Budget Impact Analysis of Risperidone Use and Adverse Event Monitoring in Autism Spectrum Disorder in Brazil: Assessment of Theoretical Versus Real Data

Abstract

Background and aims: Risperidone is used in autism spectrum disorder (ASD) to manage aggressive behavior. Budget impact analysis (BIA) assists managers in promoting more sustainable health systems; however, it is unclear whether BIAs underestimate or overestimate the estimates derived from real-world data. This study aimed to compare the estimated BIA values of risperidone use and the monitoring of adverse events in ASD using theoretical and real data. Methods: Analyses were conducted based on the clinical protocol and the Brazilian therapeutic guidelines for ASD. The perspective adopted was that of the Unified Health System (SUS), considering a time horizon of 5 years. Three possible scenarios were considered based on the maximum daily dose of risperidone. Expenses related to the acquisition of risperidone and the monitoring of adverse events were taken into account using health databases in Brazil. For the calculation based on theoretical data, the prevalence of ASD was estimated using information from the scientific literature and the Brazilian demographic census. The model calculated from real data was obtained by analyzing the linear trend of the number of users assisted in the SUS from 2017 to 2021. Results: The population estimated by the theoretical model compared with the model calculated from the real data was higher. Likewise, the 5-year budgetary impact of the theoretical model versus the model calculated from the real data was higher, with statistical significance in all scenarios (p < 0.001). In the real data model, the most economically advantageous scenarios were Scenario 1 for children (International dollars [I$] 7,630,040.73) and Scenario 3 for adults (I$60,329,288.17). Estimated expenditures for monitoring adverse events ranged from 17 to 74% in children and from 50% to 63% in adults. Conclusions: The data revealed significant differences in population and cost estimation between theoretical data and real-world data. The expenses associated with monitoring adverse events represented a substantial expenditure estimate for the SUS.