(1000) Evaluating a Universal Low Dose Aspirin Strategy after 1 Year in a Large Health System

Implementing a universal recommendation for low dose aspirin (LDA) is one strategy to optimize treatment uptake in populations with high rates of preeclampsia risk factors. This study evaluates the impact of a universal LDA (uLDA) policy on uptake in a high-risk obstetric population and assesses characteristics of the residual population not prescribed aspirin to identify potential disparities and opportunities for improvement.

Study Design:

This is a retrospective cohort study of all deliveries in a multihospital health system from 5/1/2023-5/31/2025 (uLDA initiated 5/1/2024). First, LDA prescription rates at 16 weeks were extracted from the EHR for a sub-group of “high-risk” patients defined according to the ACOG/USPSTF criteria for LDA and evaluated by month and by race. Poisson regression evaluated the incidence rate ratio (IRR) of LDA prescription before and after the universal policy. LDA prescription rates were then evaluated for the entire patent population after initiation of uLDA and characteristics of patients prescribed vs. not prescribed LDA were compared in bivariable analyses.

Results:

24,187 patients were included (4,751 “high-risk,” 19.6%) and LDA prescriptions were consistently higher in Black vs. non-Black patients in the high-risk group, with plateau for both groups beginning 1/2025 at approximately 80% (Figure 1). IRR for LDA after the intervention was 1.27 (95% CI 1.16-1.40; p < 0.01) for Black and 1.76 (95% CI 1.53-2.04; p < 0.01) for non-Black patients. There were 11,524 patients in the post-intervention group with characteristics in Table 1. Patients not prescribed LDA were more likely to be non-English speaking and to have Medicaid insurance (p < 0.01 for both) and to have substance use disorder.

Conclusion:
At 1-year following a QI initiative to increase LDA prescription rates in a large health system, these data demonstrate equitable implementation by race but residual challenges for patients with other social determinants of health including language barriers. Further QI work will attempt to refine this intervention to optimize equitable implementation.