Making Rare Diseases Count 2026

Key metrics for a minimum and expanded dataset TABLE 2 In higher-resource settings, the minimum dataset can expand into a more comprehensive dataset capturing details on prevalence patterns, socioeconomic impact, quality and coordination of care, levels of public and private investment and workforce capacity. Governments can strengthen these efforts by incorporating third-party data sources, including from payers or employers.A globally aligned minimum dataset will not solve every problem, but it can establish a shared baseline, spotlight where action is most needed and help ensure that rare disease policy and investment are grounded in evidence.Minimum dataset (all countries) DATA TYPE Incidence and burden of disease Access to treatments and servicesScale and impact of rare disease investments Estimated overall prevalence (diagnosed and undiagnosed) Type of rare disease coding system in place, e.g. ORPHAcodes and/or ICD-11 extension codes.Name and number of approved rare disease therapies Number of conditions covered on newborn screening systems Presence of rare disease COE [yes/no] Presence of national rare disease advocacy organization [yes/no] Separate reimbursement/HTA pathway for rare diseases [yes/no]Number of rare disease clinical trials (all phases) Rare diseases as named healthcare priority at the national level [yes/no] Rare diseases as named research priority at the national level [yes/no] Expanded dataset (higher-resource and more data-driven settings) DATA TYPE Incidence and burden of disease Access to treatments and servicesScale and impact of rare disease investments Detailed prevalence rates aligned to international coding standards Estimated total cost to healthcare systems, including screening/diagnostics, treatment costs, care coordination and long-term/palliative care Socioeconomic burden of disease, rigorously quantified for key stakeholdersQuality ratings covering: Availability of essential treatments, diagnostics and services Healthcare professional training and awareness Reimbursement Social services Patient advocacyTotal public-sector funding Total philanthropic funding Total private-sector investment, including number and estimated total market value of companies with rare disease focus Total number of jobs tied to rare disease research, care and/or innovation National rare disease policy assessment (quality rating) COE = centre of excellence HTA = health technology assessment Source: World Economic Forum, Rare Disease Community analysisCountries differ widely in how they manage rare disease data. This lack of alignment creates blind spots around one of the largest cost areas in healthcare systems. An internationally harmonized minimum dataset would provide a common language for understanding rare disease impact and opportunity. A key enabler is the adoption of international classification systems, notably ORPHAcodes and the ICD-11 rare disease extension codes. These standards make it possible to identify individual conditions in health records with greater precision. Many countries – starting with France and Germany, extending across Europe and now reaching Australia and Canada – have already embedded ORPHAcodes into public health systems.21 The goal is not to build a perfect system at once but to establish a practical starting point: a small set of metrics that it is feasible to collect across health systems (see Table 2).2.1 Define and track a ‘minimum dataset’ across countries Making Rare Diseases Count: How Better Data Can Unlock a Multitrillion-Dollar Opportunity 14