Data Analysis
The outcome of interest wasfilling of EAI prescription after discharge
from the ED. The variables of interest included the followingpatient
characteristics: age, sex, race, ethnicity and insurance type. We
re-categorizedrace and ethnicity into a single variable:Non-Hispanic
white (NH-white), Non-Hispanic black (NH-black), Hispanicand other.
Insurance status was categorized as commercial or Tricare,
Medicaid-in-state, Medicaid-out-of-state, self-pay and other/unknown.
Patient age was treated as a continuous variable. We used IBM SPSS
Statistics for Windows version 26 (SPSS Inc., Chicago, Ill., USA) to
perform descriptive statistics and logistic regression to measure
associations between prescription fill rates and demographic factors.We
performed bivariable logistic regression to assess for differences in
prescription filling by patient demographics and performed multivariable
logistic regression to adjust for potential confounding by all
covariables. Regression models were fit to derive adjusted ORs with 95%
CIs.