Understanding the characteristics of Latino individuals with first-time DUI offenses to facilitate effective interventions.

Literature shows that Latinos who drink are more likely to experience alcohol-related consequences and less likely to seek care for alcohol misuse than Whites. We aim to understand characteristics, consumption patterns, and openness to treatment among Latino first-time offenders driving under the influence. Latino participants were significantly younger (29.0 years) than non-Latinos (37.7 years). In adjusted models, Latino participants were significantly more likely than non-Latinos to binge drink, but there were no significant group differences in amount of alcohol consumed in a typical week. There was no significant difference in incidence of alcohol-related consequences, readiness to change drinking, and driving behaviors in this sample.

Causal inference under interference with prognostic scores for dynamic group therapy studies.

Group therapy is a common treatment modality for behavioral health conditions. Patients often enter and exit groups on an ongoing basis, leading to dynamic therapy groups. Examining the effect of high versus low session attendance on patient outcomes is a research question of interest. However, there are several challenges to identifying causal effects in this setting, including the lack of randomization, interference among patients, and the interrelatedness of patient participation. Dynamic therapy groups motivate a unique causal inference scenario, as the treatment statuses are completely defined by the patient attendance record for the therapy session, which is also the structure inducing interference. We adopt the Rubin causal model framework to define the causal effect of high versus low session attendance of group therapy at both the individual patient and peer levels. We propose a strategy to identify individual, peer, and total effects of high attendance versus low attendance on patient outcomes by the prognostic score stratification. We examine performance of our approach via simulation and apply it to data from a group cognitive behavioral therapy trial for treating depression among patients in a substance use disorders treatment setting.

Appropriate analyses of bimodal substance use frequency outcomes: a mixture model approach.

Background: In addiction research, outcome measures are often characterized by bimodal distributions. One mode can be for individuals with low substance use and the other mode for individuals with high substance use. Applying standard statistical procedures to bimodal data may result in invalid inference. Mixture models are appropriate for bimodal data because they assume that the sampled population is composed of several underlying subpopulations.Objectives: To introduce a novel mixture modeling approach to analyze bimodal substance use frequency data.Methods: We reviewed existing models used to analyze substance use frequency outcomes and developed multiple alternative variants of a finite mixture model. We applied all methods to data from a randomized controlled study in which 30-day alcohol abstinence was the primary outcome. Study data included 73 individuals (38 men and 35 women). Models were implemented in the software packages SAS, Stata, and Stan.Results: Shortcomings of existing approaches include: 1) inability to model outcomes with multiple modes, 2) invalid statistical inferences, including anti-conservative p-values, 3) sensitivity of results to the arbitrary choice to model days of substance use versus days of substance abstention, and 4) generation of predictions outside the range of common substance use frequency outcomes. Our mixture model variants avoided all of these shortcomings.Conclusions: Standard models of substance use frequency outcomes can be problematic, sometimes overstating treatment effectiveness. The mixture models developed improve the analysis of bimodal substance use frequency.

Longitudinal effects of social network changes on drinking outcomes for individuals with a first-time DUI.

BACKGROUND: Social networks are important predictors of alcohol-related outcomes, especially among those with a DUI where riskier social networks are associated with increased risk of drinking and driving. Social networks are increasingly a target for intervention; however, no studies have examined and measured whether longitudinal changes in social networks are associated with reductions in impaired driving. OBJECTIVE: The current study first examines longitudinal changes in social networks among participants receiving services following a first-time DUI, and then examines the association between network change and drinking outcomes at 4- and 10-month follow-up. METHODS: The study surveyed a subsample of participants (N = 94) enrolled in a clinical trial of individuals randomized to cognitive behavioral therapy (CBT) or usual care (UC) on an iPad using EgoWeb 2.0-an egocentric social network data collection software-about pre-DUI and post-DUI networks and their short- and long-term drinking behaviors. RESULTS: Participants were 65% male, 48% Hispanic, and an average of 32.5 years old. Overall, participants significantly reduced the proportion of network members with whom they drank from 0.41 to 0.30 (p = .001) and with whom they drank more alcohol than they wanted to from 0.15 to 0.07 (p = .0001) from two weeks prior to the DUI (measured at baseline) to 4-month follow-up. Furthermore, decreases in proportion of drinking partners over time were associated with reduced drinks per week, self-reported driving after drinking, and intentions to drive after drinking at 4-month follow-up. Participants who reported decreases in proportion of drinking partners also reported significantly less binge drinking at 10-month follow-up. Finally, increases in emotional support were associated with decreases in binge drinking at 4-month follow-up. The study found no differences in the changes in composition of networks between CBT and UC groups. CONCLUSIONS: These results suggest that individuals receiving services in DUI programs significantly reduced risky network members over time and that these social network changes were associated with reduced drinking and other indicators of risk for DUI recidivism. Clinical interventions that target reductions in risky network members may improve outcomes for those enrolled in a DUI program.

