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Implementation review demonstrates strategies for integrating artificial intelligence into routine healthcare workflows, indicating viable pathways for low-cost adoption and clinician training.
Although the benefits of artificial intelligence (AI) in clinical practice have been previously reported, its use has not been widely implemented for various reasons, including cost of investment, disruption of historical workflows, perceived negative impact on job security, and regulatory burden of bringing such technology to market. However, innovative AI applications can be implemented to leverage the advantages of technology while bypassing the need for expensive hardware and overhaul of existing workflows. Lessons gleaned from the use of such AI applications highlight how, with expanded testing and systematized approaches to regulatory approval, they can enhance workflow efficiency and quality improvement as well as assist in the training of future practitioners in resource‐limited regions and high‐volume institutions alike.
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Lew et al. (2021) studied this question.
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