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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: Unhealthy alcohol use is a major contributor to the global burden of disease and injury. The US Preventive Services Task Force has recommended alcohol screening and intervention in general medical settings since 2004. Yet less than one in six US adults report health care professionals discussing alcohol with them. Little is known about methods for increasing implementation; different staffing models may be related to implementation effectiveness. This implementation trial compared delivery of alcohol screening, brief intervention and referral to specialty treatment (SBIRT) by physicians versus non-physician providers receiving training, technical assistance, and feedback reports. Methods: The study was a cluster randomized implementation trial (ADVISe [Alcohol Drinking as a Vital Sign]). Within a private, integrated health care system, 54 adult primary care clinics were stratified by medical center and randomly assigned in blocked groups of three to SBIRT by physicians (PCP arm) versus non-physician providers and medical assistants (NPP and MA arm), versus usual care (Control arm). NIH-recommended screening questions were added to the electronic health record (EHR) to facilitate SBIRT. We examined screening and brief intervention and referral rates by arm. We also examined patient-, physician-, and system-level factors affecting screening rates and, among those who screened positive, rates of brief intervention and referral to treatment. Results: Screening rates were highest in the NPP and MA arm (51 %); followed by the PCP arm (9 %) and the Control arm (3.5 %). Screening increased over the 12 months after training in the NPP and MA arm but remained stable in the PCP arm. The PCP arm had higher brief intervention and referral rates (44 %) among patients screening positive than either the NPP and MA arm (3.4 %) or the Control arm (2.7 %). Higher ratio of MAs to physicians was related to higher screening rates in the NPP and MA arm and longer appointment times to screening and intervention rates in the PCP arm. Conclusion: Findings suggest that time frames longer than 12 months may be required for full SBIRT implementation. Screening by MAs with intervention and referral by physicians as needed can be a feasible model for increasing the implementation of this critical and under-utilized preventive health service within currently predominant primary care models. Trial registration: Clinical Trials NCT01135654 [ABSTRACT FROM AUTHOR]

Background The AUDIT-C is an extensively validated screen for unhealthy alcohol use (i.e. drinking above recommended limits or alcohol use disorder), which consists of three questions about alcohol consumption. AUDIT-C scores ⩾4 points for men and ⩾3 for women are considered positive screens based on US validation studies that compared the AUDIT-C to "gold standard" measures of unhealthy alcohol use from independent, detailed interviews. However, results of screening-positive or negative based on AUDIT-C scores-can be inconsistent with reported drinking on the AUDIT-C questions. For example, individuals can screen positive based on the AUDIT-C score while reporting drinking below US recommended limits on the same AUDIT-C. Alternatively, they can screen negative based on the AUDIT-C score while reporting drinking above US recommended limits. Such inconsistencies could complicate interpretation of screening results, but it is unclear how often they occur in practice. Methods This study used AUDIT-C data from respondents who reported past-year drinking on one of two national US surveys: a general population survey (N = 26,610) and a Veterans Health Administration (VA) outpatient survey (N = 467,416). Gender-stratified analyses estimated the prevalence of AUDIT-C screen results-positive or negative screens based on the AUDIT-C score-that were inconsistent with reported drinking (above or below US recommended limits) on the same AUDIT-C. Results Among men who reported drinking, 13.8% and 21.1% of US general population and VA samples, respectively, had screening results based on AUDIT-C scores (positive or negative) that were inconsistent with reported drinking on the AUDIT-C questions (above or below US recommended limits). Among women who reported drinking, 18.3% and 20.7% of US general population and VA samples, respectively, had screening results that were inconsistent with reported drinking. Limitations This study did not include an independent interview gold standard for unhealthy alcohol use and therefore cannot address how often observed inconsistencies represent false positive or negative screens. Conclusions Up to 21% of people who drink alcohol had alcohol screening results based on the AUDIT-C score that were inconsistent with reported drinking on the same AUDIT-C. This needs to be addressed when training clinicians to use the AUDIT-C. [ABSTRACT FROM AUTHOR]