Assessing the Accuracy of Sales Forecasts Submitted by Pharmaceutical Companies Applying for Reimbursement in Austria

Objectives: Reimbursement decisions on new medicines require an assessment of their value. In Austria, when applying for reimbursement of new medicines, pharmaceutical companies are also obliged to submit forecasts of future sales. We systematically examined the accuracy of these pharmaceutical sales forecasts and hence the usefulness of these forecasts for reimbursement evaluations. Methods: We retrospectively analyzed reimbursement applications of 102 new drugs submitted between 2005 and 2014, which were accepted for reimbursement outside of hospitals, and for which actual reimbursed sales were available for at least 3 years. The main outcome variable was the accuracy ratio, defined as the ratio of forecasted sales submitted by pharmaceutical companies when applying for reimbursement to actual sales from reimbursement data. Results: The median accuracy ratio [95% confidence interval] was 1.33 [1.03; 1.74, range 0.15–37.5], corresponding to a median overestimation of actual sales by 33%. Forecasts of actual sales for 55.9% of all examined products either overestimated actual sales by more than 100% or underestimated them by more than 50%. The accuracy of sales forecasts did not show systematic change over the analyzed decade nor was it discernibly influenced by reimbursement status (restricted or unrestricted), the degree of therapeutic benefit, or the therapeutic area of the pharmaceutical product. Sales forecasts of drugs with a higher degree of innovation and those within a dynamic market tended to be slightly more accurate. Conclusions: The majority of sales forecasts provided by applicants for reimbursement evaluations in Austria were highly inaccurate and were on average too optimistic. This is in line with published results for other jurisdictions and highlights the need for caution when using such forecasts for reimbursement procedures.

Abstract licence: CC BY

36 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.