Disparities in Retinal Vein Occlusion Presentation and Initiation of Anti-VEGF Therapy: An Academy IRIS® Registry Analysis.

OBJECTIVE: Investigate disparities in retinal vein occlusion (RVO) presentation and initiation of anti-VEGF treatment. DESIGN: Retrospective cohort study. SUBJECTS: Patients in the American Academy of Ophthalmology IRIS® (Intelligent Research in Sight) Registry database (2015-2021) with branch or central RVO and macular edema (ME). METHODS: The association of demographic characteristics and presenting visual acuity (VA) with anti-VEGF treatment initiation were quantified using multivariable logistic regression. MAIN OUTCOME MEASURES: Treatment with ≥ 1 anti-VEGF injection within 12 months after RVO diagnosis. RESULTS: A total of 304 558 eligible patients with RVO and ME were identified. Age at presentation varied by race, ethnicity, sex, and RVO type (all P values < 0.001). Within the first year after RVO presentation, 192 602 (63.2%) patients received ≥ 1 anti-VEGF injection. In a multivariable regression model adjusting for relevant covariates, female (vs. male) patients had lower odds of receiving injections (odds ratio [OR], 0.95; 95% confidence interval [CI], 0.93-0.96; P < 0.0001) as did Black/African American (vs. White) patients (OR, 0.90; 95% CI, 0.88-0.92; P < 0.0001) and Asian (vs. White) patients (OR, 0.95; 95% CI, 0.91-0.99; P = 0.02), whereas older patients (vs. patients aged < 51 years) had higher odds (61-70 years: OR, 1.20; 95% CI, 1.16-1.24; 71-80 years: OR, 1.20; 95% CI, 1.16-1.24; > 80 years: OR, 1.15; 95% CI, 1.11-1.18; all P values < 0.0001). Hispanic (vs. non-Hispanic) patients had a small increased odds of treatment initiation (OR, 1.08; 95% CI, 1.04-1.11; P < 0.0001). Results were similar in the subset of 226 143 patients with VA data. In this subset, patients with presenting VA < 20/40 to 20/200 were most frequently treated in the first year after diagnosis (∼ 70%) and patients with light perception/no light perception (LP-NLP) vision or VA of 20/20 or better were treated least frequently (36.9% and 41.9%, respectively). CONCLUSIONS: In this large national clinical registry, 37% of RVO patients with ME had no anti-VEGF treatment documented in the first year after diagnosis. Black/African American, Asian, and female patients and patients with VA of LP-NLP were least likely to receive treatment. Awareness of this undertreatment and these disparities highlight the need for initiatives to ensure all RVO patients receive timely anti-VEGF injections for optimized visual outcomes. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Is Artificial Intelligence the Cost-Saving Lens to Diabetic Retinopathy Screening in Low- and Middle-Income Countries?

Diabetes is a rapidly growing global health crisis disproportionately affecting low- and middle-income countries (LMICs). The emergence of diabetes as a global pandemic is one of the major challenges to human health, as long-term microvascular complications such as diabetic retinopathy (DR) can lead to irreversible blindness. Leveraging artificial intelligence (AI) technology may improve the diagnostic accuracy, efficiency, and accessibility of DR screenings across LMICs. However, there is a gap between the potential of AI technology and its implementation in clinical practice. The main objective of this systematic review is to summarize the currently available literature on the health economic assessments of AI implementation for DR screening in LMICs. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We conducted an extensive systematic search of PubMed/MEDLINE, Scopus, and the Web of Science on July 15, 2023. Our review included full-text English-language articles from any publication year. The Joanna Briggs Institute's (JBI) critical appraisal checklist for economic evaluations was used to rate the quality and rigor of the selected articles. The initial search generated 1,423 records and was narrowed to five full-text articles through comprehensive inclusion and exclusion criteria. Of the five articles included in our systematic review, two used a cost-effectiveness analysis, two used a cost-utility analysis, and one used both a cost-effectiveness analysis and a cost-utility analysis. Across the five articles, LMICs such as China, Thailand, and Brazil were represented in the economic evaluations and models. Overall, three out of the five articles concluded that AI-based DR screening was more cost-effective in comparison to standard-of-care screening methods. Our systematic review highlights the need for more primary health economic analyses that carefully evaluate the economic implications of adopting AI technology for DR screening in LMICs. We hope this systematic review will offer valuable guidance to healthcare providers, scientists, and legislators to support appropriate decision-making regarding the implementation of AI algorithms for DR screening in healthcare workflows.

United States Population Disparities in Ophthalmic Care: Blindness and Visual Impairment in the IRIS® Registry (Intelligent Research in Sight).

PURPOSE: To evaluate associations of patient characteristics with United States eye care use and likelihood of blindness. DESIGN: Retrospective observational study. PARTICIPANTS: Patients (19 546 016) with 2018 visual acuity (VA) records in the American Academy of Ophthalmology's IRIS® Registry (Intelligent Research in Sight). METHODS: Legal blindness (20/200 or worse) and visual impairment (VI; worse than 20/40) were identified from corrected distance acuity in the better-seeing eye and stratified by patient characteristics. Multivariable logistic regressions evaluated associations with blindness and VI. Blindness was mapped by state and compared with population characteristics. Eye care use was analyzed by comparing population demographics with United States Census estimates and proportional demographic representation among blind patients versus a nationally representative US population sample (National Health and Nutritional Examination Survey [NHANES]). MAIN OUTCOME MEASURES: Prevalence and odds ratios for VI and blindness; proportional representation in the IRIS® Registry, Census, and NHANES by patient demographics. RESULTS: Visual impairment was present in 6.98% (n = 1 364 935) and blindness in 0.98% (n = 190 817) of IRIS patients. Adjusted odds of blindness were highest among patients ≥ 85 years old (odds ratio [OR], 11.85; 95% confidence interval [CI], 10.33-13.59 vs. those 0-17 years old). Blindness also was associated positively with rural location and Medicaid, Medicare, or no insurance vs. commercial insurance. Hispanic (OR, 1.59; 95% CI, 1.46-1.74) and Black (OR, 1.73; 95% CI, 1.63-1.84) patients showed a higher odds of blindness versus White non-Hispanic patients. Proportional representation in IRIS Registry relative to the Census was higher for White than Hispanic (2- to 4-fold) or Black (11%-85%) patients (P < 0.001). Blindness overall was less prevalent in NHANES than IRIS Registry; however, prevalence in adults aged 60+ was lowest among Black participants in the NHANES (0.54%) and second highest among comparable Black adults in IRIS (1.57%). CONCLUSIONS: Legal blindness from low VA was present in 0.98% of IRIS patients and associated with rural location, public or no insurance, and older age. Compared with US Census estimates, minorities may be underrepresented among ophthalmology patients, and compared with NHANES population estimates, Black individuals may be overrepresented among blind IRIS Registry patients. These findings provide a snapshot of US ophthalmic care and highlight the need for initiatives to address disparities in use and blindness. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.