Social Networks of Clients in First-Time DUI Programs.

OBJECTIVE: Social networks play an important role in the development of and recovery from problem drinking behaviors; however, few studies have measured the social networks of individuals convicted of driving under the influence (DUI) or assessed the relationship between social network characteristics and risk for DUI relapse and recidivism. The goal of this study is to describe the social network characteristics of a first-time DUI population in the 2 weeks before the DUI incident; examine demographic differences in social network characteristics by age, ethnicity, and gender; and assess the relationship between social network characteristics and risk factors for DUI. METHOD: We collected personal (egocentric) social network survey data from 94 participants (65% male) enrolled in a randomized clinical trial comparing the effects of cognitive behavioral therapy with usual care for individuals convicted of a first-time DUI. Multivariate models were used to assess the relationship between pre-DUI personal network characteristics and risk factors for DUI measured at baseline interview. RESULTS: Results indicate that the proportion of drinking partners in one's personal network was positively associated with drinks per week, binge drinking, alcohol use, marijuana use, and alcohol-related consequences. Several dimensions of personal network support were inversely associated with risk factors for DUI. CONCLUSIONS: The pre-DUI composition of personal networks has a strong relationship to baseline risk factors for DUI; networks composed of more risky individuals (e.g., drinking partners) were associated with greater substance use and drinking and driving behaviors. Networks with greater levels of social support were associated with lower likelihood of self-reported driving after drinking and intentions to drive after drinking. Interventions that target positive and negative aspects of personal networks may enhance clinical treatments.

Group Cohesion and Climate in Cognitive Behavioral Therapy for Individuals with a First-Time DUI.

Few studies have examined group cohesion and climate in the substance use disorder treatment literature. We examined whether group cohesion and climate are associated with increased self-efficacy outcomes and reduced drinks per week, binge drinking and DUI behaviors, in a sample of individuals with a first-time DUI receiving either cognitive behavioral therapy (CBT) or usual care. Additionally, we examined whether CBT moderates these relationships. Group measures and drinking outcomes were not significantly associated. This study is the first to provide an in-depth analysis on group processes in DUI settings, and as such, provides important insights into how group processes may differ in a mandated DUI context.

Study design to evaluate a group-based therapy for support persons of adults on buprenorphine/naloxone.

BACKGROUND: Opioid use disorders (OUDs) have devastating effects on individuals, families, and communities. While medication treatments for OUD save lives and are increasingly utilized, rates of treatment dropout are very high. In addition, most existing medication treatments for OUD may often neglect the impact of untreated OUD on relationships and ignore the potential role support persons (SPs) could have on encouraging long-term recovery, which can also impact patient treatment retention. METHODS/DESIGN: The current study adapts Community Reinforcement and Family Training (CRAFT) for use with SPs (family member, spouse or friend) of patients using buprenorphine/naloxone (buprenorphine) in an outpatient community clinic setting. The study will evaluate whether the adapted intervention, also known as integrating support persons into recovery (INSPIRE), is effective in increasing patient retention on buprenorphine when compared to usual care. We will utilize a two-group randomized design where patients starting or restarting buprenorphine will be screened for support person status and recruited with their support person if eligible. Support persons will be randomly assigned to the INSPIRE intervention, which will consist of 10 rolling group sessions led by two facilitators. Patients and SPs will each be assessed at baseline, 3 months post-baseline, and 12 months post-baseline. Patient electronic medical record data will be collected at six and 12 months post-baseline. We will examine mechanisms of intervention effectiveness and also conduct pre/post-implementation surveys with clinic staff to assess issues that would affect sustainability. DISCUSSION: Incorporating the patient's support system may be an important way to improve treatment retention in medication treatments for OUD. If SPs can serve to support patient retention, this study would significantly advance work to help support the delivery of effective treatments that prevent the devastating consequences associated with OUD. Trial registration This study was registered with ClinicalTrials.gov, NCT04239235. Registered 27 January 2020, https://clinicaltrials.gov/ct2/show/NCT04239235 .

