concept

clinical safety evaluation framework

Also known as: clinical safety evaluation, clinical safety, clinical AI safety

Facts (10)

Sources

A framework to assess clinical safety and hallucination rates of LLMs ... nature.com Nature May 13, 2025 8 facts

claimThe researchers determined that the changes tested in Experiment 5 were not suitable for clinical safety evaluation because the resulting increase in hallucinations and omissions was too large to be considered useful.

claimD.P., E.A., M.D., N.M., S.K., and J.B. contributed to the concept, design, and execution of the study regarding clinical safety and hallucination rates of LLMs.

claimThe authors propose a multi-component framework that combines the assessment of hallucinations and omissions with an evaluation of their impact on clinical safety to serve as a governance and clinical safety assessment template for organizations.

referenceThe article titled 'A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation' was published in the journal npj Digital Medicine (volume 8, article 274) in 2025, authored by E. Asgari, N. Montaña-Brown, M. Dubois, and others.

claimThe framework developed by the researchers quantifies the clinical impact and implications of LLM omissions and hallucinations, which is a necessary step to meaningfully address clinical safety.

claimThe CREOLA platform was built by M.D. and S.K. to facilitate clinical safety and hallucination rate assessments in LLMs.

procedureE.A. and D.P. designed the clinical safety framework, reviewed all annotations, and scored the impact of errors on clinical safety.

claimThe authors propose a framework for assessing clinical safety and hallucination rates in large language models (LLMs) that includes an error taxonomy for classifying outputs, an experimental structure for iterative comparisons in document generation pipelines, a clinical safety framework to evaluate error harms, and a graphical user interface named CREOLA.

Medical Hallucination in Foundation Models and Their Impact on ... medrxiv.org medRxiv Nov 2, 2025 2 facts

perspectiveThe authors of the study 'Medical Hallucination in Foundation Models and Their Impact on ...' posit that clinical AI safety will require advancing reasoning transparency and adaptive uncertainty management rather than relying on domain-specific fine-tuning alone.

claimThe Pointwise and Similarity Scores in the Med-HALT benchmark do not directly capture clinical safety or potential for patient harm, as an output could be semantically similar but clinically inappropriate or omit critical warnings.