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Applied Pervasive Patient Timeline in Intensive Care Units

Author

Listed:
  • André Braga

    (Universidade do Minho, Braga, Portugal)

  • Filipe Portela

    (Universidade do Minho, Braga, Portugal)

  • Manuel Filipe Santos

    (Universidade do Minho, Braga, Portugal)

  • António Abelha

    (Centro de Ciências e Tecnologias de Computação, Universidade do Minho, Braga, Portugal)

  • José Machado

    (Centro de Ciências e Tecnologias de Computação, Universidade do Minho, Braga, Portugal)

  • Álvaro Silva

    (Intensive Care Unit, Centro Hospitalar do Porto, Porto, Portugal)

  • Fernando Rua

    (Intensive Care Unit, Centro Hospitalar do Porto, Porto, Portugal)

Abstract

This study has the objective of introducing an innovative way of presenting and representing information concerning patients in Intensive Care Units. Therefore, the Pervasive Patient Timeline, which has the purpose of offering support to intensivists' decision-making process, by providing access to a real-time environment, was developed. The solution is patient-centred as it can be accessed from anywhere, at any time and it contains patients' clinical data since they are admitted to the ICU until their discharge. The environment holds data concerning vital signs, laboratory results, therapeutics, and data mining predictions, which can be analysed to have a better understanding of patients' present and future condition. Due to the nature of the critical care environment, the pervasive aspect is crucial because it allows intensivists make decisions when they have to be made. The Pervasive Patient Timeline is focused on improving the quality of care by helping the intensivists perform better in their daily activity.

Suggested Citation

  • André Braga & Filipe Portela & Manuel Filipe Santos & António Abelha & José Machado & Álvaro Silva & Fernando Rua, 2017. "Applied Pervasive Patient Timeline in Intensive Care Units," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 6(2), pages 17-28, April.
  • Handle: RePEc:igg:jrqeh0:v:6:y:2017:i:2:p:17-28
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