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Background and Aims: The increasing trend in alcohol consumption among women, exacerbated by the COVID‐19 pandemic, is of growing concern. Screening, brief intervention, and referral to treatment in primary care is an efficacious and cost‐effective treatment approach for unhealthy alcohol use. However, disparities exist in delivery of brief interventions by sex, age and race/ethnicity. This study measures brief intervention rates among eligible patients by sex, age and race/ethnicity and their intersectionality, in the context of a program of systematic alcohol screening and brief intervention program in adult primary care in a large, integrated health‐care delivery system. Design, Setting and Participants: This was a population‐based observational study among primary care clinics in an integrated health‐care delivery system in Northern California, USA. The participants comprised adult (18+) patients (n = 287 551) screening positive for unhealthy alcohol use between January 2014 and December 2017. Measurements: Receipt of brief intervention, patient and provider characteristics from electronic health records. Findings Multi‐level logistic regression showed that women had lower odds of receiving brief intervention than men among all age, racial/ethnic groups and drinking levels. Sex differences were greater among those aged 35–49 years [odds ratio (OR) = 0.67, 95% confidence interval (CI) = 0.64, 0.69]) and 50–65 years (OR = 0.69, 95% CI =0.66, 0.72) than among other age groups. Sex differences in odds of receiving brief intervention were greater for the Latino/Hispanic group for women versus men (OR = 0.69, 95% CI = 0.66, 0.72) and smaller for the Asian/Pacific Islander group (OR = 0.76, 95% CI = 0.72, 0.81). Conclusion: In the United States, compared with men, women appear to have lower odds of receiving brief intervention for unhealthy alcohol use across all age groups, particularly during middle age. Black women and Latina/Hispanic women appear to be less likely to receive brief intervention than women in other race/ethnicity groups. Receipt of brief intervention does not appear to differ by drinking levels between men and women. [ABSTRACT FROM AUTHOR]

Background and aims: There is a higher prevalence of unhealthy alcohol use among Indigenous populations, but there have been few studies of the effectiveness of screening and treatment in primary health care. Over 24 months, we tested whether a model of service-wide support could increase screening and any alcohol treatment. Design: Cluster-randomized trial with 24-month implementation (12 months active, 12 months maintenance). Setting: Australian Aboriginal Community Controlled primary care services. Participants: Twenty-two services (83 032 clients) that use Communicare practice software and see at least 1000 clients annually, randomized to the treatment arm or control arm. Intervention and comparator: Multi-faceted early support model versus a comparator of waiting-list control (11 services). Measurements: A record (presence = 1, absence = 0) of: (i) Alcohol Use Disorders Identification Test--Consumption (AUDIT-C) screening (primary outcome), (ii) any-treatment and (iii) brief intervention. We received routinely collected practice data bimonthly over 3 years (1-year baseline, 1-year implementation, 1-year maintenance). Multi-level logistic modelling was used to compare the odds of each outcome before and after implementation. Findings: The odds of being screened within any 2-month reference period increased in both arms post-implementation, but the increase was nearly eight times greater in earlysupport services [odds ratio (OR) = 7.95, 95% confidence interval (CI) = 4.04-15.63, P < 0.001]. The change in odds of any treatment in early support was nearly double that of waiting-list controls (OR = 1.89, 95% CI = 1.19-2.98, P = 0.01) but was largely driven by decrease in controls. There was no clear evidence of difference between groups in the change in the odds of provision of brief intervention (OR = 1.95, 95% CI = 0.53-7.17, P = 0.32). Conclusions: An early support model designed to aid routine implementation of alcohol screening and treatment in Aboriginal health services resulted in improvement of Alcohol Use Disorders Identification Test--Consumption screening rates over 24 months of implementation, but the effect on treatment was less clear. [ABSTRACT FROM AUTHOR]

