in 2019 (2,841 ± 174.8 claims). The proportion of insurance payments for remote imaging increased temporarily from 47.4% in February to 56.7% in April, and then returned to 45.9% in December of 2020. Discussion: Utilization of remote retinal imaging declined steeply, while the insurance coverage increased during the initial COVID-19 lockdown in 2020, but returned to prepandemic levels by end of the year. Changes in utilization and relaxed restrictions on insurance reimbursements for teleophthalmology during the COVID-19 pandemic were not sustained.

Urgent Virtual Eye Assessments During the COVID-19 Pandemic

Purpose

We aimed to evaluate the effectiveness and safety of a virtual eye assessment triage system implemented in response to COVID-19.

Patients and Methods

We conducted a retrospective cross-sectional study using a consecutive sample of all virtual assessments conducted from March 24 to June 7, 2020 at a single ophthalmology center in Toronto, ON, Canada. Visual acuity and smartphone photographs were uploaded to an electronic assessment website. All patients were virtually triaged to an email or phone consult. Patient outcomes and satisfaction were assessed with a quality assurance survey. Primary outcome measures were the incidence of unplanned additional in-person visits and changes in treatment.

Results

We performed 1535 virtual assessments. Of the triage pathways, 15% received an email consult only and 85% received a phone consult. Subsequently, 15% required an in-person assessment, 3% were referred elsewhere, and 0.1% were sent to the emergency. Presentations were most commonly cornea (52%) and retina (25%). They were non-urgent in 68% of cases and no pharmacologic treatment was required for 49%. Of 397 patients that responded out of 653 patients surveyed, 4% had an unplanned additional visit to the emergency, after which two patients underwent urgent retinal surgery and one patient underwent urgent glaucoma surgery. Two patients (0.5%) had a minor change in treatment.

Conclusion

As routine regular in-person visits were not possible during the COVID-19 lockdown, virtual eye assessments provided an opportunity to triage patients. Virtual assessments have the potential to reduce in-person visits, but caution must be exercised to not miss vision-threatening conditions.

Perceptions of a Teleophthalmology Screening Program for Diabetic Retinopathy in Adults With Type 1 and Type 2 Diabetes in Urban Primary Care Settings

OBJECTIVES

Teleophthalmology has improved diabetic retinopathy screening, and should be expanded in urban areas, where most unscreened individuals reside. In this study we explored facilitators and barriers of teleophthalmology in primary care settings in Toronto, Canada.

METHODS

Semistructured interviews were conducted with 7 health-care providers and 7 individuals with diabetes to explore their perspectives of teleophthalmology in urban primary care settings. Interview data were analyzed using interpretive thematic analysis to generate themes.

RESULTS

Six themes were identified. Facilitators included patient-centred implementation, access to teleophthalmology at primary care sites and patients' trust in their providers' recommendations. Barriers included patients' lack of understanding of diabetic retinopathy and the health-care system, providers' lack of interest and the need to streamline administrative processes.

CONCLUSIONS

Although teleophthalmology was well-received by patients, there was limited interest from primary care providers. Strategies for increasing uptake include increasing primary care providers' awareness of teleophthalmology's value in urban centres, improving administrative processes and centralizing patient recruitment.

Evaluation of the prevalence of non-diabetic eye disease detected at first screen from a single region diabetic retinopathy screening program: a cross-sectional cohort study in Auckland, New Zealand

OBJECTIVES

To evaluate the prevalence of incidental non-diabetic ocular comorbidities detected at first screen in a large diabetic retinopathy (DR) screening programme.

DESIGN

Cross-sectional cohort study.

SETTING

Single large metropolitan diabetic eye screening programme in Auckland, New Zealand.

PARTICIPANTS

Twenty-two thousand seven hundred and seventy-one participants who attended screening from September 2008 to August 2018.

RESULTS

Hypertensive retinopathy (HTR) was observed in 14.2% (3236/22 771) participants. Drusen were present in 14.0% participants under the age of 55 years, increasing to 20.5% in those 55 years and older. The prevalence of neovascular age-related macular degeneration (AMD) was 0.5% in participants aged<55 years, 2.4% in participants aged 55-75 years and 16% in participants aged>75 years. Retinal vein occlusion and retinal arterial embolus were prevalent in 0.7% and 0.02%, respectively, in participants aged<55 years, increasing to 2.2% and 0.4%, respectively, in those >75 years. Cataracts were common being present in 37.1% of participants over the age of 75 years. Only 386 individuals (1.7%) were labelled as glaucoma suspects. Geographic atrophy, epiretinal membrane, choroidal nevi and posterior capsular opacification had an increased prevalence in older individuals.

CONCLUSIONS

Our data suggest that AMD, HTR and cataracts are routinely detected during DR screening. The incorporation of the detection of these ocular comorbidities during DR screening provide opportunities for patients to modify risk factors (smoking cessation and diet for AMD, blood pressure for HTR) and allow access to cataract surgery.

Utilization of Remote Diabetic Retinal Screening in a Suburban Healthcare System

Purpose

We conducted a cross-sectional study to assess the utilization of a tele-ophthalmology screening program in a low-risk, suburban population of patients with diabetes.

Methods

A total of 214 diabetic patients without previously documented diabetic retinopathy (DR) underwent point-of-care non-mydriatic fundus photography through their primary care providers at five Beth Israel Lahey Health locations. The characteristics of the patients who received remote screening were compared with those patients who were eligible for screening but did not take part in the program. Time-driven activity-based costing (TDABC) was implemented to examine the cost of screening by tele-ophthalmology compared with in-person examinations.

