Background: Artificial intelligence (AI) and machine learning (ML) are increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI/ML to improve care, ethical concerns and mistrust in AI-enabled health care exist among the public and medical community. To inform practice guidelines and regulatory policies that facilitate ethical and trustworthy use of AI in medicine, we conducted a literature review to identify key ethical and trust barriers and facilitators from patient and healthcare provider perspectives when using AI in cardiovascular care. Methods: In this rapid literature review, we searched six bibliographic databases to identify publications discussing transparency, trust, or ethical concerns (outcomes of interest) associated with AI/ML-based medical devices (interventions of interest) in the context of cardiovascular care from patient, caregiver, or healthcare provider perspectives. The search was completed on May 24, 2022 and was not limited by date or study design. Results: After reviewing 7,925 papers from six databases and 3,603 papers identified through citation chasing, 145 articles were included. Key ethical concerns included privacy, security, or confidentiality issues; risk of healthcare inequity or disparity; risk of patient harm; accountability and responsibility concerns; problematic informed consent and potential loss of patient autonomy; and issues related to data ownership. Major trust barriers included data privacy and security concerns, potential risk of patient harm, perceived lack of transparency about AI-enabled medical devices, concerns about AI replacing human aspects of care, concerns about prioritizing profits over patients interests, and lack of robust evidence related to the accuracy and limitations of AI-based medical devices. Ethical and trust facilitators included ensuring data privacy and data validation, conducting clinical trials in diverse cohorts, providing appropriate training and resources to patients and healthcare providers and improving their engagement in different phases of AI implementation, and establishing further regulatory oversights. Conclusion: This review revealed key ethical concerns and barriers and facilitators of trust in AI-enabled medical devices from patient and healthcare provider perspectives. Mitigation strategies, including enhancing regulatory oversight on the use of patient data and promoting AI safety and transparency are needed for effective implementation of AI in cardiovascular care.

Dr. Mooghali currently receives research support through Yale University from Arnold Ventures outside of the submitted work. Mr. Stroud has no competing interests. Dr. Yoo has no competing interests. Dr. Barry currently receives research support through the Mayo Clinic Department of Cardiology from Anumana, Inc. Ms. Grimshaw has no competing interests. Dr Ross reported receiving grants from the US Food and Drug Administration; Johnson and Johnson; Medical Device Innovation Consortium; Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Arnold Ventures outside the submitted work. Dr. Ross was also an expert witness at the request of relator attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen Inc. that was settled in September 2022. Dr. Zhu offers scientific input to research studies through a contracted services agreement between Mayo Clinic and Exact Sciences Corporation outside of the submitted work. Dr. Miller reported receiving grants from the US Food & Drug Administration during the conduct of the study and receiving grants from Arnold Ventures, and Scientific American and serving on the board of the nonprofit Bioethics International, and as bioethics advisor at GalateoBio outside the submitted work.

This publication was supported by the Food and Drug Administration (FDA) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award [Center of Excellence in Regulatory Science and Innovation grant to Yale University, U01FD005938] totaling $712,431 with 100 percent funded by FDA/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by FDA/HHS, or the U.S. Government.

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