Currently accepted at: Online Journal of Public Health Informatics
Date Submitted: Oct 9, 2025
Open Peer Review Period: Oct 23, 2025 - Dec 18, 2025
Date Accepted: Jun 5, 2026
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/85584
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Bias In Artificial Intelligence in EPIC and Its Impact on Executive Communication
ABSTRACT
Artificial intelligence (AI) in healthcare communication has significantly changed data-driven decision-making, but it has also raised concerns about bias and equity. This paper examines the impact of bias in AI systems, particularly within the EPIC electronic medical record (EMR), on executive communication and trust within healthcare organizations. Organizational communication theory explores how AI bias affects internal messaging, external reputation, and stakeholder engagement. Recent research provides evidence that biased algorithms can exacerbate inequities for marginalized populations, especially for Black and Brown patients. The paper concludes with recommendations for healthcare executives to balance innovation with ethical communication. These recommendations include conducting bias audits, ensuring transparent reporting, and promoting community involvement to enhance trust and accountability in the adoption of technology.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.