Results

Tele-ophthalmology screening was more likely to be provided for patients who were younger (OR 0.985; 95% CI 0.973–0.997, p=0.016), who were obese (OR 2.04; 95% CI: 1.47–2.84, p=0.008), who had an HbA1c above 8.0% (OR 1.60; 95% CI: 1.13–2.26, p=0.031), or who had an eye examination in the past year (OR 5.55; 95% CI: 3.89–7.92, p<0.001). Those patients newly diagnosed with DR because of the program were more likely to have diabetic nephropathy (OR 7.79; 95% CI: 1.73–35.05, p=0.007). TDABC identified a health system cost-savings of between $8 and $29 per patient screened by tele-ophthalmology compared with the cost of in-person eye examinations.

Conclusion

Tele-ophthalmology presents an opportunity to reduce the costs of screening patients without prior evidence of DR, especially those who have completed a comprehensive eye examination within the prior year.

Interventions to promote access to eyecare for non-dominant ethnic groups in high-income countries: a scoping review

PURPOSE

People who are distinct from the dominant ethnic group within a country can experience a variety of barriers to accessing eyecare services. We conducted a scoping review to map published interventions aimed at improving access to eyecare for non-Indigenous, non-dominant ethnic groups residing in high-income countries.

METHODS

We searched MEDLINE, Embase and Global Health for studies that described an intervention to promote access to eyecare for the target population. Two authors independently screened titles and abstracts followed by review of the full text of potentially relevant sources. For included studies, data extraction was carried out independently by two authors. Findings were summarised using a combination of descriptive statistics and thematic analysis.

RESULTS

We screened 5220 titles/abstracts, of which 82 reports describing 67 studies met the inclusion criteria. Most studies were conducted in the USA (90%), attempted to improve access for Black (48%) or Latinx (28%) communities at-risk for diabetic retinopathy (42%) and glaucoma (18%). Only 30% included the target population in the design of the intervention; those that did tended to be larger, collaborative initiatives, which addressed both patient and provider components of access. Forty-eight studies (72%) evaluated whether an intervention changed an outcome measure. Among these, attendance at a follow-up eye examination after screening was the most common (n=20/48, 42%), and directly supporting patients to overcome barriers to attendance was reported as the most effective approach. Building relationships between patients and providers, running coordinated, longitudinal initiatives and supporting reduction of root causes for inequity (education and economic) were key themes highlighted for success.

CONCLUSION

Although research evaluating interventions for non-dominant, non-Indigenous ethnic groups exist, key gaps remain. In particular, the paucity of relevant studies outside the USA needs to be addressed, and target communities need to be involved in the design and implementation of interventions more frequently.

Clinical staff impressions on implementation of a teleophthalmology program to improve diabetic retinopathy surveillance informed by implementation science frameworks (Preprint)

Background

The store-and-forward camera-based evaluation of the eye, or teleophthalmology, is an effective way to identify diabetic retinopathy, the leading cause of blindness in the United States, but uptake has been slow. Understanding the barriers to and facilitators of implementing teleophthalmology programs from those actively adopting, running, and sustaining such programs is important for widespread adoption.

Objective

This study aims to understand the factors that are important in introducing teleophthalmology to improve access to diagnostic eye care for patients with diabetes in primary care clinics by using implementation science.

Methods

This qualitative study in 3 urban, low-income, largely racial and ethnic minority–serving safety-net primary care clinics in Rochester, New York, interviewed nurses and physicians on implementing a teleophthalmology program by using questions informed by the Practical, Robust Implementation and Sustainability Model and the Consolidated Framework for Implementation Research.

Results

Primary care nurses operationalizing the program in their clinics saw increased work burden and a lack of self-efficacy as barriers. Continuous training on the teleophthalmology process for nurses, physicians, and administrative staff through in-service and peer training by champions and superusers were identified by interviewees as needs. Facilitators included the perceived convenience for the patient and a perceived educational advantage to the program, as it gave an opportunity for providers to discuss the importance of eye care with patients. Concerns in making and tracking referrals to ophthalmology because of challenges related to care coordination were highlighted. The financial aspects of the program (eg, patient coverage and care provider reimbursement) were unclear to many staff members, influencing adoption and sustainability.

Conclusions

Streamlining processes and workflows, training and assigning adequate staff, effectively coordinating care between primary care and eye care to improve follow-ups, and ensuring financial viability can all help streamline the adoption of teleophthalmology.

Feasibility Study of a Multimodal, Cloud-Based, Diabetic Retinal Screening Program in a Workplace Environment

Purpose

To evaluate the feasibility of capturing and interpreting retinal images in a workplace environment using a multimodal, cloud-based, diabetic retinal screening program combined with electronic self-reported questionnaires. The burden of diabetic retinopathy (DR) and other retinal conditions, healthcare utilization, and visual function were also assessed.

Methods

A cross-sectional feasibility study was conducted at the Genentech, Inc., Campus Health Center. Eyes of participants were imaged using ultra-widefield (UWF) color fundus photography (CFP) and spectral-domain optical coherence tomography (SD-OCT). A cloud-based platform was used for the automated, seamless transfer of images to a remote reading center for evaluation for DR and other retinal pathologies. Electronic surveys collected participants’ self-reported medical histories, healthcare utilization, and visual function data.

