Is Bigger Better?: A Closer Look at Small Health Systems in the United States.

BACKGROUND: Research on US health systems has focused on large systems with at least 50 physicians. Little is known about small systems. OBJECTIVES: Compare the characteristics, quality, and costs of care between small and large health systems. RESEARCH DESIGN: Retrospective, repeated cross-sectional analysis. SUBJECTS: Between 468 and 479 large health systems, and between 608 and 641 small systems serving fee-for-service Medicare beneficiaries, yearly between 2013 and 2017. MEASURES: We compared organizational, provider and beneficiary characteristics of large and small systems, and their geographic distribution, using multiple Medicare and Internal Revenue Service administrative data sources. We used mixed-effects regression models to estimate differences between small and large systems in claims-based Healthcare Effectiveness Data and Information Set (HEDIS) quality measures and HealthPartners' Total Cost of Care measure using a 100% sample of Medicare fee-for-service claims. We fit linear spline models to examine the relationship between the number of a system's affiliated physicians and its quality and costs. RESULTS: The number of both small and large systems increased from 2013 to 2017. Small systems had a larger share of practice sites (43.1% vs. 11.7% for large systems in 2017) and beneficiaries (51.4% vs. 15.5% for large systems in 2017) in rural areas or small towns. Quality performance was lower among small systems than large systems (-0.52 SDs of a composite quality measure) and increased with system size up to ∼75 physicians. There was no difference in total costs of care. CONCLUSIONS: Small systems are a growing source of care for rural Medicare populations, but their quality performance lags behind large systems. Future studies should examine the mechanisms responsible for quality differences.

Longitudinal Associations Between Changes in Cigarette Smoking and Alcohol Use, Eating Behavior, Perceived Stress, and Self-Rated Health in a Cohort of Low-Income Black Adults.

BACKGROUND: Black adults in the U.S. experience significant health disparities related to tobacco use and obesity. Conducting observational studies of the associations between smoking and other health behaviors and indicators among Black adults may contribute to the development of tailored interventions. PURPOSE: We examined associations between change in cigarette smoking and alcohol use, body mass index, eating behavior, perceived stress, and self-rated health in a cohort of Black adults who resided in low-income urban neighborhoods and participated in an ongoing longitudinal study. METHODS: Interviews were conducted in 2011, 2014, and 2018; participants (N = 904) provided at least two waves of data. We fit linear and logistic mixed-effects models to evaluate how changes in smoking status from the previous wave to the subsequent wave were related to each outcome at that subsequent wave. RESULTS: Compared to repeated smoking (smoking at previous and subsequent wave), repeated nonsmoking (nonsmoking at previous and subsequent wave) was associated with greater likelihood of recent dieting (OR = 1.59, 95% CI [1.13, 2.23], p = .007) and future intention (OR = 2.19, 95% CI [1.61, 2.98], p < .001) and self-efficacy (OR = 1.64, 95% CI [1.21, 2.23], p = .002) to eat low calorie foods, and greater odds of excellent or very good self-rated health (OR = 2.47, 95% CI [1.53, 3.99], p < .001). Transitioning from smoking to nonsmoking was associated with greater self-efficacy to eat low calorie foods (OR = 1.89, 95% CI [1.1, 3.26], p = .021), and lower perceived stress (ß = -0.69, 95% CI [-1.34, -0.05], p = .036). CONCLUSIONS: We found significant longitudinal associations between smoking behavior and eating behavior, perceived stress, and self-rated health. These findings have implications for the development of multiple behavior change programs and community-level interventions and policies.

Mixed Effects of Neighborhood Revitalization on Residents' Cardiometabolic Health.

