Presentation
A Scoping Review of Artificial Intelligence in Ophthalmology: Insights for Clinical Workflow Optimization
SessionPoster Session 2
DescriptionThe integration of artificial intelligence (AI) into healthcare has potential to revolutionize clinical practice, and ophthalmology is at the forefront of this transformation. Ophthalmology presents a fertile ground for AI-driven solutions aimed at enhancing diagnostic accuracy, personalizing treatment plans, and streamlining clinical workflows. This presentation will detail the methodology and findings of a comprehensive scoping review that maps the current landscape and future trajectory of AI applications within ophthalmology clinics. The primary focus is on how these technologies are being developed to support, augment, and automate tasks traditionally performed by ophthalmic professionals, including technicians, ophthalmologists, and administrative staff. We will explore AI's role in various stages of patient care, from initial screening and triage using chatbot-based histories to advanced diagnostic support through the analysis of optical coherence tomography (OCT), fundus photography, and visual fields. The background for this review is rooted in the growing pressures on eye care services worldwide, including an aging population and increasing prevalence of chronic eye diseases like diabetic retinopathy and glaucoma. AI offers a potential solution to mitigate these challenges by improving efficiency and expanding access to care.
This presentation will provide a detailed overview of the scoping review's findings, categorizing existing AI tools by their function within the clinical workflow, such as patient scheduling, preliminary data collection, diagnostic image analysis, clinical decision support, and patient monitoring. We will highlight successful implementations where AI has demonstrably reduced wait times, minimized diagnostic errors, and allowed clinicians to focus on more complex aspects of patient care. For instance, we will discuss AI algorithms that can autonomously screen for diabetic retinopathy, flagging high-risk patients for immediate review by an ophthalmologist, thereby optimizing resource allocation. Furthermore, we will examine the emerging use of predictive analytics to forecast disease progression and treatment response, shifting the paradigm from reactive to proactive eye care. The core message of this presentation is that while the technological capabilities of AI are advancing rapidly, its successful and safe integration is not merely a technical challenge but a profound human factors issue. The take-away point for the audience is that the ultimate value of AI in ophthalmology will be determined by how well these tools are designed to work in synergy with human clinicians. We will present evidence showing that poorly designed AI systems, or those implemented without consideration for existing workflows, can lead to increased cognitive load, alert fatigue, automation bias, and a deterioration in the quality of care. Therefore, a human-centered design approach is not just beneficial but essential for realizing the full potential of AI in enhancing the efficiency and safety of ophthalmology clinics. We will conclude by synthesizing these findings to propose a roadmap for the future development and implementation of AI in ophthalmology, one that is grounded in the principles of human factors and ergonomics to ensure these powerful tools are effective, usable, and seamlessly integrated into the complex sociotechnical system of modern eye care.
This presentation will provide a detailed overview of the scoping review's findings, categorizing existing AI tools by their function within the clinical workflow, such as patient scheduling, preliminary data collection, diagnostic image analysis, clinical decision support, and patient monitoring. We will highlight successful implementations where AI has demonstrably reduced wait times, minimized diagnostic errors, and allowed clinicians to focus on more complex aspects of patient care. For instance, we will discuss AI algorithms that can autonomously screen for diabetic retinopathy, flagging high-risk patients for immediate review by an ophthalmologist, thereby optimizing resource allocation. Furthermore, we will examine the emerging use of predictive analytics to forecast disease progression and treatment response, shifting the paradigm from reactive to proactive eye care. The core message of this presentation is that while the technological capabilities of AI are advancing rapidly, its successful and safe integration is not merely a technical challenge but a profound human factors issue. The take-away point for the audience is that the ultimate value of AI in ophthalmology will be determined by how well these tools are designed to work in synergy with human clinicians. We will present evidence showing that poorly designed AI systems, or those implemented without consideration for existing workflows, can lead to increased cognitive load, alert fatigue, automation bias, and a deterioration in the quality of care. Therefore, a human-centered design approach is not just beneficial but essential for realizing the full potential of AI in enhancing the efficiency and safety of ophthalmology clinics. We will conclude by synthesizing these findings to propose a roadmap for the future development and implementation of AI in ophthalmology, one that is grounded in the principles of human factors and ergonomics to ensure these powerful tools are effective, usable, and seamlessly integrated into the complex sociotechnical system of modern eye care.
Event Type
Poster Presentation
TimeTuesday, March 244:45pm - 6:15pm EDT
LocationRhinelander Gallery
Digital Health