Results

Among 100 participants (mean age, 43.9 years; 44% male), 33% of them self-reported diabetes. Eye examinations within the past 12 months were reported by 71% of all participants (n = 71/100) and by 85% (n = 28/33) of those with self-reported diabetes. Among participants with complete screening images from both UWF-CFP and SD-OCT, 20% (n = 6/30) of those with self-reported diabetes and 8.5% (n = 5/59) of participants with no history of diabetes were unaware they had mild/moderate nonproliferative DR. Among all participants, 20% (20/100) had a retinal finding, on either UWF-CFP or SD-OCT, or both, which prompted a referral for further evaluation.

Conclusions

A retinal screening program deployed via a secure, scalable, and interoperable cloud-based platform was feasible and conveniently integrated into the workplace.

Translational Relevance

Cloud-based platforms could be used to promote a secure, scalable, and interoperable system for retinal screening in nontraditional environments.

Diabetic and Retinal Vascular Eye Disease

The retinal vasculature is the only neurovascular system directly visible to the human eye, easily evaluated by fundoscopy and many imaging modalities. This window allows physicians to diagnose and treat retinal pathologies and detect systemic diseases including diabetes, hypertension, hypercoagulable/hyperviscosity syndromes, and vasculitis. Diabetic retinopathy is the most common retinal vascular disease, followed by retinal vein and artery occlusion. Patients with these conditions require medical optimization to prevent further damage to the eyes and to the other organs. Both the internists and medical subspecialists play a crucial role in the prevention, detection, evaluation, and management of vision-threatening retinal vascular diseases.

A 15 month experience with a primary care-based telemedicine screening program for diabetic retinopathy

Background

Using telemedicine for diabetic retinal screening is becoming popular especially amongst at-risk urban communities with poor access to care. The goal of the diabetic telemedicine project at Temple University Hospital is to improve cost-effective access to appropriate retinal care to those in need of close monitoring and/or treatment.

Methods

This will be a retrospective review of 15 months of data from March 2016 to May 2017. We will investigate how many patients were screened, how interpretable the photographs were, how often the photographs generated a diagnosis of diabetic retinopathy (DR) based on the screening photo, and how many patients followed-up for an exam in the office, if indicated.

Results

Six-hundred eighty-nine (689) digital retinal screening exams on 1377 eyes of diabetic patients were conducted in Temple’s primary care clinic. The majority of the photographs were read to have no retinopathy (755, 54.8%). Among all of the screening exams, 357 (51.8%) triggered a request for a referral to ophthalmology. Four-hundred forty-nine (449, 32.6%) of the photos were felt to be uninterpretable by the clinician. Referrals were meant to be requested for DR found in one or both eyes, inability to assess presence of retinopathy in one or both eyes, or for suspicion of a different ophthalmic diagnosis. Sixty-seven patients (9.7%) were suspected to have another ophthalmic condition based on other findings in the retinal photographs. Among the 34 patients that were successfully completed a referral visit to Temple ophthalmology, there was good concordance between the level of DR detected by their screening fundus photographs and visit diagnosis.

Conclusions

Although a little more than half of the patients did not have diabetic eye disease, about half needed a referral to ophthalmology. However, only 9.5% of the referral-warranted exams actually received an eye exam. Mere identification of referral-warranted diabetic retinopathy and other ophthalmic conditions is not enough. A successful telemedicine screening program must close the communication gap between screening and diagnosis by reviewer to provide timely follow-up by eye care specialists.

Diabetes Complications in Racial and Ethnic Minority Populations in the USA

PURPOSE OF REVIEW

Racial and ethnic minority populations have a higher burden of diabetes-related complications. There have been many epidemiologic studies to better define these racial/ethnic disparities in diabetes outcomes with additional studies offering interventions to mitigate them. This narrative review highlights the epidemiologic trends in diabetes complications specific to racial and ethnic minorities and underscores differences in microvascular and macrovascular complications of diabetes, health care utilization, and diabetes prevention efforts and also reviews interventions aimed to reduce racial/ethnic disparities and their limitations.

RECENT FINDINGS

While we have seen in general an overall improvement in complication rates for all people with diabetes, the disparities between Black and Hispanic compared to non-Hispanic White people with diabetes seem to persist. There is a continued need to better understand the underlying causes of and strategies to mitigate race/ethnicity disparities in diabetes complications in the USA.

Applications of deep learning in detection of glaucoma: A systematic review

Glaucoma is the leading cause of irreversible blindness and disability worldwide. Nevertheless, the majority of patients do not know they have the disease and detection of glaucoma progression using standard technology remains a challenge in clinical practice. Artificial intelligence (AI) is an expanding field that offers the potential to improve diagnosis and screening for glaucoma with minimal reliance on human input. Deep learning (DL) algorithms have risen to the forefront of AI by providing nearly human-level performance, at times exceeding the performance of humans for detection of glaucoma on structural and functional tests. A succinct summary of present studies and challenges to be addressed in this field is needed. Following PRISMA guidelines, we conducted a systematic review of studies that applied DL methods for detection of glaucoma using color fundus photographs, optical coherence tomography (OCT), or standard automated perimetry (SAP). In this review article we describe recent advances in DL as applied to the diagnosis of glaucoma and glaucoma progression for application in screening and clinical settings, as well as the challenges that remain when applying this novel technique in glaucoma.

