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Objectives: To examine: (1) what elements of patient-centered medical homes (PCMHs) are typically provided to low-income populations, (2) whether PCMHs improve health behaviors, experiences, and outcomes for low-income groups.Data Sources/study Setting: Existing literature on PCMH utilization among health care organizations serving low-income populations.Study Design: Systematic review and meta-analysis.Data Collection/extraction Methods: We obtained papers through existing systematic and literature reviews and via PubMed, Web of Science, and the TRIP databases, which examined PCMHs serving low-income populations. A total of 434 studies were reviewed. Thirty-three articles met eligibility criteria.Principal Findings: Patient-centered medical home interventions usually were composed of five of the six recommended components. Overall positive effect of PCMH interventions was d = 0.247 (range -0.965 to 1.42). PCMH patients had better clinical outcomes (d = 0.395), higher adherence (0.392), and lower utilization of emergency rooms (d = -0.248), but there were apparent limitations in study quality.Conclusions: Evidence shows that the PCMH model can increase health outcomes among low-income populations. However, limitations to quality include no assessment for confounding variables. Implications are discussed. [ABSTRACT FROM AUTHOR]

Objective: To examine the availability and facility‐level predictors of LGBT‐specific mental health and substance abuse treatment in the United States. Data Sources/Study Setting: 2016 National Survey of Substance Abuse Treatment Services, 2016 National Mental Health Service Survey, and 2015‐2016 Gallup Daily tracking survey. Study Design: Logistic regression models and average marginal effects were used to identify characteristics of facilities that offer LGBT‐specific programs. Linear regression models were used to estimate the association between the state‐level proportion of LGBT people and the proportion of facilities that offer LGBT‐specific programs. Data Collection/Extraction Methods: Secondary data analysis. Cases with missing values for any predictor were excluded. Principle Findings: 12.6 percent of mental health and 17.6 percent of substance abuse facilities reported LGBT‐specific programs. Several facility characteristics were statistically associated with the likelihood of mental health and substance abuse facilities providing LGBT‐specific programs, including offering outpatient or residential treatment, private ownership, religious affiliation, and payment type. The proportion of LGBT adults living within each state was statistically associated with state‐level density of LGBT‐specific mental health programs, but not substance abuse programs. Conclusions: Findings suggest limited availability of culturally competent mental health and substance abuse treatment, despite well‐documented need. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of proxy survey responses on cancer care experience reports and quality ratings.Data Sources/study Setting: Secondary analysis of data from Cancer Care Outcomes Research and Surveillance (CanCORS). Recruitment occurred from 2003 to 2005.Study Design: The study was a cross-sectional observational study. The respondents were patients with incident colorectal or lung cancer or their proxies.Data Collection/extraction Methods: Analyses used linear regression models with an independent variable for proxy versus patient responses as well as study site and clinical covariates. The outcomes were experiences with medical care, nursing care, care coordination, and care quality rating. Multiple imputation was used for missing data.Principal Findings: Among 6,471 respondents, 1,011 (16 percent) were proxies. The proportion of proxy respondents varied from 6 percent to 28 percent across study sites. Adjusted proxy scores were modestly higher for medical care experiences (+1.28 points [95 percent CI:+ 0.05 to +2.51]), but lower for nursing care (-2.81 [95 percent CI: -4.11 to -1.50]) and care coordination experiences (-2.98 [95 percent CI: -4.15 to -1.81]). There were no significant differences between adjusted patient and proxy ratings of quality.Conclusions: Proxy responses have small but statistically significant differences from patient responses. However, if ratings of care are used for financial incentives, such differences could be exaggerated across practices or areas if proxy use varies. [ABSTRACT FROM AUTHOR]

Objective: Did mental health cost-sharing decrease following implementation of the Mental Health Parity and Addiction Equity Act (MHPAEA)?Data Source: Specialty mental health copayments, coinsurance, and deductibles, 2008-2013, were obtained from benefits databases for "carve-in" plans from a national commercial managed behavioral health organization.Study Design: Bivariate and regression-adjusted analyses compare the probability of use and (conditional) level of cost-sharing pre- and postparity. An interaction term is added to compare differential levels of pre- and postparity cost-sharing changes for plans that were and were not already at parity pre-MHPAEA.Findings: Controlling for employer/plan characteristics, MHPAEA is associated with higher intermediate care copayments ($15.9) but lower outpatient ($2.6) copayments among in-network-only plans. Among plans with in- and out-of-network benefits, MHPAEA is associated with lower inpatient ($23.2) and outpatient ($2.5) copayments, but increases in inpatient and intermediate in-network and out-of-network coinsurance (about 1 percentage point). Among the few plans not at parity pre-MHPAEA, changes in use and level of cost-sharing associated with MHPAEA were more dramatic.Conclusion: Mixed evidence that MHPAEA led to more generous mental health benefits may stem from the finding that many plans were already at parity pre-MHPAEA. Future policy focus in mental health may shift to slowing growth in cost-sharing for all health services. [ABSTRACT FROM AUTHOR]

