Portuguese hospitals' main challenges in implementing Big Data projects for early detection of adverse events

  • Ana Oliveira Bianchi de Aguiar (Student)

Student thesis: Master's Thesis


Big Data has been creating much excitement and promises to solve many of the current health systems’ challenges. A specific application allows predicting adverse events, such as nosocomial infections, 24-48 hours earlier than traditional methods, by analysing in real-time physiological data allied with clinical information, and by extracting knowledge from this stored data. However, the implementation of this kind of projects is not without challenges. Hence, the objective of this thesis is to understand the main barriers in implementing Big Data projects for early detection of adverse events in the specific case of Portuguese hospitals. The collection of primary data, through surveys and interviews, allowed identifying three main barriers. Firstly, there is a generalized low knowledge regarding Big Data, which can hinder the consideration of these projects in the yearly budget and create difficulties in understanding how it can be applied and benefit the hospital. Secondly, a shortage of “Data Scientists” in Portuguese hospitals was reported, being this skilled labour crucial to creatively look at the data and understand how it generates value. Finally, an initial high investment with still undiscovered business value is a true barrier, reflecting the hospitals’ budget constraints. However, two initially identified obstacles were not validated by this analysis. Firstly, being an organizational change necessary to adapt to this new paradigm, resistance from managers and caregivers is not expected. Furthermore, data security and privacy were not considered true impediments but rather a requirement of the technology.
Date of Award2015
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorSusana Frazão Ferreira Fernandes Pinheiro (Supervisor)


  • Mestrado em Gestão: Programa Internacional

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