Defining a standards framework for ophthalmology real-world data methodologies through an expert-led Delphi consensus

Background/Objectives: Real-world data (RWD) is becoming increasingly important in ophthalmology, offering insights into clinical outcomes, therapeutic approaches, and healthcare practices. However, methodological variability limits comparability and generalisability across RWD studies. This Delphi consensus aimed to establish expert agreement on the need for standardised methodologies in ophthalmology RWD studies, identify the key clinical and patient-reported data elements that should be collected, and explore strategies for consistent implementation. Methods: A modified Delphi methodology was followed. A steering committee (SC) of three ophthalmologists developed 38 consensus statements across five key topics. These statements were developed into an online four-point Likert scale survey and distributed to healthcare professionals experienced in managing retinal diseases via members of The Ophthalmology Network. Consensus was defined a priori as ≥75% agreement. Results were shared with the SC and key recommendations were discussed. Results: A total of 244 responses were received, predominantly from retina specialists (n = 232, 95%), with broad representation across six regions, the largest being Europe (n = 116, 48%). Consensus was achieved for all 38 statements, with 36 (95%) reaching ≥90%. These statements covered key principles, including: variability of current standards, ideal clinical standards for RWD collection, RWD analysis methodology, ideal patient-reported standards, and implementing and reporting consistent standards/frameworks. As the stopping criteria were met, no further Delphi rounds were conducted. Eight key recommendations were developed. Conclusions: The outputs from this consensus aim to guide future ophthalmology RWD studies towards improved consistency, reliability, and generalisability, ultimately strengthening the evidence base for clinical decision-making to improve patient outcomes.