Changes in alcohol consumption reported on routine healthcare screenings are associated with changes in depression symptoms.

BACKGROUND: The Alcohol Use Disorders Identification Test-Consumption version (AUDIT-C) has been robustly validated as a point-in-time screen for unhealthy alcohol use, but less is known about the significance of changes in AUDIT-C scores from routine screenings over time. Unhealthy alcohol use and depression commonly co-occur, and changes in drinking often co-occur with changes in depression symptoms. We assess the associations between changes in AUDIT-C scores and changes in depression symptoms reported on brief screens completed in routine care. METHODS: The study sample included 198,335 primary care patients who completed two AUDIT-C screens 11 to 24 months apart and the Patient Health Questionnaire-2 (PHQ-2) depression screen on the same day as each AUDIT-C. Both screening measures were completed as part of routine care within a large health system in Washington state. AUDIT-C scores were categorized to reflect five drinking levels at both time points, resulting in 25 subgroups with different change patterns. For each of the 25 subgroups, within-group changes in the prevalence of positive PHQ-2 depression screens were characterized using risk ratios (RRs) and McNemar's tests. RESULTS: Patient subgroups with increases in AUDIT-C risk categories generally experienced increases in the prevalence of positive depression screens (RRs ranging from 0.95 to 2.00). Patient subgroups with decreases in AUDIT-C risk categories generally experienced decreases in the prevalence of positive depression screens (RRs ranging from 0.52 to 1.01). Patient subgroups that did not have changes in AUDIT-C risk categories experienced little or no change in the prevalence of positive depression screens (RRs ranging from 0.98 to 1.15). CONCLUSIONS: As hypothesized, changes in alcohol consumption reported on AUDIT-C screens completed in routine care were associated with changes in depression screening results. Results support the validity and clinical utility of monitoring changes in AUDIT-C scores over time as a meaningful measure of changes in drinking.

Practical assessment of DSM-5 alcohol use disorder criteria in routine care: High test-retest reliability of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is underdiagnosed and undertreated in medical settings, in part due to a lack of AUD assessment instruments that are reliable and practical for use in routine care. This study evaluates the test-retest reliability of a patient-report Alcohol Symptom Checklist questionnaire when it is used in routine care, including primary care and mental health specialty settings. METHODS: We performed a pragmatic test-retest reliability study using electronic health record (EHR) data from Kaiser Permanente Washington, an integrated health system in Washington state. The sample included 454 patients who reported high-risk drinking on a behavioral health screen and completed two Alcohol Symptom Checklists 1 to 21 days apart. Subgroups of these patients who completed both checklists in primary care (n = 271) or mental health settings (n = 79) were also examined. The primary measure was an Alcohol Symptom Checklist on which patients self-reported whether they experienced each of the 11 AUD criteria within the past year, as defined by the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5). RESULTS: Alcohol Symptom Checklists completed in routine care and documented in EHRs had excellent test-retest reliability for measuring AUD criterion counts (ICC = 0.79, 95% CI: 0.76 to 0.82). Test-retest reliability estimates were also high and not significantly different for the subsamples of patients who completed both checklists in primary care (ICC = 0.82, 95% CI: 0.77 to 0.85) or mental health settings (ICC = 0.74, 95% CI: 0.62 to 0.83). Test-retest reliability was not moderated by having a past two-year AUD diagnosis, nor by the age or sex of the patient completing it. CONCLUSIONS: Alcohol Symptom Checklists can reliably and pragmatically assess AUD criteria in routine care among patients who screen positive for high-risk drinking. The Alcohol Symptom Checklist may be a valuable tool in supporting AUD-related care and monitoring AUD criteria longitudinally in routine primary care and mental health settings.

Veteran families with complex needs: a qualitative study of the veterans' support system.

