Adjusting for Health Status in Non-Linear Models of Health Care Disparities

Association of Disability Status and Type With Binge Drinking and Prescription Opioid Misuse Among Adults From a 3-State Sample

BACKGROUND

Research examining at-risk substance use by disability status is limited, with little investigation into differences by disability type. We investigated binge drinking and prescription opioid misuse among adults with and without disabilities, and by type of disability, to inform need for assessment and intervention within these populations.

METHODS

Secondary analyses of adults who completed the disability, alcohol, and prescription opioid misuse items in the 2018 Ohio, Florida, or Nebraska Behavioral Risk Factor Surveillance System surveys (n = 28 341), the only states that included prescription opioid misuse in 2018. Self-reported disability status (yes/no) relied on 6 standardized questions assessing difficulties with: vision, hearing, mobility, cognition, self-care, and independent living (dichotomous, nonmutually exclusive, for each disability). Logistic regression models estimated the association of disability status and type with (1) past 30-day binge drinking and (2) past-year prescription opioid misuse. Additional models were restricted to separate subsamples of adults who: (a) currently drink, (b) received a past-year prescription opioid, and (c) did not receive a past-year prescription opioid.

RESULTS

One-third reported at least one disability, with mobility (19.5%), cognitive (11.5%), and hearing (10.2%) disability being the most common. Disability status was associated with lower odds of binge drinking (adjusted odds ratio [AOR] = 0.74, 95% confidence interval [CI] 0.68-0.80, P ≤ .01). However, among adults who currently drink, people with disabilities had higher odds of binge drinking (AOR = 1.11, 95% CI 1.01-1.22, P ≤ .05]. Disability was associated with higher odds of past-year prescription opioid misuse (AOR = 2.51, 95% CI 2.17-2.91, P ≤ .01).

CONCLUSIONS

Adults with disabilities had higher odds of prescription opioid misuse, and among adults who currently drink, higher odds for binge drinking were observed. The magnitude of the association between disability status and prescription opioid misuse was particularly concerning. Providers should be trained to screen and treat for substance use problems for people with disabilities.

Evaluating Effects of Multilevel Interventions on Disparity in Health and Healthcare Decisions

In this paper, we introduce an analytic approach for assessing effects of multilevel interventions on disparity in health outcomes and health-related decision outcomes (i.e., a treatment decision made by a healthcare provider). We outline common challenges that are encountered in interventional health disparity research, including issues of effect scale and interpretation, choice of covariates for adjustment and its impact on effect magnitude, and the methodological challenges involved with studying decision-based outcomes. To address these challenges, we introduce total effects of interventions on disparity for the entire sample and the treated sample, and corresponding direct effects that are relevant for decision-based outcomes. We provide weighting and g-computation estimators in the presence of study attrition and sketch a simulation-based procedure for sample size determinations based on precision (e.g., confidence interval width). We validate our proposed methods through a brief simulation study and apply our approach to evaluate the RICH LIFE intervention, a multilevel healthcare intervention designed to reduce racial and ethnic disparities in hypertension control.

Social Risk Factors and Racial and Ethnic Disparities in Health Care Resource Utilization Among Medicare Advantage Beneficiaries With Psychiatric Disorders

The intersection of social risk and race and ethnicity on mental health care utilization is understudied. This study examined disparities in health care treatment, adjusting for clinical need, among 25,780 Medicare Advantage beneficiaries with a diagnosis of a psychiatric disorder. We assessed contributions to disparities from racial and ethnic differences in the composition and returns of social risk variables. Black and Hispanic beneficiaries had lower rates of mental health outpatient visits than Whites. Assessing composition, Black and Hispanic beneficiaries experienced greater financial, food, and housing insecurity than White beneficiaries, factors associated with greater mental health treatment. Assessing returns, food insecurity was associated with an exacerbation of Hispanic-White disparities. Health care systems need to address the financial, food and housing insecurity of racial and ethnic minority groups with psychiatric disorder. Accounting for racial and ethnic differences in social risk adjustment-based payment reforms has significant implications for provider reimbursement and outcomes.

