Cost Estimation of Managing Retinitis Pigmentosa in France in a Multi-Payer Environment From a Societal Perspective

OBJECTIVES: To assess the economic burden of retinitis pigmentosa (RP) in light of the various payers involved in its financing.

METHODS: All medical, non-medical, direct and indirect costs related to RP were gathered based on a previously published systematic literature review and a burden of XLRP study conducted in Europe and Israel. A four-state lifetime horizon economic model was developed according to the natural disease progression (normal vision, moderate visual impairment, severe visual impairment, blindness) starting with patients at 18 years old. All costs were related to the payer financing it: national health insurance, private insurance, patient, society. Base case scenario was conducted within a societal perspective.

RESULTS: Lifelong medical management of patients diagnosed for RP represents more than 1.8 million euros with disease progression towards more advanced stages associated with a significant increase of indirect costs. 46% of total costs consist of direct non-medical costs: disabled adult allowance (AAH), formal assistance, technical and non-technical assistance and home adaptation. 50% are indirect non-medical costs: productivity losses for patients and carers. Only 3% of total expenditure is funded by the national health insurance system.

CONCLUSIONS: RP is associated with a substantial economic burden, half of which is attributable to social benefits to compensate for disability-induced loss of income and funded by payers other than the national health insurance. Although the French National Authority for Health (HAS) only considers direct medical costs supported by the health insurance in economic evaluations, this expenditure only represents a marginal share of total spending. Following HAS guidelines, an economic evaluation of RP would overlook more than half of the total lifetime costs associated with the disease. Therefore, for RP, adopting a societal perspective is crucial for accurately estimating the economic burden and show the full impact a new innovation would bring.