This study emphasizes the necessity for transparent AI tool labeling in healthcare to enhance patient trust. Conducted in 2024 across Michigan, it involved 159 participants in virtual deliberations aimed at gathering public opinions on critical content for health AI tool labels. Participants prioritized five key areas: privacy and security, equitable efficacy across demographics, safety and effectiveness, clear application in care, and overall health improvement. A significant 94% agreed that patients should be informed about AI tool usage. The results reveal prevalent public apprehensions regarding AI’s impact on healthcare, bolstering calls for enhanced communication and ethical standards. This approach can address existing gaps, ensuring patients are well-informed and fostering a trusting healthcare environment as AI adoption grows. By integrating these insights into AI labeling processes, healthcare systems can bolster transparency, empowering patients to make informed decisions about their care.
For further insights, refer to the American Journal of Managed Care, 2026;32(1):e18-e24.
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