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J Epidemiol Community Health ; 62(9): 798-803, 2008 Sep.
Article in English | MEDLINE | ID: mdl-18701730

ABSTRACT

BACKGROUND: In 1998, highly active antiretroviral therapy (HAART) was widespread, but the diffusion of these life-saving treatments was not uniform. As half of all AIDS patients in the USA have Medicaid coverage, this study of a multistate Medicaid claims dataset was undertaken to assess disparities in the rates of HAART. METHODS: Data came from 1998 Medicaid claims files from five states with varying HIV prevalence. ICD-9 codes were used to identify people with a diagnosis of HIV/AIDS or AIDS-defining illness. Multivariate analyses assessed associations between age, gender, race and state of residence for antiretroviral regimens consistent with HAART, as defined by 1998 Centers for Disease Control and Prevention (CDC) guidelines. RESULTS: Among 7202 Medicaid enrolees with a diagnosis of HIV/AIDS or AIDS, 62% received HAART and 25% received no antiretroviral therapy. Multivariate analyses showed that age, race, gender and state were all significant predictors of receiving HAART: white, non-Hispanic patients were most likely to receive HAART (68.3%), with lower rates in Hispanic and black, non-Hispanic segments of the population (59.3% and 57.5%, respectively, p<0.001). Women were less likely to receive HAART than men (51.8% vs 69.3%, p<0.001). CONCLUSION: Despite similar insurance coverage and drug benefits, life-saving treatments for HIV/AIDS diffused at widely varying rates in different segments of the Medicaid population. Research is needed to determine the extent to which racial, gender, interstate and region disparities currently correspond to barriers to such care.


Subject(s)
Anti-HIV Agents/administration & dosage , Antiretroviral Therapy, Highly Active/statistics & numerical data , HIV Infections/drug therapy , Adult , Age Factors , Aged , Anti-HIV Agents/therapeutic use , Delivery of Health Care/statistics & numerical data , Female , HIV Infections/ethnology , Humans , Male , Medicaid/statistics & numerical data , Middle Aged , Sex Factors , United States/epidemiology
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