Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User Interface for Intensive Care Unit Instability Decision Support.

Journal: Applied clinical informatics
Published Date: Oct 4, 2023

Abstract

BACKGROUND: Critical instability forecast and treatment can be optimized by artificial intelligence (AI)-enabled clinical decision support. It is important that the user-facing display of AI output facilitates clinical thinking and workflow for all disciplines involved in bedside care.

Authors

  • Stephanie Helman
    Department of Acute and Tertiary Care Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
  • Martha Ann Terry
    Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
  • Tiffany Pellathy
    Veterans Administration Center for Health Equity Research and Promotion, Pittsburgh, Pennsylvania, United States.
  • Marilyn Hravnak
    Department of Acute and Tertiary Care, University of Pittsburgh Schools of Nursing, 336 Victoria Hall; 3500 Victoria St., Pittsburgh, PA, 15261, USA. mhra@pitt.edu.
  • Elisabeth George
    Department of Nursing, University of Pittsburgh Medical Center, Presbyterian Hospital, Pittsburgh, Pennsylvania, United States.
  • Salah Al-Zaiti
    Department of Acute & Tertiary Care Nursing, University of Pittsburgh, Pittsburgh, PA, USA. ssa33@pitt.edu.
  • Gilles Clermont
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.

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