Economic Evaluation of AI-Enabled Glaucoma Screening: A Dominant Strategy for Improved Health Outcomes and Cost Savings

Abstract

Abstract Objective: Glaucoma, a leading cause of irreversible blindness worldwide, necessitates early detection and appropriate management to prevent visual impairment. While previous studies examining the benefits of routine glaucoma screening have produced divergent results, this research proposes a novel approach leveraging artificial intelligence (AI) to address the limitations of existing methods. Methods: We constructed a Markov model, explicitly accounting for bottlenecks in glaucoma specialist visits, which can impact disease progression due to prolonged waiting times. Data from a reputable glaucoma specialist clinic was used, including 10-year costs for routine tests, AI screening, and glaucoma treatment. The analysis compared the costs and health outcomes of AI-enabled glaucoma screening and monitoring to conventional case finding and follow-up. Results: Our results indicate a substantial difference in total costs between AI and human-driven screening and monitoring over the 10-year observation period, with AI leading to financial savings of EUR 2602. Additionally, AI adoption reduced the risk of glaucoma development by 14% and the risk of unilateral or bilateral blindness by 4.6%. Conclusions: AI-enabled glaucoma screening emerges as a dominant strategy, exhibiting both financial benefits for healthcare systems and improved health outcomes for patients. By overcoming the inefficiencies of conventional approaches and addressing glaucoma-related challenges, AI technology holds the potential to revolutionize glaucoma care, improving patient well-being, and reducing the burden of disease. Despite limitations in explicitly modelling glaucoma progression and combining visual impaired states, sensitivity analyses consistently demonstrated cost reduction and decreased the risk of visual impairment with AI implementation.