Clinical language models exploit note-specific artifacts (templates, separators, boilerplate) that do not reflect patient state, causing them to fail under deployment shifts despite strong in-hospital accuracy

Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g., templates, separators, boilerplate) that do not reflect patient state.

http://arxiv.org/abs/2608.27397v1