Associations Between a Primary Care-Delivered Alcohol-Related Brief Intervention and Subsequent Opioid-Related Outcomes.

OBJECTIVE: The co-occurrence of unhealthy alcohol use and opioid misuse is high and associated with increased rates of overdose, emergency health care utilization, and death. The current study examined whether receipt of an alcohol-related brief intervention is associated with reduced risk of negative downstream opioid-related outcomes. METHODS: This retrospective cohort study included all VISN-6 Veterans Affairs (VA) patients with Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) screening results (N=492,748) from 2014 to 2019. Logistic regression was used to examine the association between documentation of an alcohol-related brief intervention and probability of a new 1) opioid prescription, 2) opioid use disorder (OUD) diagnosis, or 3) opioid-related hospitalization in the following year, controlling for demographic and clinical covariates. RESULTS: Of the veterans, 13% (N=63,804) had "positive" AUDIT-C screen results. Of those, 72% (N=46,216) had a documented alcohol-related brief intervention. Within 1 year, 8.5% (N=5,430) had a new opioid prescription, 1.1% (N=698) had a new OUD diagnosis, and 0.8% (N=499) had a new opioid-related hospitalization. In adjusted models, veterans with positive AUDIT-C screen results who did not receive an alcohol-related brief intervention had higher odds of new opioid prescriptions (adjusted odds ratio [OR]=1.10, 95% CI=1.03-1.17) and new OUD diagnoses (adjusted OR=1.19, 95% CI=1.02-1.40), while new opioid-related hospitalizations (adjusted OR=1.19, 95% CI=0.99-1.44) were higher although not statistically significant. Removal of medications for OUD (MOUD) did not impact associations. All outcomes were significantly associated with an alcohol-related brief intervention in unadjusted models. CONCLUSIONS: The VA's standard alcohol-related brief intervention is associated with subsequent lower odds of a new opioid prescription or a new OUD diagnosis. Results suggest a reduction in a cascade of new opioid-related outcomes from prescriptions through hospitalizations.

Association between patient-reported social and behavioral risks and health care costs in high-risk Veterans health administration patients.

OBJECTIVE: Social risks complicate patients' ability to manage their conditions and access healthcare, but their association with health expenditures is not well established. To identify patient-reported social risk, behavioral, and health factors associated with health expenditures in Veterans Affairs (VA) patients at high risk for hospitalization or death. DATA SOURCES, STUDY SETTING, AND STUDY DESIGN: Prospective cohort study among high-risk Veterans obtaining VA care. Patient-reported social risk, function, and other measures derived from a 2018 survey sent to 10,000 VA patients were linked to clinical and demographic characteristics extracted from VA data. Response-weighted generalized linear and marginalized two-part models were used to examine VA expenditures (total, outpatient, medication, inpatient) 1 year after survey completion in adjusted models. PRINCIPAL FINDINGS: Among 4680 survey respondents, the average age was 70.9 years, 6.3% were female, 16.7% were African American, 20% had body mass index ≥35, 42.4% had difficulty with two or more basic or instrumental activities of daily living, 19.3% reported transportation barriers, 12.5% reported medication insecurity and 21.8% reported food insecurity. Medication insecurity was associated with lower outpatient expenditures (-$1859.51 per patient per year, 95% confidence interval [CI]: -3200.77 to -518.25) and lower total expenditures (-$4304.99 per patient per year, 95% CI: -7564.87 to -1045.10). Transportation barriers were negatively associated with medication expenditures (-$558.42, 95% CI: -1087.93 to -31.91). Patients with one functional impairment had higher outpatient expenditures ($2997.59 per patient year, 95% CI: 1185.81-4809.36) than patients without functional impairments. No social risks were associated with inpatient expenditures. CONCLUSIONS: In this study of VA patients at high risk for hospitalization and mortality, few social and functional measures were independently associated with the costs of VA care. Individuals with functional limitations and those with barriers to accessing medications and transportation may benefit from targeted interventions to ensure that they are receiving the services that they need.

Ready, set, go! The role of organizational readiness to predict adoption of a family caregiver training program using the Rogers' diffusion of innovation theory.

