Presentation (CTI)

OBJECTIVES: There is limited real-world evidence (RWE) on healthcare resource utilisation (HCRU) in rare diseases, especially when stratified by disease severity. This creates challenges for regulatory submissions and early access to treatment. We were commissioned by a global pharmaceutical company to estimate the monthly cost of secondary care HCRU for a rare, progressive disease, stratified by WHO Functional Class (FC), risk status, and therapy regimen.
METHODS: We conducted a retrospective, non-interventional cohort study using pseudonymised patient-level data from a UK National Cohort Registry, linked to NHS Hospital Episode Statistics (HES). After obtaining Research Ethics Committee and Health Research Authority approvals, we developed a robust linkage methodology to join clinical registry data with inpatient, outpatient, and emergency care records. We analysed three years pre- and five years post-diagnosis, calculating average monthly resource use and costs per patient using the NHS National Tariff Payment System. Metrics were stratified by disease severity and therapy regimen. A Data Access Request Service (DARS) application was also submitted to expand the cohort for future analysis.
RESULTS: We estimated average monthly HCRU costs across different levels of disease severity and treatment intensity. Distinct patterns of healthcare utilisation were observed before and after diagnosis. Interim findings supported the client’s regulatory submission to NICE for a new therapy. The client reported that we delivered the analysis 60% faster than their typical timelines (10 months vs. 24 months).
CONCLUSIONS: This study demonstrates how linked national datasets can be used to generate timely, high-quality RWE in rare diseases. Our approach enabled stratified cost estimation to inform regulatory decision-making and offers a scalable framework to address evidence gaps in complex conditions.