Implementation and sustainment of a statewide telemedicine diabetic retinopathy screening network for federally designated safety-net clinics

Context

Diabetic retinopathy (DR) is the leading cause of incident blindness among working-age adults in the United States. Federally designated safety-net clinics (FDSC) often serve as point-of-contact for patients least likely to receive recommended DR screenings, creating opportunity for targeted interventions to increase screening access and compliance.

Study design and methods

With such a goal, we implemented and assessed the longitudinal performance of an FDSC-based telemedicine DR screening (TDRS) network of 22 clinical sites providing nonmydriatic fundus photography with remote interpretation and reporting. Retrospective analysis of patient encounters between February 2014 and January 2019 was performed to assess rates of pathology and referral. A generalized estimating equation logistic regression model was used for subset analysis from audits of pre- and post-implementation screening rates. Finally, patient surveys were conducted and assessed as a measure of intervention acceptability.

Results

Of the 13,923 individual telescreening encounters (4327 female, 4220 male, and 5376 unspecified; mean [SD] age, 54.9 [12.5] years) studied, 10,540 were of adequate quality to identify 3532 (33.5%) patients with ocular pathology: 2319 (22.0%) patients had some level of DR with 1604 (15.2%) requiring specialist referral, and 808 (7.7%) patients required referral for other ocular pathologies. The mean screening rate for audited clinics in the year prior to program implementation was 29.9% (641/2147), which increased to 47.7% (1012/2124) in the program’s first year, doubling patients’ odds of being screened (OR 2.2; 95% CI: 1.3–3.7; P = .003). These gains were sustained over four years following implementation (OR 1.9; 95% CI: 1.1–3.1; P = .018) despite varied clinic screening performance (4-year averaged range, 22.9–55.1%). Odds of early detection likewise doubled for patients with consecutive screenings (OR 2.2, 95% CI: 2.0–2.4; P < .001). Finally, surveyed patients preferred TDRS to specialist exams (82.5%; 776/941) and would recommend the service to friends (92.7%; 868/936).

Conclusion and relevance

A statewide, FDSC-centered TDRS network was successfully established and sustained in a medically underserved region of the United States. Our results suggest that large TDRS networks in FDSCs can increase screening access and compliance for otherwise unscreened populations, but outcomes can vary greatly among clinics. Further work to optimize program implementation is needed to maximize this model’s impact.

A Review of Advancements and Evidence Gaps in Diabetic Retinopathy Screening Models

Diabetic retinopathy (DR) is a microvascular complication of diabetes with a prevalence of ~35%, and is one of the leading causes of visual impairment in people of working age in most developed countries. The earliest stage of DR, non-proliferative DR (NPDR), may progress to sight-threatening DR (STDR). Thus, early detection of DR and active regular screening of patients with diabetes are necessary for earlier intervention to prevent sight loss. While some countries offer systematic DR screening, most nations are reliant on opportunistic screening or do not offer any screening owing to limited healthcare resources and infrastructure. Currently, retinal imaging approaches for DR screening include those with and without mydriasis, imaging in single or multiple fields, and the use of conventional or ultra-wide-field imaging. Advances in telescreening and automated detection facilitate screening in previously hard-to-reach communities. Despite the heterogeneity in approaches to fit local needs, an evidence base must be created for each model to inform practice. In this review, we appraise different aspects of DR screening, including technological advances, identify evidence gaps, and propose several studies to improve DR screening globally, with a view to identifying patients with moderate-to-severe NPDR who would benefit if a convenient treatment option to delay progression to STDR became available.

The role of tele-ophthalmology in diabetic retinopathy screening

Diabetic retinopathy (DR) is the leading cause of legal blindness in the United States. Considering the increasing incidence of DR, it is extremely important to detect the most cost-effective tools for DR screening, so as to manage this surge in demand and the socioeconomic burden it places on the health care system. Despite the advances in retinal imaging, analysis techniques are still superseded by expert ophthalmologist interpretation. Teleophthalmology presents an immense opportunity, with high rates of sensitivity and specificity, to manage the steadily increasing demand for eye care of patients with diabetes, but challenges remain in the delivery of practical, viable, and clinically proven solutions.

Nonmydriatic Photographic Screening for Diabetic Retinopathy in Pregnant Patients with Pre-Existing Diabetes in a Safety Net Population: 1 Year Results from the Diabetic Retinopathy in Pregnant Patients Study

Background: Pregnant patients with pre-existing diabetes mellitus (DM) are at increased risk for development or progression of existing diabetic retinopathy (DR). A quality improvement project was initiated to improve DR screening during pregnancy at a safety net hospital. This article highlights the utility and generalizability of our telemedicine-based screening model. Materials and Methods: In April 2018, we implemented a photographic retinal screening system in the Maternal Fetal Medicine (MFM) clinic at Santa Clara Valley Medical Center in San Jose, CA. The system is intended to screen all pregnant patients with pre-existing diabetes (type 1 and 2). Retinal images are automatically uploaded to a secure server and interpreted by a retina specialist (C.K.P.). Results: A total of 71 pregnant patients with pre-existing DM were seen in the MFM clinic during the study period. Sixty-six of 71 patients (93.0%) were screened compared with 69.1% in the year prior. Of the 64 patients screened with readable images 11 (17.2%) had DR, whereas 53 did not. Forty-nine of the 64 (74.2%) patients screened underwent screening using the new nonmydriatic system in the MFM clinic. Only 7 out of 47 (14.9%) patients with readable images in the MFM clinic required referral to the ophthalmology clinic. Conclusion: Our model for DR screening in pregnant patients in safety net hospitals is effective in improving screening rates and expediting evaluation and treatment for those in need. This system can prevent irreversible vision loss in pregnant patients and provides an effective framework for ophthalmic care in a safety net hospital system.

