Patient-Facing Generative AI in Telemedicine

Authors

  • Patrick Sullivan Author

Keywords:

generative AI, telemedicine, patient communication, safety, health equity

Abstract

This review examines patient-facing generative artificial intelligence in telemedicine. The organizing question is how generated explanations and triage suggestions can be evaluated for comprehension, equity, safety, and escalation. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to allowing conversational fluency to mask clinical uncertainty and delayed care. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in teleconsultation and patient communication.

References

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Published

2026-08-08

Issue

Vol. 1 (2026): Archive

Section

Review

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Copyright (c) 2026 Translational Medicine and Digital Health

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This work is licensed under a Creative Commons Attribution 4.0 International License.