The Hidden Carbon Cost of Digital Ophthalmology: A Call for Sustainable Data Practices

Digital transformation has revolutionised healthcare, enhancing patient care across all specialties. Although these technological advancements have undoubtedly improved diagnostic precision and patient outcomes, the environmental cost of storing and managing these data remains largely overlooked. In Australia, the healthcare sector contributes approximately 7% of the nation's total carbon emissions 1. As medical fields increasingly rely on high-resolution imaging and longitudinal data, the sustainability of these practices warrants urgent attention. Ophthalmology, a data-intensive speciality, exemplifies this challenge. From optical coherence tomography (OCT) to fundus photography and visual field testing, the volume of data generated in routine practice is immense. Although surgical waste and resource use have received attention in ophthalmology's sustainability discourse 2, the environmental impact of data storage remains under-addressed. Globally, data centres represent 1%–1.5% of total electricity use and are becoming increasingly energy intensive. Within Australia, estimates suggest a single data centre may consume the energy equivalent, in a year, of heating 50 000 homes 3. With the rise of AI and big data analytics, electricity consumption in data centres is projected to increase by 50%–60% by 2030 4, driven by the need for high-performance computing and continuous data availability. A single OCT scan can exceed 100 MB, and longitudinal care often involves hundreds of such images per patient. With millions of retinal assessments and diagnostic imaging performed annually, the cumulative data storage demand is staggering. Although telemedicine is often promoted as a sustainable alternative to in-person consultations—particularly for reducing travel-related emissions—it also contributes to the growing volume of stored digital data. In ophthalmology, remote consultations frequently involve high-resolution imaging and video files, which are archived for clinical and medico-legal purposes. Although the environmental benefits of reduced transport are real, the energy demands of long-term data storage must also be considered, especially in systems lacking efficient lifecycle management. This underscores the need to evaluate sustainability across the entire digital care continuum. Many institutions store data indefinitely, often redundantly, without clear retention policies or sustainability frameworks. This practice not only strains digital infrastructure but also contributes to unnecessary energy use and emissions. As artificial intelligence (AI) becomes more integrated into ophthalmic care, the demand for big data—large, annotated datasets—will only increase, further amplifying the environmental footprint of data storage. These environmental concerns are compounded by several systemic challenges in ophthalmic data management. Understanding these challenges is the first step towards developing responsible digital care models. As sustainability is rarely included in clinical training or digital health policy discussions, ophthalmologists may be less aware of the environmental implications of data storage practices. This results in missed opportunities to reduce carbon footprint associated with data management, hindering progress towards environmentally responsible care. Currently, RANZCO has implemented sustainability policies including carbon reduction, education, waste minimisation and event greening 2. Building on these commitments, it is crucial further to integrate sustainability metrics into accreditation standards. Initiatives like EyeSustain offer pledges and toolkits for ophthalmic practices to reduce waste and carbon emissions 12. Similar frameworks should be adopted locally, including guidance on sustainable telemedicine practices, such as data minimisation and retention policies. Ophthalmology's digital transformation has brought undeniable benefits to patient care, but it has also introduced new environmental responsibilities. As data volume grows, so too does the carbon footprint of this digital infrastructure. By implementing sustainable data practices, as outlined above, the specialty can mitigate its environmental impact without compromising clinical excellence. We urge ophthalmic institutions, professional bodies, and policymakers to prioritise digital sustainability. Integrating environmental considerations into data governance is not only a technical upgrade, but also a moral imperative in the face of climate change. The RANZCO Sustainability Committee has overseen this editorial version and fully supports its publication. The authors have nothing to report. The authors declare no conflicts of interest. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.