Background and Aims: Unhealthy alcohol consumption is a key concern for Aboriginal and Torres Strait Islander ('Indigenous') communities. It is important to identify and treat at‐risk drinkers, to prevent harms to physical or social wellbeing. We aimed to test whether training and support for Aboriginal Community Controlled Health Service (ACCHS) staff would increase rates of alcohol screening and brief intervention. Design Cluster randomized trial. Setting: Australia. Cases/Intervention/Measurements Twenty‐two ACCHSs that see at least 1000 clients per year and use Communicare as practice management software. The study included data on 70 419 clients, training, regular data feedback, collaborative support and funding for resources ($9000). Blinding was not used. The comparator was waiting‐list control (equal allocation). Alcohol Use Disorder Identification Test (AUDIT‐C) screening and records of brief interventions were extracted from practice management software at 2‐monthly intervals. Observations described the clinical actions taken for clients over each 2‐month interval. The baseline period (28 August 2016–28 August 2017) was compared with the post‐implementation period (29 August 2017–28 August 2018). We used multi‐level logistic regression to test the hypotheses that clients attending a service receiving active support would be more likely to be screened with AUDIT‐C (primary outcome) or to receive a brief intervention (secondary outcome). Findings We observed an increase in the odds of screening with AUDIT‐C for both groups, but the increase was 5.52 [95% confidence interval (CI) = 4.31, 7.07] times larger at services receiving support. We found little evidence that the support programme increased the odds of a recorded brief intervention relative to control services (odds ratio = 2.06; 95% CI = 0.90, 4.69). Differences in baseline screening activity between treatment and control reduce the certainty of our findings. Conclusions: Providing Aboriginal Community Controlled Health Services with training and support can improve alcohol (AUDIT‐C) screening rates. [ABSTRACT FROM AUTHOR]

Aims To evaluate the association between Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) alcohol screening scores, collected as part of routine clinical care, and three outcomes in the following year (Aim 1), and the association between changes in AUDIT-C risk group at 1-year follow-up and the same outcomes in the subsequent year (Aim 2). Design Cohort study. Setting Twenty-four US Veterans Affairs (VA) healthcare systems (2004-07), before systematic implementation of brief intervention. Participants A total of 486 115 out-patients with AUDIT-Cs documented in their electronic health records (EHRs) on two occasions ≥ 12 months apart ('baseline' and 'follow-up'). Measurements Independent measures were baseline AUDIT-C scores and change in standard AUDIT-C risk groups (no use, low-risk use and mild, moderate, severe misuse) from baseline to follow-up. Outcome measures were (1) high-density lipoprotein cholesterol (HDL), (2) alcohol-related gastrointestinal hospitalizations ('GI hospitalizations') and (3) physical trauma, each in the years after baseline and follow-up. Findings Baseline AUDIT-C scores had a positive association with outcomes in the following year. Across AUDIT-C scores 0-12, mean HDL ranged from 41.4 [95% confidence interval (CI) = 41.3-41.5] to 53.5 (95% CI = 51.4-55.6) mg/l, and probabilities of GI hospitalizations from 0.49% (95% CI = 0.48-0.51%) to 1.8% (95% CI = 1.3-2.3%) and trauma from 3.0% (95% CI = 2.95-3.06%) to 6.0% (95% CI = 5.2-6.8%). At follow-up, patients who increased to moderate or severe alcohol misuse had consistently higher mean HDL and probabilities of subsequent GI hospitalizations or trauma compared with those who did not ( P-values all < 0.05). For example, among those with baseline low-risk use, in those with persistent low-risk use versus severe misuse at follow-up, the probabilities of subsequent trauma were 2.65% (95% CI = 2.54-2.75%) versus 5.15% (95% CI = 3.86-6.45%), respectively. However, for patients who decreased to lower AUDIT-C risk groups at follow-up, findings were inconsistent across outcomes, with only mean HDL decreasing in most groups that decreased use ( P-values all < 0.05). Conclusions When AUDIT-C screening is conducted in clinical settings, baseline AUDIT-C scores and score increases to moderate-severe alcohol misuse at follow-up screening appear to have predictive validity for HDL cholesterol, alcohol-related gastrointestinal hospitalizations and physical trauma. Decreasing AUDIT-C scores collected in clinical settings appear to have predictive validity for only HDL. [ABSTRACT FROM AUTHOR]