Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study.

Journal: Frontiers in neurology
Published Date: Jan 18, 2024

Abstract

INTRODUCTION: In a drip-and-ship model for endovascular thrombectomy (EVT), early identification of large vessel occlusion (LVO) and timely referral to a comprehensive center (CSC) are crucial when patients are admitted to an acute stroke center (ASC). Several artificial intelligence (AI) decision-aid tools are increasingly being used to facilitate the rapid identification of LVO. This retrospective cohort study aimed to evaluate the impact of deploying e-Stroke AI decision support software in the hyperacute stroke pathway on process metrics and patient outcomes at an ASC in the United Kingdom.

Authors

  • Kiruba Nagaratnam
    Stroke Medicine, Royal Berkshire NHS Foundation Trust, Reading, United Kingdom.
  • Ain Neuhaus
    Stroke Medicine, Oxford University Hospitals NHS Trust, Oxford, United Kingdom.
  • James H Briggs
    Stroke Medicine, Royal Berkshire NHS Foundation Trust, Reading, United Kingdom.
  • Gary A Ford
    Stroke Medicine, Oxford University Hospitals NHS Trust, Oxford, United Kingdom.
  • Zoe V J Woodhead
    Brainomix Limited, Oxford, United Kingdom.
  • Dibyaa Maharjan
    Stroke Medicine, Royal Berkshire NHS Foundation Trust, Reading, United Kingdom.
  • George Harston
    Stroke Medicine, Oxford University Hospitals NHS Trust, Oxford, United Kingdom.

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