BACKGROUND: Caregivers FIRST is an evidence-based program addressing gaps in caregivers' skills. In 2020, the Veterans Health Administration Caregiver Support Program (CSP) nationally endorsed Caregivers FIRST, offering credit in leadership performance plans to encourage all VA medical centers (VAMCs) to implement locally. This study examines the association of organizational readiness with VAMC adoption of Caregivers FIRST. METHODS: In a cohort observational study, we surveyed CSP managers about their facilities' readiness to implement using the Organizational Readiness for Implementing Change (ORIC) instrument and compared change commitment and change efficacy domains among VAMCs "adopters" defined as delivering Caregivers FIRST within 1 year of the national announcement to those that did not ("non-adopters"). Within "adopters," we categorized time to adoption based on Rogers' diffusion of innovation theory including "innovators," "early adopters," "early majority," "late adopters," and "laggards." Organizational readiness and site characteristics (facility complexity, staffing levels, volume of applications for caregiver assistance services) were compared between "adopters," "non-adopters," and between time to adoption subcategories. Separate logistic regression models were used to assess whether ORIC and site characteristics were associated with early adoption among "adopters." RESULTS: Fifty-one of 63 (81%) VAMCs with CSP manager survey respondents adopted Caregivers FIRST during the first year. ORIC change commitment and efficacy were similar for "adopters" and "non-adopters." However, sites that adopted earlier (innovators and early adopters) had higher ORIC change commitment and efficacy scores than the rest of the "adopters." Logistic regression results indicated that higher ORIC change commitment (odds ratio [OR] = 2.57; 95% confidence interval [CI], 1.11-5.95) and ORIC change efficacy (OR = 2.60; 95% CI, 1.12-6.03) scores were associated with increased odds that a VAMC was an early adopter (categorized as an "innovator," "early adopter", or "early majority"). Site-level characteristics were not associated with Caregivers FIRST early adoption. CONCLUSIONS: To our knowledge, this study is the first to prospectively assess organizational readiness and the timing of subsequent program adoption. Early adoption was associated with higher ORIC change commitment and change efficacy and not site-level characteristics. These findings yield insights into the role of organizational readiness to accelerate program adoption. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03474380. Registered on March 22, 2018.

Informing a home time measure reflective of quality of life: A data driven investigation of time frames and settings of health care utilization.

OBJECTIVE: To evaluate short- and long-term measures of health care utilization-days in the emergency department (ED), inpatient (IP) care, and rehabilitation in a post-acute care (PAC) facility-to understand how home time (i.e., days alive and not in an acute or PAC setting) corresponds to quality of life (QoL). DATA SOURCES: Survey data on community-residing veterans combined with multipayer administrative data on health care utilization. STUDY DESIGN: VA or Medicare health care utilization, quantified as days of care received in the ED, IP, and PAC in the 6 and 18 months preceding survey completion, were used to predict seven QoL-related measures collected during the survey. Elastic net machine learning was used to construct models, with resulting regression coefficients used to develop a weighted utilization variable. This was then compared with an unweighted count of days with any utilization. PRINCIPAL FINDINGS: In the short term (6 months), PAC utilization emerged as the most salient predictor of decreased QoL, whereas no setting predominated in the long term (18 months). Results varied by outcome and time frame, with some protective effects observed. In the 6-month time frame, each weighted day of utilization was associated with a greater likelihood of activity of daily living deficits (0.5%, 95% CI: 0.1%-0.9%), as was the case with each unweighted day of utilization (0.6%, 95% CI: 0.3%-1.0%). The same was true in the 18-month time frame (for both weighted and unweighted, 0.1%, 95% CI: 0.0%-0.3%). Days of utilization were also significantly associated with greater rates of instrumental ADL deficits and fair/poor health, albeit not consistently across all models. Neither measure outperformed the other in direct comparisons. CONCLUSIONS: These results can provide guidance on how to measure home time using multipayer administrative data. While no setting predominated in the long term, all settings were significant predictors of QoL measures.

Association between patient-reported social, behavioral, and health factors and emergency department visits in high-risk VA patients.

RESEARCH OBJECTIVE: To identify patient-reported social risk, behavioral, and health factors associated with emergency department (ED) utilization in high-risk Veterans Affairs (VA) patients. DATA SOURCES: Patient survey, VA, Medicare data. STUDY DESIGN: Prospective cohort study using multivariable logistic regression to identify patient-reported factors associated with all-cause and ambulatory care sensitive condition (ACSC)-related ED visits among VA patients at high risk for hospitalization or death. DATA EXTRACTION METHODS: Patient-reported measures derived from a 2018 survey sent to 10,000 VA patients; clinical and demographic characteristics derived from VA data; ED visits derived from VA and Medicare claims. PRINCIPAL FINDINGS: Among 4680 survey respondents, 52.5% and 16.3% experienced an all-cause or ACSC-related ED visit in the following year, respectively. An ED visit was more likely among individuals with functional status limitations (6.0% points (Confidence Interval [CI] 0.017-0.103)) and transportation barriers (5.2% points [CI 0.005-0.099]). An ACSC-related ED visit was more likely among individuals with functional status limitations (3.2% points [CI 0.003-0.062]) and self-rated poorer health (7.4% points (CI 0.030-0.119) poor; 6.2% points (CI 0.029-0.096) fair; 4.1% points (CI 0.009-0.073) good; compared with excellent/very good). CONCLUSIONS: Patient-reported factors not present in most electronic health records were significantly associated with future ED visits in high-risk VA patients.

