A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare.
Ahmed, Molla Imaduddin Spooner, Brendan Isherwood, John Lane, Mark Orrock, Emma Dennison, Ashley
Ahmed, Molla Imaduddin
Spooner, Brendan
Isherwood, John
Lane, Mark
Orrock, Emma
Dennison, Ashley
Abstract
Artificial intelligence (AI) is expected to improve healthcare outcomes by facilitating early diagnosis, reducing the medical administrative burden, aiding drug development, personalising medical and oncological management, monitoring healthcare parameters on an individual basis, and allowing clinicians to spend more time with their patients. In the post-pandemic world where there is a drive for efficient delivery of healthcare and manage long waiting times for patients to access care, AI has an important role in supporting clinicians and healthcare systems to streamline the care pathways and provide timely and high-quality care for the patients. Despite AI technologies being used in healthcare for some decades, and all the theoretical potential of AI, the uptake in healthcare has been uneven and slower than anticipated and there remain a number of barriers, both overt and covert, which have limited its incorporation. This literature review highlighted barriers in six key areas: ethical, technological, liability and regulatory, workforce, social, and patient safety barriers. Defining and understanding the barriers preventing the acceptance and implementation of AI in the setting of healthcare will enable clinical staff and healthcare leaders to overcome the identified hurdles and incorporate AI technologies for the benefit of patients and clinical staff.
MIDER Authors
Date
2023-10-04
Type
Article
Subject
artificial intelligence
Collections
Citation
Cureus. 2023 Oct 4;15(10):e46454.
Journal / Source Title
Cureus
DOI
10.7759/cureus.46454
PMID
37927664
Publisher
Springer Nature
Publisher’s URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC10623210/