JMIR Publications

ABSTRACT

Background:

Although individually uncommon, rare diseases (RD) affect an estimated 300 million people worldwide. Establishing a public health approach to RD requires counting diseases and affected patients. However, RD are under-represented in medical terminologies, with only a small fraction of RD possessing specific and unambiguous codes, and these codes not being explicitly designated as rare.

Objective:

This paper presents the Orphanet Nomenclature of RD, the only RD-specific codification and classification framework meeting the high-quality standards of a medical terminology. We describe its development, updating, and mapping methodology, and provide an updated and precise count of RD, essential to inform policy, resource allocation, and healthcare strategies.

Methods:

To tackle the challenge of RD codification and interoperability, Orphanet has developed a nomenclature of RD that provides unique and time-stable disease identifiers (ORPHAcodes) and meets the gold standards for implementation in health information systems and systematic research collections. The Orphanet Nomenclature of RD is multilingual and versioned; its development and updates rely on standardized procedures, manual curation and expert validation, reflecting advancements in RD knowledge and clinical practice. Its production process also includes systematic medical validated mappings to major biomedical terminologies to ensure semantic interoperability.

Results:

As of July 2025, the Orphanet Nomenclature includes a total of 6527 RD, multiclassified into 29 classifications, each corresponding to a medical domain, accurately representing the complex multisystemic nature of RD. Extensive qualified mappings ensure semantic interoperability: overall, 97.4% of RD are mapped to at least one ICD-10 code (with only 6.3% exhibiting an exact equivalence), 71.7% are mapped to at least one ICD-11 code (15.3% with an exact equivalence) and 93.8% are mapped to SNOMED CT (all with an exact equivalence). Genetic diseases represent 72.2% of all RD, and 63.4% are mapped to at least one phenotypic OMIM number.

Conclusions:

By addressing the underrepresentation of RD in medical terminologies, ORPHAcodes enable accurate patient identification, advance research and healthcare interoperability, and help in shaping public health policies. The recognition of the Orphanet Nomenclature as the reference terminology for RD clinical coding in Europe underscores its pivotal role in the global RD ecosystem.