Race, Ethnic, Sex, and Socioeconomic Inequities in Interhospital Transfer for Acute Ischemic Stroke in the United States.

Abstract

Patients with stroke in the United States can be transferred for higher level of care. Little is known about possible inequities in interhospital transfers (IHTs) for acute ischemic stroke. We hypothesized that historically marginalized populations would have lower odds of IHT. A cross-sectional analysis was done for adults with a primary diagnosis of acute ischemic stroke in 2010 to 2017; n=747 982 were identified in the National Inpatient Sample. Yearly rates for IHT were assessed and adjusted odds ratios (aORs) of IHT in 2014 to 2017 were compared with that of 2010 to 2013. Multinomial logistic regression was used to determine the aOR of IHT, adjusting for sociodemographic variables (model 1), sociodemographic and medical variables such as comorbidity and mortality risk (model 2), and sociodemographic, medical, and hospital variables (model 3). After adjusting for sociodemographic, medical, and hospital characteristics, there were no significant temporal differences in IHT from 2010 to 2017. Overall, women were less likely than men to be transferred in all models (model 3: aOR, 0.89 [0.86-0.92]). Compared with those who were White, individuals who were Black (aOR, 0.93 [0.88-0.99]), Hispanic (aOR, 0.90 [0.83-0.97]), other (aOR, 0.90 [0.82-0.99]), or of unknown race, ethnicity (aOR, 0.89 [0.80-1.00]) were less likely to be transferred (model 2), but these differences dissipated when further adjusting for hospital-level characteristics (model 3). Compared with those with private insurance, those with Medicaid (aOR, 0.86 [0.80-0.91]), self-pay (aOR, 0.64 [0.59-0.70]), and no charge (aOR, 0.64 [0.46-0.88]) were less likely to be transferred (model 3). Individuals with lower income were less likely to be transferred compared with those with higher income (model 3: aOR, 0.85 [0.80-0.90], third versus fourth quartile). Adjusted odds of IHT for acute ischemic stroke remained stable from 2010 to 2017. There are numerous inequities in the rates of IHT by race, ethnicity, sex, insurance, and income. Further studies are needed to understand these inequities and develop policies and interventions to mitigate them.