Increased Documented Brief Alcohol Interventions With a Performance Measure and Electronic Decision Support
ABSTRACT Alcohol screening and brief interventions (BIs) are ranked the third highest US prevention priority, but effective methods of implementing BI into routine care have not been described.
This study evaluated the prevalence of documented BI among Veterans Affairs (VA) outpatients with alcohol misuse before, during, and after implementation of a national performance measure (PM) linked to incentives and dissemination of an electronic clinical reminder (CR) for BI.
VA outpatients were included in this study if they were randomly sampled for national medical record reviews and screened positive for alcohol misuse (Alcohol Use Disorders Identification Test-Consumption score ≥5) between July 2006 and September 2008 (N=6788). Consistent with the PM, BI was defined as documented advice to reduce or abstain from drinking plus feedback linking drinking to health. The prevalence of BI was evaluated among outpatients who screened positive for alcohol misuse during 4 successive phases of BI implementation: baseline year (n=3504), after announcement (n=753) and implementation (n=697) of the PM, and after CR dissemination (n=1834), unadjusted and adjusted for patient characteristics.
Among patients with alcohol misuse, the adjusted prevalence of BI increased significantly over successive phases of BI implementation, from 5.5% (95% CI 4.1%-7.5%), 7.6% (5.6%-10.3%), 19.1% (15.4%-23.7%), to 29.0% (25.0%-33.4%) during the baseline year, after PM announcement, PM implementation, and CR dissemination, respectively (test for trend P<0.001).
A national PM supported by dissemination of an electronic CR for BI was associated with meaningful increases in the prevalence of documented brief alcohol interventions.
SourceAvailable from: onlinelibrary.wiley.com[Show abstract] [Hide abstract]
ABSTRACT: Background In practice, nonalcoholic fatty liver disease (NAFLD) is diagnosed based on elevated liver enzymes and confirmatory liver biopsy or abdominal imaging. Neither method is feasible in identifying individuals with NAFLD in a large-scale healthcare system.AimTo develop and validate an algorithm to identify patients with NAFLD using automated data.Methods Using the Veterans Administration Corporate Data Warehouse, we identified patients who had persistent ALT elevation (≥2 values ≥40 IU/mL ≥6 months apart) and did not have evidence of hepatitis B, hepatitis C or excessive alcohol use. We conducted a structured chart review of 450 patients classified as NAFLD and 150 patients who were classified as non-NAFLD by the database algorithm, and subsequently refined the database algorithm.ResultsThe sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) for the initial database definition of NAFLD were 78.4% (95% CI: 70.0–86.8%), 74.5% (95% CI: 68.1–80.9%), 64.1% (95% CI: 56.4–71.7%) and 85.6% (95% CI: 79.4–91.8%), respectively. Reclassifying patients as having NAFLD if they had two elevated ALTs that were at least 6 months apart but within 2 years of each other, increased the specificity and PPV of the algorithm to 92.4% (95% CI: 88.8–96.0%) and 80.8% (95% CI: 72.5–89.0%), respectively. However, the sensitivity and NPV decreased to 55.0% (95% CI: 46.1–63.9%) and 78.0% (95% CI: 72.1–83.8%), respectively.Conclusions Predictive algorithms using automated data can be used to identify patients with NAFLD, determine prevalence of NAFLD at the system-wide level, and may help select a target population for future clinical studies in veterans with NAFLD.Alimentary Pharmacology & Therapeutics 08/2014; 40(8). DOI:10.1111/apt.12923 · 4.55 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: Brief alcohol intervention, including advice to reduce or abstain from drinking, is widely recommended for general medical outpatients with unhealthy alcohol use, but it is challenging to implement. Among other implementation challenges, providers report reluctance to deliver such interventions, citing concerns about negatively affecting their patient relationships. The purpose of this study was to determine whether patient-reported receipt of brief intervention was associated with patient-reported indicators of high-quality care among veteran outpatients with unhealthy alcohol use. Cross-sectional secondary data analysis was performed using the Veterans Health Administration (VA) Survey of Healthcare Experiences of Patients (SHEP). The study included veteran outpatients who (1) responded to the outpatient long-form SHEP (2009-2011), (2) screened positive for unhealthy alcohol use (Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire score ≥ 3 for women, ≥ 4 for men), and (3) responded to questions assessing receipt of brief intervention and quality of care. We used logistic regression models to estimate the adjusted predicted prevalence of reporting two indicators of high-quality care-patient ratings of their VA provider and of overall VA healthcare (range 0-10, dichotomized as ≥ 9 indicating high quality)-for both patients who did and did not report receipt of brief intervention (receiving alcohol-related advice from a provider) within the previous year. Among 10,612 eligible veterans, 43.8 % reported having received brief intervention, and 84.2 % and 79.1 % rated their quality of care as high from their provider and the VA healthcare system, respectively. In adjusted analyses, compared to veterans who reported receiving no brief intervention, a higher proportion of veterans reporting receipt of brief intervention rated the quality of healthcare from their provider (86.9 % vs. 82.0 %, p < 0.01) and the VA overall (82.7 % vs. 75.9 %, p < 0.01) as high. In this cross-sectional analysis of veterans with unhealthy alcohol use, a higher proportion of those who reported receipt of brief intervention reported receiving high-quality care compared to those who reported having received no such intervention. These findings do not support provider concerns that delivering brief intervention adversely affects patients' perceptions of care.Journal of General Internal Medicine 02/2015; DOI:10.1007/s11606-015-3218-5 · 3.42 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: Military service members may be prone to relapse to problem drinking after remission, given a culture of alcohol use as a coping mechanism for stressful or traumatic events associated with military duties or exposures. However, the prevalence and correlates of relapse are unknown. We sought to identify socio-demographic, military, behavioral, and health characteristics associated with relapse among current and former military members with remittent problem drinking. Participants in the longitudinal Millennium Cohort Study who reported problem drinking at baseline (2001-2003) and were remittent at first follow-up (2004-2006) were included (n=6909). Logistic regression models identified demographic, military service, behavioral, and health characteristics that predicted relapse (report of ≥1 past-year alcohol-related problem on the validated Patient Health Questionnaire) at the second follow-up (2007-2008). Sixteen percent of those with remittent problem drinking relapsed. Reserve/National Guard members compared with active-duty members (odds ratio [OR]=1.71, 95% confidence interval [CI]: 1.45-2.01), members separated from the military during follow-up (OR=1.46, 95% CI: 1.16-1.83), and deployers who reported combat exposure (OR=1.32, 95% CI: 1.07-1.62, relative to non-deployers) were significantly more likely to relapse. Those with multiple deployments were significantly less likely to relapse (OR=0.73, 95% CI: 0.58-0.92). Behavioral factors and mental health conditions also predicted relapse. Relapse was common and associated with military and non-military factors. Targeted intervention to prevent relapse may be indicated for military personnel in particular subgroups, such as Reservists, veterans, and those who deploy with combat exposure. Copyright © 2015. Published by Elsevier Ireland Ltd.Drug and Alcohol Dependence 01/2015; 148. DOI:10.1016/j.drugalcdep.2014.12.031 · 3.28 Impact Factor