INTRODUCTION: Despite the growing recognition of the importance of neighborhood conditions for cardiometabolic health, causal relationships have been difficult to establish owing to a reliance on cross-sectional designs and selection bias. This is the first natural experiment to examine the impact of neighborhood revitalization on cardiometabolic outcomes in residents from 2 predominantly African American neighborhoods, one of which has experienced significant revitalization (intervention), whereas the other has not (comparison). METHODS: The sample included 532 adults (95% African American, 80% female, mean age=58.9 years) from 2 sociodemographically similar, low-income neighborhoods in Pittsburgh, PA, with preintervention and postintervention measures (2016 and 2018) of BMI, diastolic and systolic blood pressure, HbA1c, and high-density lipoprotein cholesterol and covariates. Data were collected in 2016 and 2018 and analyzed in 2020. RESULTS: Difference-in-difference analyses showed significant improvement in high-density lipoprotein cholesterol in intervention residents relative to that in the comparison neighborhood (ß=3.88, 95% CI=0.47, 7.29). There was also a significant difference-in-difference estimate in diastolic blood pressure (ß=3.00, 95% CI=0.57, 5.43), with residents of the intervention neighborhood showing a greater increase in diastolic blood pressure than those in the comparison neighborhood. No statistically significant differences were found for other outcomes. CONCLUSIONS: Investing in disadvantaged neighborhoods has been suggested as a strategy to reduce health disparities. Using a natural experiment, findings suggest that improving neighborhood conditions may have a mixed impact on certain aspects of cardiometabolic health. Findings underscore the importance of examining the upstream causes of health disparities using rigorous designs and longer follow-up periods that provide more powerful tests of causality.

Factors related to health civic engagement: results from the 2018 National Survey of Health Attitudes to understand progress towards a Culture of Health.

BACKGROUND: Civic engagement, including voting, volunteering, and participating in civic organizations, is associated with better psychological, physical and behavioral health and well-being. In addition, civic engagement is increasingly viewed (e.g., in Robert Wood Johnson Foundation's Culture of Health action framework) as a potentially important driver for raising awareness of and addressing unhealthy conditions in communities. As such, it is important to understand the factors that may promote civic engagement, with a particular focus on the less-understood, health civic engagement, or civic engagement in health-related and health-specific activities. Using data from a nationally representative sample of adults in the United States (U.S.), we examined whether the extent to which individuals feel they belong in their community (i.e., perceived sense of community) and the value they placed on investing in community health were associated with individuals' health civic engagement. METHODS: Using data collected on 7187 nationally representative respondents from the 2018 National Survey of Health Attitudes, we examined associations between sense of community, valued investment in community health, and perceived barriers to taking action to invest in community health, with health civic engagement. We constructed continuous scales for each of these constructs and employed multiple linear regressions adjusting for multiple covariates including U.S. region and city size of residence, educational attainment, family income, race/ethnicity, household size, employment status, and years living in the community. RESULTS: Participants who endorsed (i.e., responded with mostly or completely) all 16 sense of community scale items endorsed an average of 22.8% (95%CI: 19.8-25.7%) more of the health civic engagement scale items compared with respondents who did not endorse any of the sense of community items. Those who endorsed (responded that it was an important or top priority) all items capturing valued investment in community health endorsed 14.0% (95%CI: 11.2-16.8%) more of the health civic engagement items than those who did not endorse any valued investment in community health items. CONCLUSIONS: Health civic engagement, including voting and volunteering to ultimately guide government decisions about health issues, may help improve conditions that influence health and well-being for all. Focusing on individuals' sense of community and highlighting investments in community health may concurrently be associated with increased health civic engagement and improved community and population health.

Psychometric evaluation of the Medicare Advantage and prescription drug plan disenrollment reasons survey.

OBJECTIVES: To develop and assess the reliability and validity of composite measures of reasons for disenrollment from Medicare Advantage (MA) and prescription drug plans (PDPs). DATA SOURCE: Medicare beneficiaries who responded to the Medicare Advantage and Prescription Drug Plan Disenrollment Reasons Survey. STUDY DESIGN: Separate multilevel factor analyses of MA and PDP data suggested groupings of survey items to form composite measures, for which internal consistency and interunit reliability were estimated. The association of each composite with an overall plan rating was examined to evaluate criterion validity. PRINCIPAL FINDINGS: Five composites were identified: financial reasons for disenrollment; problems with prescription drug benefits and coverage; problems getting information and help from the plan; problems getting needed care, coverage, and cost information; and problems with coverage of doctors and hospitals. Beneficiary-level internal consistency reliability exceeded 0.70 for all but one composite (financial reasons); plan-level internal consistency reliability exceeded 0.80 for all composites; average interunit reliability for plans with ≥ 30 survey completes exceeded 0.75 for 3 of 5 composites. As expected, greater endorsement of reasons for disenrollment was associated with lower overall plan ratings. CONCLUSIONS: The Disenrollment Reasons Survey provides a reliable and valid assessment of beneficiaries' reasons for leaving their plans. Multiple reasons for disenrollment may indicate especially poor experiences.

