BACKGROUND: Treatment disparities in Alzheimer's disease (AD) have received little attention. Determining whether disparities exist in this subpopulation is an important health policy issue. OBJECTIVE: The aim was to determine whether an association existed between race/ethnicity and exposure to AD pharmacotherapy across 4 state Medicaid populations. METHODS: Data from the Centers for Medicare and Medicaid Services (CMS) were used in this retrospective study. Persons with AD enrolled in California, Florida, New Jersey, or New York Medicaid programs on January 1, 2004, and remained in that program for 1 year. Individuals had an AD diagnosis based on the ICD-9-CM code 331.0. Outcomes of interest were exposure to a cholinesterase inhibitor (ChEI) or memantine. Multivariate logistic regression was used to test for the association between race/ethnicity and exposure to a ChEI or memantine. Variables of interest included demographic characteristics and resource utilization factors. The Oaxaca-Blinder decomposition method was used to test for disparities to determine whether exposure to AD pharmacotherapy was influenced by race. RESULTS: Race, age, long-term care admittance, inpatient care admittance, state of residence, and sex were significant predictors of AD pharmacotherapy exposure (P < 0.0001 for all variables). Racial/ethnic disparities were observed with respect to exposure to a ChEI or memantine between non-Hispanic whites and Hispanics (in favor of Hispanics) in Florida (P < 0.0001), between non-Hispanic blacks and Hispanics (in favor of Hispanics) in California (P < 0.0001) and Florida (P < 0.0001), between non-Hispanic blacks and non-Hispanic others (in favor of non-Hispanic others) in California (P < 0.0001) and New York (P < 0.0001), and between Hispanics and non-Hispanic others (in favor of non-Hispanic others) in California (P = 0.001) and New York (P < 0.0001). CONCLUSIONS: Disparities in AD pharmacotherapy exposure among minority populations are just as prevalent, if not of greater magnitude, than minority/white disparities.
BACKGROUND: Treatment disparities in Alzheimer's disease (AD) have received little attention. Determining whether disparities exist in this subpopulation is an important health policy issue. OBJECTIVE: The aim was to determine whether an association existed between race/ethnicity and exposure to AD pharmacotherapy across 4 state Medicaid populations. METHODS: Data from the Centers for Medicare and Medicaid Services (CMS) were used in this retrospective study. Persons with AD enrolled in California, Florida, New Jersey, or New York Medicaid programs on January 1, 2004, and remained in that program for 1 year. Individuals had an AD diagnosis based on the ICD-9-CM code 331.0. Outcomes of interest were exposure to a cholinesterase inhibitor (ChEI) or memantine. Multivariate logistic regression was used to test for the association between race/ethnicity and exposure to a ChEI or memantine. Variables of interest included demographic characteristics and resource utilization factors. The Oaxaca-Blinder decomposition method was used to test for disparities to determine whether exposure to AD pharmacotherapy was influenced by race. RESULTS: Race, age, long-term care admittance, inpatient care admittance, state of residence, and sex were significant predictors of AD pharmacotherapy exposure (P < 0.0001 for all variables). Racial/ethnic disparities were observed with respect to exposure to a ChEI or memantine between non-Hispanic whites and Hispanics (in favor of Hispanics) in Florida (P < 0.0001), between non-Hispanic blacks and Hispanics (in favor of Hispanics) in California (P < 0.0001) and Florida (P < 0.0001), between non-Hispanic blacks and non-Hispanic others (in favor of non-Hispanic others) in California (P < 0.0001) and New York (P < 0.0001), and between Hispanics and non-Hispanic others (in favor of non-Hispanic others) in California (P = 0.001) and New York (P < 0.0001). CONCLUSIONS: Disparities in AD pharmacotherapy exposure among minority populations are just as prevalent, if not of greater magnitude, than minority/white disparities.
Authors: Colleen J Maxwell; Mary Vu; David B Hogan; Scott B Patten; Micaela Jantzi; Marie-Jeanne Kergoat; Nathalie Jetté; Susan E Bronskill; George Heckman; John P Hirdes Journal: Drugs Aging Date: 2013-07 Impact factor: 3.923
Authors: Carolyn T Thorpe; Nicole R Fowler; Katherine Harrigan; Xinhua Zhao; Yihuang Kang; Joseph T Hanlon; Walid F Gellad; Loren J Schleiden; Joshua M Thorpe Journal: J Am Geriatr Soc Date: 2016-08-22 Impact factor: 5.562
Authors: Xiaopu Zhou; Yu Chen; Kin Y Mok; Qianhua Zhao; Keliang Chen; Yuewen Chen; John Hardy; Yun Li; Amy K Y Fu; Qihao Guo; Nancy Y Ip Journal: Proc Natl Acad Sci U S A Date: 2018-02-05 Impact factor: 11.205
Authors: Pei-Jung Lin; Allan T Daly; Natalia Olchanski; Joshua T Cohen; Peter J Neumann; Jessica D Faul; Howard M Fillit; Karen M Freund Journal: Med Care Date: 2021-08-01 Impact factor: 3.178