From Big Data's 5Vs to clinical practice's 5Ws: enhancing data-driven decision making in healthcare.

Journal: Journal of clinical monitoring and computing
Published Date:

Abstract

The use of AI-based algorithms is rapidly growing in healthcare, but there is still an ongoing debate about how to manage and ensure accountability for their clinical use. While most of the studies focus on demonstrating a good algorithm performance it is important to acknowledge that several additional steps are needed for reaching an effective implementation of AI-based models in daily clinical practice, with implementation being one of the main key factors. We propose a model characterized by five questions that can guide in this process. Additionally, we believe that a hybrid intelligence, human and artificial respectively, is the new clinical paradigm that offer the most benefits for developing clinical decision support systems for bedside use.

Authors

  • Valentina Bellini
    Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126, Parma, Italy.
  • Marco Cascella
    Department of Medicine, Surgery and Dentistry, University of Salerno, 84081, Baronissi, Italy.
  • Jonathan Montomoli
    Department of Anesthesia and Intensive Care, Infermi Hospital, Romagna Local Health Authority, Rimini, Italy.
  • Elena Bignami
    Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy. Electronic address: bignami.elena@hsr.it.