A Cluster Randomized Trial of a Family Health History Platform to Identify and Manage Patients at Increased Risk for Colorectal Cancer.

BACKGROUND: Obtaining comprehensive family health history (FHH) to inform colorectal cancer (CRC) risk management in primary care settings is challenging. OBJECTIVE: To examine the effectiveness of a patient-facing FHH platform to identify and manage patients at increased CRC risk. DESIGN: Two-site, two-arm, cluster-randomized, implementation-effectiveness trial with primary care providers (PCPs) randomized to immediate intervention versus wait-list control. PARTICIPANTS: PCPs treating patients at least one half-day per week; patients aged 40-64 with no medical conditions that increased CRC risk. INTERVENTIONS: Immediate-arm patients entered their FHH into a web-based platform that provided risk assessment and guideline-driven decision support; wait-list control patients did so 12 months later. MAIN MEASURES: McNemar's test examined differences between the platform and electronic medical record (EMR) in rates of increased risk documentation. General estimating equations using logistic regression models compared arms in risk-concordant provider actions and patient screening test completion. Referral for genetic consultation was analyzed descriptively. KEY RESULTS: Seventeen PCPs were randomized to each arm. Patients (n = 252 immediate, n = 253 control) averaged 51.4 (SD = 7.2) years, with 83% assigned male at birth, 58% White persons, and 33% Black persons. The percentage of patients identified as increased risk for CRC was greater with the platform (9.9%) versus EMR (5.2%), difference = 4.8% (95% CI: 2.6%, 6.9%), p < .0001. There was no difference in PCP risk-concordant action [odds ratio (OR) = 0.7, 95% CI (0.4, 1.2; p = 0.16)]. Among 177 patients with a risk-concordant screening test ordered, there was no difference in test completion, OR = 0.8 [0.5,1.3]; p = 0.36. Of 50 patients identified by the platform as increased risk, 78.6% immediate and 68.2% control patients received a recommendation for genetic consultation, of which only one in each arm had a referral placed. CONCLUSIONS: FHH tools could accurately assess and document the clinical needs of patients at increased risk for CRC. Barriers to acting on those recommendations warrant further exploration. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02247336 https://clinicaltrials.gov/ct2/show/NCT02247336.

Identifying Family and Unpaid Caregivers in Electronic Health Records: Descriptive Analysis.

BACKGROUND: Most efforts to identify caregivers for research use passive approaches such as self-nomination. We describe an approach in which electronic health records (EHRs) can help identify, recruit, and increase diverse representations of family and other unpaid caregivers. OBJECTIVE: Few health systems have implemented systematic processes for identifying caregivers. This study aimed to develop and evaluate an EHR-driven process for identifying veterans likely to have unpaid caregivers in a caregiver survey study. We additionally examined whether there were EHR-derived veteran characteristics associated with veterans having unpaid caregivers. METHODS: We selected EHR home- and community-based referrals suggestive of veterans' need for supportive care from friends or family. We identified veterans with these referrals across the 8 US Department of Veteran Affairs medical centers enrolled in our study. Phone calls to a subset of these veterans confirmed whether they had a caregiver, specifically an unpaid caregiver. We calculated the screening contact rate for unpaid caregivers of veterans using attempted phone screening and for those who completed phone screening. The veteran characteristics from the EHR were compared across referral and screening groups using descriptive statistics, and logistic regression was used to compare the likelihood of having an unpaid caregiver among veterans who completed phone screening. RESULTS: During the study period, our EHR-driven process identified 12,212 veterans with home- and community-based referrals; 2134 (17.47%) veteran households were called for phone screening. Among the 2134 veterans called, 1367 (64.06%) answered the call, and 813 (38.1%) veterans had a caregiver based on self-report of the veteran, their caregiver, or another person in the household. The unpaid caregiver identification rate was 38.1% and 59.5% among those with an attempted phone screening and completed phone screening, respectively. Veterans had increased odds of having an unpaid caregiver if they were married (adjusted odds ratio [OR] 2.69, 95% CI 1.68-4.34), had respite care (adjusted OR 2.17, 95% CI 1.41-3.41), or had adult day health care (adjusted OR 3.69, 95% CI 1.60-10.00). Veterans with a dementia diagnosis (adjusted OR 1.37, 95% CI 1.00-1.89) or veteran-directed care referral (adjusted OR 1.95, 95% CI 0.97-4.20) were also suggestive of an association with having an unpaid caregiver. CONCLUSIONS: The EHR-driven process to identify veterans likely to have unpaid caregivers is systematic and resource intensive. Approximately 60% (813/1367) of veterans who were successfully screened had unpaid caregivers. In the absence of discrete fields in the EHR, our EHR-driven process can be used to identify unpaid caregivers; however, incorporating caregiver identification fields into the EHR would support a more efficient and systematic identification of caregivers. TRIAL REGISTRATION: ClincalTrials.gov NCT03474380; https://clinicaltrials.gov/ct2/show/NCT03474380.