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.

Association Between Bariatric Surgery and Macrovascular Disease Outcomes in Patients With Type 2 Diabetes and Severe Obesity.

Importance: Macrovascular disease is a leading cause of morbidity and mortality for patients with type 2 diabetes, and medical management, including lifestyle changes, may not be successful at lowering risk. Objective: To investigate the relationship between bariatric surgery and incident macrovascular (coronary artery disease and cerebrovascular diseases) events in patients with severe obesity and type 2 diabetes. Design, Setting, and Participants: In this retrospective, matched cohort study, patients with severe obesity (body mass index ≥35) aged 19 to 79 years with diabetes who underwent bariatric surgery from 2005 to 2011 in 4 integrated health systems in the United States (n = 5301) were matched to 14 934 control patients on site, age, sex, body mass index, hemoglobin A1c, insulin use, observed diabetes duration, and prior health care utilization, with follow-up through September 2015. Exposures: Bariatric procedures (76% Roux-en-Y gastric bypass, 17% sleeve gastrectomy, and 7% adjustable gastric banding) were compared with usual care for diabetes. Main Outcomes and Measures: Multivariable-adjusted Cox regression analysis investigated time to incident macrovascular disease (defined as first occurrence of coronary artery disease [acute myocardial infarction, unstable angina, percutaneous coronary intervention, or coronary artery bypass grafting] or cerebrovascular events [ischemic stroke, hemorrhagic stroke, carotid stenting, or carotid endarterectomy]). Secondary outcomes included coronary artery disease and cerebrovascular outcomes separately. Results: Among a combined 20 235 surgical and nonsurgical patients, the mean (SD) age was 50 (10) years; 76% of the surgical and 75% of the nonsurgical patients were female; and the baseline mean (SD) body mass index was 44.7 (6.9) and 43.8 (6.7) in the surgical and nonsurgical groups, respectively. At the end of the study period, there were 106 macrovascular events in surgical patients (including 37 cerebrovascular and 78 coronary artery events over a median of 4.7 years; interquartile range, 3.2-6.2 years) and 596 events in the matched control patients (including 227 cerebrovascular and 398 coronary artery events over a median of 4.6 years; interquartile range, 3.1-6.1 years). Bariatric surgery was associated with a lower composite incidence of macrovascular events at 5 years (2.1% in the surgical group vs 4.3% in the nonsurgical group; hazard ratio, 0.60 [95% CI, 0.42-0.86]), as well as a lower incidence of coronary artery disease (1.6% in the surgical group vs 2.8% in the nonsurgical group; hazard ratio, 0.64 [95% CI, 0.42-0.99]). The incidence of cerebrovascular disease was not significantly different between groups at 5 years (0.7% in the surgical group vs 1.7% in the nonsurgical group; hazard ratio, 0.69 [95% CI, 0.38-1.25]). Conclusions and Relevance: In this observational study of patients with type 2 diabetes and severe obesity who underwent surgery, compared with those who did not undergo surgery, bariatric surgery was associated with a lower risk of macrovascular outcomes. The findings require confirmation in randomized clinical trials. Health care professionals should engage patients with severe obesity and type 2 diabetes in a shared decision making conversation about the potential role of bariatric surgery in the prevention of macrovascular events.

Microvascular Outcomes in Patients With Diabetes After Bariatric Surgery Versus Usual Care: A Matched Cohort Study.

