Documentation of Stigmatizing Language in Electronic Health Records and Birth Outcomes

Stigmatizing language represents biases. Understanding its impact is crucial to improve perinatal health. We aimed to examine the association between stigmatizing language in electronic health records (EHR) and birth outcomes.

We analyzed EHR data of patients admitted for childbirth (n = 18,897) between 2017 and 2019 using natural language processing at two hospitals in the United States. Independent variables were any stigmatizing language, and by category: marginalized language/identities, difficult patient, and unilateral/authoritarian decisions. Outcome variables included low-risk cesarean birth (Society for Maternal and Fetal Medicine [SMFM] and nulliparous, term, singleton, vertex [NTSV] definitions), postpartum hemorrhage, and chorioamnionitis.

Compared with patients with no stigmatizing language, patients with any stigmatizing language had higher odds of SMFM low-risk cesarean birth (adjusted odds ratio [aOR] = 1.36, 95% confidence interval [CI] = 1.23-1.50, p < 0.01), postpartum hemorrhage (aOR = 1.68, 95% CI = 1.51-1.88, p < 0.01), and chorioamnionitis (aOR = 1.23, 95% CI = 1.07-1.42, p < 0.01). Labeling patients as difficult was associated with higher odds of low-risk cesarean birth (SMFM aOR = 1.19, 95% CI = 1.07-1.33, p < 0.01), postpartum hemorrhage (aOR = 2.07, 95% CI = 1.85-2.30, p < 0.01), and chorioamnionitis (aOR = 1.33, 95% CI = 1.14-1.55, p < 0.01). Patients who had language from unilateral/authoritarian category had higher odds of low-risk cesarean birth (SMFM aOR = 1.46, 95% CI = 1.31-1.62, p < 0.01) and postpartum hemorrhage (aOR = 1.31, 95% CI = 1.17-1.46, p < 0.01).

Stigmatizing language in clinical notes was associated with birth outcomes. These findings highlight the need to improve perinatal health through examining individual behaviors and structural-level policies that reinforce bias.