Objective: To determine associations between need, enabling, and predisposing factors with mental health service use among National Guard soldiers in the first year following a combat deployment to Iraq or Afghanistan.Data Sources/study Setting: Primary data were collected between 2011 and 2013 from 1,426 Guard soldiers representing 36 units.Study Design: Associations between Guard soldier factors and any mental health service use were assessed using multivariable logistic regression models in a cross-sectional study. Further analysis among service users (N = 405) assessed VA treatment versus treatment in other settings.Principal Findings: Fifty-six percent of Guard soldiers meeting cutoffs on symptom scales received mental health services with 81 percent of those reporting care from the VA. Mental health service use was associated with need (mental health screens and physical health) and residing in micropolitan communities. Among service users, predisposing factors (middle age range and female gender) and enabling factors (employment, income above $50,000, and private insurance) were associated with greater non-VA services use.Conclusion: Overall service use was strongly associated with need, whereas sector of use (non-VA vs. VA) was insignificantly associated with need but strongly associated with enabling factors. These findings have implications for the recent extension of veteran health coverage to non-VA providers. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects of past Medicaid eligibility expansions to parents on coverage, access to care, out-of-pocket (OOP) spending, and mental health outcomes, and consider implications for the Affordable Care Act (ACA) Medicaid expansion.Data Sources: Person-level data from the National Health Interview Survey (1998-2010) is used to measure insurance coverage and related outcomes for low-income parents. Using state identifiers available at the National Center for Health Statistics Research Data Center, we attach state Medicaid eligibility thresholds for parents collected from a variety of sources to NHIS observations.Study Design: We use changes in the Medicaid eligibility threshold for parents within states over time to identify the effects of changes in eligibility on low-income parents.Principal Findings: We find that expanding Medicaid eligibility increases insurance coverage, reduces unmet needs due to cost and OOP spending, and improves mental health status among low-income parents. Moreover, our findings suggest that uninsured populations in states not currently participating in the ACA Medicaid expansion would experience even larger improvements in coverage and related outcomes than those in participating states if they chose to expand eligibility.Conclusions: The ACA Medicaid expansion has the potential to improve a wide variety of coverage, access, financial, and health outcomes for uninsured parents in states that choose to expand coverage. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effect of the Oregon and New Mexico Health Insurance Flexibility and Accountability (HIFA) demonstrations. HIFA is an optional state Medicaid expansion targeted at adults and children with incomes below 200 percent of the federal poverty level (FPL). The study has five research questions: What type of health insurance do HIFA enrollees self report in surveys? What are the demographic characteristics of these enrollees? What type of health insurance coverage, if any, did HIFA enrollees have just prior to enrollment in the HIFA program? Among those with prior coverage, what prompted participation in the HIFA program? What type of health insurance, if any, would HIFA enrollees have in the absence of HIFA?Methods: Data were collected via telephone interviews with a total of 406 enrollees from Oregon and 409 enrollees from New Mexico. The survey was conducted between July 7 and September 20, 2009, for both states. The sample frame for the survey was based on administrative records of adults enrolled in June 2009. After completion of the survey, active enrollment status as of the date the telephone interview was confirmed. Respondents no longer enrolled at the time of the survey (7 cases in NM and 14 in OR) were excluded from the analysis. The final sample size was 794 verified HIFA enrollees.Results: HIFA enrollees tended to be middle-aged, male, and relatively unhealthy. Employment status varied tremendously from the self-employed to retired to unable to work. HIFA enrollees were reasonably well educated with 80 percent having at least a high school education. Most HIFA enrollees (90 percent) reported being uninsured just prior to participation in HIFA. Of those who were uninsured, most reported having been uninsured for an extended time-a year or more. Most enrollees joined HIFA because they lacked access to health insurance or could not afford insurance on the private market. The overwhelming majority (76 percent) of respondents believed that they would be uninsured in the absence of HIFA, with few considering either an employer plan or private purchase to be a viable option. Over 90 percent of enrollees correctly indicated they had insurance coverage. However, characterization of the type of coverage was problematic, particularly in the absence of the program-specific name.Conclusions: HIFA enrolled a relatively sick, male, middle-aged population that tended to have been long-term uninsured--the kind of enrollees for which the programs were designed--with little apparent crowd-out of private insurance. The reported health status coupled with low incomes suggests that individual purchase is unlikely, a sentiment echoed by the respondents. In the absence of HIFA, most enrollees believed they would rejoin the ranks of the uninsured from where they came. [ABSTRACT FROM AUTHOR]