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often equal, or sometimes even exceed, those of human subjects on a variety of tasks, especially those related to image classification and pattern recognition. As one of the medical fields that is highly dependent on ancillary imaging tests, ophthalmology has been in a prime position to witness the application of deep learning algorithms that can help analyze the vast amount of data coming from those tests. In particular, glaucoma stands as one of the conditions where application of deep learning algorithms could potentially lead to better use of the vast amount of information coming from structural and functional tests evaluating the optic nerve and macula. The purpose of this article is to critically review recent applications of deep learning models in glaucoma, discussing their advantages but also focusing on the challenges inherent to the development of such models for screening, diagnosis and detection of progression. After a brief general overview of deep learning and how it compares to traditional machine learning classifiers, we discuss issues related to the training and validation of deep learning models and how they specifically apply to glaucoma. We then discuss specific scenarios where deep learning has been proposed for use in glaucoma, such as screening with fundus photography, and diagnosis and detection of glaucoma progression with optical coherence tomography and standard automated perimetry.

Translational Relevance

Deep learning algorithms have the potential to significantly improve diagnostic capabilities in glaucoma, but their application in clinical practice requires careful validation, with consideration of the target population, the reference standards used to build the models, and potential sources of bias.

Rates of Eye Care and Diabetic Eye Disease among Insured Patients with Newly Diagnosed Type 2 Diabetes

PURPOSE

To determine rates of eye examinations and diabetic eye disease in the first 5 years after diagnosis of type 2 diabetes (DM2) among continuously insured adults.

DESIGN

Retrospective, longitudinal cohort study.

PARTICIPANTS

Insured patients aged 40 years or older with newly diagnosed DM2 (n = 42 684), and control patients without diabetes matched on age, sex, and race were identified from a nationwide commercial claims database containing data from 2007 to 2015.

METHODS

All patients were tracked for 6 years: 1 year before and 5 years after the index diabetes diagnosis. Receipt of eye care for individual patients was identified using International Classification of Diseases 9th edition (ICD-9) procedure codes or Current Procedural Terminology (CPT) codes indicating an eye examination, as well as encounters indicating the patient was seen by an ophthalmologist. A diagnosis of diabetic eye disease was determined by using ICD-9 codes.

MAIN OUTCOME MEASURES

Outcome measures included annual receipt of eye care and development of diabetic eye disease, namely, diabetic retinopathy (DR). Associations between these outcomes and demographic factors were tested with multivariable logistic regression.

RESULTS

Diabetic patients received more eye examinations than controls in each year, but no more than 40.4% of diabetic patients received an examination in any given year. Patients with Medicare Advantage received fewer eye examinations at 5 years (odds ratio [OR], 0.79; P < 0.01) than those with private insurance but were less likely to develop DR (OR, 0.71; P < 0.01). Hispanic patients had higher rates of DR (OR, 1.60; P < 0.01) and received fewer eye examinations (OR, 0.75; P < 0.01) at 5 years compared with White patients. Men received fewer eye examinations (OR, 0.84; P < 0.01) and were more likely to develop DR at 5 years (OR, 1.17; P < 0.01) than women. Patients with higher education were more likely to receive an eye examination and less likely to develop DR.

CONCLUSIONS

The majority of diabetic patients do not receive adequate eye care within the 5 years after initial diabetes diagnosis despite having insurance. Efforts should be made to improve adherence to screening guidelines, especially for vulnerable populations.

Fundamental principles of an effective diabetic retinopathy screening program

BACKGROUND

Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults worldwide. Early detection and treatment are necessary to forestall vision loss from DR.

METHODS

A working group of ophthalmic and diabetes experts was established to develop a consensus on the key principles of an effective DR screening program. Recommendations are based on analysis of a structured literature review.

RESULTS

The recommendations for implementing an effective DR screening program are: (1) Examination methods must be suitable for the screening region, and DR classification/grading systems must be systematic and uniformly applied. Two-field retinal imaging is sufficient for DR screening and is preferable to seven-field imaging, and referable DR should be well defined and reliably identifiable by qualified screening staff; (2) in many countries/regions, screening can and should take place outside the ophthalmology clinic; (3) screening staff should be accredited and show evidence of ongoing training; (4) screening programs should adhere to relevant national quality assurance standards; (5) studies that use uniform definitions of risk to determine optimum risk-based screening intervals are required; (6) technology infrastructure should be in place to ensure that high-quality images can be stored securely to protect patient information; (7) although screening for diabetic macular edema (DME) in conjunction with DR evaluations may have merit, there is currently insufficient evidence to support implementation of programs solely for DME screening.

CONCLUSION

Use of these recommendations may yield more effective DR screening programs that reduce the risk of vision loss worldwide.

Cost Analysis of Teleophthalmology Screening for Diabetic Retinopathy Using Teleophthalmology Billing Codes

BACKGROUND AND OBJECTIVE

To evaluate the financial sustainability of teleophthalmology screening for diabetic retinopathy (DR) using telehealth billing codes.