BACKGROUND: Families with complex needs face significant challenges accessing and navigating health and social services. For veteran families, these challenges are exacerbated by interactions between military and civilian systems of care, and the density of the veterans' non-profit sector. This qualitative study was designed to gather rich, detailed information on complex needs in veteran families; and explore service providers' and families' experiences of accessing and navigating the veterans' support system. METHODS: The study comprised participant background questionnaires (n = 34), focus groups with frontline service providers (n = 18), and one-on-one interviews with veteran families (n = 16) in Australia. The semi-structured focus groups and interviews were designed to gather rich, detailed information on four study topics: (i) health and wellbeing needs in veteran families; (ii) service-access barriers and facilitators; (iii) unmet needs and gaps in service provision; and (iv) practical solutions for improving service delivery. The study recruited participants who could best address the focus on veteran families with complex needs. The questionnaire data was used to describe relevant characteristics of the participant sample. The focus groups and interviews were audio-recorded, transcribed, and a reflexive thematic analysis was conducted to identify patterns of shared meaning in the qualitative data. RESULTS: Both service providers and families found the veterans' support system difficult to access and navigate. System fragmentation was perceived to impede care coordination, and delay access to holistic care for veteran families with complex needs. The medico-legal aspects of compensation and rehabilitation processes were perceived to harm veteran identity, and undermine health and wellbeing outcomes. Recovery-oriented practice was viewed as a way to promote veteran independence and self-management. Participants expressed a strong preference for family-centred care that was informed by an understanding of military lifestyle and culture. CONCLUSION: The health and wellbeing needs of veteran families intensify during the transition from full-time military service to civilian environments, and service- or reintegration-related difficulties may emerge (or persist) for a significant period of time thereafter. Veteran families with complex needs are unduly burdened by care coordination demands. There is a pressing need for high-quality implementation studies that evaluate initiatives for integrating fragmented systems of care.

Practical Assessment of Alcohol Use Disorder in Routine Primary Care: Performance of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated. OBJECTIVE: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care. DESIGN: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity. PATIENTS: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020. MAIN MEASURE: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs. KEY RESULTS: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11). CONCLUSIONS: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.

Pilot Cohorts for Development of Concurrent Mobile Treatment for Alcohol and Tobacco Use Disorders.

Alcohol and tobacco are the 2 most frequently used drugs in the United States and represent the highest co-occurrence of polysubstance use. The objective of this study was to refine an intervention combining mobile contingency management with cognitive-behavioral telephone counseling for concurrent treatment of alcohol and tobacco use disorders. Two cohorts (n = 13 total, n = 5 women) of participants were enrolled, with 10/13 completing treatment and 7/13 completing the 6-month follow-up. At enrollment, participants were drinking a mean of 28.9 drinks per week (SD = 14.1), with a mean of 14.7 heavy drinking days in the past month (SD = 9.9), and a mean of 18.1 cigarettes per day (SD = 11.7). Treatment included a mobile application that participants used to record carbon monoxide and breath alcohol content readings to bioverify abstinence. Participants received up to 4 sessions of phone cognitive-behavioral therapy and monetary reinforcement contingent on abstinence. In cohort 1, 4/6 participants reported abstinent or low-risk drinking post-monitoring. Six weeks post quit-date, 2/6 participants were CO-bioverified abstinent from tobacco use, with 2/6 in dual remission. These results were maintained at 6-months. In cohort 2, 6/7 reported abstinent or low-risk drinking post-monitoring, 5 weeks post quit-date. At the post-monitoring visit, 5/7 were CO-bioverified abstinent from smoking, with 5/7 in dual remission. At 6-months, 3/7 reporting abstinent or low-risk drinking, 1/7 had bioverified abstinence from smoking, with 1/7 in dual remission. Observations suggest that it is possible to develop a concurrent mobile treatment for alcohol and tobacco use disorders.

Effect of a Care Management Intervention on 12-Month Drinking Outcomes Among Patients With and Without DSM-IV Alcohol Dependence at Baseline.

