Forty-seven percent of pregnancies have stigmatizing language in their clinical notes in an electronic health record cohort

Neha Simha, Hannah Takasuka, Li-Ching Chen, Umair Khan, Tomiko T Oskotsky, Marina Sirota, et al.

Summary: Researchers analyzed more than 640,000 clinical notes from nearly 26,000 pregnancies at a single academic medical center, using an automated computer program trained to recognize language that could stigmatize or demean patients. The program found that nearly half of all pregnancies had at least one note containing such language. Black patients and those with lower levels of education were significantly more likely to have stigmatizing language in their records. Pregnancies that ended in preterm birth were also more likely to contain this kind of language.

Why it matters: The words clinicians use in patient notes are not neutral. Language that demeans or makes assumptions about a patient can shape how future clinicians think about that person and influence the care they receive. The finding that Black patients are disproportionately described using stigmatizing language is consistent with well-documented inequities in obstetric outcomes and raises important questions about how documentation practices may contribute to those gaps. For health systems and researchers, this study shows that automated tools can be used to audit records for bias at a scale that was previously impossible with manual review.

Expert perspective: This study is a preprint — meaning it has not yet completed formal peer review — and the automated detection tool it uses has not been fully validated against a large, independently reviewed set of notes. Without knowing how often the tool incorrectly flags language as stigmatizing or misses language that is, the headline figure of 47% carries real uncertainty and should not be treated as a precise, established fact. The study also drew on one academic medical center, and documentation habits there may differ from those at community hospitals or safety-net clinics. It is also important to note that Black patients in this cohort may have had more complex medical situations or more clinical contact, which could partly explain the higher rates of flagged language — the study cannot fully rule out this possibility. The finding of more stigmatizing language in preterm births is similarly complicated by the fact that difficult pregnancies simply generate more documentation overall. Despite these cautions, the core finding — that measurable differences in language exist across racial groups and can be detected at scale — is credible and important. The practical implication, that health systems should be auditing their records for documentation bias, is sound.

Relevance: Real-World Data; Data Quality; Clinical Informatics

Source: https://pubmed.ncbi.nlm.nih.gov/42619892/

---