Objective:

The article examines patient perspectives on AI-assisted health care communication, including factors that shape acceptance, concerns about its use, and the role of clinician oversight.

Approach:

• Evidence described: The article draws on survey findings, a study of patient perceptions of AI-drafted chart messages, and perspectives from a patient advocate, social media commenters, and a study coauthor.
• Topics covered: It discusses contexts and stakes of AI use, patient characteristics, privacy and reliability concerns, disclosure, response times, and clinician review.

Key Findings:

• Acceptance of AI in health care varies by use context and perceived stakes. Survey findings also link patient age, race and ethnicity, education, gender, and household income with receptiveness to, utilization of, and trust in AI-based tools.
• In one survey, 50% of respondents accepted AI for routine tasks such as chart summaries and clinical notes when humans maintained oversight; about 28% were comfortable with AI-reviewed insurance claims even with oversight.
• Patients may value faster responses and reduced clinician workload while raising concerns about privacy, reliability, and whether a clinician personally reviewed a message.
• Participants in a study of AI-drafted chart messages valued prompt answers, and the study coauthor said trust depended on substantive human checking and revision. Participants wanted AI use disclosed.
• Some participants found AI-generated messages lengthy or formulaic, while others found their comprehensive, reassuring language supportive; some favored replies unmistakably written by a person.

Interpretation:

The article reports that patient views depend on the context and stakes of AI use, as well as the visibility and substance of clinician involvement. Survey respondents were more comfortable with AI performing routine tasks than with AI-reviewed insurance claims, even when human oversight was present.

Limitations:

• The supplied context does not provide full study methods, sample sizes, or detailed participant characteristics.
• Some perspectives described in the article come from an informal social media post and an individual patient advocate’s account.

Conclusion:

The article reports that disclosure and substantive clinician review are important to participants’ trust in AI-drafted patient messages.

Sources:

• Article context supplied by the user