SOFTWARE DE ASSISTÊNCIA AO PRÉ-NATAL: FERRAMENTA DE APOIO À GESTÃO DA INFORMÁTICA EM SAÚDE - Pires, Márian Oleques (2022)
The study is part of the Sustainable Development Goals,specifically, in the “Health and Well-being” axis, focusing on the goals: 3.1) By 2030, reduce the global maternal mortality rate to less than 70 deaths per 100,000 births alive; and 3.2) By 2030, end preventable deaths of newborns and children under 5 years old. It is also included in the Agenda of Research Priorities of the Ministry of Health, Axis 14 - Maternal and Child Health, focusing on the analysis of the sociodemographic profile and factors associated with maternal mortality. To reach the proposed goals, a collective and collaborative effort is required, in which the University occupies an important space. With a view to improving maternal and child health in the central region of the state of Rio Grande do Sul, especially with regard to the prenatal component, we have, for Objective: To develop a web software for prenatal care as a tool to support the management of health informatics. Methodology: A technological development study that initially started with an expanded analysis of the tools to support the management of health informatics with a focus on available prenatal care and, later, the detection of relevant information on variables related to prenatal care was carried out. -natal, from the science of data extracted from SINASC (period 2016 to 2020) with a view to the production of relevant knowledge, capable of subsidizing strategic actions for the qualification of prenatal care in the central region of Rio Grande do Sul. And, in parallel, the web software in Python language was developed based on the agile Scrum method, from July/2021 to July/2022. Results: It is demonstrated that data science has a growing potential to provide relevant and concise information to support management and health care, in this study, with a focus on prenatal care. in order to facilitate managers' understanding of maternal and child decision-making processes. Extracting knowledge computationally through algorithms is an agile and promising route, in addition to being less costly and more effective to obtain new knowledge and discoveries of relevant information. Conclusion: Data science is a promising and prospective tool in the health area, especially for its potential to analyze big data and, thus, allow scientifically based strategic planning, with a better understanding of the target audience and, consequently, with greater adherence and adaptability to the demands of users and services. Product and its applicability: Development of a web software, with different functionalities, such as: registration and login in the system, import of databases, registration of databases in the system, selection of algorithms for data analysis, registration of analysis algorithms of data and generation of graphs/tables capable of supporting strategic planning in maternal and child health.