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Prevalence and Treatment for Alcohol Use Disorders Based on Kentucky Medicaid 2012-2019 Datasets.
Hu, Huirong; Mitra, Riten; Han, Yuchen; Pal, Subhadip; Huang, Haojiang; McClain, Craig J; Vatsalya, Vatsalya; Kulasekera, K B; Kong, Maiying.
Afiliação
  • Hu H; Department of Bioinformatics and Biostatistics, University of Louisville School of Public Health and Information Sciences, Louisville, Kentucky, USA, 40202.
  • Mitra R; Department of Bioinformatics and Biostatistics, University of Louisville School of Public Health and Information Sciences, Louisville, Kentucky, USA, 40202.
  • Han Y; Department of Bioinformatics and Biostatistics, University of Louisville School of Public Health and Information Sciences, Louisville, Kentucky, USA, 40202.
  • Pal S; Department of Bioinformatics and Biostatistics, University of Louisville School of Public Health and Information Sciences, Louisville, Kentucky, USA, 40202.
  • Huang H; Department of Psychiatry and Behavioral Sciences, University of Louisville School of Medicine, Louisville, Kentucky 40202, USA.
  • McClain CJ; Department of Pharmacology and Toxicology, University of Louisville School of Medicine, Louisville, Kentucky, USA, 40202.
  • Vatsalya V; Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Louisville School of Medicine, Louisville, Kentucky, USA, 40202.
  • Kulasekera KB; Robley Rex Louisville VAMC, Louisville, KY, USA, 40206.
  • Kong M; Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Louisville School of Medicine, Louisville, Kentucky, USA, 40202.
Article em En | MEDLINE | ID: mdl-36683779
Alcohol use is the leading substance use in the United States. Persons with alcohol use disorder (AUD) face enormous health consequences and family problems. Analysis of Medicaid enrollee data is critical to understand different aspects of AUD and the treatment utilization for patients with AUD. Yearly patient-level data were constructed from the Kentucky 2012-2019 Medicaid claims data. ICD-9-CM and ICD-10-CM codes were used to identify patients with AUD and their comorbid conditions, the 11-digit National Drug Codes were used to identify medication treatments, and procedure codes were used to identify psychosocial and behavioral therapies. Logistic regression models were used to examine factors that were associated with AUD prevalence and AUD treatments. The prevalence of AUD trended up over time. Patients living in metro areas, between ages 45-54, having mental disorders, tobacco use, and with a family history of alcoholism had significantly higher rates of AUD. About 60% of patients diagnosed with AUD had major depressive disorder or anxiety. The treatment utilization for AUD also trended up from 2012 to 2019; however, it was still lower than 25% in 2019. Pharmacological treatments were used in only 2.89% of AUD cases in 2012, which increased to 8.13% in 2019. Psychosocial treatments were used in only 1.59% of AUD cases in 2012 that increased to 18.95% in 2019. The prevalence of AUD trended up over years. However, the treatment utilization for AUD was lower than 25%, even as of 2019. There is an urgent need for comprehensive, evidence-based, personalized AUD treatments.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article