PATIENTS AND METHODS

The authors performed an Institutional Review Board-approved retrospective review of medical records, billing data, and quality metrics at the University of California Davis Health System from patients screened for DR through an internal medicine-based telemedicine program using CPT codes 92227 or 92228.

RESULTS

A total of 290 patients received teleophthalmology screening over a 12-month period, resulting in an increase in the DR screening rate from 49% to 63% (P < .0001). The average payment per patient was $19.86, with an estimated cost of $41.02 per patient. The projected per-patient incentive bonus was $43.06 with a downstream referral revenue of $39.38 per patient. One hundred seventy-eight clinic visits were eliminated, providing an estimated cost savings of $42.53 per patient.

CONCLUSION

Sustainable teleophthalmology screening may be achieved by billing telehealth codes but only with health care incentive bonuses, patient referrals, and by accounting for the projected cost-savings of eliminating office visits. [Ophthalmic Surg Lasers Imaging Retina. 2020;51:S26-S34.].

Evaluation of a Remote Diagnosis Imaging Model vs Dilated Eye Examination in Referable Macular Degeneration

Importance

In improving clinical outcomes, developing a sustainable, transformative care delivery model is important for accessible, efficient, low-cost, high-quality community-based imaging and diagnosis of retinal diseases.

Objective

To test the feasibility and accuracy of the remote diagnosis imaging model as a clinical screening tool to facilitate the identification of referable macular degeneration.

Design, Setting, and Participants

A nonrandomized study of 159 patients was conducted in sites with a relatively high disease prevalence (Duke University Health System endocrinology clinic and 2 Duke University Health System assisted living centers in North Carolina). All patients underwent remote diagnosis imaging, defined as color fundus photography (CFP) and optical coherence tomography (OCT) of nondilated pupils, acquired by nonexpert imagers using a retinal imaging device located at the point of service. The criterion standard examination was defined as a traditional dilated eye examination performed by retinal specialists. Deidentified remote diagnosis images were graded for interpretability and presence of referable macular degeneration, defined as any condition requiring a retinal specialist attention. Data analysis was performed from November 20, 2015, to February 10, 2019.

Main Outcomes and Measures

Primary outcome was feasibility of the remote retinal imaging. Secondary outcomes were operational characteristics and diagnostic and referral accuracy.

Results

Of the 159 patients included in the study, the mean (SD) age of enrolled participants was 65 (17) years, with a female to male ratio of 1.3 to 1. Most patients were white (111 [69.8%]), 44 were black patients (27.7%), approximately 1% were Asian patients and Hispanic patients, and 2 patients declined to disclose their race/ethnicity. Thirty-five eyes (22.0%) were determined to require referral to the retinal specialist by criterion standard examination. Remote diagnosis image interpretability was better when OCT was used compared with CFP (241 [96.4%] vs 164 [65.6%]). Remote diagnosis had high diagnostic accuracy in identifying referable macular degeneration: OCT and CFP both had 94% sensitivity (95% CI, 84%-98%), and OCT had specificity higher than for CFP (93% [95% CI, 87%-96% ] vs 63% [95% CI, 53%-71%]). Substantial agreement was found between the criterion standard and OCT (κ = 0.83; 95% CI, 0.76-0.91; P < .001) and between the criterion standard and CFP (κ = 0.76; 95% CI, 0.64-0.87; P < .001). The nonvalidated patient satisfaction survey revealed that 122 participants (76.7%; mean score, 4.16; 95% CI, 3.98-4.35) preferred remote imaging over the standard care examination.

Conclusions and Relevance

Remote diagnosis imaging and a standard examination by a retinal specialist appeared equivalent in identifying referable macular degeneration in patients with high disease prevalence; these results may assist in delivering timely treatment and seem to warrant future research into additional metrics.

Estimates of the Percentage of US Adults With Diabetes Who Could Be Screened for Diabetic Retinopathy in Primary Care Settings

Importance

Prior studies found that screening for diabetic retinopathy (DR) in primary care settings using telemedicine increased screening rates among individuals with diabetes. This finding has led to interest in expanding the use of primary care-based screening for DR.

Objective

To estimate the percentages of US adults with diabetes and high-risk US adults with diabetes who have regular contact with primary care physicians and therefore could potentially receive timely screening for DR in primary care settings.

Design, Setting, and Participants

The empirical analyses used data from the cross-sectional population-based 2016 National Health Interview Survey on US adults 18 years or older with self-reported diabetes (n = 3229). Based on previous research, individuals who had lower income, lower educational levels, or type 2 diabetes; who were African American or Hispanic, uninsured, or not using insulin or oral medication for diabetes; or who did not have DR were defined as being at high risk of missing recommended eye examinations. Data were collected throughout 2016 and analyzed from July 17 through November 5, 2018.

Main Outcomes and Measures

Outcomes were whether an individual visited a primary care physician and whether an individual missed having a dilated eye examination in the past year.

Results

The survey sample included 3229 participants. Using weighted percentages of the full sample, 15.3% (95% CI, 13.8%-17.0%) had lower income, 19.7% (95% CI, 17.8%-21.6%) had lower educational levels, 15.4% (95% CI, 13.5%-17.4%) were African American, 16.0% (95% CI, 13.7%-18.6%) were Hispanic, 6.1% (95% CI, 4.9%-7.5%) were uninsured, and 50.1% (95% CI, 47.7%-52.4%) were female; the mean age was 60.1 years (95% CI, 59.4-60.8 years). In addition, 87.7% (95% CI, 85.9%-89.3%) visited a primary care physician in the past year. Of those who did not receive a dilated eye examination in the past year, 82.2% (95% CI, 78.4%-85.4%) visited a primary care physician during the year. Except for the uninsured subgroup, more than 78% of each high-risk subgroup had visited a primary care physician in the past year.

