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Healthcare Delivery: Leveraging Artificial Intelligence to Strengthen Healthcare Quality

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Advances in Human Factors and Ergonomics in Healthcare and Medical Devices (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 263))

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Abstract

The capabilities of artificial intelligence (AI) in medicine are expanding at an unprecedented pace. AI has the potential to serve as an invaluable asset in harnessing large amounts of data to generate new diagnostic models, inform clinical decision making, and to expand the capabilities of modern medicine. AI has proven beneficial in various fields of diagnostic medicine including radiology, pathology, and laboratory medicine. AI programs have been shown to increase workflow without compromising accurate identification of abnormalities. Aspects of human error in medicine can be mitigated through the use of machine learning programs to serve as quality assurance and failsafe strategy. The advent of AI in healthcare carries many ethical, legal, and accountability challenges. These challenges include issues of transparency, data security, informed consent, and liability. Lack of familiarity with AI systems and fear of unforeseen consequences warrants caution in the implementation of these new tools. However, undue delays in the implementation of AI may unnecessarily hinder the progress of medicine and limit the level of care that can be provided to patients. Healthcare providers should ensure they are well-positioned to adapt to this new technological era of medicine by remaining up to date on the implications of technological advances. Medical education will require continuous revaluation and adaptation to ensure learners gain the appropriate digital literacy to function effectively in AI-assisted medical practice. The implementation of these technologies into healthcare systems represents the greatest healthcare transition of our time. Optimizing this transition in a growing number of medical disciplines will require tactful implementation and diligent risk management.

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Author information

Authors and Affiliations

  1. Northern Medical Program, Faculty of Medicine, University of British Columbia, Prince George, BC, V2N 4Z9, Canada

    Patrick Seitzinger

  2. Royal University Hospital, Saskatchewan Health Authority, 103 Hospital Drive, Saskatoon, SK, S7N 0W8, Canada

    Zoher Rafid-Hamed & Jawahar (Jay) Kalra

  3. Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK, S7N 0W8, Canada

    Jawahar (Jay) Kalra

Authors
  1. Patrick Seitzinger
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  2. Zoher Rafid-Hamed
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  3. Jawahar (Jay) Kalra
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Corresponding author

Correspondence to Jawahar (Jay) Kalra .

Editor information

Editors and Affiliations

  1. Dept.of Pathology, College of Medicine, Univ.of Saskatchewan Royal Univ.Hospital, Saskatoon, SK, Canada

    Jay Kalra

  2. Center for Applied Sys. Engineering, Veterans Affairs, Indianapolis, IN, USA

    Nancy J. Lightner

  3. Campus du Moulin de la Housse, Université de Reims Champagne-Ardenne, Reims Cedex 2, France

    Redha Taiar

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Seitzinger, P., Rafid-Hamed, Z., Kalra, J.(. (2021). Healthcare Delivery: Leveraging Artificial Intelligence to Strengthen Healthcare Quality. In: Kalra, J., Lightner, N.J., Taiar, R. (eds) Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. AHFE 2021. Lecture Notes in Networks and Systems, vol 263. Springer, Cham. https://doi.org/10.1007/978-3-030-80744-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-80744-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80743-6

  • Online ISBN: 978-3-030-80744-3

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