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Novel P2Y12 inhibitors prasugrel and ticagrelor were approved for patients with acute coronary syndrome (ACS) in 2009 and 2011, respectively. We assessed the association of racial, ethnic, and socioeconomic factors with initiation of and adherence to novel P2Y12 inhibitors in a commercially insured population.We performed a retrospective cohort analysis of adults undergoing percutaneous coronary intervention with placement of a drug-eluting stent, stratified by ACS status, between January 2008 and December 2016 using Clinformatics Data Mart (OptumInsight). We estimated multivariable logistic regression models to identify factors associated with the initiation of clopidogrel vs novel P2Y12 inhibitors as well as subsequent 6-month medication adherence, assessed via pharmacy records.A total of 55,664 patients were included in the analysis. Hispanic ethnicity was independently associated with the initiation of clopidogrel compared with novel P2Y12 inhibitors among ACS patients (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.04-1.36; P.01). ACS patients with an annual median household income of over $100,000 were less likely to be started on clopidogrel when compared with those who earned less than $40,000 (OR, 0.67; 95% CI, 0.61-0.75; P.01). Black race, Hispanic ethnicity, and lower household income were each associated with significantly reduced odds of P2Y12 inhibitor adherence.Hispanic ethnicity and lower household income were associated with novel P2Y12 inhibitor initiation, and non-White race and ethnicity were associated with lower P2Y12 inhibitor adherence over 6-month follow-up. These findings highlight continued inequity of care, even in an insured population, and point to a need for new strategies to close these gaps.

Concerns about the external validity of traditional randomized clinical trials (RCTs), together with the widespread availability of real-world data and advanced data analytic tools, have led to claims that common sense and clinical observation, rather than RCTs, should be the preferred method to generate evidence to support clinical decision-making. However, over the past 4 decades, results from well-done RCTs have repeatedly contradicted practices supported by common sense and clinical observation. Common sense and clinical observation fail for several reasons: incomplete understanding of pathophysiology, biases and unmeasured confounding in observational research, and failure to understand risks and benefits of treatments within complex systems. Concerns about traditional RCT models are legitimate, but randomization remains a critical tool to understand the causal relationship between treatments and outcomes. Instead, development and promulgation of tools to apply randomization to real-world data are needed to build the best evidence base in cardiovascular medicine.