Propensity score analysis for health care disparities: a deweighting approach

BACKGROUND

Propensity score weighting is a useful tool to make causal or unconfounded comparisons between groups. According to the definition by the Institute of Medicine (IOM), estimates of health care disparities should be adjusted for health-status factors but not for socioeconomic status (SES) variables. There have been attempts to use propensity score weighting to generate estimates that are concordant with IOM's definition. However, the existing propensity score methods do not preserve SES distributions in minority and majority groups unless SES variables are independent of health status variables.

METHODS

The present study introduces a deweighting method that uses two types of propensity scores. One is a function of all covariates of health status and SES variables and is used to weight study subjects to adjust for them. The other is a function of only the SES variables and is used to deweight the subjects to preserve the original SES distributions.

RESULTS

The procedure of deweighting is illustrated using a dataset from a right heart catheterization (RHC) study, where it was used to examine whether there was a disparity between black and white patients in receiving RHC. The empirical example provided promising evidence that the deweighting method successfully preserved the marginal SES distributions for both racial groups but balanced the conditional distributions of health status given SES.

CONCLUSIONS

Deweighting is a promising tool for implementing the IOM-definition of health care disparities. The method is expected to be broadly applied to quantitative research on health care disparities.

Federal Housing Assistance and Chronic Disease Among US Adults, 2005-2018

Introduction

Housing insecurity is associated with poor health outcomes. Characterization of chronic disease outcomes among adults with and without housing assistance would enable housing programs to better understand their population's health care needs.

Methods

We used National Health and Nutrition Examination Survey (NHANES) data from 2005 through 2018 linked to US Department of Housing and Urban Development (HUD) administrative records to estimate the prevalence of obesity, diabetes, and hypertension and to assess the independent associations between housing assistance and chronic conditions among adults receiving HUD assistance and HUD-assistance-eligible adults not receiving HUD assistance at the time of their NHANES examination. We estimated propensity scores to adjust for potential confounders among linkage-eligible adults who had an income-to-poverty ratio less than 2 and were not receiving HUD assistance. Sensitivity analysis used 2013-2018 NHANES cycles to account for disability status.

Results

Adults not receiving HUD assistance had a significantly lower adjusted prevalence of obesity (42.1%; 95% CI, 40.4%-43.8%) compared with adults receiving HUD assistance (47.5%; 95% CI, 44.8%-50.3%), but we found no differences for diabetes and hypertension. We found significant associations between housing assistance and obesity (adjusted odds ratio = 1.29; 95% CI, 1.12-1.47), but these were not significant in the sensitivity analysis with and without controlling for disability status. We found no significant associations between housing assistance and diabetes or hypertension.

Conclusion

Based on data from a cross-sectional survey, we observed a higher prevalence of obesity among adults with HUD assistance compared with HUD-assistance-eligible adults without HUD assistance. Results from this study can help inform research on understanding the prevalence of chronic disease among adults with HUD assistance.

Patient cognitive impairment associated with higher home health care delivery costs

OBJECTIVE

To assess whether home health agencies incur significantly higher care delivery costs for patients with cognitive impairment across three timeframes relevant to home health payment policy.

DATA SOURCES

Linked Medicare home health claims and patient assessments, National Health and Aging Trends Study (NHATS), and home health agency cost reports for a nationally representative sample of Medicare beneficiaries receiving home health between 2011 and 2016.

STUDY DESIGN

We modeled care delivery costs incurred by the home health agency as a function of patient cognitive impairment using multivariable, propensity score-adjusted, generalized linear models.

DATA COLLECTION/EXTRACTION METHODS

We identified NHATS participants who experienced an index home health episode between 2011 and 2016 (n = 1214; weighted n = 5,856,333) and linked their NHATS survey data to standardized patient assessment and claims data for the episode, as well as cost report data for the home health agency that provided care.

PRINCIPAL FINDINGS

Across the first 30, 60, and 120 days of caring for a patient with cognitive impairment, we estimate additional costs of care to the home health agency of $186.19 (p = 0.02), $282.46 (p = 0.01), and $740.91 (p = 0.04), respectively.

CONCLUSIONS

Home health agencies incur significantly higher costs when caring for a patient with cognitive impairment. As patient cognitive function is not considered in the most recent Medicare home health reimbursement model, agencies may be disincentivized from providing care to those with cognitive impairment. Policy makers and researchers should carefully monitor home health access among Medicare beneficiaries with cognitive impairment and further investigate the inclusion of patient cognitive function in future risk adjustment models.