Background: Bariatric surgery improves glycemic control in patients with type 2 diabetes mellitus (T2DM), but less is known about microvascular outcomes. Objective: To investigate the relationship between bariatric surgery and incident microvascular complications of T2DM. Design: Retrospective matched cohort study from 2005 to 2011 with follow-up through September 2015. Setting: 4 integrated health systems in the United States. Participants: Patients aged 19 to 79 years with T2DM who had bariatric surgery (n = 4024) were matched on age, sex, body mass index, hemoglobin A1c level, insulin use, diabetes duration, and intensity of health care use up to 3 nonsurgical participants (n = 11 059). Intervention: Bariatric procedures (76% gastric bypass, 17% sleeve gastrectomy, and 7% adjustable gastric banding) compared with usual care. Measurements: Adjusted Cox regression analysis investigated time to incident microvascular disease, defined as first occurrence of diabetic retinopathy, neuropathy, or nephropathy. Results: Median follow-up was 4.3 years for both surgical and nonsurgical patients. Bariatric surgery was associated with significantly lower risk for incident microvascular disease at 5 years (16.9% for surgical vs. 34.7% for nonsurgical patients; adjusted hazard ratio [HR], 0.41 [95% CI, 0.34 to 0.48]). Bariatric surgery was associated with lower cumulative incidence at 5 years of diabetic neuropathy (7.2% for surgical vs. 21.4% for nonsurgical patients; HR, 0.37 [CI, 0.30 to 0.47]), nephropathy (4.9% for surgical vs. 10.0% for nonsurgical patients; HR, 0.41 [CI, 0.29 to 0.58]), and retinopathy (7.2% for surgical vs. 11.2% for nonsurgical patients; HR, 0.55 [CI, 0.42 to 0.73]). Limitation: Electronic health record databases could misclassify microvascular disease status for some patients. Conclusion: In this large, multicenter study of adults with T2DM, bariatric surgery was associated with lower overall incidence of microvascular disease (including lower risk for neuropathy, nephropathy, and retinopathy) than usual care. Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases.

Does Documented Brief Intervention Predict Decreases in Alcohol Use in Primary Care?

BACKGROUND: Brief intervention (BI) is recommended for patients with unhealthy alcohol use, but the effectiveness of BI in usual care settings remains unclear. OBJECTIVE: We evaluated whether BI predicts decreases in drinking 6 months after a positive screen for unhealthy alcohol use. METHOD: We enrolled patients who recently screened positive for unhealthy alcohol use during a routine screen in Veterans Health Administration primary care. We conducted medical record review to assess whether providers documented advice to reduce or abstain, feedback about risks to health, feedback about how patient drinking compares to norms or recommended limits, and discussion of drinking-related goals. BI elements were coded from 7 days before the date of the positive screen to 60 days after. We conducted baseline and 6-month follow-up telephone interviews to assess change in past 30-day drinking. We fit regression models examining each BI element and another model for the total count of instances of any combination of elements. RESULTS: Of the 327 patients included, 86% had at least one documented instance of receiving advice, 86% had risk feedback, 55% had normative feedback, 38% had goal discussion, and 75% had three or more instances of any combination of elements of BI. None of the individual BI elements, nor the total number of instances, were significantly associated with decreased drinking. CONCLUSIONS: Results suggest that provider documentation of elements of BI and increasing numbers of instances of BI elements were not associated with decreased heavy drinking at 6-month follow-up among patients identified with unhealthy alcohol use.

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.

Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models.

Exposures derived from electronic health records (EHR) may be misclassified, leading to biased estimates of their association with outcomes of interest. An example of this problem arises in the context of cancer screening where test indication, the purpose for which a test was performed, is often unavailable. This poses a challenge to understanding the effectiveness of screening tests because estimates of screening test effectiveness are biased if some diagnostic tests are misclassified as screening. Prediction models have been developed for a variety of exposure variables that can be derived from EHR, but no previous research has investigated appropriate methods for obtaining unbiased association estimates using these predicted probabilities. The full likelihood incorporating information on both the predicted probability of exposure-class membership and the association between the exposure and outcome of interest can be expressed using a finite mixture model. When the regression model of interest is a generalized linear model (GLM), the expectation-maximization algorithm can be used to estimate the parameters using standard software for GLMs. Using simulation studies, we compared the bias and efficiency of this mixture model approach to alternative approaches including multiple imputation and dichotomization of the predicted probabilities to create a proxy for the missing predictor. The mixture model was the only approach that was unbiased across all scenarios investigated. Finally, we explored the performance of these alternatives in a study of colorectal cancer screening with colonoscopy. These findings have broad applicability in studies using EHR data where gold-standard exposures are unavailable and prediction models have been developed for estimating proxies.

Radiologists' interpretive skills in screening vs. diagnostic mammography: are they related?

