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Background: Despite the United States Preventive Services Task Force recommendation to screen adults for unhealthy alcohol use, the implementation of alcohol screening in primary care remains suboptimal. Methods: A pre and post-implementation study design that used Agile implementation process to increase screening for unhealthy alcohol use in adult patients from October 2021 to June 2022 at a large primary care clinic serving minority and underprivileged adults in Indianapolis. Results: In comparison to a baseline screening rate of 0%, the agile implementation process increased and sustained screening rates above 80% for alcohol use using the Alcohol Use Disorders Identification Test – Consumption tool (AUDIT-C). Conclusions: Using the agile implementation process, we were able to successfully implement evidence-based recommendations to screen for unhealthy alcohol use in primary care. [ABSTRACT FROM AUTHOR]

Researchers and practitioners recognise the importance of context when implementing healthcare interventions, but the influence of wider environment is rarely mapped. This paper identifies the country and policy-related factors potentially explaining the country differences in outcomes of an intervention focused on improving detection and management of heavy alcohol use in primary care in Colombia, Mexico and Peru. Qualitative data obtained through interviews, logbooks and document analysis are used to explain quantitative data on number of alcohol screenings and screening providers in each of the countries. Existing alcohol screening standards in Mexico, and policy prioritisation of primary care and consideration of alcohol as a public health issue in Colombia and Mexico positively contributed to the outcome, while the COVID-19 pandemic had a negative impact. In Peru, the context was unsupportive due to a combination of: political instability amongst regional health authorities; lack of focus on strengthening primary care due to the expansion of community mental health centres; alcohol considered as an addiction rather than a public health issue; and the impact of COVID-19 on healthcare. We found that wider environment-related factors interacted with the intervention implemented and can help explain country differences in outcomes. [ABSTRACT FROM AUTHOR]

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]

Researchers and practitioners recognise the importance of context when implementing healthcare interventions, but the influence of wider environment is rarely mapped. This paper identifies the country and policy-related factors potentially explaining the country differences in outcomes of an intervention focused on improving detection and management of heavy alcohol use in primary care in Colombia, Mexico and Peru. Qualitative data obtained through interviews, logbooks and document analysis are used to explain quantitative data on number of alcohol screenings and screening providers in each of the countries. Existing alcohol screening standards in Mexico, and policy prioritisation of primary care and consideration of alcohol as a public health issue in Colombia and Mexico positively contributed to the outcome, while the COVID-19 pandemic had a negative impact. In Peru, the context was unsupportive due to a combination of: political instability amongst regional health authorities; lack of focus on strengthening primary care due to the expansion of community mental health centres; alcohol considered as an addiction rather than a public health issue; and the impact of COVID-19 on healthcare. We found that wider environment-related factors interacted with the intervention implemented and can help explain country differences in outcomes.

Background: Although alcohol use disorder can complicate depression management, there is no standard process for assessing AUD symptoms (i.e., AUD diagnostic criteria) in primary care for patients who screen positive for depression. This study characterizes the association between depressive symptoms and high-risk drinking reported by primary care patients on screening measures in routine care. Then, using data from a novel clinical program, this study characterizes the association between depressive symptoms and AUD symptoms reported by primary care patients with high-risk drinking via an Alcohol Symptom Checklist.Methods: In this cross-sectional study, electronic health record data were obtained from patients who visited 33 Kaiser Permanente Washington primary care clinics between 03/2018 and 02/2020 and completed depression (PHQ-2) and alcohol consumption (AUDIT-C) screening measures as part of routine care (N = 369,943). Patients who reported high-risk drinking (AUDIT-C scores 7-12) also completed an Alcohol Symptom Checklist where they reported the presence or absence of 11 AUD criteria as defined by the DSM-5 (N = 8,184). Generalized linear models estimated and compared the prevalence of high-risk drinking (AUDIT-C scores 7-12) and probable AUD (2-11 AUD symptoms on Alcohol Symptom Checklists) for patients with and without positive depression screens.Results: Patients who screened positive for depression had a 131% higher prevalence of high-risk drinking than those who screened negative (5.2% vs. 2.2%; p < 0.001). Among patients with high-risk drinking, positive depression screens were associated with a significantly higher prevalence of probable AUD (69.8% vs. 48.0%; p < 0.001), with large differences in the prevalence of probable AUD observed with increasing PHQ-2 scores (e.g., probable AUD prevalence of 37.6%, 55.3% and 65.2%, for PHQ-2 scores of 0, 1, and 2, respectively). Although the overall prevalence of high-risk drinking was higher for male patients, similar patterns of association between depression screens, high-risk drinking, and AUD symptoms were observed for male and female patients.Conclusions: Patients with positive depression screens are more likely to have high-risk drinking. Large percentages of patients with positive depression screens and high-risk drinking report symptoms consistent with AUD to healthcare providers when given the opportunity to do so using an Alcohol Symptom Checklist. [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: We have previously shown that service-wide support can increase the odds of alcohol screening in any 2-month period in a cluster randomized trial of service-wide support to Aboriginal and Torres Strait Islander Community Controlled Health Services (ACCHS). Here we report an exploratory analysis on whether the resulting pattern of screening was appropriate. Aim: we assess whether that increase in screening was associated with: (i) increased first-time screening, (ii) increased annual screening, (iii) whether frequently screened clients fell into one of four risk categories as defined by national guidelines. Methods: Setting and participants: 22 ACCHS; randomized to receive the support model in the treatment ('early-support') arm over 24-months or to the waitlist control arm. Intervention: eight-component support, including training, sharing of experience, audit-and-feedback and resource support. Analysis: records of clients with visits before and after start of implementation were included. Multilevel logistic modelling was used to compare (i) the odds of previously unscreened clients receiving an AUDIT-C screen, (ii) odds of clients being screened with AUDIT-C at least once annually. We describe the characteristics of a sub-cohort of clients who received four or more screens annually, including if they were in a high-risk category. Results: Of the original trial sample, 43,054 met inclusion criteria, accounting for 81.7% of the screening events in the overall trial. The support did not significantly increase the odds of first-time screening (OR = 1.33, 95% CI 0.81–2.18, p = 0.25) or of annual screening (OR = 0.99, 95% CI 0.42–2.37, p = 0.98). Screening more than once annually occurred in 6240 clients. Of the 841 clients with four or more screens annually, over 50% did not fall into a high-risk category. Females were overrepresented. More males than females fell into high-risk categories. Conclusion: The significant increase in odds of screening observed in the main trial did not translate to significant improvement in first-time or annual screening following implementation of support. This appeared to be due to some clients being screened more frequently than annually, while more than half remained unscreened. Further strategies to improve alcohol screening should focus on appropriate screening regularity as well as overall rates, to ensure clinically useful information about alcohol consumption. Trial Registration ACTRN12618001892202, retrospectively registered 16 November 2018 https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12618001892202. [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]