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A prospective randomized study of patient-centered AI for clinical visit preparation — arXiv:2610.41437

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.41437
License (as archived): CC0-1.0
Archived: 2026-11-02T07:04:25.892Z
SHA-256 of the archived text: a4e52038efbde15fdade956e2ec1b27c5f22e7bdfff030919b4143f7fb08e9ae
Stable URL of this page: https://metraipolis.com/documento/dc_ced5dfc1df98

How to cite

A prospective randomized study of patient-centered AI for clinical visit preparation — arXiv:2610.41437 — arXiv (en), https://arxiv.org/abs/2610.41437 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ced5dfc1df98 (Metraipolis archive dc_ced5dfc1df98, sha256 a4e52038efbde15fdade956e2ec1b27c5f22e7bdfff030919b4143f7fb08e9ae)

BibTeX

@misc{dcced5dfc1df98,
  title = {A prospective randomized study of patient-centered AI for clinical visit preparation — arXiv:2610.41437},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.41437},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ced5dfc1df98; sha256 a4e52038efbde15fdade956e2ec1b27c5f22e7bdfff030919b4143f7fb08e9ae},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.41437. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Patients often arrive at brief, time-constrained clinical visits unsure of what to expect or ask, and millions of adults now turn to general-purpose AI chatbots to prepare beforehand. Yet whether conversational AI improves visit readiness remains unclear. We designed a large language model (LLM)-based visit preparation agent to guide patients before an appointment by gathering clinical context, setting visit expectations, providing relevant health information, building a prioritized list of questions for their clinician, and generating a summary. In a prospective consented randomized study in the Google Health app, 802 U.S. adults held 866 health-related conversations with the visit preparation agent (standard or concise variant) or a minimally prompted control chatbot built on the same LLM. The visit preparation agent significantly outperformed the control across blinded clinician evaluations and patient self-reports. In clinician reviews of completed sessions (n = 272), the agent achieved a 16.6% higher rate of comprehensive preparation (67.2% vs. 50.6%; P < 0.05) and an 8.5% higher rate of alignment with patients' health context (98.9% vs. 90.4%; P < 0.01), while maintaining high medical safety and appropriateness across all study arms. Patient post-surveys (n = 460) showed 16.8% higher visit preparedness (73.8% vs. 57.0%; P < 0.01), 14.3% higher confidence in knowing what to ask (81.4% vs. 67.1%; P < 0.01), and 12.0% higher overall satisfaction (74.0% vs. 62.0%; P < 0.05). Clinician and participant metrics were not significantly correlated, indicating that expert review and patient self-assessment capture complementary dimensions of patient-facing AI. These findings suggest that LLM chatbots can safely help patients prepare for clinical visits, with greater benefit when following a structured workflow, and motivate future studies on in-visit communication and clinical outcomes.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.CL, nuovi lavori del giorno).
Categorie arXiv: Human-Computer Interaction (cs.HC) ; Computation and Language (cs.CL); Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2610.41437 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-02T06:57:13.246Z dalla pagina https://arxiv.org/list/cs.CL/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).