The association of alcohol use with all-cause and cardiovascular disease-related hospitalizations or death in older, high-risk Veterans.

BACKGROUND: The prevalence of alcohol misuse among older adults has grown dramatically in the past decade, yet little is known about the association of alcohol misuse with hospitalization and death in this patient population. METHODS: We examined the association between alcohol use (measured by a screening instrument in primary care) and rates of all-cause and cardiovascular disease (CVD)-related 6-month hospitalization or death via electronic health records (EHRs) in a nationally representative sample of older, high-risk Veterans. Models were adjusted for sociodemographic and clinical characteristics, including frailty and comorbid conditions. RESULTS: The all-cause hospitalization or death rate at 6 months was 14.9%, and the CVD-related hospitalization or death rate was 1.8%. In adjusted analyses, all-cause hospitalization or death was higher in older Veterans who were nondrinkers or harmful use drinkers compared to moderate use drinkers, but CVD-related hospitalization or death was similar in all categories of drinking. CONCLUSIONS: These findings suggest that the complex association between alcohol and all-cause acute healthcare utilization found in the broader population is similar in older, high-risk Veteran patients. These findings do not support an association between alcohol consumption and CVD-specific hospitalizations.

Subgroups of High-Risk Veterans Affairs Patients Based on Social Determinants of Health Predict Risk of Future Hospitalization.

OBJECTIVE: Population segmentation has been recognized as a foundational step to help tailor interventions. Prior studies have predominantly identified subgroups based on diagnoses. In this study, we identify clinically coherent subgroups using social determinants of health (SDH) measures collected from Veterans at high risk of hospitalization or death. STUDY DESIGN AND SETTING: SDH measures were obtained for 4684 Veterans at high risk of hospitalization through mail survey. Eleven self-report measures known to impact hospitalization and amenable to intervention were chosen a priori by the study team to identify subgroups through latent class analysis. Associations between subgroups and demographic and comorbidity characteristics were calculated through multinomial logistic regression. Odds of 180-day hospitalization were compared across subgroups through logistic regression. RESULTS: Five subgroups of high-risk patients emerged-those with: minimal SDH vulnerabilities (8% hospitalized), poor/fair health with few SDH vulnerabilities (12% hospitalized), social isolation (10% hospitalized), multiple SDH vulnerabilities (12% hospitalized), and multiple SDH vulnerabilities without food or medication insecurity (10% hospitalized). In logistic regression, the "multiple SDH vulnerabilities" subgroup had greater odds of 180-day hospitalization than did the "minimal SDH vulnerabilities" reference subgroup (odds ratio: 1.53, 95% confidence interval: 1.09-2.14). CONCLUSION: Self-reported SDH measures can identify meaningful subgroups that may be used to offer tailored interventions to reduce their risk of hospitalization and other adverse events.

Improving Veteran Access to Integrated Management of Back Pain (AIM-Back): Protocol for an Embedded Pragmatic Cluster-Randomized Trial.