Cognitive impairment associated with greater care intensity during home health care

BACKGROUND

In Medicare-funded home health care (HHC), one in three patients has cognitive impairment (CI), but little is known about the care intensity they receive in this setting. Recent HHC reimbursement changes fail to adjust for patient CI, potentially creating a financial disincentive to caring for these individuals.

METHODS

This cohort study included a nationally representative sample of 1214 Medicare HHC patients between 2011 and 2016. Multivariable logistic and negative binomial regressions modelled the relationship between patient CI and care intensity-measured as the number and type of visits received during HHC and likelihood of receiving multiple successive HHC episodes.

RESULTS

Patients with CI had 45% (P < .05) greater odds of receiving multiple successive HHC episodes and received an additional 2.82 total (P < .001), 1.39 nursing (P = .003), 0.72 physical therapy (P = .03), and 0.60 occupational therapy visits (P = .01) during the index HHC episode.

DISCUSSION

Recent HHC reimbursement changes do not reflect the more intensive care needs of patients with CI.

Family Caregiver Training Needs and Medicare Home Health Visit Utilization

BACKGROUND

Medicare home health providers are now required to deliver family caregiver training, but potential consequences for service intensity are unknown.

OBJECTIVE

The objective of this study was to assess how family caregiver training needs affect the number and type of home health visits received.

DESIGN

Observational study using linked National Health and Aging Trends Study (NHATS), Outcomes and Assessment Information Set (OASIS), and Medicare claims data. Propensity score adjusted, multivariable logistic, and negative binomial regressions model the relationship between caregivers' training needs and number/type of home health visits.

SUBJECTS

A total of 1217 (weighted n=5,870,905) National Health and Aging Trends Study participants receiving Medicare-funded home health between 2011 and 2016.

MEASURES

Number and type of home health visits, from Medicare claims. Family caregivers' training needs, from home health clinician reports.

RESULTS

Receipt of nursing visits was more likely when family caregivers had medication management [adjusted odds ratio (aOR): 3.03; 95% confidence interval (CI): 1.06, 8.68] or household chore training needs (aOR: 3.38; 95% CI: 1.33, 8.59). Receipt of therapy visits was more likely when caregivers had self-care training needs (aOR: 1.70; 95% CI: 1.01, 2.86). Receipt of aide visits was more likely when caregivers had household chore (aOR: 3.54; 95% CI: 1.82, 6.92) or self-care training needs (aOR: 2.12; 95% CI: 1.11, 4.05). Medication management training needs were associated with receiving an additional 1.06 (95% CI: 0.11, 2.01) nursing visits, and household chores training needs were associated with an additional 3.24 total (95% CI: 0.21, 6.28) and 1.32 aide visits (95% CI: 0.36, 2.27).

CONCLUSION

Family caregivers' activity-specific training needs may affect home health visit utilization.

Decomposition analysis as a framework for understanding heterogeneity of treatment effects in non-randomized health care studies

This paper uses the decomposition framework from the economics literature to examine the statistical structure of treatment effects estimated with observational data compared to those estimated from randomized studies. It begins with the estimation of treatment effects using a dummy variable in regression models and then presents the decomposition method from economics which estimates separate regression models for the comparison groups and recovers the treatment effect using bootstrapping methods. This method shows that the overall treatment effect is a weighted average of structural relationships of patient features with outcomes within each treatment arm and differences in the distributions of these features across the arms. In large randomized trials, it is assumed that the distribution of features across arms is very similar. Importantly, randomization not only balances observed features but also unobserved. Applying high dimensional balancing methods such as propensity score matching to the observational data causes the distributional terms of the decomposition model to be eliminated but unobserved features may still not be balanced in the observational data. Finally, a correction for non-random selection into the treatment groups is introduced via a switching regime model. Theoretically, the treatment effect estimates obtained from this model should be the same as those from a randomized trial. However, there are significant challenges in identifying instrumental variables that are necessary for estimating such models. At a minimum, decomposition models are useful tools for understanding the relationship between treatment effects estimated from observational versus randomized data.

