Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and...

Area of Science:

• Healthcare technology
• Artificial intelligence in medicine
• Patient-centered care

Background:

• Artificial intelligence (AI) is transforming healthcare, yet patient views on its diagnostic and communication roles are under-researched.
• Understanding patient perceptions is vital for effective AI integration.

Purpose of the Study:

• To explore patient perspectives on AI applications in healthcare, focusing on diagnostic processes and communication.
• To identify patient concerns, expectations, and opportunities for AI development and implementation.

Main Methods:

• Qualitative focus group methodology with co-design principles.
• 17 adult participants engaged in discussions on five AI scenarios (portal messaging, radiology review, digital scribe, virtual human, decision support).
• Inductive thematic analysis of transcribed sessions and facilitator notes.

Main Results:

• Patient comfort with AI varied by interaction level; digital scribe and radiology review were most favored, virtual humans least.
• Key themes included validation (reliability), usability (diagnostic impact), transparency (disclosure), opportunities (care improvement), and privacy (data security).
• Participants valued the co-design process and felt their input was significant.

Conclusions:

• Patient perspectives are essential for designing and implementing healthcare AI tools.
• Transparency, human oversight, clear communication, and data privacy are critical for patient trust and AI acceptance in diagnostics.
• Findings guide responsible, patient-centered AI deployment for clinicians, organizations, and policymakers.