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Big Data Analytics in a Public General Hospital

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Book cover Machine Learning, Optimization, and Big Data (MOD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10122))

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Abstract

Obtaining information and knowledge from big data has become a common practice today, especially in health care. However, a number of challenges make the use of analytics in health care data difficult. The aim of this paper is to present the big data analytics framework defined and implemented at an important Brazilian public hospital, which decided to use this technology to provide insights that will help improve clinical practices. The framework was validated by a use case in which the goal is to discover the behavior patterns of nosocomial infections in the institution. The architecture was defined, evaluated, and implemented. The overall result was very positive, with a relatively simple process for use that was able to produce interesting analytical results.

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Acknowledgments

The authors would like to thank CAPGEMINI Brazil for their financial support; the EMC Brazil for providing the computer servers and technical support; and Hospital de Clínicas de Porto Alegre for their assistance with the data supply and technical information. Finally, we would like to thank for the team involved in this project: Ulisses Souza, Raul Hara, Margarita Bastos, Kefreen Batista, Jean Michel, Luis Macedo, Lais Cervoni, Juliano Pessini and the staff of CAPGEMINI.

Author information

Authors and Affiliations

  1. Universidade de Mogi das Cruzes, Mogi das Cruzes, São Paulo, Brazil

    Ricardo S. Santos

  2. Aeronautics Institute of Technology, São José dos Campos, São Paulo, Brazil

    José M. Parente de Oliveira

  3. Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil

    Tiago A. Vaz & Rodrigo P. Santos

Authors
  1. Ricardo S. Santos
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  2. Tiago A. Vaz
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  3. Rodrigo P. Santos
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  4. José M. Parente de Oliveira
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Corresponding author

Correspondence to Ricardo S. Santos .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. Semantic Technology Laboratory, National Research Council (CNR), Catania, Italy

    Piero Conca

  3. Dipartimento di Sociologia e Metodi della Ricerca Sociale, Università di Catania, Catania, Italy

    Giovanni Giuffrida

  4. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Giuseppe Nicosia

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© 2016 Springer International Publishing AG

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Santos, R.S., Vaz, T.A., Santos, R.P., de Oliveira, J.M.P. (2016). Big Data Analytics in a Public General Hospital. In: Pardalos, P., Conca, P., Giuffrida, G., Nicosia, G. (eds) Machine Learning, Optimization, and Big Data. MOD 2016. Lecture Notes in Computer Science(), vol 10122. Springer, Cham. https://doi.org/10.1007/978-3-319-51469-7_38

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  • DOI: https://doi.org/10.1007/978-3-319-51469-7_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51468-0

  • Online ISBN: 978-3-319-51469-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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