Shifting From Passive Quality Reporting to Active Nudging to Influence Consumer Choice of Health Plan.

Comparative quality information on health plan and provider performance is increasingly available in the form of quality report cards, but consumers rarely make use of these passively provided decision support tools. In 2012-2013, the Centers for Medicare & Medicaid Services (CMS) initiated quality-based nudges designed to encourage beneficiaries to move into higher quality Medicare Advantage (MA) plans. We assess the impacts of CMS' targeted quality-based nudges with longitudinal analysis of 2009-2014 MA plan enrollment trends. Nudges are associated with 17% reductions in enrollment in the lowest-performing plans and 3% increases in enrollment in the highest performing plans (annually, p < .01 for both), occurring at the time of nudge implementation and relative to trends for plans with moderate performance that were not targeted by nudges. These findings suggest that quality-based nudges can successfully steer consumers into higher quality plans and provide opportunities for purchasers and payers to increase consumers' use of quality information.

Randomized Clinical Trial Examining Cognitive Behavioral Therapy for Individuals With a First-Time DUI Offense.

BACKGROUND: Driving under the influence (DUI) programs are a unique setting to reduce disparities in treatment access to those who may not otherwise access treatment. Providing evidence-based therapy in these programs may help prevent DUI recidivism. METHODS: We conducted a randomized clinical trial of 312 participants enrolled in 1 of 3 DUI programs in California. Participants were 21 and older with a first-time DUI offense who screened positive for at-risk drinking in the past year. Participants were randomly assigned to a 12-session manualized cognitive behavioral therapy (CBT) or usual care (UC) group and then surveyed 4 and 10 months later. We conducted intent-to-treat analyses to test the hypothesis that participants receiving CBT would report reduced impaired driving, alcohol consumption (drinks per week, abstinence, and binge drinking), and alcohol-related negative consequences. We also explored whether race/ethnicity and gender moderated CBT findings. RESULTS: Participants were 72.3% male and 51.7% Hispanic, with an average age of 33.2 (SD = 12.4). Relative to UC, participants receiving CBT had lower odds of driving after drinking at the 4- and 10-month follow-ups compared to participants receiving UC (odds ratio [OR] = 0.37, p = 0.032, and OR = 0.29, p = 0.065, respectively). This intervention effect was more pronounced for females at 10-month follow-up. The remaining 4 outcomes did not significantly differ between UC versus CBT at 4- and 10-month follow-ups. Participants in both UC and CBT reported significant within-group reductions in 2 of 5 outcomes, binge drinking and alcohol-related consequences, at 10-month follow-up (p < 0.001). CONCLUSIONS: In the short-term, individuals receiving CBT reported significantly lower rates of repeated DUI than individuals receiving UC, which may suggest that learning cognitive behavioral strategies to prevent impaired driving may be useful in achieving short-term reductions in impaired driving.

Rates and Impact of Adherence to Recommended Care for Unhealthy Alcohol Use.