BACKGROUND: Coordinated efforts between the National Institutes of Health, the Department of Defense, and the Department of Veterans Affairs have built the capacity for large-scale clinical research investigating the effectiveness of nonpharmacologic pain treatments. This is an encouraging development; however, what constitutes best practice for nonpharmacologic management of low back pain (LBP) is largely unknown. DESIGN: The Improving Veteran Access to Integrated Management of Back Pain (AIM-Back) trial is an embedded pragmatic cluster-randomized trial that will examine the effectiveness of two different care pathways for LBP. Sixteen primary care clinics will be randomized 1:1 to receive training in delivery of 1) an integrated sequenced-care pathway or 2) a coordinated pain navigator pathway. Primary outcomes are pain interference and physical function (Patient-Reported Outcomes Measurement Information System Short Form [PROMIS-SF]) collected in the electronic health record at 3 months (n=1,680). A subset of veteran participants (n=848) have consented to complete additional surveys at baseline and at 3, 6, and 12 months for supplementary pain and other measures. SUMMARY: AIM-Back care pathways will be tested for effectiveness, and treatment heterogeneity will be investigated to identify which veterans may respond best to a given pathway. Health care utilization patterns (including opioid use) will also be compared between care pathways. Therefore, the AIM-Back trial will provide important information that can inform the future delivery of nonpharmacologic treatment of LBP.

Patient-Reported Social and Behavioral Determinants of Health and Estimated Risk of Hospitalization in High-Risk Veterans Affairs Patients.

Importance: Despite recognition of the association between individual social and behavioral determinants of health (SDH) and patient outcomes, little is known regarding the value of SDH in explaining variation in outcomes for high-risk patients. Objective: To describe SDH factors among veterans who are at high risk for hospitalization, and to determine whether adding patient-reported SDH measures to electronic health record (EHR) measures improves estimation of 90-day and 180-day all-cause hospital admission. Design, Setting, and Participants: A survey was mailed between April 16 and June 29, 2018, to a nationally representative sample of 10 000 Veterans Affairs (VA) patients whose 1-year risk of hospitalization or death was in the 75th percentile or higher based on a VA EHR-derived risk score. The survey included multiple SDH measures, such as resilience, social support, health literacy, smoking status, transportation barriers, and recent life stressors. Main Outcomes and Measures: The EHR-based characteristics of survey respondents and nonrespondents were compared using standardized differences. Estimation of 90-day and 180-day hospital admission risk was assessed for 3 logistic regression models: (1) a base model of all prespecified EHR-based covariates, (2) a restricted model of EHR-based covariates chosen via forward selection based on minimizing Akaike information criterion (AIC), and (3) a model of EHR- and survey-based covariates chosen via forward selection based on AIC minimization. Results: In total, 4685 individuals (response rate 46.9%) responded to the survey. Respondents were comparable to nonrespondents in most characteristics, but survey respondents were older (eg, >80 years old, 881 [18.8%] vs 800 [15.1%]), comprised a higher percentage of men (4391 [93.7%] vs 4794 [90.2%]), and were composed of more White non-Hispanic individuals (3366 [71.8%] vs 3259 [61.3%]). Based on AIC, the regression model with survey-based covariates and EHR-based covariates better estimated hospital admission at 90 days (AIC, 1947.7) and 180 days (AIC, 2951.9) than restricted models with only EHR-based covariates (AIC, 1980.2 at 90 days; AIC, 2981.9 at 180 days). This result was due to inclusion of self-reported measures such as marital or partner status, health-related locus of control, resilience, smoking status, health literacy, and medication insecurity. Conclusions and Relevance: Augmenting EHR data with patient-reported social information improved estimation of 90-day and 180-day hospitalization risk, highlighting specific SDH factors that might identify individuals who are at high risk for hospitalization.

Early-phase study of a telephone-based intervention to reduce weight regain among bariatric surgery patients.

OBJECTIVE: This study describes early-phase development of a behavioral intervention to reduce weight regain following bariatric surgery. We utilized the Obesity-Related Behavioral Intervention Trials model to guide intervention development and evaluation. We sought to establish recruitment, retention, and fidelity monitoring procedures; evaluate feasibility of utilizing weight from the electronic medical record (EMR) as an outcome; observe improvement in behavioral risk factors; and evaluate treatment acceptability. METHOD: The intervention comprised 4 weekly telephone calls addressing behavior change strategies for diet, physical activity, and nutrition supplement adherence and 5 biweekly calls addressing weight loss maintenance constructs. Veterans (N = 33) who received bariatric surgery 9-15 months prior consented to a 16-week, pre-post study. Self-reported outcomes were obtained by telephone at baseline and 16 weeks. Clinic weights were obtained from the EMR 6 months pre- and postconsent. Qualitative interviews were conducted at 16 weeks to evaluate treatment acceptability. We aimed to achieve a recruitment rate of ≥ 25% and retention rate of ≥ 80%, and have ≥ 50% of participants regain < 3% of their baseline weight. RESULTS: Results supported the feasibility of recruiting (48%) and retaining participants (93% provided survey data; 100% had EMR weight). Pre-post changes in weight (73% with < 3% weight regain) and physical activity (Cohen's ds 0.38 to 0.52) supported the potential for the intervention to yield clinically significant results. Intervention adherence (mean 7.8 calls of 9 received) and positive feedback from interviews supported treatment acceptability. CONCLUSIONS: The intervention should be evaluated in an adequately powered randomized controlled trial. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

An electronic family health history tool to identify and manage patients at increased risk for colorectal cancer: protocol for a randomized controlled trial.

