(1090) Automated Clinical Decision Support eliminates racial disparities in aspirin recommendation

Objective: ACOG and USPSTF have recommended aspirin (ASA) to reduce the probability of developing preeclampsia. Black pregnant people are particularly at risk for being missed. We previously proposed using discrete fields within the Electronic Health Record (EHR) could improve identification of those for whom ASA should be recommended. The aim of this study was to describe the effect of an automated clinical decision support (CDS) on clinician practices as well as evaluate if standardized CDS would decrease disparity in treatment recommendations.

Study Design: A retrospective cohort study of patients with clinic visits from 3/8/2022 to 5/7/2022. We excluded patients who saw infertility and family planning providers. The CDS is triggered to recommend ASA if the patient is pregnant, < =24 weeks, is not already taking aspirin based on the medication record, and meets either 1 high risk factor or 2 moderate risk factors by ACOG/USPSTF criteria. Risk factors were passively queried based on discrete fields (e.g. age, self-reported race and ethnicity, BMI, multiple gestation) and ICD-10 codes (history of preeclampsia, hypertension, diabetes, renal disease, and autoimmune disease).

Results: The CDS fired for 221 unique patients. Of these, in 72 (32.6%) of instances clinicians accepted the ASA order, 44 (19.9%) canceled, and 100 acknowledged the prompt (Figure 1). Of those who acknowledged, most were because the patient was already on ASA (80%) but it had not been documented in the EHR medication list. In total, 152 patients were either already on ASA or received ASA in response to the CDS prompt, representing 69% of patients receiving aspirin. This is an improvement from baseline before CDS implementation (28%)
Frequency of recommendation did not differ by subgroup analysis, including race and ethnicity (Table 1).

Conclusion: A CDS that identifies patients at risk for preeclampsia resulted in increased recommendation and documentation of ASA use and eliminated disparity in treatment recommendations.