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Real-world Data to Generate Evidence About Healthcare Interventions: The Application of an Ethics Framework for Big Data in Health and Research.

Wendy Lipworth
Published in: Asian bioethics review (2019)
It is increasingly recognised that evidence generated using "real-world data" (RWD) is crucial for assessing the safety and effectiveness of health-related interventions. This, however, raises a number of issues, including those related to (1) the quality of RWD, and of the scientific methods used to generate evidence from it, and (2) the potential for those gathering and using RWD be driven by commercial, political, professional or personal self-interest. This article is an application of the framework presented in this issue of ABR (Xafis et al. 2019). Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end to demonstrate how those generating or using RWD can make use of values when deliberating about ethical issues.
Keyphrases
  • big data
  • healthcare
  • artificial intelligence
  • machine learning
  • physical activity
  • health information
  • public health
  • randomized controlled trial
  • systematic review
  • mental health
  • health promotion