Conclusions and Relevance

Screening for DR in primary care settings has the potential to provide timely screening to a large portion of US adults with diabetes because most US adults with diabetes, including those at high-risk of missing recommended eye examinations, have regular contact with primary care physicians.

Telemedicine for Diabetic Retinopathy Screening in an Urban, Insured Population Using Fundus Cameras in a Primary Care Office Setting

BACKGROUND AND OBJECTIVE

This study examines the rate of adherence to recommended ophthalmology follow-up after primary care-based telemedicine diabetic retinopathy (DR) screening.

PATIENTS AND METHODS

Retrospective observational study of 5,764 insured diabetic patients undergoing telemedicine DR screening between May 2015 and April 2017 in an urban primary care setting. Patients underwent non-mydriatic fundus photography for telemedicine DR screening. The main outcome measure was the "capture rate."

RESULTS

Of the patients studied, 31.7% were found to have any retinal pathology, and 20% were found to have DR. In the 11.8% percent of patients with sight-threatening retinopathy who were recommended to have a retinal examination, the capture rate was 81.9%.

CONCLUSION

The authors' study demonstrated higher capture rate than has been previously reported, indicating that telemedicine DR screening in an urban, insured population may be a useful method for triaging high-risk patients without losing patients to follow-up. [Ophthalmic Surg Lasers Imaging Retina. 2019;50: e274-e277.].

Detection of anaemia from retinal fundus images via deep learning

Owing to the invasiveness of diagnostic tests for anaemia and the costs associated with screening for it, the condition is often undetected. Here, we show that anaemia can be detected via machine-learning algorithms trained using retinal fundus images, study participant metadata (including race or ethnicity, age, sex and blood pressure) or the combination of both data types (images and study participant metadata). In a validation dataset of 11,388 study participants from the UK Biobank, the fundus-image-only, metadata-only and combined models predicted haemoglobin concentration (in g dl-1) with mean absolute error values of 0.73 (95% confidence interval: 0.72-0.74), 0.67 (0.66-0.68) and 0.63 (0.62-0.64), respectively, and with areas under the receiver operating characteristic curve (AUC) values of 0.74 (0.71-0.76), 0.87 (0.85-0.89) and 0.88 (0.86-0.89), respectively. For 539 study participants with self-reported diabetes, the combined model predicted haemoglobin concentration with a mean absolute error of 0.73 (0.68-0.78) and anaemia an AUC of 0.89 (0.85-0.93). Automated anaemia screening on the basis of fundus images could particularly aid patients with diabetes undergoing regular retinal imaging and for whom anaemia can increase morbidity and mortality risks.

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.

Scaling Up Teleophthalmology for Diabetic Eye Screening: Opportunities for Widespread Implementation in the USA

PURPOSE OF REVIEW

We discuss opportunities to address key barriers to widespread implementation of teleophthalmology programs for diabetic eye screening in the United States (U.S.).

RECENT FINDINGS

Teleophthalmology is an evidence-based form of diabetic eye screening. This technology has been proven to substantially increase diabetic eye screening rates and decrease blindness. However, teleophthalmology implementation remains limited among U.S. health systems. Major barriers include financial concerns as well as limited utilization by providers, clinical staff, and patients. Possible interventions include increasingly affordable camera technology, demonstration of financially sustainable billing models, and engaging key stakeholders. Significant opportunities exist to overcome barriers to scale up and promote widespread implementation of teleophthalmology in the USA. Further development of methods to sustain effective increases in diabetic eye screening rates using this technology is needed. In addition, the demonstration of cost-effectiveness in a variety of billing models should be investigated to facilitate widespread implementation of teleophthalmology in U.S. health systems.

A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs

PURPOSE

To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT).

DESIGN

Cross-sectional study.

METHODS

A total of 9282 pairs of optic disc photographs and SDOCT optic nerve head scans from 927 eyes of 490 subjects were randomly divided into the validation plus training (80%) and test sets (20%). A DL convolutional neural network was trained to predict the SDOCT BMO-MRW global and sector values when evaluating optic disc photographs. The predictions of the DL network were compared to the actual SDOCT measurements. The area under the receiver operating curve (AUC) was used to evaluate the ability of the network to discriminate glaucomatous visual field loss from normal eyes.

RESULTS

The DL predictions of global BMO-MRW from all optic disc photographs in the test set (mean ± standard deviation [SD]: 228.8 ± 63.1 μm) were highly correlated with the observed values from SDOCT (mean ± SD: 226.0 ± 73.8 μm) (Pearson's r = 0.88; R² = 77%; P < .001), with mean absolute error of the predictions of 27.8 μm. The AUCs for discriminating glaucomatous from healthy eyes with the DL predictions and actual SDOCT global BMO-MRW measurements were 0.945 (95% confidence interval [CI]: 0.874-0.980) and 0.933 (95% CI: 0.856-0.975), respectively (P = .587).

CONCLUSIONS

A DL network can be trained to quantify the amount of neuroretinal damage on optic disc photographs using SDOCT BMO-MRW as a reference. This algorithm showed high accuracy for glaucoma detection, and may potentially eliminate the need for human gradings of disc photographs.