BACKGROUND: The CHOICE care management intervention did not improve drinking relative to usual care (UC) for patients with frequent heavy drinking at high risk of alcohol use disorders. Patients with alcohol dependence were hypothesized to benefit most. We conducted preplanned secondary analyses to test whether the CHOICE intervention improved drinking relative to UC among patients with and without baseline DSM-IV alcohol dependence. METHODS: A total of 304 patients reporting frequent heavy drinking from 3 VA primary care clinics were randomized (stratified by DSM-IV alcohol dependence, sex, and site) to UC or the patient-centered, nurse-delivered, 12-month CHOICE care management intervention. Primary outcomes included percent heavy drinking days (%HDD) using 28-day timeline follow-back and a "good drinking outcome" (GDO)-abstaining or drinking below recommended limits and no alcohol-related symptoms on the Short Inventory of Problems at 12 months. Generalized estimating equation binomial regression models (clustered on provider) with interaction terms between dependence and intervention group were fit. RESULTS: At baseline, 59% of intervention and UC patients had DSM-IV alcohol dependence. Mean drinking outcomes improved for all subgroups. For participants with dependence, 12-month outcomes did not differ for intervention versus UC patients (%HDD 37% versus 38%, p = 0.76 and GDO 16% versus 16%, p = 0.77). For participants without dependence, %HDD did not differ between intervention (41%) and UC (31%) patients (p = 0.12), but the proportion with GDO was significantly higher among UC participants (26% versus 13%, p = 0.046). Neither outcome was significantly modified by dependence (interaction p values 0.19 for %HDD and 0.10 for GDO). CONCLUSIONS: Among participants with frequent heavy drinking, care management had no benefit relative to UC for patients with dependence, but UC may have had benefits for those without dependence. TRIAL REGISTRATION: ClinicalTrials.gov NCT01400581.

Alcohol-Related Nurse Care Management in Primary Care: A Randomized Clinical Trial.

Importance: Experts recommend that alcohol use disorders (AUDs) be managed in primary care, but effective approaches are unclear. Objective: To test whether 12 months of alcohol care management, compared with usual care, improved drinking outcomes among patients with or at high risk for AUDs. Design, Setting, and Participants: This randomized clinical trial was conducted at 3 Veterans Affairs (VA) primary care clinics. Between October 11, 2011, and September 30, 2014, the study enrolled 304 outpatients who reported heavy drinking (≥4 drinks per day for women and ≥5 drinks per day for men). Interventions: Nurse care managers offered outreach and engagement, repeated brief counseling using motivational interviewing and shared decision making about treatment options, and nurse practitioner-prescribed AUD medications (if desired), supported by an interdisciplinary team (CHOICE intervention). The comparison was usual primary care. Main Outcomes and Measures: Primary outcomes, assessed by blinded telephone interviewers at 12 months, were percentage of heavy drinking days in the prior 28 days measured by timeline follow-back interviews and a binary good drinking outcome, defined as abstinence or drinking below recommended limits in the prior 28 days (according to timeline follow-back interviews) and no alcohol-related symptoms in the past 3 months as measured by the Short Inventory of Problems. Results: Of 304 participants, 275 (90%) were male, 206 (68%) were white, and the mean (SD) age was 51.4 (13.8) years. At baseline, both the CHOICE intervention (n = 150) and usual care (n = 154) groups reported heavy drinking on 61% of days (95% CI, 56%-66%). During the 12-month intervention, 137 of 150 patients in the intervention group (91%) had at least 1 nurse visit, and 77 of 150 (51%) had at least 6 nurse visits. A greater proportion of patients in the intervention group than in the usual care group received alcohol-related care: 42% (95% CI, 35%-49%; 63 of 150 patients) vs 26% (95% CI, 19%-35%; 40 of 154 patients). Alcohol-related care included more AUD medication use: 32% (95% CI, 26%-39%; 48 of 150 patients in the intervention group) vs 8% (95% CI, 5%-13%; 13 of 154 patients in the usual care group). No significant differences in primary outcomes were observed at 12 months between patients in both groups. The percentages of heavy drinking days were 39% (95% CI, 32%-47%) and 35% (95% CI, 28%-42%), and the percentages of patients with a good drinking outcome were 15% (95% CI, 9%-22%; 18 of 124 patients) and 20% (95 % CI, 14%-28%; 27 of 134 patients), in the intervention and usual care groups, respectively (P = .32-.44). Findings at 3 months were similar. Conclusions and Relevance: The CHOICE intervention did not decrease heavy drinking or related problems despite increased engagement in alcohol-related care. Trial Registration: clinicaltrials.gov Identifier: NCT01400581.

Mental health productivity monitoring in the Veterans Health Administration: Challenges and lessons learned.

