Disparities in the appropriateness of medication use: Analysis of the REasons for Geographic And Racial Differences in Stroke (REGARDS) population-based cohort study.

Abstract

Prior work has identified disparities in the quality and outcomes of healthcare across socioeconomic subgroups. Medication use may be subject to similar disparities. To assess the association between demographic and socioeconomic factors (gender, age, race, income, education, and rural or urban residence) and appropriateness of medication use. US adults aged ≥45 years (n=26,798) from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study were included in the analyses, of which 13,623 participants aged ≥65 years (recruited 2003-2007). Potentially inappropriate medication (PIM) use in older adults and drug-drug interactions (DDIs) were identified through 2015 Beers Criteria and clinically significant drug interactions list by Ament et al., respectively as measures of medication appropriateness. Multivariable logistic regression was used to assess the association of disparity parameters with PIM use and DDIs. Interactions between race and other disparity variables were investigated. Approximately 87% of the participants aged ≥65 years used at least one drug listed in the Beers Criteria, and 3.8% of all participants used two or more drugs with DDIs. Significant gender-race interaction across prescription-only drug users revealed that white females compared with white males (OR=1.33, 95% CI 1.20-1.48) and black males compared with white males (OR=1.60, 95% CI 1.41-1.82) were more likely to receive PIM. Individuals with lower income and education also were more likely to use PIM in this sub-group. Females were less likely than males (female vs. male: OR=0.55, 95% CI 0.48-0.63) and individuals resided in small rural areas as opposed to urban areas (small rural vs. urban: OR=1.37, 95% CI 1.07-1.76) were more likely to have DDIs. Demographic and socioeconomic disparities in PIM use and DDIs exist. Future studies should seek to better understand factors contributing to the disparities in order to guide development of interventions.