Costs of a community-based glaucoma detection programme: analysis of the Philadelphia Glaucoma Detection and Treatment Project

Screening Strategies and Methodologies

PRCIS

While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease.

PURPOSE

To review the current evidence and concepts around screening for glaucoma.

METHODS/RESULTS

A group of glaucoma-focused clinician scientists drew on knowledge and experience around glaucoma, its etiology, and the options for screening. Glaucoma is a chronic progressive optic neuropathy affecting around 76 million individuals worldwide and is the leading cause of irreversible blindness globally. Early stages of the disease are asymptomatic meaning a substantial proportion of cases remain undiagnosed. Early detection and timely intervention reduce the risk of glaucoma-related visual morbidity. However, imperfect tests and a relatively low prevalence currently limit the viability of population-based screening approaches. The diagnostic yield of opportunistic screening strategies, relying on the identification of disease during unrelated health care encounters, such as cataract clinics and diabetic retinopathy screening programs, focusing on older people and/or those with a family history, are hindered by a large number of false-positive and false-negative results. Polygenic risk scores (PRS) offer personalized risk assessment for adult-onset glaucoma. In addition, artificial intelligence (AI) algorithms have shown impressive performance, comparable to expert humans, in discriminating between potentially glaucomatous and non-glaucomatous eyes. These emerging technologies may offer a meaningful improvement in diagnostic yield in glaucoma screening.

CONCLUSIONS

While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease.

Improving Access to Refractive Services in Adults: A Health Examination Center-Based Model

Purpose: To assess the potential of a health examination center-based screening model in improving service for uncorrected refractive error. Methods: Individuals aged ≥18 years undergoing the routine physical examinations at a tertiary hospital in the northeast China were invited. Presenting visual acuity, noncycloplegic autorefraction, noncontact tonometry, fundus photography, and slit-lamp examination were performed. Refractive error was defined as having spherical equivalent ≤ -0.75 D or ≥ +1 D and uncorrected refractive error was considered as refractive error combined with presenting visual acuity < 6/12 in the better eye. Costs for the screening were assessed. Results: A total of 5,284 participants (61 ± 14 years) were included. The overall prevalence of myopia and hyperopia was 38.7% (95% CI, 37.4-40.0%) and 23.5% (95% CI, 22.3-24.6%), respectively. The prevalence of uncorrected refractive error was 7.85% (95% CI, 7.13-8.58%). Women (p < 0.001 and p = 0.003), those with age ≥ 70 years (p < 0.001 and p = 0.003), and myopia (p < 0.001 and p < 0.001) were at higher risk of uncorrected refractive error and uncorrected refractive error-related visual impairment. Spectacle coverage rate was 70.6% (95% CI, 68.2-73.0%). The cost to identify a single case of refractive error and uncorrected refractive error was US$3.2 and US$25.2, respectively. Conclusion: The prevalence of uncorrected refractive error is high in the urban Chinese adults. Health examination center-based refractive error screening is able to provide an efficient and low-cost model to improve the refractive services in China.

Teleophthalmology Screening for Early Detection of Ocular Diseases in Underserved Populations in Israel

Background: The purpose of this study was to investigate the feasibility and effectiveness of an innovative telemedicine community-based intervention to increase detection of previously undiagnosed ocular diseases in high-risk populations in Israel. Methods: A team comprising an ocular technician, a project manager, and a driver was sent to underserved areas in Israel. Patient demographics, ocular, and medical information were recorded. Visual acuity (VA), intraocular pressure and fundus photographs were obtained. The data were transferred to the Ophthalmology Reading Center in Tel-Aviv Medical Center, where it was interpreted by an ophthalmologist. A letter was sent to the patients indicating examination results. It instructed them to return for a follow-up examination if indicated. Results: A total of 124 individuals underwent telemedicine remote screening examinations in 10 locations. The mean age was 79.9 ± 7.2 years, with female predominance of 67%. The major pathologies detected were (1) reduction in VA >6/12 in at least one eye (n = 48, 38.7%); (2) glaucoma suspicion in the optic disk (n = 18, 14.5%); (3) ocular hypertension >21 mmHg (n = 15, 12.1%); (4) age-related macular degeneration (AMD; n = 15, 12.1%); (5) diabetic retinopathy (n = 6, 4.8%); (6) visually significant cataract (n = 6, 4.8%); and (7) other pathologies (n = 11, 8.9%); 97.7% of the patients reported high satisfaction rates (they were satisfied or very satisfied from the project model). Conclusions: Our pilot telemedicine screening project effectively detected ocular diseases in underserved areas in Israel and helped improve access to eye care. This project has the potential of reaching a national level, allow for early diagnosis, and prevent vision loss and blindness in underserved areas.

