Blockchain no ecossistema tecnológico da Plataforma revELA: no contexto da esclerose lateral amiotrófica (ELA)

• Ano de defesa: 2025
• Autor(a) principal: Fonseca, Aleika Lwiza Alves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio Grande do Norte; Brasil; UFRN; PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO
• Palavras-chave em Português: Registro eletrônico em saúde; Esclerose Lateral Amiotrófica; Registro Nacional da ELA; Blockchain; Hyperledger Fabric; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: https://repositorio.ufrn.br/handle/123456789/63360

The National ALS Registry is a digital health solution that aims to collect epidemiological data from various patients with Amyotrophic Lateral Sclerosis (ALS) in Brazil. When using technological solutions such as this one, for electronic health data recording, concerns arise regarding security, data integrity, and the importance of an interoperable platform for sharing with other systems. To address these concerns, blockchain technology has been attracting a lot of attention in several areas that already see the possibilities for progress with its incorporation. Considering the needs for security, auditability, and interoperability, and to make the National ALS Registry increasingly secure and reliable, this paper presents the configuration of a blockchain network with the Hyperledger Fabric framework and the implementation of an API, developed with Node.js, used to integrate the blockchain with the National ALS Registry. To evaluate the performance of the proposed solution, the Hyperledger Caliper tool was used, which is a reference for benchmarking blockchain solutions. The results show the viability of using this technology and the relevance of its use is highlighted throughout the text. Although the performance analysis was not satisfactory, with average latency above 19s and throughput values below 100 transactions per second, the data obtained allows us to identify points for improvement in the implementation and optimization of the network.