Published online by Cambridge University Press: 14 December 2023
In Brazil, the incorporation or disinvestment of health technologies into the Unified Health System (SUS) are advised by the National Committee for Health Technology Incorporation (Conitec). Despite the thorough evaluation carried out by Conitec, the results measured after implementation do not always reflect the economic and clinical impact expected from the incorporation. Thus, real-world evidence (RWE) is essential for monitoring health technologies. The aim of this study was to report how Brazil is using the RWE to obtain additional information about the incorporated technologies.
Actions related to the use of RWE for monitoring of technologies incorporated into the SUS were described. The period evaluated was between 2012 and 2022.
The first Conitec recommendation in which the use of real-life data in the decision-making process was evidenced occurred in 2016. Administrative data from a cohort of patients identified that beta-interferons for Multiple Sclerosis were less effective than the other drugs used in the Brazilian public system. A further eight reports have been published assessing the performance of technologies using administrative data.
Another strategy for RWE generation was through the funding of primary studies, highlighting a study with 21 rare diseases and another one to evaluate Zolgensma gene therapy, acquired through court for Spinal Muscular Atrophy. Both studies are ongoing and aim to evaluate the effectiveness, safety, adherence, and cost of medications in the evaluated diseases. Conitec is also following studies in RWE financed by pharmaceutical companies to evaluate effectiveness for incorporated technologies subject to reassessment. Additionally, managed access arrangements have been promoted for generating RWE when there is uncertainty about outcomes.
Real-world evidence from administrative data and clinical research allows monitoring after the implementation of technologies in the Unified Health System in Brazil. This makes it possible to reallocate resources in health and contribute for the system sustainability, in addition to generating data that reduce the uncertainties assumed at the time of incorporation.