Clinical questions and evidence search: what the evidence shows

AI search tools and chatbots that answer clinicians' medical questions in plain language, from the medical literature, an expert-written reference or a general-purpose model.

These tools answer clinicians' medical questions in conversational form. In a 2026 American Medical Association survey of nearly 1,700 physicians, 81% reported using AI professionally, more than double the 2023 rate. FDA's guidance on clinical decision support software describes the types of decision-support functions excluded from the definition of a device; no FDA clearance was found for any of the three tools.

A systematic review of 519 studies of large language models in health care found 5% evaluated them on real patient care data. A 2026 review of 4,609 such studies in clinical medicine found 1,048 that used real-world patient data, 19 of them prospective randomized trials. In NOHARM, a preprint that tested 20 large language models and four retrieval-based clinical tools on a 1,100-task benchmark of primary care-to-specialist consultation cases, applying the recommendations directly carried potential for severe harm in up to 24.6% of cases; omissions accounted for more than 80% of severe errors. Open questions include whether the answers change clinicians' decisions and patient outcomes in routine care.

The tools reviewed in this category

General information, not medical advice. Every fact links to its source, and the page shows the date it was last reviewed.