Manhattan Vision Screening and Follow-up Study in Vulnerable Populations (NYC-SIGHT): Design and Methodology

PRCIS

The Manhattan Vision Screening and Follow-up Study in Vulnerable Populations is a 5-year prospective, cluster-randomized study to improve detection and management of glaucoma and other eye diseases in vulnerable populations living in affordable housing developments.

PURPOSE

To describe the study design and methodology of the Manhattan Vision Screening and Follow-up Study in Vulnerable Populations, which aims to investigate whether community-based vision screenings can improve detection and management of glaucoma, vision impairment, cataract, and other eye diseases among vulnerable populations living in affordable housing developments in upper Manhattan.

MATERIALS AND METHODS

This 5-year prospective, cluster-randomized, controlled trial consists of vision screening and referral for follow-up eye care among eligible residents aged 40 and older. Visual acuity, intraocular pressure (IOP), and fundus photography are measured. Participants with visual worse than 20/40, or IOP 23 to 29 mm Hg, or unreadable fundus images fail the screening and are scheduled with the on-site optometrist. Those with an abnormal image and/or IOP ≥30 mm Hg, are assigned as "fast-track" and referred to ophthalmology. Participants living in 7 developments randomized to the Enhanced Intervention Group who fail the screening and need vision correction receive complimentary eyeglasses. Those referred to ophthalmology receive enhanced support with patient navigators to assist with follow-up eye care. Participants living in 3 developments randomized to the Usual Care Group who fail the screening and need vision correction are given an eyeglasses prescription only and a list of optical shops. No enhanced support is given to the Usual Care Group. All participants referred to ophthalmology are assisted in making their initial eye exam appointment.

CONCLUSION

This study targets vulnerable populations where they live to ensure improved access to and utilization of eye care services in those who are least likely to seek eye care.

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a "new normal", the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.

Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks

Purpose: This study developed and evaluated a deep learning ensemble method to automatically grade the stages of glaucoma depending on its severity.Materials and Methods: After cross-validation of three glaucoma specialists, the final dataset comprised of 3,460 fundus photographs taken from 2,204 patients were divided into three classes: unaffected controls, early-stage glaucoma, and late-stage glaucoma. The mean deviation value of standard automated perimetry was used to classify the glaucoma cases. We modeled 56 convolutional neural networks (CNN) with different characteristics and developed an ensemble system to derive the best performance by combining several modeling results.Results: The proposed method with an accuracy of 88.1% and an average area under the receiver operating characteristic of 0.975 demonstrates significantly better performance to classify glaucoma stages compared to the best single CNN model that has an accuracy of 85.2% and an average area under the receiver operating characteristic of 0.950. The false negative is the least adjacent misprediction, and it is less in the proposed method than in the best single CNN model.Conclusions: The method of averaging multiple CNN models can better classify glaucoma stages by using fundus photographs than a single CNN model. The ensemble method would be useful as a clinical decision support system in glaucoma screening for primary care because it provides high and stable performance with a relatively small amount of data.

The Vision Detroit Project: Visual Burden, Barriers, and Access to Eye Care in an Urban Setting

Purpose: Vision loss and blindness are among the top ten disabilities in the United States, yet access and utilization of eye care remains low. Vision Detroit aimed to address eye-care disparities via community-based screenings. By investigating burden of eye disease and barriers to eye-care utilization in an underserved urban community, we may direct efforts to improve access.Methods: Twenty-three screenings were conducted from March 2015-November 2017. Patient information gathered at screenings were demographics, medical and social history, eye exam/referral history, insurance status, primary care physician (PCP) status, and patient-perceived eye-care barriers.Results: Three-hundred-eighty patients were screened, 42% African American and 51% Hispanic. Average age was 53 ± 16.4 years, 70% reported vision problems, 50% reported over two years of vision problems, and average habitual visual acuity in best-seeing eye was 20/37. Eye-care underutilization was reported in 61% of type-2 diabetics. Older age and PCP recommendations/referrals were associated with increased utilization in all patients. Insurance was the most common barrier (53%); of the 55% insured, 31% reported financial barriers. Employed patients were more likely than unemployed to report a time barrier (odds ratio = 1.76, 95% confidence interval 1.03-3.01). Those with high school or less education reported "unaware of need", "unsure where to go", "transportation", and "insurance" as barriers more often.Conclusions: Visual burden was pervasive, yet access was suboptimal. Financial, logistical, and awareness barriers were common. PCP referral and older age were associated with increased utilization. Those less educated reported more barriers, highlighting the need to address fiscal concerns and eye-health education.

Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma

Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a gaze-contingent simulated visual field (VF) loss paradigm, in which participants experienced a variable magnitude of simulated VF loss based on longitudinal data from a real glaucoma patient (thereby controlling for other variables, such as age and general health). Fifty-five young participants with healthy vision were asked to view two short videos and three pictures, either with: (1) no VF loss, (2) moderate VF loss, or (3) advanced VF loss. Eye-movements were recorded using a remote eye tracker. Key eye-movement parameters were computed, including saccade amplitude, the spread of saccade endpoints (bivariate contour ellipse area), location of saccade landing positions, and similarity of fixations locations among participants (quantified using kernel density estimation). The simulated VF loss caused some statistically significant effects in the eye movement parameters. Yet, these effects were not capable of consistently identifying simulated VF loss, despite it being of a magnitude likely easily detectable by standard automated perimetry.

Feeling the pressure: a cross-sectional study exploring feasibility of a healthcare Pop-Up for intraocular pressure measurements in shopping centres in England

OBJECTIVES

To test the hypothesis that a shopping centre Pop-Up health check combining an intraocular pressure (IOP) check with a general health check (blood pressure (BP)) is more readily accepted by the general public than an IOP check only. We investigate public awareness of IOP compared with BP and the feasibility of measuring IOP in large numbers in a Pop-Up.

DESIGN

A cross-sectional study using a tailor-made healthcare Pop-Up.

SETTING

The 'Feeling the Pressure' Pop-Up was sited in eight regionally-different shopping centres in England.

PARTICIPANTS

Adult members of the public in shopping centres.

METHODS

On one day we measured IOP only and on another measured BP and IOP. IOP was measured by Icare IC100 tonometer (Helsinki, Finland). Potential participants were asked about their awareness of IOP and BP and when they last visited their optometrist.

RESULTS

More people attended the combined BP + IOP days (461; 60%; 95% CI 56% to 64%) than IOP-only days (307; 40%, 95% CI 37% to 43%) over 16 days of testing. We recorded IOP in 652 participants (median (IQR) age and IOP of 54 (42 to 68) years and 13 (11 to 15) mm Hg, respectively). Fewer people reported awareness about IOP (19%, 95% CI 16% to 23%) compared with BP (71%, 95% CI 66% to 75%). Of 768 participants, 60 (8%) reported no previous optometric eye examination and 185 (24%) reported >2 years since their most recent examination.

CONCLUSIONS

Measuring IOP in large numbers of the public via a shopping centre Pop-Up is feasible. Public engagement was greater when a BP check was offered alongside an IOP check, suggesting unfamiliar health checks can be promoted by aligning them with a more familiar check. Our findings hint at strategies for public health schemes that engage the public with their eye health.

Philadelphia glaucoma detection and treatment project: ocular outcomes and adherence to follow-up at a single health centre

OBJECTIVES

To determine ocular outcomes and factors associated with adherence to ophthalmic follow-up in a medically underserved population at a single health centre in Philadelphia.

DESIGN

Retrospective chart review.

PARTICIPANTS

Patients from a community glaucoma screening program.

METHODS

Chart review was conducted for participants who received a complete eye examination at the Philadelphia District Health Center 5 between January 1, 2012 and May 31, 2014 within the Philadelphia Glaucoma Detection and Treatment Project. Multivariate logistic regression was used to determine factors related to ophthalmic follow-up adherence.

RESULTS

A total of 249 participants completed an eye examination (mean age = 57.7 ± 6.9 years). Most were African American (n = 220; 88.4%); female (n = 129; 51.8%). Forty-seven participants (18.9%) received glaucoma-related diagnoses, 20 (8.0%) were prescribed ocular medication, and 26 (10.4%) underwent laser therapy. Ninety (36.1%) attended their recommended follow-up eye examination at the health centre. Glaucoma-related diagnosis (p ≤ 0.001), recommendation of a 4- to 6-week follow-up period (p < 0.001), prescribed eye drops (p < 0.001), or received laser therapy (p = 0.047) were factors most predictive of ophthalmic follow-up adherence.

