Plataforma inteligente para a comunicação com hipertensos: revisão sistemática - Linhares, Jessika Lorena Parente (2022)
Brazil is experiencing an accelerated epidemiological transition, this rapid process of population aging, brings as a consequence the significant growth of chronic diseases, especially arterial hypertension. In this context of the high number of affected patients, Brazil is facing a pandemic caused by the new Coronavirus, thus observing the urgent need for monitoring this risk group. Some preventive measures were defined by the Ministry of Health, among them, the implementation of non-face-to-face alternatives for attendance and monitoring of affected users, through the use of virtual or remote communication technologies. The present study aims to answer research questions relevant to the use of chatbots in the care of hypertensive patients, outlining an overview on the subject. This is a Systematic Literature Review using the methodology proposed by Kitchenham et al. (2007). The review protocol was systematized based on the following primary research question: What is the state of the art in the development of Chatbots for self-care and treated approach to people with Systemic Arterial Hypertension. To carry out the research, the following databases were used: Web of Science, Medline (Pubmed), Scopus and Compendex, through automated search with the Parsifal tool. The searches were based on the title, abstract and keywords, using the search string defined in English. After surveying the studies in the bases, a total of 6110 articles were found, 16 articles were pre-selected. After applying the inclusion and exclusion criteria, it was noted that no study fit the protocol pattern. Chatbots have technologies capable of providing the user with highly personalized health interventions, however, a gap is perceived in the field of digital health, when monitoring the existence of this tool for hypertensive patients. More studies are needed to develop interventions that use artificial intelligence virtual assistants for this audience. For future Chatbots, we suggest that we include the recording of variables that influence the control of SAH and features such as risk assessment of patients, screening of users and from this information provided recommendations and alerts.