LLM Hallucinations in Clinical Documentation: Scoping Review with ☸SAIMSARA

Abstract

To synthesize contemporary evidence regarding the prevalence, characteristics, and mitigation strategies for LLM hallucinations within clinical documentation and medical information extraction tasks. The review uses 46 references and builds its evidence map from 32 original studies with 32465 total participants/sample observations (topic-deduplicated ΣN). This scoping review suggests that LLM hallucination in clinical documentation is a measurable but highly context-dependent risk, with rates spanning from roughly 0.73% in monitored agentic deployments to 31–35% in ambient transcription and zero-shot extraction tasks. The dominant signal across included evidence is that architectural and workflow safeguards—particularly retrieval-augmented generation, multi-agent verification, and domain-specific fine-tuning—were associated with hallucination rates approaching or below human documentation benchmarks. These findings support a role for LLMs as assistive documentation tools embedded within human-in-the-loop workflows rather than autonomous systems, especially given persistent risks of unique errors, hallucinations, inaccuracies, and omissions. Future research should prioritize standardized hallucination metrics and prospective, multi-site safety evaluations to clarify which mitigation architectures most reliably preserve documentation integrity across clinical specialties.

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