Objectives: To assess the feasibility of using existing claims-based algorithms to identify community-dwelling Medicare beneficiaries with disability based solely on the conditions for which they are being treated, and improving on these algorithms by combining them in predictive models.Data Source: Data on 12,415 community-dwelling fee-for-service Medicare beneficiaries who first responded to the Medicare Current Beneficiary Survey (MCBS) in 2003-2006.Study Design: Logistic regression models in which six claims-based disability indicators are used to predict self-reported disability. Receiver operating characteristic (ROC) curves were used to assess the performance of the predictive models.Principal Findings: The predictive performance of the regression-based models is better than that of the individual claims-based indicators. At a predicted probability threshold chosen to maximize the sum of sensitivity and specificity, sensitivity is 0.72 for beneficiaries age 65 or older and specificity is 0.65. For those under 65, sensitivity is 0.54 and specificity is 0.67. The findings also suggest ways to improve predictive performance for specific disability populations of interest to researchers.Conclusions: Predictive models that incorporate multiple claims-based indicators provide an improved tool for researchers seeking to identify people with disabilities in claims data. [ABSTRACT FROM AUTHOR]

Objective: To examine how similar racial/ethnic disparities in clinical quality (Healthcare Effectiveness Data and Information Set [HEDIS]) and patient experience (Consumer Assessment of Healthcare Providers and Systems [CAHPS]) measures are for different measures within Medicare Advantage (MA) plans.Data Sources/study Setting: 5.7 million/492,495 MA beneficiaries with 2008-2009 HEDIS/CAHPS data.Study Design: Binomial (HEDIS) and linear (CAHPS) hierarchical mixed models generated contract estimates for HEDIS/CAHPS measures for Hispanics, blacks, Asian-Pacific Islanders, and whites. We examine the correlation of within-plan disparities for HEDIS and CAHPS measures across measures.Principal Findings: Plans with disparities for a given minority group (vs. whites) for a particular measure have a moderate tendency for similar disparities for other measures of the same type (mean r = 0.51/.21 and 53/34 percent positive and statistically significant for CAHPS/HEDIS). This pattern holds to a lesser extent for correlations of CAHPS disparities and HEDIS disparities (mean r = 0.05/0.14/0.23 and 4.4/5.6/4.4 percent) positive and statistically significant for blacks/Hispanics/API.Conclusions: Similarities in CAHPS and HEDIS disparities across measures might reflect common structural factors, such as language services or provider incentives, affecting several measures simultaneously. Health plan structural changes might reduce disparities across multiple measures. [ABSTRACT FROM AUTHOR]

Objective: Rank county health using a Bayesian factor analysis model.Data Sources: Secondary county data from the National Center for Health Statistics (through 2007) and Behavioral Risk Factor Surveillance System (through 2009).Study Design: Our model builds on the existing county health rankings (CHRs) by using data-derived weights to compute ranks from mortality and morbidity variables, and by quantifying uncertainty based on population, spatial correlation, and missing data. We apply our model to Wisconsin, which has comprehensive data, and Texas, which has substantial missing information.Data Collection Methods: The data were downloaded from www.countyhealthrankings.org.Principal Findings: Our estimated rankings are more similar to the CHRs for Wisconsin than Texas, as the data-derived factor weights are closer to the assigned weights for Wisconsin. The correlations between the CHRs and our ranks are 0.89 for Wisconsin and 0.65 for Texas. Uncertainty is especially severe for Texas given the state's substantial missing data.Conclusions: The reliability of comprehensive CHRs varies from state to state. We advise focusing on the counties that remain among the least healthy after incorporating alternate weighting methods and accounting for uncertainty. Our results also highlight the need for broader geographic coverage in health data. [ABSTRACT FROM AUTHOR]