Demographic differences in the cascade of care for unhealthy alcohol use: A cross-sectional analysis of data from the 2015–2019 National Survey on Drug Use and Health

Background: The screening, brief intervention, and referral to treatment (SBIRT) model is recommended by the U.S. Preventive Services Task Force to improve recognition of and intervention for unhealthy alcohol use. How SBIRT implementation differs by demographic characteristics is poorly understood. Methods: We analyzed data from the 2015–2019 National Survey on Drug Use and Health from respondents ≥18 years old who used an outpatient clinic and had at least one alcoholic drink within the past year. Respondents were grouped into one of three mutually exclusive groups: “no binge drinking or alcohol use disorder (AUD),” “binge drinking without AUD,” or “AUD.” Outcome variables were likelihood of screening, brief intervention (BI), referral to treatment (RT), and AUD treatment. The demographic predictors on which outcomes were regressed included gender, age, race and ethnicity, sexual orientation, insurance status, and history of military involvement. Consistent with SBIRT guidelines, the entire sample was included in the screening model; screened persons with either binge drinking without AUD or with AUD were included in the BI model; screened persons with AUD were included in the RT model, and persons referred to treatment with AUD were included in the AUD treatment model. Results: Analyses included 120,804 respondents. Women were more likely than men to be screened, but less likely to receive BI or RT. When referred to treatment, women were more likely than men to receive it. Persons aged ≥50 were least likely to be screened about alcohol, but most likely to receive BI, while persons aged 18–25 were least likely to receive BI or AUD treatment. Racial and ethnic minorities were less likely than White persons to be screened; Asians were less likely to receive RT, and Black persons were less likely to receive treatment than White persons. Persons identifying as gay, lesbian, or bisexual were equally as likely or more likely to receive SBIRT or AUD treatment as those identifying as heterosexual. Persons without insurance were less likely to be screened than those with insurance. Persons with a history of military involvement were more likely to be screened and receive BI and RT than persons who had not served in the military. Conclusions: Demographic disparities in SBIRT implementation exist. Addressing the sources of these disparities and minimizing attrition from care could improve outcomes for persons with unhealthy alcohol use.