Background: The coronavirus disease 2019 (COVID-19) pandemic led to the suspension or postponement of care for nonurgent conditions worldwide. Regula Mais Brasil is an initiative of the Unified Health System (SUS) in Brazil to optimize the management of referrals to specialized care by using telehealth. Objectives: To report the expansion of telehealth activities of Regula Mais Brasil in response to COVID-19 and to assess qualification of referrals in primary health care (PHC) units as well as the added value of teleconsultation in qualifying referral cases. Methods: Descriptive study of the teleconsultations carried out as an additional strategy to the remotely operated referral management system, responsible for navigating cases from PHC units to specialized care in Recife, Brazil, between May 6, 2020 and September 30, 2020. Teleconsultation was implemented as a tool for reducing delays in the access to health care due to COVID-19 and ultimately allowed for reclassification of the referral ade-quacy and priority. Changes in referral priority ratings and referral decisions after teleconsultation were analyzed. Results: A total of 622 referral cases were analyzed. Approved referrals represented 51.9% of cases. The main reason for approved referrals was the need for diagnostic resources. There was a reduction in priority ratings in 449 cases (72.2%) after teleconsultation. There was a statistically significant association between the change of priority ratings and the decision on referral (Pearson's v 2 , p-value <0.0001). Results show that telemedicine had an impact on the prioritization and qualification of cases referred to specialized services. Conclusions: A need was detected to rapidly adapt tools available for telemedicine in Brazil. Our results demonstrate that teleconsultation as an additional strategy to the remotely operated referral management system has contributed toward improving equitable access to specialized services.
A transformação digital é uma realidade na área da saúde em todo o mundo, e a inteli - gência artificial (IA) permite o desenvolvimento de métodos diagnósticos de maior precisão dentro da cardiologia, sinalizando alterações subclínicas e permitindo diagnósticos mais precoces. Por meio da análise de grandes bancos de dados de eletrocardiograma (ECG) por ferramentas como aprendizado de máquina (ML, machine learning ), redes neurais são desenhadas, permitindo o desenvolvimento de algoritmos capazes de fornecer inúmeras informações sobre o quadro dos pacientes e predizer a possibilidade de desenvolvimento de doenças graves, o que torna o ECG, um método tão antigo, acessível e de baixo custo, um biomarcador poderoso e não invasivo. Os algoritmos desenvolvidos a partir do traçado de ECG para detecção de risco aumentado de infarto agudo do miocárdio e morte súbita, disfunção sistólica do ventrículo esquerdo, valvopatias, identificação de distúrbios eletrolíticos, sinalização dos pacientes com risco de desenvolvimento de fibrilação atrial e eventos embólicos decorrentes dessa arritmia, são algumas das utilizações promissoras dessa técnica e permitem a abordagem precoce de afecções e a redução da morbidade e da mortalidade em geral. A IA auxilia o profissional de saúde acelerando os processos, reduzindo erros e o apoiando no diagnóstico e tomada de decisões. Mas a figura e experiência do profissional ainda é insubstituível para validar esses resultados.
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