BACKGROUND: Unhealthy alcohol use is a major worldwide health problem. Yet few studies have assessed provider adherence to the alcohol-related care recommended in clinical practice guidelines, nor links between adherence to recommended care and outcomes. OBJECTIVES: To describe quality of care for unhealthy alcohol use and its impacts on drinking behavior RESEARCH DESIGN: Prospective observational cohort study of quality of alcohol care for the population of patients screening positive for unhealthy alcohol use in a large Veterans Affairs health system. PARTICIPANTS: A total of 719 patients who screened positive for unhealthy alcohol use at one of 11 primary care practices and who completed baseline and 6-month telephone interviews. MAIN MEASURES: Using administrative encounter and medical record data, we assessed three composite and 21 individual process-based measures of care delivered across primary and specialty care settings. We assessed self-reported daily alcohol use using telephone interviews at baseline and 6-month follow-up. KEY RESULTS: The median proportion of patients who received recommended care across measures was 32.8% (range < 1% for initiating pharmacotherapy to 93% for depression screening). There was negligible change in drinking for the study population between baseline and 6 months. In covariate-adjusted analyses, no composites were significantly associated with changes in heavy drinking days or drinks per week, and just one of nine individual measures tested was significantly associated. In a subsample of patients drinking above recommended weekly limits prior to screening, two of nine individual measures were significantly associated. CONCLUSIONS: This study shows wide variability in receipt of recommended care for unhealthy alcohol use. Receipt of recommended interventions for reducing drinking was frequently not associated with decreased drinking. Results suggest deficits in provision of comprehensive alcohol care and in understanding how to improve population-based drinking outcomes.

Sample selection in the face of design constraints: Use of clustering to define sample strata for qualitative research.

OBJECTIVE: To sample 40 physician organizations stratified on the basis of longitudinal cost of care measures for qualitative interviews in order to describe the range of care delivery structures and processes that are being deployed to influence the total costs of caring for patients. DATA SOURCES: Three years of physician organization-level total cost of care data (n = 156 in California) from the Integrated Healthcare Association's value-based pay-for-performance program. STUDY DESIGN: We fit total cost of care data using mixture and K-means clustering algorithms to segment the population of physician organizations into sampling strata based on 3-year cost trajectories (ie, cost curves). PRINCIPAL FINDINGS: A mixture of multivariate normal distributions can classify physician organization cost curves into clusters defined by total cost level, shape, and within-cluster variation. K-means clustering does not accommodate differing levels of within-cluster variation and resulted in more clusters being allocated to unstable cost curves. A mixture of regressions approach focuses overly on anomalous trajectories and is sensitive to model coding. CONCLUSIONS: Statistical clustering can be used to form sampling strata when longitudinal measures are of primary interest. Many clustering algorithms are available; the choice of the clustering algorithm can strongly impact the resulting strata because various algorithms focus on different aspects of the observed data.

Reducing disparities requires multiple strategies.

Disparities in care are a complex issue requiring multiple strategies to solve, including approaches to improve the measurement of quality and reporting stratified performance estimates.

Adjusting Medicare Advantage star ratings for socioeconomic status and disability.

OBJECTIVES: Studies have identified potential unintended effects of not adjusting clinical performance measures in value-based purchasing programs for socioeconomic status (SES) factors. We examine the impact of SES and disability adjustments on Medicare Advantage (MA) plans' and prescription drug plans' (PDPs') contract star ratings. These analyses informed the development of the Categorical Adjustment Index (CAI), which CMS implemented with the 2017 star ratings. STUDY DESIGN: Retrospective analyses of MA and PDP performance using 2012 Medicare beneficiary-level characteristics and performance data from the Star Rating Program. METHODS: We modeled within-contract associations of beneficiary SES (Medicaid and Medicare dual eligibility [DE] or receipt of a low-income subsidy [LIS]) and disability with performance on 16 clinical measures. We estimated variability in contract-level DE/LIS and disability disparities using mixed-effects regression models. We simulated the impact of applying the CAI to adjust star ratings for DE/LIS and disability to construct the 2017 star ratings. RESULTS: DE/LIS was negatively associated with performance for 12 of 16 measures and positively associated for 2 of 16 measures. Disability was negatively associated with performance for 11 of 15 measures and positively associated for 3 of 15 measures. Adjusting star ratings using the CAI resulted in half-star rating increases for 8.5% of MA and 33.3% of PDP contracts that exceeded 50% DE/LIS beneficiaries. CONCLUSIONS: Increases in star ratings following adjustment of clinical performance for SES and disability using the CAI focused on contracts with higher percentages of DE/LIS beneficiaries. Adjustment for enrollee characteristics may improve the accuracy of quality measurement and remove incentives for providers to avoid caring for more challenging patient populations.

Differences in alcohol cognitions, consumption, and consequences among first-time DUI offenders who co-use alcohol and marijuana.