Eye Care Utilization Among Insured People With Diabetes in the U.S., 2010-2014

OBJECTIVE

Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults, and although screening with eye exams is effective, screening rates are low. We evaluated eye exam visits over a 5-year period in a large population of insured patients 10-64 years of age with diabetes.

RESEARCH DESIGN AND METHODS

We used claims data from IBM Watson Health to identify patients with diabetes and continuous insurance coverage from 2010 to 2014. Diabetes and DR were defined using ICD-9 Clinical Modification codes. We calculated eye exam visit frequency by diabetes type over a 5-year period and estimated period prevalence and cumulative incidence of DR among those receiving an eye exam.

RESULTS

Among the 298,383 insured patients with type 2 diabetes and no diagnosed DR, almost half had no eye exam visits over the 5-year period and only 15.3% met the American Diabetes Association (ADA) recommendations for annual or biennial eye exams. For the 2,949 patients with type 1 diabetes, one-third had no eye exam visits and 26.3% met ADA recommendations. The 5-year period prevalence and cumulative incidence of DR were 24.4% and 15.8%, respectively, for patients with type 2 diabetes and 54.0% and 33.4% for patients with type 1 diabetes.

CONCLUSIONS

The frequency of eye exams was alarmingly low, adding to the abundant literature that systemic changes in health care may be needed to detect and prevent vision-threatening eye disease among people with diabetes.

Identification of barriers, facilitators and system-based implementation strategies to increase teleophthalmology use for diabetic eye screening in a rural US primary care clinic: a qualitative study

OBJECTIVE

Teleophthalmology for diabetic eye screening is an evidence-based intervention substantially underused in US multipayer primary care clinics, even when equipment and trained personnel are readily available. We sought to identify patient and primary care provider (PCP) barriers, facilitators, as well as strategies to increase teleophthalmology use.

DESIGN

We conducted standardised open-ended, individual interviews and analysed the transcripts using both inductive and directed content analysis to identify barriers and facilitators to teleophthalmology use. The Chronic Care Model was used as a framework for the development of the interview guide and for categorising implementation strategies to increase teleophthalmology use.

SETTING

A rural, US multipayer primary care clinic with an established teleophthalmology programme for diabetic eye screening.

PARTICIPANTS

We conducted interviews with 29 participants (20 patients with diabetes and 9 PCPs).

RESULTS

Major patient barriers to teleophthalmology use included being unfamiliar with teleophthalmology, misconceptions about diabetic eye screening and logistical challenges. Major patient facilitators included a recommendation from the patient's PCP and factors related to convenience. Major PCP barriers to referring patients for teleophthalmology included difficulty identifying when patients are due for diabetic eye screening and being unfamiliar with teleophthalmology. Major PCP facilitators included the ease of the referral process and the communication of screening results. Based on our results, we developed a model that maps where these key patient and PCP barriers occur in the teleophthalmology referral process. Patients and PCPs also identified implementation strategies to directly address barriers and facilitators to teleophthalmology use.

CONCLUSIONS

Patients and PCPs have limited familiarity with teleophthalmology for diabetic eye screening. PCPs were expected to initiate teleophthalmology referrals, but reported significant difficulty identifying when patients are due for diabetic eye screening. System-based implementation strategies primarily targeting PCP barriers in conjunction with improved patient and provider education may increase teleophthalmology use in rural, US multipayer primary care clinics.

Use of Telehealth Screening to Detect Diabetic Retinopathy and Other Ocular Findings in Primary Care Settings

Purpose: To determine the incidence of diabetic retinopathy (DR) and other ocular findings in previously diagnosed diabetes using telehealth retinal screening with nonmydriatic fundus photography (nFP) in primary care physicians' offices. Methods: A retrospective study based on electronic chart review was performed. All diabetic patients who participated in the Wills Eye Hospital (WEH) telehealth retinal screening program from July 1, 2012 to February 20, 2017 were included. In addition to evaluation of DR, other eye pathologies of the retina were detected using nFP. Results: Overall, 9,946 diabetics participated in the WEH telehealth screening system. After exclusion of missing or unreadable images, 15,180 eyes of 7,624 (76.7%) patients were eligible for final analysis. A total of 1,269 (16.6%) patients were noted to have DR changes in at least one eye. Of those, 475 (37.4%) had mild nonproliferative DR (NPDR) in the more severely affected eye, 712 (56.1%) had moderate NPDR, 33 (2.6%) had severe NPDR, 19 (1.5%) had proliferative DR, and 30 (2.4%) have received pan-retinal photocoagulation previously. In addition, there was evidence of diabetic macular edema detectable on nFP in 34 eyes of 29 patients. Other ocular findings included hypertensive retinopathy (709, 9.3%), increased or asymmetric cup-to-disc ratio (562, 7.4%), age-related cataract (379, 5.0%), cotton-wool spots (221, 2.9%), choroidal nevus (74, 1.0%), age-related macular degeneration (AMD) (66, 0.9%), and epiretinal membrane (48, 0.6%). Patients with hypertensive retinopathy, glaucomatous findings, cataract, or AMD were significantly older (p < 0.001) than those without these ocular pathologies. Conclusion: The WEH Telehealth Screening Program identified DR in approximately one out of six patients and other ocular pathologies in over 25% of the diabetic population that received screenings in Philadelphia area primary care offices. Given the importance of early detection and routine eye care to prevent vision loss for DR patients, these findings have a significant impact.