BACKGROUND: Colorectal cancer is the fourth most commonly diagnosed cancer in the United States. Approximately 3-10% of the population has an increased risk for colorectal cancer due to family history and warrants more frequent or intensive screening. Yet, < 50% of that high-risk population receives guideline-concordant care. Systematic collection of family health history and decision support may improve guideline-concordant screening for patients at increased risk of colorectal cancer. We seek to test the effectiveness of a web-based, systematic family health history collection tool and decision support platform (MeTree) to improve risk assessment and appropriate management of colorectal cancer risk among patients in the Department of Veterans Affairs primary care practices. METHODS: In this ongoing randomized controlled trial, primary care providers at the Durham Veterans Affairs Health Care System and the Madison VA Medical Center are randomized to immediate intervention or wait-list control. Veterans are eligible if assigned to enrolled providers, have an upcoming primary care appointment, and have no conditions that would place them at increased risk for colorectal cancer (such as personal history, adenomatous polyps, or inflammatory bowel disease). Those with a recent lower endoscopy (e.g. colonoscopy, sigmoidoscopy) are excluded. Immediate intervention patients put their family health history information into a web-based platform, MeTree, which provides both patient- and provider-facing decision support reports. Wait-list control patients access MeTree 12 months post-consent. The primary outcome is the risk-concordant colorectal cancer screening referral rate obtained via chart review. Secondary outcomes include patient completion of risk management recommendations (e.g. colonoscopy) and referral for genetic consultation. We will also conduct an economic analysis and an assessment of providers' experience with MeTree clinical decision support recommendations to inform future implementation efforts if the intervention is found to be effective. DISCUSSION: This trial will assess the feasibility and effectiveness of patient-collected family health history linked to decision support to promote risk-appropriate screening in a large healthcare system such as the Department of Veterans Affairs. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02247336 . Registered on 25 September 2014.

The role of group cohesion in a group-based behavioral weight loss intervention.

Behavioral weight loss interventions are often delivered in groups. Group cohesion may enhance program attendance and, thereby, weight loss. In this secondary analysis, our goals were to: (1a) assess whether group cohesion measured early in a behavioral weight loss intervention predicts program attendance and weight loss outcomes and, if so, (1b) explore whether attendance mediates the link between group cohesion and weight loss; (2) characterize the association between change in group cohesion and weight loss throughout the intervention. Veterans (n = 324) initiated a 16-week, group-based behavioral weight loss program involving biweekly in-person group visits. In linear regression models, early group cohesion was unrelated to group attendance or weight loss. Although group cohesion significantly increased during the intervention, this change was not associated with weight loss. These findings are consistent with the limited literature; however, they are inconsistent with theoretical assertions and clinical observations of the influence of group factors on outcomes.

Limited Osteoporosis Screening Effectiveness Due to Low Treatment Rates in a National Sample of Older Men.

OBJECTIVE: To determine the association between dual-energy x-ray absorptiometry (DXA) testing for osteoporosis and subsequent fractures in US male veterans without a previous fracture. PATIENTS AND METHODS: This is a propensity score-matched observational study using Centers for Medicare and Medicaid Services and Veterans Affairs (VA) data from January 1, 2000, through December 31, 2010, with a mean follow-up time of 4.7 years (range, 0-10 years). Men receiving VA primary care aged 65 to 99 years without a previous fracture (N=2,539,812) were included. Men undergoing DXA testing were propensity score matched with untested controls in a 1:3 ratio, indicating the probability of DXA testing within the next year. Time to first clinical fracture was the primary outcome. Comorbidities, demographic characteristics, medications, DXA results, and osteoporosis treatment were defined using administrative data and natural language processing. A landmark analysis contingent on surviving to 12 months after screening was completed, accounting for competing risk of mortality. RESULTS: During follow-up of 153,311 men tested by DXA and 390,158 controls, 56,083 (10.3%) had sustained a fracture and 111,774 (20.6%) died. Overall, DXA testing was not associated with a decrease in fractures; conclusions are limited by unmeasured confounders and low medication initiation and adherence in those meeting treatment thresholds (12% of follow-up time). In contrast, DXA testing in prespecified subgroups was associated with a lower risk of fracture in comparison to the overall population who underwent DXA testing: androgen deprivation therapy (hazard ratio [HR], 0.77; 95% CI, 0.66-0.89), glucocorticoids (HR, 0.77; 95% CI, 0.72-0.84), age 80 years and older (HR, 0.85; 0.81-0.90), 1 or more VA guideline risk factors (HR, 0.91; 95% CI, 0.87-0.95), and high Fracture Risk Assessment Tool using body mass index score (HR, 0.90; 95% CI, 0.86-0.95). CONCLUSION: Current VA DXA testing practices are ineffective overall; interventions to improve treatment adherence are needed. Targeted DXA testing in higher-risk men was associated with a lower fracture risk.

