CEMARA

CEMARA collects and maintains standardized clinical and epidemiological records of patients with rare diseases (affecting fewer than 1 in 2,000 individuals and encompassing approximately 5,000–7,000 conditions in Europe) to enable continuous follow-up, population-level analysis of disease distribution and impact, and support research cohort generation.

Key Features:

• Registry scope: Aggregates over 56,593 registered cases across 171 clinical sites involving more than 850 healthcare professionals in France.
• Data capture and follow-up: Systematic collection and maintenance of comprehensive patient records to enable continuous longitudinal follow-up.
• Epidemiological analysis: Enables analysis of epidemiological patterns and disease distribution at the population level.
• Architecture: Implements an n-tier architecture for scalable data management.
• Resource-demand analysis: Analyzes relationships between healthcare needs and available service provision to align demand for rare disease care with resources.
• Ontology integration: Shares a common ontology in conjunction with Orphanet to standardize data and enhance interoperability.
• Collaborative network: Supports collaboration among clinical sites, including participation by 41 of 131 Reference Centres (RC) in France.
• Cohort generation: Has facilitated initiation of new rare disease cohorts within two years of implementation.

Scientific Applications:

• Epidemiological surveillance: Monitoring disease prevalence, distribution, and patterns across participating sites.
• Healthcare resource planning: Informing allocation of clinical resources by analyzing demand versus provision for rare disease care.
• Cohort and research study initiation: Enabling the creation of patient cohorts for natural history studies and clinical research.
• Clinical management and longitudinal follow-up: Supporting continuous patient follow-up for clinical care and outcome assessment.
• Data standardization and interoperability: Facilitating standardized data exchange through ontology alignment with Orphanet.

Methodology:

Systematic collection and maintenance of patient records, n-tier architecture for data management, epidemiological pattern analysis, analysis of healthcare needs versus service provision, and ontology alignment with Orphanet.