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Faculty have requested this content not be shared on social media
CME Credit Offered
CME Credit Offered
Abstract Award
Abstract Award
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Poster Session 2

(623) Stigmatizing language and the association with patient-related factors in pregnant individuals with diabetes

Thursday, January 30, 2025
4:00 PM – 6:00 PM  
Objective: Healthcare providers' biases can negatively influence the quality of care patients receive and exacerbate health disparities. These biases can manifest through verbal and written communication. In this study, we aimed to identify the prevalence of stigmatizing language in clinical notes and to identify the clinician and patient demographic characteristics associated with the use of such language in a population of pregnant individuals with diabetes.

Study Design: We conducted a retrospective cohort study from 2018-2019 of individuals with singleton, non-anomalous pregnancies diagnosed with pre-existing or gestational diabetes using an academic-community obstetric outcomes database. Using a Natural Language Processing (NLP) algorithm, we identified pre-specified stigmatizing terms in electronic health record clinic notes (Fig. 1). We then compared the characteristics of patients with and without documented stigmatizing language in their medical records.

Results: Out of 1433 individuals, 128 (9%) had stigmatizing language in their medical records during their pregnancy, comprising 259 unique notes and a median of 2.0 (range 1.0-12.0) notes per patient. The most frequently used terms were "noncompliant" (47%) and "refused" (42%). Physicians (48%), nurses (22%), and mid-level providers (12%) were the primary providers who used this language. When adjusting for diabetes type, providers were 70% less likely to use stigmatizing language when describing white individuals compared to their black and other race counterparts (aOR 0.26, 95% CI 0.17-0.39; p< 0.001). Additionally, all providers were almost five times more likely to use stigmatizing language when describing patients on public versus private insurance (aOR 4.95, 95% CI 3.26-7.73; p< 0.001) (Table 1).  

Conclusion:

Non-white birthing individuals and those on public insurance diagnosed with diabetes in pregnancy were significantly more likely to have stigmatizing language documented within their medical records. This documentation may contribute to health inequities for marginalized birthing individuals.