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
- CAMBOSS AI
- CChatGPT
- CClaude
- CClinicalKey AI
- CDoximity GPT
- CDyna AI
- CGlass Health
- CGoogle Gemini
- COpenEvidence
- CUpToDate Expert AI
General information, not medical advice. Every fact links to its source, and the page shows the date it was last reviewed.