Patient predictors of weight loss following a behavioral weight management intervention among US Veterans with severe obesity.

PURPOSE: Identification of patient characteristics that are associated with behavioral weight loss success among bariatric surgery candidates could inform selection of optimal bariatric surgery candidates. We examined the associations between psychosocial characteristics and weight loss in a group of Veterans with severe obesity who participated in a behavioral weight loss intervention. METHODS: The MAINTAIN trial involved a 16-week weight loss program followed by randomization among participants losing at least 4 kg to a maintenance intervention or usual care. This secondary analysis was performed on Veterans who participated in the 16-week weight loss program and met NIH criteria for bariatric surgery (body mass index [BMI] 35.0-39.9 with at least 1 obesity-related comorbidity or BMI ≥ 40). Unadjusted and adjusted associations between baseline patient characteristics and weight loss during the 16-week induction phase were evaluated with linear regression. Missing weight measurements were multiply imputed, and results combined across ten imputations. RESULTS: Among the 206 patients who met inclusion criteria, mean initial BMI was 40.8 kg/m2 (SD 6.0), and mean age was 59.2 years (SD 9.4). Approximately 20% of participants were female, 51.5% were Black, and 44.7% were White. Estimated mean 16-week weight loss was 5.16 kg (SD 4.31). In adjusted analyses, greater social support and older age were associated with greater weight loss (p < 0.05). None of the nine psychosocial characteristics we examined were associated with greater weight loss. CONCLUSIONS: Understanding and strengthening the level of social support for bariatric surgery candidates may be important given that it appears to be strongly correlated with behavioral weight loss success. LEVEL OF EVIDENCE: Level II, Evidence obtained from well-designed controlled trials without randomization. TRIAL REGISTRATION: ClinicalTrials.gov NCT01357551 http://clinicaltrials.gov/show/NCT01357551 .

Maintenance of Weight Loss After Initiation of Nutrition Training: A Randomized Trial.

BACKGROUND: Weight regain after successful weight loss interventions is common. OBJECTIVE: To establish the efficacy of a weight loss maintenance program compared with usual care in obese adults. DESIGN: 2-group, parallel, randomized trial stratified by initial weight loss (<10 kg vs. ≥10 kg), conducted from 20 August 2012 to 18 December 2015. Outcome assessors were blinded to treatment assignment. (ClinicalTrials.gov: NCT01357551). SETTING: 3 primary care clinics at the Veterans Affairs Medical Center in Durham and Raleigh, North Carolina. PATIENTS: Obese outpatients (body mass index ≥30 kg/m2) who lost 4 kg or more of body weight during a 16-week, group-based weight loss program. INTERVENTION: The maintenance intervention, delivered primarily by telephone, addressed satisfaction with outcomes, relapse-prevention planning, self-monitoring, and social support. Usual care involved no contact except for study measurements. MEASUREMENTS: Primary outcome was mean weight regain at week 56. Secondary outcomes included self-reported caloric intake, walking, and moderate physical activity. RESULTS: Of 504 patients in the initial program, 222 lost at least 4 kg of body weight and were randomly assigned to maintenance (n = 110) or usual care (n = 112). Retention was 85%. Most patients were middle-aged white men. Mean weight loss during initiation was 7.2 kg (SD, 3.1); mean weight at randomization was 103.6 kg (SD, 20.4). Estimated mean weight regain was statistically significantly lower in the intervention (0.75 kg) than the usual care (2.36 kg) group (estimated mean difference, 1.60 kg [95% CI, 0.07 to 3.13 kg]; P = 0.040). No statistically significant differences in secondary outcomes were seen at 56 weeks. No adverse events directly attributable to the intervention were observed. LIMITATIONS: Results may not generalize to other settings or populations. Dietary intake and physical activity were self-reported. Duration was limited to 56 weeks. CONCLUSION: An intervention focused on maintenance-specific strategies and delivered in a resource-conserving way modestly slowed the rate of weight regain in obese adults. PRIMARY FUNDING SOURCE: Veterans Affairs Health Services Research and Development Service.