Medicaid Expansion and Racial and Ethnic Disparities in Access to Health Care: Applying the National Academy of Medicine Definition of Health Care Disparities

Since 2014, 32 states implemented Medicaid expansion by removing the categorical criteria for childless adults and by expanding income eligibility to 138% of the federal poverty level (FPL) for all non-elderly adults. Previous studies found that the Affordable Care Act (ACA) Medicaid expansion improved rates of being insured, unmet needs for care due to cost, number of physician visits, and health status among low-income adults. However, a few recent studies focused on the expansion's effect on racial/ethnic disparities and used the National Academy of Medicine (NAM) disparity approach with a limited set of access measures. This quasi-experimental study examined the effect of Medicaid expansion on racial/ethnic disparities in access to health care for U.S. citizens aged 19 to 64 with income below 138% of the federal poverty line. The difference-in-differences model compared changes over time in 2 measures of insurance coverage and 8 measures of access to health care, using National Health Interview Survey (NHIS) data from 2010 to 2016. Analyses used the NAM definition of disparities. Medicaid expansion was associated with significant decreases in uninsured rates and increases in Medicaid coverage among all racial/ethnic groups. There were differences across racial/ethnic groups regarding which specific access measures improved. For delayed care and unmet need for care, decreases in racial/ethnic disparities were observed. After the ACA Medicaid expansion, most access outcomes improved for disadvantaged groups, but also for others, with the result that disparities were not significantly reduced.

Effect of the Patient-Centered Medical Home on Racial Disparities in Quality of Care

BACKGROUND

Research demonstrates that the patient-centered medical home (PCMH) is associated with improved clinical outcomes and quality of care, and the populations that can most benefit from this model require long-term management, e.g., persons with chronic illness and behavioral health conditions. However, different populations may not benefit equally from the PCMH, and empirical evidence about the effects of this model on racial disparities is limited.

OBJECTIVE

Estimate the association between enrollment in National Committee for Quality Assurance (NCQA)-recognized PCMHs and racial disparities in quality of care for adults with major depressive disorder (MDD) and comorbid medical conditions.

DESIGN

Applying a quasi-experimental instrumental variable design to account for differential selection into the PCMH, we used generalized estimating equations to determine the probability of receiving eight disease-specific quality measures.

SUBJECTS

Medicaid enrollees in three states not dually enrolled in Medicare, ages 18-64 with MDD and > 1 other chronic condition. A subgroup analysis was conducted for enrollees with comorbid diabetes.

INTERVENTIONS

Enrollment in an NCQA-recognized PCMH.

MAIN MEASURES

Disease-specific quality indicators for MDD (e.g., antidepressant use, receipt of psychotherapy), and for diabetes, (e.g. A1c testing, LDL-C testing, retinal exams, and medical attention for nephropathy).

KEY RESULTS

PCMH enrollment was associated with an increase in the overall likelihood of receiving six of eight recommended services and a decrease in the likelihood of receiving any psychotherapy (4.94 percentage points, p < 0.01) and retinal exams (5.51 percentage points, p < 0.05). Although both groups improved, PCMH enrollment was associated with an exacerbation of the Black-white disparity in adequate antidepressant use by 4.20 percentage points (p < 0.01).

CONCLUSIONS

While PCMH enrollment may improve the overall quality of care, the effect is inconsistent across racial groups and not always associated with reductions in racial disparities in quality.

Disparities in Shared Decision Making and Service Receipt Among Children With Special Health Care Needs and Developmental Delay: A National Survey Analysis

Shared decision making (SDM) is associated with increased service satisfaction among pediatric patients. Our objective was to examine the association between SDM and service use experiences across racial/ethnic child groups. This secondary data analysis used the 2009-2010 National Survey of Children with Special Health Care Needs (CSHCN) and 2011 Pathways to Diagnosis and Services Survey. We used a rank-and-replace matching approach consistent with Institute of Medicine recommendations for health disparities research. We included CSHCN aged 6 to 17 years. The exposure of interest was parents of CSHCN reporting engagement in SDM with clinicians. There were 4032 CSHCN included in analysis. CSHCNs experiencing SDM had a 16% higher probability of reporting service use compared to those not experiencing it (95% CI, 14.24-19.42). Black children experiencing SDM reported seeing all needed care providers at a lower rate than whites (79% and 87.6% respectively; 95% CI, -14.05-3.27). The benefit of SDM over not experiencing it for blacks was 12.2% less than for whites for the outcome of seeing all needed care providers. For the outcome of receiving all needed treatments and services, the SDM benefit was 9.1% lower for Hispanics compared with whites. SDM can improve service experiences but implementation flexibility may be needed.