Achieving quality outcomes and cost efficiency within mental health are overarching objectives of the Veterans Health Administration (VHA). The mental health care workforce has long been oriented toward the goal of high quality outcomes; however, cost efficiency has only recently been elevated into this important value equation. With increased demand for access to mental health services within the VHA, leadership sought to advance methods of determining and improving mental health provider productivity. Monitoring of productivity data may also provide data signaling the potential need for additional staffing to keep up with demand for services. This article outlines VHA's development and specification of mental health productivity policy, implementation strategies, and a discussion of challenges and lessons learned for other systems to consider in implementing productivity monitoring. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Increased Rates of Documented Alcohol Counseling in Primary Care: More Counseling or Just More Documentation?

BACKGROUND: Clinical performance measures often require documentation of patient counseling by healthcare providers. Little is known about whether such measures encourage delivery of counseling or merely its documentation. OBJECTIVE: To assess changes in provider documentation of alcohol counseling and patient report of receiving alcohol counseling in the Veterans Administration (VA) from 2009 to 2012. DESIGN: Retrospective time-series analysis. PARTICIPANTS: A total of 5413 men who screened positive for unhealthy alcohol use at an outpatient visit and responded to a confidential mailed survey regarding alcohol counseling from a VA provider in the prior year. MAIN MEASURES: Rates of provider documentation of alcohol counseling in the electronic health record and patient report of such counseling on the survey were assessed over 4 fiscal years. Annual rates were calculated overall and with patients categorized into four mutually exclusive groups based on their own reports of alcohol counseling (yes/no) and whether alcohol counseling was documented by a provider (yes/no). KEY RESULTS: Provider documentation of alcohol counseling increased 23.6% (95% CI: 17.0, 30.2), from 59.4% to 83.0%, while patient report of alcohol counseling showed no significant change (4.0%, 95% CI: -2.3, 10.3), increasing from 66.1% to 70.1%. An 18.7% (95% CI: 11.7, 25.7) increase in the proportion of patients who reported counseling that was documented by a provider largely reflected a 14.7% decline (95% CI: 8.5, 20.8) in the proportion of patients who reported alcohol counseling that was not documented by a provider. The proportion of patients who did not report counseling but whose providers documented it did not show a significant change (4.9%, 95%CI: 0.0, 9.9). CONCLUSIONS: If patient report is accurate, increased rates of documented alcohol counseling in the VA from 2009 to 2012 predominantly reflected improved documentation of previously undocumented counseling rather than delivery of additional counseling or increased documentation of counseling that did not meaningfully occur.

Frequency of Cannabis Use Among Primary Care Patients in Washington State.

INTRODUCTION: Over 12% of US adults report past-year cannabis use, and among those who use daily, 25% or more have a cannabis use disorder. Use is increasing as legal access expands. Yet, cannabis use is not routinely assessed in primary care, and little is known about use among primary care patients and relevant demographic and behavioral health subgroups. This study describes the prevalence and frequency of past-year cannabis use among primary care patients assessed for use during a primary care visit. METHODS: This observational cohort study included adults who made a visit to primary care clinics with annual behavioral health screening, including a single-item question about frequency past-year cannabis use (March 2015 to February 2016; n = 29,857). Depression, alcohol and other drug use were also assessed by behavioral health screening. Screening results, tobacco use, and diagnoses for past-year behavioral health conditions (e.g., mental health and substance use disorders) were obtained from EHRs. RESULTS: Among patients who completed the cannabis use question (n = 22,095; 74% of eligible patients), 15.3% (14.8% to 15.8%) reported any past-year use: 12.2% (11.8% to 12.6%) less than daily, and 3.1% (2.9%-3.3%) daily. Among 2228 patients age 18 to 29 years, 36.0% (34.0% to 38.0%) reported any cannabis use and 8.1% (7.0% to 9.3%) daily use. Daily cannabis use was common among men age 18 to 29 years who used tobacco or screened positive for depression or used tobacco: 25.5% (18.8% to 32.1%) and 31.7% (23.3% to 40.0%), respectively. CONCLUSIONS: Cannabis use was common in adult primary care patients, especially among younger patients and those with behavioral health conditions. Results highlight the need for primary care approaches to address cannabis use.

Health care cost trajectories in the year prior to and following intake into Veterans Health Administration outpatient substance use disorders treatment.

