SMART: a service-oriented architecture for monitoring and assessing Brazil’s Telehealth outcomes

• Autor(a) principal: Paiva, Jailton Carlos de
• Data de Publicação: 2018
• Outros Autores: Carvalho, Túlio de Paiva Marques, Vilela, Allyson Bruno Campos Barros, Nóbrega, Giovani Ângelo Silva da, Souza, Beatriz Soares de, Valentim, Ricardo Alexsandro de Medeiros
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/29299
• topic: Telehealth; Evaluation; Standardization; SOA; Integration; Interoperability

Introduction: Brazilian Telehealth Program was instituted by the Ministry of Health in 2007. Its initial structure was composed of nine telehealth centers administered by public higher education institutions. No standards, processes, applications or quality indicators had been defined since its creation. All this, combined with the decentralization of the centers, led each one of them to develop their own system, with different programming languages and architectures. The lack of regulation and integration of the information with the Ministry of Health made it difficult to evaluate the program. In this context, this paper describes the specification, implementation, and validation of an architecture, entitled SMART, to integrate the various telehealth platforms developed by the centers. Such architecture aims to standardize information so that the Ministry of Health can monitor and evaluate the results of Telehealth actions. Methods: SMART’s architecture consists of four main components: a web tool for data manipulation; a web service to receive the center’s production data; a component responsible for converting the received data into decision support data; and a component that collects data from external sources to compose the data warehouse. Results: The architecture was validated with performance tests, which were executed under extreme workloads. The results of the experiments were summarized in order to attest SMART’s effectiveness. Conclusion: The analysis of the results obtained on real data shows that the project’s performance remained stable under the workloads and its high quality was proven due to the absence of errors during the experiments