Building a National Interoperable Rare Eye Disease Data Warehouse: Methodological Framework and Implementation Report...

Rare eye diseases are characterized by low prevalence, clinical heterogeneity, and fragmented data collection, which limit the reliability of analysis results and multicenter research. In France, the development of health data warehouses is strictly regulated by national data protection authorities. While international initiatives aim to harmonize rare disease registries, capturing hyperspecialized, multimodal clinical records and ophthalmology-specific imaging within a fully compliant and sustainable infrastructure remains a major operational challenge.

This study aims to describe the methodological framework, regulatory implementation, and early operational outcomes of FREDD (French Rare Eye Disease Database), a national interoperable health data warehouse dedicated to rare eye diseases, and to analyze its key success factors, technical bottlenecks, and long-term financial sustainability models.

Developed under the oversight of the French National Institute of Health and Medical Research (Institut national de la santé et de la recherche médicale; INSERM), the warehouse implements a centralized 3-layer architecture encompassing data collection, processing, and research reuse environments. The dataset extends the national minimum rare disease dataset with detailed ophthalmology variables structured through a dynamic electronic case report form, as well as a dedicated collection of ophthalmic images. Interoperability is achieved using international domain ontologies and a custom parsing tool (FREDDEX) designed to automatically prefill clinical data from the existing French national rare disease registry. Centralized monitoring, data curation, and cross-center quality tracking are driven by a dedicated in-house dashboard (FREDDIn [FREDD Insights]), while unstructured retinal images are processed through a standardized pseudonymization and human-verified validation pipeline.

Official regulatory authorization was obtained in April 2024, and active data collection began in March 2025 across 5 pilot expert centers, focusing its initial phase on inherited retinal dystrophies, primarily retinitis pigmentosa. Over a 1-year period, the warehouse successfully integrated clinical data from 1649 patients-representing 20.3% of all retinitis pigmentosa cases registered nationally-and accumulated more than 10,000 ophthalmic images. The centralized dashboard maintained an overall data inconsistency rate of approximately 7%, chiefly reflecting logical dependencies. Among the included patients, 36.7% (605/1649) patients had associated imaging data, with fundus photography being the most widely available modality (768/1649, 46.6%).

The implementation of this database demonstrates that a highly specialized, multimodal health data warehouse can be successfully deployed in a highly regulated environment when regulatory anticipation, governance formalization, and technical flexibility are addressed in parallel. While initial development was supported by institutional grants, long-term sustainability will require a structured cost-recovery model. Future milestones will focus on expanding center coverage nationwide, refining image annotation frameworks for AI readiness, and deploying automated export pathways toward European registries.