BACKGROUND: A significant portion of alcohol-related DUI offenders engage in co-use of alcohol and marijuana (AM). Given expanding marijuana legalization and the impaired driving risks associated with co-use, it is of increased importance to understand how characteristics of AM co-users compare to those who use alcohol only (AO) in order to inform DUI interventions and prevent recidivism. METHODS: Participants were 277 first-time DUI offenders enrolled in a first-time DUI offender program across three locations. Using well-established measures, we evaluated differences in alcohol-related cognitions (positive expectancies and self-efficacy), frequency and quantity of alcohol consumption, and alcohol-related consequences between AO users and AM co-users by running a series of multivariate generalized linear models. RESULTS: Compared to AO users, AM co-users reported lower self-efficacy to achieve abstinence and avoid DUI. Differences in abstinence self-efficacy largely explain higher relative rates of average and peak drinking quantity and higher odds of binge drinking among AM co-user. Despite lower self-efficacy and higher drinking quantity, there were no significant differences between AM and AO-users on alcohol-related consequences and past month reports of drinking and driving. CONCLUSIONS: Our results provide preliminary evidence that DUI offenders who co-use alcohol and marijuana have higher alcohol use and lower self-efficacy than AO-users, and long-term consequences for this group should be monitored in future research. DUI programs may screen and identify co-users and consider tailoring their interventions to build self-efficacy to address the risks associated with AM co-use uniquely.

Delivering Clinical Practice Guideline-Concordant Care for PTSD and Major Depression in Military Treatment Facilities.

Providing accessible, high-quality care for psychological health (PH) conditions, such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD), is important to maintaining a healthy, mission-ready force. It is unclear whether the current system of care meets the needs of service members with PTSD or MDD, and little is known about the barriers to delivering guideline-concordant care. RAND used existing provider workforce data, a provider survey, and key informant interviews to (1) provide an overview of the PH workforce at military treatment facilities (MTFs), (2) examine the extent to which care for PTSD and MDD in military treatment facilities is consistent with Department of Veterans Affairs/Department of Defense clinical practice guidelines, and (3) identify facilitators and barriers to providing this care. This study provides a comprehensive assessment of providers' perspectives on their capacity to deliver PH care within MTFs and presents detailed results by provider type and service branch. Findings suggest that most providers report using guideline-concordant psychotherapies, but use varied by provider type. The majority of providers reported receiving at least minimal training and supervision in at least one recommended psychotherapy for PTSD and for MDD. Still, more than one-quarter of providers reported that limits on travel and lack of protected time in their schedule affected their ability to access additional professional training. Finally, most providers reported routinely screening patients for PTSD and MDD with a validated screening instrument, but fewer providers reported using a validated screening instrument to monitor treatment progress.

Quality of Care for PTSD and Depression in the Military Health System: Final Report.

The U.S. Department of Defense (DoD) strives to maintain a physically and psychologically healthy, mission-ready force, and the care provided by the Military Health System (MHS) is critical to meeting this goal. Attention has been directed to ensuring the quality and availability of programs and services for posttraumatic stress disorder (PTSD) and depression. This study is a comprehensive assessment of the quality of care delivered by the MHS in 2013-2014 for over 38,000 active-component service members with PTSD or depression. The assessment includes performance on 30 quality measures to evaluate the receipt of recommended assessments and treatments. These measures draw on multiple data sources including administrative encounter data, medical record review data, and patient self-reported outcome monitoring data. The assessment identified strengths and areas for improvement for the MHS. In particular, the MHS excels at screening for suicide risk and substance use, but rates of appropriate follow-up for service members with suicide risk are lower. Most service members received at least some psychotherapy, but less than half of psychotherapy delivered was evidence-based. In analyses focused on Army soldiers, outcome monitoring increased notably over time, yet preliminary analyses suggest that more work is needed to ensure that services are effective in reducing symptoms. When comparing performance between 2012-2013 and 2013-2014, most measures demonstrated slight improvement, but targeted efforts will be needed to support further improvements. RAND provides recommendations for strategies to improve the quality of care delivered for these conditions.

Bayesian models for semicontinuous outcomes in rolling admission therapy groups.

