(371) Predicting Non-Transfusion Severe Maternal Morbidity by Race using the Obstetric Co-Morbidity Index

Black patients experience disproportionate rates of severe maternal morbidity (SMM). Understanding differences in the role of co-morbidities to predict SMM by race may highlight opportunities for interventions to reduce disparities, but whether a validated obstetric co-morbidity index (OB-CMI) differentially predicts SMM by race is not well understood.

Study Design: This retrospective cohort study evaluates 3 years of deliveries within a large health system that includes both academic and community hospitals (2019-2021). Patient demographic, co-morbidity (including OB-CMI components), and outcome data were extracted from the medical record through established ICD-10 codes and electronic health data. Race was categorized as Black vs. non-Black based on patient self-report and SMM was defined according to the CDC indicators, excluding transfusion. Receiver-operator-characteristic (ROC) curves for the OB-CMI were constructed and compared for Black vs. non-Black patients.

Results: 42,492 deliveries were included (16,557 Black, 39.0%). There were significant differences in demographics, co-morbidities, and outcomes for Black vs. non-Black patients (Table). The median OB-CMI score was higher for Black vs. non-Black patients [3 (IQR 1-5) vs. 2 (IQR 0-3), p< 0.01]. Adverse obstetric outcomes including preterm birth, preeclampsia, and SMM without transfusion were all higher for Black patients. OB-CMI was significantly better at classifying non-transfusion SMM for non-Black compared to Black patients (AUC 0.81 vs. 0.76, p< 0.01; Figure), representing high classification accuracy for non-Black compared to moderate accuracy for Black patients.

Conclusion: In a large and diverse delivery cohort with significant differences in co-morbidities and outcomes by race, there was also a significant difference in OB-CMI classification for non-transfusion SMM by race. This highlights an underlying disparity in the predictive function of an established risk factor index and suggests that other elements may drive risk for Black patients.