Assessing national and subnational inequalities in medical care utilization and financial risk protection in Rwanda

Background

Ensuring equitable access to medical care with financial risk protection has been at the center of achieving universal health coverage. In this paper, we assess the levels and trends of inequalities in medical care utilization and household catastrophic health spending (HCHS) at the national and sub-national levels in Rwanda.

Methods

Using the Rwanda Integrated Living Conditions Surveys of 2005, 2010, 2014, and 2016, we applied multivariable logit models to generate the levels and trends of adjusted inequalities in medical care utilization and HCHS across the four survey years by four socio-demographic dimensions: poverty, gender, education, and residence. We measured the national- and district-level inequalities in both absolute and relative terms.

Results

At the national level, after controlling for other factors, we found significant inequalities in medical care utilization by poverty and education and -in HCHS by poverty in all four years. From 2005 to 2016, inequalities in medical care utilization by the four dimensions did not change significantly, while the inequality in HCHS by poverty was reduced significantly. At the district level, inequalities in both medical care utilization and HCHS were larger than zero in all four years and decreased over time.

Conclusions

Poverty and poor education were significant contributors to inequalities in medical care utilization and HCHS in Rwanda. Policies or interventions targeting poor households or households headed by persons receiving no education are needed in order to effectively reduce inequalities in medical care utilization and HCHS.

Electronic supplementary material

The online version of this article (10.1186/s12939-019-0953-y) contains supplementary material, which is available to authorized users.

Do racial and ethnic disparities in health care use vary with health?

OBJECTIVE

To determine the relationship between health status and the magnitude of black-white and Hispanic-white disparities in the likelihood of having any office-based or hospital outpatient department visits, as well as number of visits.

DATA SOURCE

2010-2014 Medical Expenditure Panel Survey.

STUDY DESIGN

The probability of having a visit is modeled using a Probit model, and the number of visits using a negative binomial model. We use a nonlinear rank-and-replace method to adjust minority health status to be comparable to that of whites, and predict utilization at different levels of health by fixing an indicator of health status. We compare estimated differences in predicted utilization across racial/ethnic groups for each level of health status to map out the relationship between the racial/ethnic disparity and health status, also stratifying by health insurance coverage.

EXTRACTION METHODS

We subset to nonelderly adults.

PRINCIPAL FINDINGS

We find that Hispanic-white differences in the probability of having an office-based or hospital outpatient department were widest among adults in excellent health (27 percentage points, 95% CI: [23, 31]) and narrowest when reporting poor or fair health (15 p.p. [13, 17]). Black-white and Hispanic-white differences in the number of visits were wider for adults who report poor or fair health (5.3 visits [4.0, 6.6] and 5.7 [4.3, 7.0], respectively) compared to excellent health (1.7 [1.2, 2.1] and 1.5 [1.1, 2.0], respectively) among adults who are full-year privately insured.

CONCLUSIONS

The magnitudes of racial/ethnic disparities vary with level of health.

Measuring Geographic "Hot Spots" of Racial/Ethnic Disparities: An Application to Mental Health Care

This article identifies geographic "hot spots" of racial/ethnic disparities in mental health care access. Using data from the 2001-2003 Collaborative Psychiatric Epidemiology Surveys(CPES), we identified metropolitan statistical areas(MSAs) with the largest mental health care access disparities ("hot spots") as well as areas without disparities ("cold spots"). Racial/ethnic disparities were identified after adjustment for clinical need. Richmond, Virginia and Columbus, Georgia were found to be hot spots for Black-White disparities, regardless of method used. Fresno, California and Dallas, Texas were ranked as having the highest Latino-White disparities and Riverside, California and Houston, Texas consistently ranked high in Asian-White mental health care disparities across different methods. We recommend that institutions and government agencies in these "hot spot" areas work together to address key mechanisms underlying these disparities. We discuss the potential and limitations of these methods as tools for understanding health care disparities in other contexts.

