A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare
Spooner, Brendan
Spooner, Brendan
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Molla Imaduddin Ahmed 1, Brendan Spooner 2, John Isherwood 3, Mark Lane 4, Emma Orrock 5, Ashley Dennison 3 Affiliations collapse Affiliations 1Paediatric Respiratory Medicine, University Hospitals of Leicester NHS Trust, Leicester, GBR. 2Intensive Care and Anaesthesia, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, GBR. 3Hepatobiliary and Pancreatic Surgery, University Hospitals of Leicester NHS Trust, Leicester, GBR. 4Ophthalmology, Birmingham and Midland Eye Centre, Birmingham, GBR. 5Head of Clinical Senates, East and West Midlands Clinical Senate, Leicester, GBR.
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Publication date
2023-10
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Abstract
rtificial 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.
Citation
Molla Imaduddin Ahmed 1, Brendan Spooner 2, John Isherwood 3, Mark Lane 4, Emma Orrock 5, Ashley Dennison 3
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