CONCLUSIONS

The collaborative effort of eye care providers and health centres offers an important opportunity to detect, treat, and manage glaucoma and other ocular pathology in medically underserved communities. Having a glaucoma-related diagnosis, initiating treatment, and scheduling regular follow-up visits are the most important factors influencing adherence to follow-up eye appointments.

The estimated healthcare cost of diabetic retinopathy in Indonesia and its projection for 2025

PURPOSE

To estimate the total healthcare cost associated with diabetic retinopathy (DR) in type 2 diabetes in Indonesia and its projection for 2025.

METHODS

A prevalence-based cost-of-illness model was constructed from previous population-based DR study. Projection for 2025 was derived from estimated diabetes population in 2025. Direct treatment costs of DR were estimated from the perspective of healthcare. Patient perspective costs were obtained from thorough interview including only transportation cost and lost of working days related to treatment. We developed four cost-of-illness models according to DR severity level, DR without necessary treatment, needing laser treatment, laser +intravitreal (IVT) injection and laser + IVT +vitrectomy. All costs were estimated in 2017 US$.

RESULTS

The healthcare costs of DR in Indonesia were estimated to be $2.4 billion in 2017 and $8.9 billion in 2025. The total cost in 2017 consisted of the cost for no DR and mild-moderate non-proliferative DR (NPDR) requiring eye screening ($25.9 million), severe NPDR or proliferative DR (PDR) requiring laser treatment ($0.25 billion), severe NPDR or PDR requiring both laser and IVT injection ($1.75 billion) and advance level of PDR requiring vitrectomy ($0.44 billion).

CONCLUSIONS

The estimated healthcare cost of DR in Indonesia in 2017 was considerably high, nearly 2% of the 2017 national state budget, and projected to increase significantly to more than threefold in 2025. The highest cost may incur for DR requiring both laser and IVT injection. Therefore, public health intervention to delay or prevent severe DR may substantially reduce the healthcare cost of DR in Indonesia.

Cost-effectiveness analysis of iStent trabecular micro-bypass stent for patients with open-angle glaucoma in Colombia

OBJECTIVE

To estimate the cost-effectiveness of trabecular micro bypass stent vs laser trabeculoplasty or medications only, for patients with open-angle glaucoma in a setting of the Colombian System Health.

METHODS

This is a cost-effectiveness analysis that based its assumptions in external data sources, used to extrapolate the quality-of-life related to health, survival, and costs. A Markov model, with stages from 0 (ocular hypertension without glaucoma) to 5 and bilateral blindness, was developed inclusive of Colombians older than 40 years in 2018, from a societal perspective, comparing trabecular micro-bypass stents vs laser trabeculoplasty, timolol + dorzolamide + brimonidine, timolol + dorzolamide + latanoprost, or timolol + dorzolamide + brimatoprost, in terms of clinical and economic outcomes over a lifetime horizon. Both costs and health outcomes had an annual rate discount of 5%. Health outcomes were evaluated in terms of QALYs related with loss of visual acuity. Trabecular micro-bypass costs include the joint use of timolol, and the costs of laser trabeculoplasty include the combined use of timolol + dorzolamide.

RESULTS

Trabecular micro-bypass stents were estimated to have 127,971 more discounted QALYs vs laser trabeculoplasty; 405,982 vs timolol + dorzolamide + brimonidine; and 378,287 vs timolol + dorzolamide + latanoprost or timolol + dorzolamide + brimatoprost. Cumulative costs with trabecular micro-bypass stents at 40 years was $13,252,318 lower than laser trabeculoplasty; $6,403,534, lower than timolol + dorzolamide + brimonidine; $22,311,064, lower than timolol + dorzolamide + latanoprost; and $29,156,113 lower than timolol + dorzolamide + brimatoprost.

CONCLUSIONS

The trabecular micro-bypass stent is a highly cost-saving strategy due to more QALYs related to a lower rate of the population with loss of visual acuity in the long-term, and because the costs associated with additional medications and complications are lower with trabecular micro-bypass stents.

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs

PURPOSE

To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs.

DESIGN

A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs.

PARTICIPANTS

We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm.

METHODS

This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm.

MAIN OUTCOME MEASURES

The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON.

RESULTS

In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%).

CONCLUSIONS

A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results.