Supplemental Insurance and Racial Health Disparities under Medicare Part B

OBJECTIVE

To assess the impact of preferences, socioeconomic status (SES), and supplemental insurance (SI) on racial/ethnic disparities in the probability and use of services at physicians' offices, hospitals, and emergency departments among Medicare beneficiaries enrolled in Part B.

RESEARCH DESIGN AND SUBJECTS

This study includes black and white beneficiaries from the 2009-2011 panel of the Medicare Current Beneficiary Survey who were enrolled in Medicare Part B. Logit and negative binomial multivariate regression analysis were used in conjunction with rank-and-replace methods to determine factors influencing utilization and black-white utilization disparities.

PRINCIPAL FINDINGS

Among Part B beneficiaries, significant disparities exist for each studied service. Examining contributing factors, 12-19 percent of the black-white health-adjusted difference in the probability of use is explained by differences in SES, whereas differences in the distribution of SI accounts for 20 percent or more. For volume, SES is found to account for 2-11 percent of differences with SI making up another 9-10 percent.

CONCLUSIONS

A substantial portion of the difference in black-white beneficiary use of outpatient services is due to SI. Policies aimed at increasing coverage are likely to increase the probability of visits with modest increases in volume.

Impact of comorbid mental health needs on racial/ethnic disparities in general medical care utilization among older adults

OBJECTIVE

The objective is to apply the Institute of Medicine definition of healthcare disparities in order to compare (1) racial/ethnic disparities in general medical care use among older adults with and without comorbid mental health need and (2) racial/ethnic disparities in general medical care use within the group with comorbid mental health need.

METHODS

Data were obtained from the Medical Expenditure Panel Survey (years 2004-2012). The sample included 21,263 participants aged 65+ years (14,973 non-Latino Caucasians, 3530 African-Americans, and 2760 Latinos). Physical illness was determined by having one of the 11 priority chronic health illnesses. Comorbid mental health need was defined as having one of the chronic illnesses plus a Kessler-6 Scale >12, or two-item Patient Health Questionnaire >2. General medical care use refers to receipt of non-mental health specialty care. Two-part generalized linear models were used to estimate and compare general medical care use and expenditures among older adults with and without a comorbid mental health need.

RESULTS

Racial/ethnic disparities in general medical care expenditures were greater among those with comorbid mental health need compared with those without. Among those with comorbid mental health need, non-Latino Caucasians had significantly greater expenditures on prescription drug use than African-Americans and Latinos.

CONCLUSIONS

Expenditure disparities reflect differences in the amount of resources provided to African-Americans and Latinos compared with non-Latino Caucasians. This is not equivalent to disparities in quality of care. Interventions and policies are needed to ensure that racial/ethnic minority older adults receive equitable services that enable them to manage effectively their comorbid mental and physical health needs. Copyright © 2016 John Wiley & Sons, Ltd.

The Effect of Medicare Part D on Prescription Drug Spending and Health Care Use: 6 Years of Follow-up, 2007-2012

BACKGROUND

Previous studies have shown that Medicare Part D was associated with a reduction in out-of-pocket expenditures for Medicare beneficiaries during the early years of its implementation (2006 and 2007). However, a question remains regarding the effect of Part D on out-of-pocket expenditures in the longer term.

OBJECTIVE

To evaluate the effects of Part D on prescription drug expenditures and certain health care use for a longer time period using a large, nationally representative sample of Medicare beneficiaries.

METHODS

Using Medical Expenditure Panel Survey (MEPS) data from 2000 through 2005 (pre-Part D period) and from 2007 through 2012 (Part D era), this study identified a cohort of elderly Medicare beneficiaries (treatment group) and a near-elderly non-Medicare population (control group). A difference-in-differences analysis was conducted to estimate the effect of Part D on prescription medication use and expenditures and outpatient visits. Propensity score weights and sampling weights were applied to obtain unbiased effect estimates accounting for complex survey designs.

RESULTS

A total of 26,585 elderly Medicare beneficiaries and 20,688 near-elderly non-Medicare beneficiaries were identified. The introduction of Part D was associated with an adjusted average reduction of $105 in annual out-of-pocket spending on prescription drugs during the post-Part D period (2007 through 2012). The reduction in annual out-of-pocket spending ranged from $49 to $152 during the post-Part D period. No significant increase was found in total prescription expenditures or prescription medication use following the introduction of Part D nor were there significant changes in outpatient visits.