PURPOSE: This study aims to determine whether radiologists who perform well in screening also perform well in interpreting diagnostic mammography. MATERIALS AND METHODS: We evaluated the accuracy of 468 radiologists interpreting 2,234,947 screening and 196,164 diagnostic mammograms. Adjusting for site, radiologist, and patient characteristics, we identified radiologists with performance in the highest tertile and compared to those with lower performance. RESULTS: A moderate correlation was noted for radiologists' accuracy when interpreting screening versus their accuracy on diagnostic examinations: sensitivity (rspearman=0.51, 95% CI: 0.22, 0.80; P=.0006) and specificity (rspearman=0.40, 95% CI: 0.30, 0.49; P<.0001). CONCLUSION: Different educational approaches to screening and diagnostic imaging should be considered.

Boosting medical diagnostics by pooling independent judgments.

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors' diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches.

Long-term Microvascular Disease Outcomes in Patients With Type 2 Diabetes After Bariatric Surgery: Evidence for the Legacy Effect of Surgery.

OBJECTIVE: To identify and quantify any legacy effect of bariatric surgery on risk of incident microvascular disease in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We conducted a retrospective observational cohort study (n = 4,683; 40% racial/ethnic minority) of patients with type 2 diabetes who underwent bariatric surgery from 2001 through 2011. The primary outcome measure was incident microvascular disease defined as a composite indicator of the first occurrence of retinopathy, neuropathy, and/or nephropathy. The Cox proportional hazards framework was used to investigate the associations between type 2 diabetes remission/relapse status and time to microvascular disease. RESULTS: Covariate-adjusted analyses showed that patients who experienced type 2 diabetes remission had 29% lower risk of incident microvascular disease compared with patients who never remitted (hazard ratio [HR] 0.71 [95% CI 0.60, 0.85]). Among patients who experienced a relapse after remission, the length of time spent in remission was inversely related to the risk of incident microvascular disease; for every additional year of time spent in remission prior to relapse, the risk of microvascular disease was reduced by 19% (HR 0.81 [95% CI 0.67, 0.99]) compared with patients who never remitted. CONCLUSIONS: Our results indicate that remission of type 2 diabetes after bariatric surgery confers benefits for risk of incident microvascular disease even if patients eventually experience a relapse of their type 2 diabetes. This provides support for a legacy effect of bariatric surgery, where even a transient period of surgically induced type 2 diabetes remission is associated with lower long-term microvascular disease risk.

Long-Term Weight Change after Initiating Second-Generation Antidepressants.

(1) OBJECTIVE: To examine the relationship between the choice of second-generation antidepressant drug treatment and long-term weight change; (2) METHODS: We conducted a retrospective cohort study to investigate the relationship between choice of antidepressant medication and weight change at two years among adult patients with a new antidepressant treatment episode between January, 2006 and October, 2009 in a large health system in Washington State. Medication use, encounters, diagnoses, height, and weight were collected from electronic databases. We modeled change in weight and BMI at two years after initiation of treatment using inverse probability weighted linear regression models that adjusted for potential confounders. Fluoxetine was the reference treatment; (3) RESULTS: In intent-to-treat analyses, non-smokers who initiated bupropion treatment on average lost 7.1 lbs compared to fluoxetine users who were non-smokers (95% CI: -11.3, -2.8; p-value < 0.01); smokers who initiated bupropion treatment gained on average 2.2 lbs compared to fluoxetine users who were smokers (95% CI: -2.3, 6.8; p-value = 0.33). Changes in weight associated with all other antidepressant medications were not significantly different than fluoxetine, except for sertraline users, who gained an average of 5.9 lbs compared to fluoxetine users (95% CI: 0.8, 10.9; p-value = 0.02); (4) CONCLUSION: Antidepressant drug therapy is significantly associated with long-term weight change at two years. Bupropion may be considered as the first-line drug of choice for overweight and obese patients unless there are other existing contraindications.

Patient-Reported Offers of Alcohol Treatment for Primary Care Patients at High-Risk for an Alcohol Use Disorder.

