Influence of comorbid drug use disorder on receipt of evidence-based treatment for alcohol use disorder among VA patients with alcohol use disorder and Hepatitis C and/or HIV

Abstract

Background: Alcohol use is risky for patients with hepatitis C virus (HCV) and/or human immunodeficiency virus (HIV) infection, but alcohol use disorder (AUD) treatment is underutilized in these populations. Comorbid drug use disorders (DUD) are common, but their influence on AUD treatment receipt is understudied. We evaluated the association between DUD and AUD treatment receipt in two national samples of patients with AUD, those with HIV and those with HCV, in the U.S. Veterans Health Administration. Methods: Samples included patients with AUD and HCV and/or HIV among positive alcohol screens (AUDIT-C≥5) documented 10/01/09-5/30/13 in the national electronic health record. Poisson regression models estimated incidence rate ratios for receiving specialty treatment (stop codes) and pharmacotherapy (filled prescription for naltrexone, disulfiram, acamprosate, or topiramate) within 365 days of positive alcohol screening for patients with DUD versus those without. Models were clustered on patient and adjusted for potential confounders. Results: Among 22,039 patients with HCV/AUD, 45.2% (N=9,964) had DUD, which was associated with receiving specialty treatment [adjusted incidence rate ratio: 1.89 (95% confidence interval 1.82-1.96)] and pharmacotherapy [aIRR: 1.50 (1.37-1.65)]. Among 1,834 patients with HIV/AUD, 56.9% (N=1,043) had DUD, which was associated with receiving specialty treatment [aIRR: 1.94 (1.68-2.24)], but not pharmacotherapy. Conclusions: Rates of AUD treatment receipt among patients with AUD and HCV and/or HIV were low overall, but likelihood of treatment receipt was generally higher among those with comorbid DUD. Future research should investigate mechanisms underlying these associations, such as enhanced readiness for treatment or differential provider prescribing or referral practices.

Association of Mental Health Treatment With Outcomes for US Veterans Diagnosed With Non–Small Cell Lung Cancer

“…Specific programs evaluated include mental health intensive case management for schizophrenia and bipolar disorder, psychotherapy for depressive and anxiety disorders, PTSD therapy, and substance use treatment programs. Program participation was ascertained from Current Procedural Terminology codes and VA stop codes, an internal coding system used to capture workload data …”

“…Program participation was ascertained from Current Procedural Terminology codes and VA stop codes, an internal coding system used to capture workload data. [18][19][20]…”

Dopamine beta‐hydroxylase and its genetic variants in human health and disease

“…However, disulfiram also serves as a copper chelator and, therefore, it does not just inhibit ALDH, but also DβH (Gaval‐Cruz and Weinshenker ). In the nearly 70 years of use of disulfiram for alcohol abuse, it has been documented to decrease the incidence of the abuse of other substances such as cocaine and marijuana (Weathermon and Crabb ; Frost et al ; Mohammad et al ).…”

Documented brief intervention associated with reduced linkage to specialty addictions treatment in a national sample of VA patients with unhealthy alcohol use with and without alcohol use disorders

“…Covariates included sociodemographic characteristics and mental health or substance use-related measures associated with brief intervention and receipt of specialty addictions treatment [42,[47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. Sociodemographic characteristics were measured based on EHR documentation at the time of screening, and included sex, age, race/ethnicity, marital status and VA co-payment eligibility status/disability rating (proxy for socioeconomic status) [48,62].…”

“…Modified Poisson regression models [64] were fit with positive screens as the unit of analysis to estimate the relative rate [incidence rate ratio (IRR)] of receiving VA specialty addictions treatment for screens followed by documented brief intervention relative to those without. Poisson regression models were used instead of logistic regression in order to directly estimate relative risk [64,65], consistent with prior studies examining these outcomes in VA data [38,61,66]. Regression analyses were clustered at the patient level, and standard errors were calculated with the robust sandwich estimator to correct for correlation between screens collected from the same patient and for misspecification of the Poisson model's variance structure [64,65,67].…”