Forecasting spending on orphan diseases to maintain the long-run financial sustainability of healthcare system17

The paper deals with the rare diseases' burden forecasting in the context of information gaps on these diseases. There are many countries pumping up public funding for rare diseases' treatment despite lack of accurate data on patients numbers. This study is aimed at the formulation the one-size-fits-all approach for forecasting treatment costs of rare NCD. The approach is based on cohort component method and requires minimum exogenous data set. The model utilizing the proposed approach was developed for forecasting The Circle of Good Foundation's treatment costs on cystic fibrosis and Pompe's disease in 2022-2050. The authors found that forecasted number of patients in 2022 does not deviate dramatically from actual data for 2019-2021 and predicted cost pattern does not conflict with experts up to 2050. This supports study's hypothesis that the quality of treatment costs forecast does not depend significantly on prevalence and degree of knowledge of rare disease. The results will be of interest to government authorities, charity foundations and pharmaceutical companies for upgrading decision-making on funding rare diseases' treatment costs and improvement market planning for new drugs in pharmaceutical companies.