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Big Data in Healthcare Institutions: An architecture proposal

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Resumo:Healthcare institutions are complex organizations dedicated to providing care to the population. Continuous improvement has made the care provided a factor of excellence in the population, improving people’s daily lives and increasing average life expectancy. Even so, the resulting aging has caused patterns to increase day by day and the paradigm of medicine to shift from reaction to prevention. Often, the principle of evidence-based medicine is compromised by lack of evidence on pathogenic mechanisms, risk prediction, lack of resources, and effective therapeutic strategies. This is even more evident in pandemic situations. The current data management tools (centered in a single machine) do not have an ideal behavior for the processing of large amounts of information. This fact combined with the lack of sensitivity for the health area makes it imminent the need to create and implement an architecture that performs this management and processing effectively. In this sense, this paper aims to study the problem of knowledge construction from Big Data in health institutions. The main goal is to present an architecture that deals with the adversities of the big data universe when applied to health.
Autores principais:Lopes, José
Outros Autores:Sousa, Regina; Abelha, António; Machado, José Manuel
Assunto:Big Data Healthcare Information Systems Real-Time Information System System Architecture
Ano:2023
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Healthcare institutions are complex organizations dedicated to providing care to the population. Continuous improvement has made the care provided a factor of excellence in the population, improving people’s daily lives and increasing average life expectancy. Even so, the resulting aging has caused patterns to increase day by day and the paradigm of medicine to shift from reaction to prevention. Often, the principle of evidence-based medicine is compromised by lack of evidence on pathogenic mechanisms, risk prediction, lack of resources, and effective therapeutic strategies. This is even more evident in pandemic situations. The current data management tools (centered in a single machine) do not have an ideal behavior for the processing of large amounts of information. This fact combined with the lack of sensitivity for the health area makes it imminent the need to create and implement an architecture that performs this management and processing effectively. In this sense, this paper aims to study the problem of knowledge construction from Big Data in health institutions. The main goal is to present an architecture that deals with the adversities of the big data universe when applied to health.