Veterans Health Administration (VHA) patients with substance use disorder (SUD) diagnoses incur significantly higher overall health care costs compared to the average annual costs of VHA patients. Because SUDs are relapsing/remitting chronic illnesses, it is important to understand how service costs shift over time in relation to active SUD treatment episodes in order to identify strategies which may enhance treatment outcomes and thereby reduce costs. The primary aim of the current study was to examine VHA health care costs derived from VHA administrative data for 330 Veterans during the years prior to and following patient entry into outpatient SUD treatment in two VHA facilities. Secondary aims were to examine the impact on treatment costs of patient diagnosis (alcohol dependence only vs. stimulant dependence) and participation in an abstinence incentive intervention. There was a significant effect of time on health care costs (p<0.001). Average total costs per patient per quarter were $2204 for quarters 1 through 3, increased significantly to $7507 in quarter 4 and $8030 in quarter 5, then decreased significantly to $3969 in quarters 6 through 8. Increases in quarter 4 and 5 were attributable to inpatient costs whereas increases in the quarters following treatment entry were attributable to outpatient costs (quarters 5-8). Overall costs for patients with alcohol dependence only were approximately 30% higher than overall costs for patients whose diagnoses included stimulant dependence, attributable to higher outpatient costs. There was no significant effect of the 8-week incentive intervention on post-treatment entry costs. Overall, entering SUD treatment corresponded to an increase in health care costs in the quarters both immediately preceding and immediately following treatment entry followed by a tapering down of costs through 12month follow-up; however, longer follow-up is needed to inform the stability of this pattern. Additional research will be needed to determine whether efforts to increase access to SUD treatment, identify patients with SUD earlier on in the course of their disorder and integrate SUD treatment services into primary care settings may assist in engaging patients in treatment prior to experiencing a mental or physical health crisis requiring inpatient treatment and thereby reduce health care costs associated with SUD diagnoses.

Patient-centered primary care for adults at high risk for AUDs: the Choosing Healthier Drinking Options In primary CarE (CHOICE) trial.

BACKGROUND: Most patients with alcohol use disorders (AUDs) never receive alcohol treatment, and experts have recommended management of AUDs in primary care. The Choosing Healthier Drinking Options In primary CarE (CHOICE) trial was a randomized controlled effectiveness trial of a novel intervention for primary care patients at high risk for AUDs. This report describes the conceptual and scientific foundation of the CHOICE model of care, critical elements of the CHOICE trial design consistent with the Template for Intervention Description and Replication (TIDieR), results of recruitment, and baseline characteristics of the enrolled sample. METHODS: The CHOICE intervention is a multi-contact, extended counseling intervention, based on the Chronic Care Model, shared decision-making, motivational interviewing, and evidence-based options for managing AUDs, designed to be practical in primary care. Outpatients who received care at 3 Veterans Affairs primary care sites in the Pacific Northwest and reported frequent heavy drinking (≥4 drinks/day for women; ≥5 for men) were recruited (2011-2014) into a trial in which half of the participants would be offered additional alcohol-related care from a nurse. CHOICE nurses offered 12 months of patient-centered care, including proactive outreach and engagement, repeated brief motivational interventions, monitoring with and without alcohol biomarkers, medications for AUDs, and/or specialty alcohol treatment as appropriate and per patient preference. A CHOICE nurse practitioner was available to prescribe medications for AUDs. RESULTS: A total of 304 patients consented to participate in the CHOICE trial. Among consenting participants, 90% were men, the mean age was 51 (range 22-75), and most met DSM-IV criteria for alcohol abuse (14%) or dependence (59%). Many participants also screened positive for tobacco use (44%), depression (45%), anxiety disorders (30-41%) and non-tobacco drug use disorders (19%). At baseline, participants had a median AUDIT score of 18 [Interquartile range (IQR) 14-24] and a median readiness to change drinking score of 5 (IQR 2.75-6.25) on a 1-10 Likert scale. CONCLUSION: The CHOICE trial tested a patient-centered intervention for AUDs and recruited primary care patients at high risk for AUDs, with a spectrum of severity, co-morbidity, and readiness to change drinking. Trial registration The trial is registered at clinicaltrial.gov (NCT01400581).

Predictive validity of clinical AUDIT-C alcohol screening scores and changes in scores for three objective alcohol-related outcomes in a Veterans Affairs population.

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.

Changes in Patient-Reported Alcohol-Related Advice Following Veterans Health Administration Implementation of Brief Alcohol Interventions.

