Presentation (CTI)

OBJECTIVES: European and UK retinal services face increasing pressure due to rising prevalence of chronic retinal diseases, expanding demand for intravitreal treatments, and constrained clinic capacity and workforce resources. Treatment pathways for wAMD and DME differ substantially in intensity and resource utilisation. This study aims to develop a conceptual framework to characterise how differential treatment intensity influences healthcare resource allocation and opportunity costs in capacity-constrained retinal services
METHODS: A structured framework conceptualising capacity as a binding constraint within the retinal service was developed, reflecting principles of constrained optimization whereby finite resources must be allocated across competing demands. This was informed by a targeted literature review and health economic principles. Key system constraints include capacity limitations, treatment burden, clinic throughput restrictions, and workforce pressures. The framework conceptualises the system in terms of inputs (capacity constraints), treatment characteristics (treatment intensity and durability), and outputs (resource utilization and service throughput). It maps relationships between treatment intensity and resource utilisation across wAMD and DME pathways within finite healthcare system capacity.
RESULTS: Capacity was identified as a binding constraint within retinal services. High-frequency injection and monitoring pathways consumed a disproportionate share of finite resources, including clinic time and workforce capacity. wAMD and DME pathways compete for shared intravitreal service capacity, with higher-intensity treatment paradigms reducing overall system efficiency. This results in opportunity cost, whereby capacity consumed by high-frequency pathways may displace or delay care for other patients or conditions affecting access and outcomes
CONCLUSIONS: In capacity-constrained retinal services, treatment value extends beyond clinical effectiveness on its impact on healthcare resource utilisation and system efficiency. Approaches that reduce treatment burden may improve throughout; however, value depends on integration within optimised care pathways. This framework highlights the importance of incorporating capacity constraints into healthcare decision-making and supports future quantitative modelling and healthcare resource allocation and service planning.