Trends in the likelihood of receiving percutaneous coronary intervention in a low-volume hospital and disparities by sociodemographic communities

Abstract

Introduction Over the past two decades, percutaneous coronary intervention (PCI) capacity has increased while coronary artery disease has decreased, potentially lowering per-hospital PCI volumes, which is associated with less favorable patient outcomes. Trends in the likelihood of receiving PCI in a low-volume center have not been well-documented, and it is unknown whether certain socioeconomic factors are associated with a greater risk of PCI in a low-volume facility. Our study aims to determine the likelihood of being treated in a low-volume PCI center over time and if this likelihood differs by sociodemographic factors. Methods We conducted a retrospective cohort study of 374,066 hospitalized patients in California receiving PCI from January 1, 2010, to December 31, 2018. Our primary outcome was the likelihood of PCI discharges at a low-volume hospital (<150 PCI/year), and secondary outcomes included whether this likelihood varied across different sociodemographic groups and across low-volume hospitals stratified by high or low ZIP code median income. Results The proportion of PCI discharges from low-volume hospitals increased from 5.4% to 11.0% over the study period. Patients of all sociodemographic groups considered were more likely to visit low-volume hospitals over time (P<0.001). Latinx patients were more likely to receive PCI at a low-volume hospital compared with non-Latinx White in 2010 with a 166% higher gap in 2018 (unadjusted proportions). The gaps in relative risk (RR) between Black, Latinx and Asian patients versus non-Latinx white increased over time, whereas the gap between private versus public/no insurance, and high versus low income decreased (interaction P<0.001). In low-income ZIP codes, patients with Medicaid were less likely to visit low-volume hospitals than patients with private insurance in 2010; however, this gap reversed and increased by 500% in 2018. Patients with low income were more likely to receive PCI at low-volume hospitals relative to patients with high income in all study years. Conclusions The likelihood of receiving PCI at low-volume hospitals has increased across all race/ethnicity, insurance, and income groups over time; however, this increase has not occurred evenly across all sociodemographic groups.

Disparity issues in coronary artery surgery

“…The likelihood of receiving PCI at low-volume hospitals has increased across all race/ethnicity, insurance, and income groups over time [11 ▪ ].…”

Do PCI Facility Openings Differentially Affect AMI Patients by Individual Race and Community Segregation?

“…5,6 Patients from racial and ethnic minorities are less likely to be admitted to specialized facilities 7 and face an increasing likelihood of undergoing cardiac procedures, such as percutaneous coronary intervention (PCI), at low-volume hospitals which have been associated with less favorable outcomes. 8 One of the gaps in the literature is that many of these studies tend to be cross-sectional, examining a single point in time to determine the existence of disparities; 3 however, it remains unknown whether changes in the built environment, such as the opening of PCI-capable facilities, have widened or narrowed disparities over time. The second conspicuous gap in knowledge lies in a more precise identification of how changes in the provision of care have differentially affected patients at the individual level based on the social construction of race and at the population level, when acknowledging that residential segregation may affect cardiac outcomes.…”

Percutaneous Coronary Intervention in Acute Myocardial Infarction: Community Wealth Matters

“…When comparing patients with different income levels, those with lower income were also more likely to receive PCI at low‐volume hospitals in low‐income areas. 10 While these studies provide some understanding of PCI disparities, their conceptualization of inequity focuses on unidimensional measures (eg, income, race and ethnicity, and rurality).…”