OBJECTIVE: Brief alcohol interventions are recommended for primary care patients who screen positive for alcohol misuse, but implementation is challenging. The U.S. Veterans Health Administration (Veterans Affairs [VA]) implemented brief interventions for patients with alcohol misuse in 2008, and rates of brief interventions documented in the electronic medical record increased from 24% to 78% (2008-2011). This study examined whether an independent measure of brief interventions-patient-reported alcohol-related advice-also increased among VA outpatients who screened positive for alcohol misuse on a mailed survey. METHOD: This retrospective cross-sectional study included VA outpatient respondents to the VA's Survey of Healthcare Experiences of Patients (SHEP; 2007-2011) who reported past-year alcohol use and answered a question about alcohol-related advice. Alcohol-related advice was defined as a report of past-year advice from a VA clinician to abstain from or reduce drinking. The adjusted prevalence of alcoholrelated advice among patients who screened positive for alcohol misuse (SHEP AUDIT-C ≥ 5) was estimated for each year. RESULTS: Among patients with alcohol misuse (n = 61,843), the adjusted prevalence of alcohol-related advice increased from 40.4% (95% CI [39.3%, 41.5%]) in 2007 to 55.5% (95% CI [53.3%, 57.8%]) in 2011. Rates of alcoholrelated advice increased significantly each year except the last. CONCLUSIONS: The VA's efforts to implement brief interventions were associated with increased patient-reported alcohol-related advice over time, with a majority of patients with alcohol misuse reporting its receipt. Other systems considering similar approaches to implementation may benefit from collecting patient-reported measures of brief interventions for an additional perspective on implementation.

Excellent Patient Care Processes in Poor Hospitals? Why Hospital-Level and Patient-Level Care Quality-Outcome Relationships Can Differ.

Studies finding weak or nonexistent relationships between hospital performance on providing recommended care and hospital-level clinical outcomes raise questions about the value and validity of process of care performance measures. Such findings may cause clinicians to question the effectiveness of the care process presumably captured by the performance measure. However, one cannot infer from hospital-level results whether patients who received the specified care had comparable, worse or superior outcomes relative to patients not receiving that care. To make such an inference has been labeled the "ecological fallacy," an error that is well known among epidemiologists and sociologists, but less so among health care researchers and policy makers. We discuss such inappropriate inferences in the health care performance measurement field and illustrate how and why process measure-outcome relationships can differ at the patient and hospital levels. We also offer recommendations for appropriate multilevel analyses to evaluate process measure-outcome relationships at the patient and hospital levels and for a more effective role for performance measure bodies and research funding organizations in encouraging such multilevel analyses.

Improving fatigue and depression in individuals with multiple sclerosis using telephone-administered physical activity counseling.

OBJECTIVE: To evaluate the impact of a physical activity intervention consisting of telephone counseling with home-based monitoring to improve fatigue and depression in individuals with multiple sclerosis (MS). METHOD: Single-blind randomized controlled trial. Sixty-four individuals with MS received either telephone counseling (N = 31), or self-directed physical activity education (N = 33). The education condition (EC) consisted of advice to increase physical activity and a DVD with examples of in-home exercises for multiple physical ability levels. The telephone counseling condition (TC) included EC as well as mailed graphic feedback, 6 telephone counseling sessions using principles of motivational interviewing, and telehealth home monitoring to track progress on physical activity goals. Booster sessions were provided when participants indicated they did not meet their goals. Assessment was conducted at baseline, 3-month, and 6-month follow-up. RESULTS: TC participants reported significantly reduced fatigue (d = -.70), reduced depression (d = -.72) and increased physical activity (d = .92) relative to EC participants. Of individuals receiving TC, 33.3% experienced clinically significant improvement in fatigue (vs. 18.2% in EC) and 53.3% experienced clinically significant improvement in depression (vs. 9.1% in EC). Improvements in physical activity mediated improvements in fatigue with a similar trend for depression. TC was highly feasible (participants completed 99.5% of schedule telephone sessions) and well tolerated (100% rated it highly successful). CONCLUSION: Telephone-based counseling with home monitoring is a promising modality to improve physical activity and treat fatigue and depression.

Recommendations for the Design and Analysis of Treatment Trials for Alcohol Use Disorders.

