Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study

As health systems incorporate artificial intelligence (AI) into various aspects of patient care, there is growing interest in understanding how to ensure transparent and trustworthy implementation. However, little attention has been given to what information patients need about these technologies to promote transparency of their use. We conducted three asynchronous online focus groups with 42 patients across the United States discussing perspectives on their information needs for trust and uptake of AI, focusing on its use in cardiovascular care. Data were analyzed using a rapid content analysis approach. Our results suggest that patients have a set of core information needs, including specific information factors pertaining to the AI tool, oversight, and healthcare experience, that are relevant to calibrating trust as well as perspectives concerning information delivery, disclosure, consent, and physician AI use. Identifying patient information needs is a critical starting point for calibrating trust in healthcare AI systems and designing strategies for information delivery. These findings highlight the importance of patient-centered engagement when developing AI model documentation and communicating and provisioning information about these technologies in clinical encounters.

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Publication Details

Journal
PLOS Digital Health
Published
2025-04-21
DOI
https://doi.org/10.1371/journal.pdig.0000826
Citations
9
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
5.89

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article

Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study

Austin M. Stroud, Jennifer Miller, Jennifer L. Ridgeway, Xuan Zhu et al.
9 citations
PLOS Digital Health
Artificial Intelligence in Healthcare and Education
5.89
article

Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study

Austin M. Stroud, Jennifer Miller, Jennifer L. Ridgeway, Xuan Zhu, Sarah A. Minteer, Barbara Barry
article en
9 citations

Abstract

As health systems incorporate artificial intelligence (AI) into various aspects of patient care, there is growing interest in understanding how to ensure transparent and trustworthy implementation. However, little attention has been given to what information patients need about these technologies to promote transparency of their use. We conducted three asynchronous online focus groups with 42 patients across the United States discussing perspectives on their information needs for trust and uptake of AI, focusing on its use in cardiovascular care. Data were analyzed using a rapid content analysis approach. Our results suggest that patients have a set of core information needs, including specific information factors pertaining to the AI tool, oversight, and healthcare experience, that are relevant to calibrating trust as well as perspectives concerning information delivery, disclosure, consent, and physician AI use. Identifying patient information needs is a critical starting point for calibrating trust in healthcare AI systems and designing strategies for information delivery. These findings highlight the importance of patient-centered engagement when developing AI model documentation and communicating and provisioning information about these technologies in clinical encounters.

PLOS Digital HealthVol. 4(4)
Mayo Clinic (US), Yale University (US), Mayo Clinic in Arizona (US), Mayo Clinic in Florida (US)
U.S. Food and Drug Administration
Openalex Percentile: Top 4%
Artificial Intelligence in Healthcare and Education
5.89
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