Implementation of Lung Cancer Screening in the Veterans Health Administration.

Importance: The US Preventive Services Task Force recommends annual lung cancer screening (LCS) with low-dose computed tomography for current and former heavy smokers aged 55 to 80 years. There is little published experience regarding implementing this recommendation in clinical practice. Objectives: To describe organizational- and patient-level experiences with implementing an LCS program in selected Veterans Health Administration (VHA) hospitals and to estimate the number of VHA patients who may be candidates for LCS. Design, Setting, and Participants: This clinical demonstration project was conducted at 8 academic VHA hospitals among 93 033 primary care patients who were assessed on screening criteria; 2106 patients underwent LCS between July 1, 2013, and June 30, 2015. Interventions: Implementation Guide and support, full-time LCS coordinators, electronic tools, tracking database, patient education materials, and radiologic and nodule follow-up guidelines. Main Outcomes and Measures: Description of implementation processes; percentages of patients who agreed to undergo LCS, had positive findings on results of low-dose computed tomographic scans (nodules to be tracked or suspicious findings), were found to have lung cancer, or had incidental findings; and estimated number of VHA patients who met the criteria for LCS. Results: Of the 4246 patients who met the criteria for LCS, 2452 (57.7%) agreed to undergo screening and 2106 (2028 men and 78 women; mean [SD] age, 64.9 [5.1] years) underwent LCS. Wide variation in processes and patient experiences occurred among the 8 sites. Of the 2106 patients screened, 1257 (59.7%) had nodules; 1184 of these patients (56.2%) required tracking, 42 (2.0%) required further evaluation but the findings were not cancer, and 31 (1.5%) had lung cancer. A variety of incidental findings, such as emphysema, other pulmonary abnormalities, and coronary artery calcification, were noted on the scans of 857 patients (40.7%). Conclusions and Relevance: It is estimated that nearly 900 000 of a population of 6.7 million VHA patients met the criteria for LCS. Implementation of LCS in the VHA will likely lead to large numbers of patients eligible for LCS and will require substantial clinical effort for both patients and staff.

A Collaborative Paradigm for Improving Management of Sleep Disorders in Primary Care: A Randomized Clinical Trial.

OBJECTIVES: To test a collaborative care model for interfacing sleep specialists with primary care providers to enhance patients' sleep disorders management. METHODS: This study used a randomized, parallel group, clinical intervention trial design. A total of 137 adult (29 women) VA outpatients with sleep complaints were enrolled and randomly assigned to (1) an intervention (INT) consisting of a one-time consultation with a sleep specialist who provided diagnostic feedback and treatment recommendations to the patient and the patient's primary care provider; or (2) a control condition consisting of their usual primary care (UPC). Provider-focused outcomes included rates of adherence to recommended diagnostic procedures and sleep-focused interventions. Patient-focused outcomes included measures taken from sleep diaries and actigraphy; Pittsburgh Sleep Quality Index (PSQI) scores; and self-report measures of sleepiness, fatigue, mood, quality of life, and satisfaction with health care. RESULTS: The proportions of provider-initiated sleep-focused interventions were significantly higher in the INT group than in the UPC group for polysomnography referrals (49% versus 6%; P < 0.001) and mental health clinic referrals (19% versus 6%; P = 0.02). At the 10-mo follow up, INT recipients showed greater estimated mean reductions in diary total wake time (-17.0 min; 95% confidence interval [CI]: -30.9, -3.1; P = 0.02) and greater increases in sleep efficiency (+3.7%; 95% CI: 0.8, 6.5; P = 0.01) than did UPC participants. A greater proportion of the INT group showed ≥ 1 standard deviation decline on the PSQI from baseline to the 10-mo follow-up (41% versus 21%; P = 0.02). Moreover, 69% of the INT group had normal (≤ 10) Epworth Sleepiness Scale scores at the 10-mo follow-up, whereas only 50% of the UPC group fell below this clinical cutoff (P = 0.03). CONCLUSIONS: A one-time sleep consultation significantly increased healthcare providers' attention to sleep problems and resulted in benefits to patients' sleep/wake symptoms. CLINICAL TRIALS REGISTRATION: This study is registered with clinicaltrials.gov with identifier # NCT00390572.