Persistence of racial disparities in prescription of first-generation antipsychotics in the USA

2015 
Purpose The aim of this study was to estimate the prevalence of first-generation antipsychotics (FGA) prescribed for treatment of psychiatric and neurological conditions and use of benztropine to reduce extrapyramidal side effects (EPS) by patient race/ethnicity in a nationally representative sample of adult outpatient visits. Methods The study sample included all outpatient visits (N = 8154) among patients aged 18–69 years where a prescription for one or more antipsychotics was recorded across 6 years of the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey (2005–2010). Use of FGA was compared by race/ethnicity using multiple logistic regression models accounting for patient and clinical characteristics stratified by neighborhood poverty rate. Frequency of EPS was determined by use of benztropine to reduce or prevent EPS. Results Black patients were significantly more likely than White patients to use FGA (odds ratio = 1.48, p = 0.040) accounting for psychiatric and neurological diagnoses, treatment setting, metabolic factors, neighborhood poverty, and payer source. Black patients were more than twice as likely as White patients to receive higher-potency FGA (haloperidol or fluphenazine), particularly in higher-poverty areas (odds ratio = 2.50, p < 0.001). Use of FGA, higher among Black than White patients, was positively associated with use of benztropine to reduce EPS. Conclusions Racial disparities in the pharmacological treatment of severe mental disorders persist 30 years after the introduction of second-generation antipsychotics. The relatively high frequency of FGA of use among Black patients compared with White patients despite more Food and Drug Administration-approved indications and lower EPS risk for second-generation antipsychotics requires additional research. Copyright © 2015 John Wiley & Sons, Ltd.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    73
    References
    16
    Citations
    NaN
    KQI
    []