Alcohol and other drug abuse are frequently treated in a group therapy setting. If participants are allowed to enroll in therapy on a rolling basis, irregular patterns of participant overlap can induce complex correlations of participant outcomes. Previous work has accounted for common session attendance by modeling random effects for each therapy session, which map to participant outcomes via a multiple membership construction when modeling normally distributed outcome measures. We build on this earlier work by extending the models to semicontinuous outcomes, or outcomes that are a mixture of continuous and discrete distributions. This results in multivariate session effects, for which we allow temporal dependencies of various orders. We illustrate our methods using data from a group-based intervention to treat substance abuse and depression, focusing on the outcome of average number of drinks per day. Alcohol and other drug abuse are frequently treated in a group therapy setting. If 2 clients attend the some of the same sessions, we might expect that-on average-their posttreatment outcomes would be more similar than if they had not attended any sessions together. Hence, if participants are allowed to enroll in therapy on a rolling basis, irregular patterns of session attendance can induce complex relationships between participant outcomes. Statistical methods have been developed previously to account for rolling admission group therapy when the outcomes are normally distributed. In the case of alcohol and other drug use interventions, however, a substantial fraction of participants often report zero use after treatment. We extend previous work to build models that accommodate semicontinuous outcomes, which are a mixture of continuous and discrete distributions, for such situations. We find that modern Bayesian statistical methods and software allow users to efficiently estimate nonstandard models such as these. We illustrate our methods using data from a group-based intervention to treat substance abuse and depression, focusing on the outcome of average number of drinks per day. We find that the intervention is associated with a drop in the probability of any drinking, but find no evidence of a change in the amount of drinking, conditional on some drinking. (PsycINFO Database Record

Medicare Advantage and Fee-for-Service Performance on Clinical Quality and Patient Experience Measures: Comparisons from Three Large States.

OBJECTIVE: To compare performance between Medicare Advantage (MA) and Fee-for-Service (FFS) Medicare during a time of policy changes affecting both programs. DATA SOURCES/STUDY SETTING: Performance data for 16 clinical quality measures and 6 patient experience measures for 9.9 million beneficiaries living in California, New York, and Florida. STUDY DESIGN: We compared MA and FFS performance overall, by plan type, and within service areas associated with contracts between CMS and MA organizations. Case mix-adjusted analyses (for measures not typically adjusted) were used to explore the effect of case mix on MA/FFS differences. DATA COLLECTION/EXTRACTION METHODS: Performance measures were submitted by MA organizations, obtained from the nationwide fielding of the Medicare Consumer Assessment of Healthcare Providers and Systems (MCAHPS) Survey, or derived from claims. PRINCIPAL FINDINGS: Overall, MA outperformed FFS on all 16 clinical quality measures. Differences were large for HEDIS measures and small for Part D measures and remained after case mix adjustment. MA enrollees reported better experiences overall, but FFS beneficiaries reported better access to care. Relative to FFS, performance gaps were much wider for HMOs than PPOs. Excluding HEDIS measures, MA/FFS differences were much smaller in contract-level comparisons. CONCLUSIONS: Medicare Advantage/Fee-for-Service differences are often large but vary in important ways across types of measures and contracts.

What Role Does Efficiency Play in Understanding the Relationship Between Cost and Quality in Physician Organizations?

BACKGROUND: The belief that there is inefficiency, or the potential to improve patient health at current levels of spending, is driving the push for greater value in health care. Previous studies demonstrate overuse of a narrow set of services, suggesting provider inefficiency, but existing studies neither quantify inefficiency more broadly nor assess its variation across physician organizations (POs). DATA AND METHODS: We used data on quality of care and total cost of care from 129 California POs participating in a statewide value-based pay-for-performance program. We estimated a production function with quality as the output and cost as the input, using a stochastic frontier model, to develop a measure of relative efficiency for each PO. To validate the efficiency measure, we examined correlations of PO efficiency estimates with indicators representing overuse of services. RESULTS: The estimated production function showed that PO quality was positively associated with costs, although there were diminishing marginal returns to spending. A certain minimum level of spending was associated with high quality even among efficient POs. Most strikingly, however, POs had substantial variation in efficiency, producing widely differing levels of quality for the same cost. CONCLUSIONS: Differences among POs in the efficiency with which they produce quality suggest opportunities for improvements in care delivery that increase quality without increasing spending.