Advancing health equity in preeclampsia prevention - PROJECT SUMMARY The higher incidence of preeclampsia in Black compared to White pregnant populations is one of the leading contributors to racial disparities in maternal morbidity and mortality. Due to the higher preeclampsia rate in Black populations, the U.S. Preventive Services Task Force, American College of Obstetricians and Gynecologists, and Society for Maternal-Fetal Medicine endorse a decision algorithm that includes patient race to guide the use of low-dose aspirin to prevent preeclampsia. In this algorithm, Black patients need fewer preeclampsia risk factors than do patients of other races before aspirin is recommended for prevention. Black race was included in the algorithm because of a large epidemiologic literature demonstrating disparities in both preeclampsia and preeclampsia-related morbidity and mortality between Black and White pregnant populations. However, preeclampsia research has focused almost exclusively on Black-White disparities, with little research examining rates in other racial groups. Our preliminary research suggests that the current low- dose aspirin algorithm is missing multiple racial groups who have high rates of preeclampsia but who are underrepresented in the scientific literature. Without the inclusion of all racial groups with high rates of preeclampsia, the current low-dose aspirin therapy algorithm cannot be equitably applied to all pregnant people to reduce preeclampsia disparities. The objectives of the proposed research are thus to identify the understudied minoritized racial and ethnic groups who experience disparities in preeclampsia and to model the potential to prevent preeclampsia if they were included in the low-dose aspirin decision algorithm. In Aim 1, we will use hospital discharge data from the Healthcare Cost and Utilization Project’s State Inpatient Databases to estimate preeclampsia rates in diverse racial groups and identify those with high rates of preeclampsia. In Aim 2, we will use Markov state-transition models to compare 4 strategies for modifying the low-dose aspirin algorithm to be inclusive of more racial groups and will determine which of these strategies can best prevent preeclampsia and reduce racial disparities: (1) no change to the algorithm, (2) adding new racial groups with high rates of preeclampsia, (3) removing race from the algorithm, and (4) recommending aspirin to all pregnant patients. The long-term goal of this research is to ensure that all patients have equitable access to low-dose aspirin, one of few evidence-based therapies shown to prevent preeclampsia. By modifying a clinical algorithm used nationwide, this research will have important impacts on reducing disparities in preeclampsia and associated maternal morbidity and mortality in the United States.
