OBJECTIVES: In Belgium reimbursement submissions must contain scientific and financial elements. The financial part relies on budget impact (BI) estimates from the payer's perspective for the next 3 years. Real cost monitoring is difficult because official cost data become available with a substantial delay while commercial IMS data measure total sales. Our aim was to develop a method to monitor pharmaceutical expenses in Belgium and compare the outcome with the expected costs of the BI- estimation: a method combining both data sources allowed to monitor in a timely manner only the reimbursed pharmaceutical cost. METHODS: The method was applied on the class of cholesterol lowering drugs representing 9% of ambulatory expenses. BI-estimations were provided in the applicant's dossier. Monthly IMS-sales data (= S, IMS-Health) and official cost data (= C, Riziv ) were extracted from the respective databases. RESULTS: All correlations between historical monthly product data from both sources yielded an R² > 0.75 which was considered as a cut-off to apply the method (minimal R² = 0.8164). Expected reimbursement pharmaceutical cost was calculated as: Expected C = S / k where k is the average monthly ratio of S to C during a common 12 month period. The expected C calculation extends real C data by 6 months. Quality control of the method was assessed by comparing the expected C and real C yielding a mean monthly error lower than 5% with a 3 month cumulated error of less than 2%. BI-estimates were inferior to expected and real C. CONCLUSIONS: A method was developed to predict 3rd payer's pharmaceutical cost combining recent commercial sales data and official but less recent cost data ensuring reliable application of this method for control of estimates of BI.