BACKGROUND: Over the past 60 years, the view that "alcoholism" is a disease for which the only acceptable goal of treatment is abstinence has given way to the recognition that alcohol use disorders (AUDs) occur on a continuum of severity, for which a variety of treatment options are appropriate. However, because the available treatments for AUDs are not effective for everyone, more research is needed to develop novel and more efficacious treatments to address the range of AUD severity in diverse populations. Here we offer recommendations for the design and analysis of alcohol treatment trials, with a specific focus on the careful conduct of randomized clinical trials of medications and nonpharmacological interventions for AUDs. METHODS: This paper provides a narrative review of the quality of published clinical trials and recommendations for the optimal design and analysis of treatment trials for AUDs. RESULTS: Despite considerable improvements in the design of alcohol clinical trials over the past 2 decades, many studies of AUD treatments have used faulty design features and statistical methods that are known to produce biased estimates of treatment efficacy. CONCLUSIONS: The published statistical and methodological literatures provide clear guidance on methods to improve clinical trial design and analysis. Consistent use of state-of-the-art design features and analytic approaches will enhance the internal and external validity of treatment trials for AUDs across the spectrum of severity. The ultimate result of this attention to methodological rigor is that better treatment options will be identified for patients with an AUD.

Guidelines for the Reporting of Treatment Trials for Alcohol Use Disorders.

BACKGROUND: The primary goals in conducting clinical trials of treatments for alcohol use disorders (AUDs) are to identify efficacious treatments and determine which treatments are most efficacious for which patients. Accurate reporting of study design features and results is imperative to enable readers of research reports to evaluate to what extent a study has achieved these goals. Guidance on quality of clinical trial reporting has evolved substantially over the past 2 decades, primarily through the publication and widespread adoption of the Consolidated Standards of Reporting Trials statement. However, there is room to improve the adoption of those standards in reporting the design and findings of treatment trials for AUD. METHODS: This paper provides a narrative review of guidance on reporting quality in AUD treatment trials. RESULTS: Despite improvements in the reporting of results of treatment trials for AUD over the past 2 decades, many published reports provide insufficient information on design or methods. CONCLUSIONS: The reporting of alcohol treatment trial design, analysis, and results requires improvement in 4 primary areas: (i) trial registration, (ii) procedures for recruitment and retention, (iii) procedures for randomization and intervention design considerations, and (iv) statistical methods used to assess treatment efficacy. Improvements in these areas and the adoption of reporting standards by authors, reviewers, and editors are critical to an accurate assessment of the reliability and validity of treatment effects. Continued developments in this area are needed to move AUD treatment research forward via systematic reviews and meta-analyses that maximize the utility of completed studies.

Comparison of provider-documented and patient-reported brief intervention for unhealthy alcohol use in VA outpatients.

BACKGROUND: Performance measures for brief alcohol interventions (BIs) are currently based on provider documentation of BI. However, provider documentation may not be a reliable measure of whether or not patients are offered clinically meaningful BIs. In particular, BI documented with clinical decision support in an electronic medical record (EMR) could appear identical irrespective of the quality of BI provided. We hypothesized that differences in how BI was implemented across health systems could lead to differences in the proportion of documented BI recalled and reported by patients across health systems. METHODS: Male outpatients with unhealthy alcohol use identified by confidential satisfaction surveys (2009-2012) were assessed for whether they reported receiving BI in the past year (patient-reported BI) and whether they had BI documented in the EMR during the same period (documented BI). We evaluated and compared the prevalence of documented BI to patient-reported BI across 21 VA networks to determine whether documented BI had a variable association with patient-reported BI across the networks. RESULTS: Of 9896 eligible male outpatients with unhealthy alcohol use, 59.0% (95% CI 57.4-60.5%) reported BI (50.4-64.9% across networks) and 37.4% (95% CI 36.0-38.9%) had BI documented in the EMR (28.0-44.2% across networks). Overall, 72.9% (95% CI 70.8-75.5%) of patients with documented BI also reported BI. The association between documented BI and patient-reported BI did not vary across VA networks in adjusted logistic regression models. CONCLUSIONS: Performance measures of BI that rely on provider documentation in EMRs appear comparable to patient report for comparing care across VA networks.