BACKGROUND: This study assessed patient-reported alcohol treatment offers by health care providers following routine annual screening for alcohol use in primary care. METHODS: A telephone interview within 30 days of the annual screen assessed demographics, alcohol and other drug use, mental health symptoms, and offers of formal treatment for alcohol by a Veterans Affairs health care provider. We included male patients (n = 349) at high risk for an alcohol use disorder (AUD) who had not received alcohol treatment in the past 3 months. We assessed self-reported receipt of any offers of formal treatment for alcohol use and associations of offers of formal treatment for alcohol with demographic and clinical variables. RESULTS: A total of 145 patients (41.5%) reported an offer of at least 1 type of formal treatment for alcohol use. More severe alcohol misuse (odds ratio, 1.07; 95% confidence interval, 1.03-1.11) and younger age (odds ratio, 0.97, 95% confidence interval, 0.95-0.99) were associated with reporting an offer of formal treatment. CONCLUSION: Most primary care patients at high risk for an AUD were not offered treatment following annual screening. Our results highlight the importance of training primary care providers in what constitutes appropriate medical treatment for this population and the most effective ways of offering treatment.

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations.

OBJECTIVE: Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. SETTING: 73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012. METHODS: We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. RESULTS: Facilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. CONCLUSIONS: Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use.

The Association of Panic Disorder, Posttraumatic Stress Disorder, and Major Depression With Smoking in American Indians.

INTRODUCTION: Rates of cigarette smoking are disproportionately high among American Indian populations, although regional differences exist in smoking prevalence. Previous research has noted that anxiety and depression are associated with higher rates of cigarette use. We asked whether lifetime panic disorder, posttraumatic stress disorder, and major depression were related to lifetime cigarette smoking in two geographically distinct American Indian tribes. METHODS: Data were collected in 1997-1999 from 1506 Northern Plains and 1268 Southwest tribal members; data were analyzed in 2009. Regression analyses examined the association between lifetime anxiety and depressive disorders and odds of lifetime smoking status after controlling for sociodemographic variables and alcohol use disorders. Institutional and tribal approvals were obtained for all study procedures, and all participants provided informed consent. RESULTS: Odds of smoking were two times higher in Southwest participants with panic disorder and major depression, and 1.7 times higher in those with posttraumatic stress disorder, after controlling for sociodemographic variables. After accounting for alcohol use disorders, only major depression remained significantly associated with smoking. In the Northern Plains, psychiatric disorders were not associated with smoking. Increasing psychiatric comorbidity was significantly linked to increased smoking odds in both tribes, especially in the Southwest. CONCLUSIONS: This study is the first to examine the association between psychiatric conditions and lifetime smoking in two large, geographically diverse community samples of American Indians. While the direction of the relationship between nicotine use and psychiatric disorders cannot be determined, understanding unique social, environmental, and cultural differences that contribute to the tobacco-psychiatric disorder relationship may help guide tribe-specific commercial tobacco control strategies.

Learning About Missing Data Mechanisms in Electronic Health Records-based Research: A Survey-based Approach.

BACKGROUND: Bias due to missing data is a major concern in electronic health record (EHR)-based research. As part of an ongoing EHR-based study of weight change among patients treated for depression, we conducted a survey to investigate determinants of missingness in the available weight information and to evaluate the missing-at-random assumption. METHODS: We identified 8,345 individuals enrolled in a large EHR-based health care system who had monotherapy treatment for depression from April 2008 to March 2010. A stratified sample of 1,153 individuals completed a detailed survey. Logistic regression was used to investigate determinants of whether a patient (1) had an opportunity to be weighed at treatment initiation (baseline), and (2) had a weight measurement recorded. Parallel analyses were conducted to investigate missingness during follow-up. Throughout, inverse-probability weighting was used to adjust for the design and survey nonresponse. Analyses were also conducted to investigate potential recall bias. RESULTS: Missingness at baseline and during follow-up was associated with numerous factors not routinely collected in the EHR including whether or not the patient had ever chosen not to be weighed, external weight control activities, and self-reported baseline weight. Patient attitudes about their weight and perceptions regarding the potential impact of their depression treatment on weight were not related to missingness. CONCLUSION: Adopting a comprehensive strategy to investigate missingness early in the research process gives researchers information necessary to evaluate key assumptions. While the survey presented focuses on outcome data, the overarching strategy can be applied to any and all data elements subject to missingness.

Collective intelligence meets medical decision-making: the collective outperforms the best radiologist.

While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules ("majority", "quorum", and "weighted quorum") when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.