ArticlemedRxiv : the preprint server for health sciences2026
Validating LLM judges for automated oversight of patient communication.
Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
20 authors.
Funding
Abstract
LLMs are increasingly used to mediate patient communication, yet scalable evaluation of their safety, accuracy, and communication quality remains an open problem. LLM judges have emerged as automated evaluators, but whether they can holistically replicate human expert judgment is unvalidated. Informed consent for clinical trials presents a demanding case for such validation because it requires conveying complex information to lay audiences under ethical and safety constraints. We developed a stakeholder-informed seven-criterion evaluation rubric spanning safety, reliability, and communication quality. Clinician reference ratings showed strong interrater reliability across all criteria. We validated the rubric on the Informed CONsent Benchmark (ICON-Bench) and benchmarked 19 LLM judges across multiple implementation strategies. LLM judges achieved strong clinician agreement for safety screening and factual verification (Spearman
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.