OBJECTIVES: The Conditional Reimbursement System (CRS) enables confidential risk-sharing agreements with the Pharmaceuticals Pricing Board (PPB) in Finland (population 5.5 million). Since 2017, 50 medications have been reimbursed through the CRS. We have previously demonstrated that the CRS has drastically improved reimbursement access in hematology and oncology. Here, we assessed whether the faster access with CRS has led to improved patient life expectancy in cancer.

METHODS: Reimbursement decisions (n=209) from the PPB and data on purchases and paid reimbursements from the Social Insurance Institution (SII) of Finland were used to estimate the reimbursement times and population sizes, respectively. The modelled evaluation applied the PICOSTEPS assessment framework, historical reimbursement decision control from 2012 to 2016 (PPB), intervention decision time with CRS from 2018 to 11/2021 (PPB), and average life-years accrued from the assessments of therapies and subpopulations (NICE). Outcomes included undiscounted life-years gained (LYG), assessed with the distribution transition method, which enabled the inclusion of population impact at the year 2020 level (SII).

RESULTS: We estimate that the CRS has resulted in 9,000-17,000 LYGs for Finnish cancer patients, depending on the length of the control period. Among subgroups, breast cancer, lung cancer, chronic lymphatic leukemia, thyroid cancer, and prostate cancer demonstrated the highest gains, reflecting the number of new medicines available as well as the size of these populations. The results are likely to be underestimates, as the method does not fully consider the higher probability of reimbursement with CRS, nor peak sales taking place after year 2020.

CONCLUSIONS: CRS was related to considerable LYGs due to improved access to new medicines in hematology and oncology although conservative estimates were used. The shortcomings of analysis were use of foreign estimates for life-years, in addition to probable underestimates of average life-year estimates and affected patient population sizes for some conditions and medicines.