CONCLUSIONS

A continued reduction of Part D out-of-pocket drug expenditures was found each year from 2007 to 2012.

DISCLOSURES

No funding has been received to conduct this study or prepare this manuscript. The authors have no conflicts of interest to declare. Study concept and design were primarily contributed by Park with assistance from Jung. Both authors contributed equally to data analysis and interpretation. The manuscript was written primarily by Park, with assistance from Jung, and revised primarily by Jung.

Effects of Psychiatric Disorders on Labor Market Outcomes: A Latent Variable Approach Using Multiple Clinical Indicators

In this paper, we estimate the effect of psychiatric disorders on labor market outcomes using a structural equation model with a latent index for mental illness, an approach that acknowledges the continuous nature of psychiatric disability. We also address the potential endogeneity of mental illness using an approach proposed by Lewbel (2012) that relies on heteroscedastic covariance restrictions rather than questionable exclusion restrictions for identification. Data come from the US National Comorbidity Survey - Replication and the National Latino and Asian American Study. We find that mental illness adversely affects employment and labor force participation and also reduces the number of weeks worked and increases work absenteeism. To assist in the interpretation of findings, we simulate the labor market outcomes of individuals meeting diagnostic criteria for mental disorder if they had the same mental health symptom profile as individuals not meeting diagnostic criteria. We estimate potential gains in employment for 3.5 million individuals, and reduction in workplace costs of absenteeism of $21.6 billion due to the resultant improvement in mental health. Copyright © 2015 John Wiley & Sons, Ltd.

Trends in Racial-Ethnic Disparities in Access to Mental Health Care, 2004-2012

OBJECTIVE

This study compared trends in racial-ethnic disparities in mental health care access among whites, blacks, Hispanics, and Asians by using the Institute of Medicine definition of disparities as all differences except those due to clinical appropriateness, clinical need, and patient preferences.

METHODS

Racial-ethnic disparities in mental health care access were examined by using data from a nationally representative sample of 214,597 adults from the 2004-2012 Medical Expenditure Panel Surveys. The main outcome measures included three mental health care access measures (use of any mental health care, any outpatient care, and any psychotropic medication in the past year).

RESULTS

Significant disparities were found in 2004-2005 and in 2011-2012 for all three racial-ethnic minority groups compared with whites in all three measures of access. Between 2004 and 2012, black-white disparities in any mental health care and any psychotropic medication use increased, respectively, from 8.2% to 10.8% and from 7.6% to 10.0%. Similarly, Hispanic-white disparities in any mental health care and any psychotropic medication use increased, respectively, from 8.4% to 10.9% and 7.3% to 10.3%.

CONCLUSIONS

No reductions in racial-ethnic disparities in access to mental health care were identified between 2004 and 2012. For blacks and Hispanics, disparities were exacerbated over this period. Clinical interventions that improve identification of symptoms of mental illness, expansion of health insurance, and other policy interventions that remove financial barriers to access may help to reduce these disparities.

Housing Assistance and Blood Lead Levels: Children in the United States, 2005-2012

OBJECTIVES

To compare blood lead levels (BLLs) among US children aged 1 to 5 years according to receipt of federal housing assistance.

METHODS

In our analyses, we used 2005 to 2012 data for National Health and Nutrition Examination Survey (NHANES) respondents that were linked to 1999 to 2014 administrative records from the US Department of Housing and Urban Development (HUD). After we restricted the analysis to children with family income-to-poverty ratios below 200%, we compared geometric mean BLLs and the prevalence of BLLs of 3 micrograms per deciliter or higher among children who were living in assisted housing at the time of their NHANES blood draw (n = 151) with data for children who did not receive housing assistance (n = 1099).

RESULTS

After adjustment, children living in assisted housing had a significantly lower geometric mean BLL (1.44 µg/dL; 95% confidence interval [CI] = 1.31, 1.57) than comparable children who did not receive housing assistance (1.79 µg/dL; 95% CI = 1.59, 2.01; P < .01). The prevalence ratio for BLLs of 3 micrograms per deciliter or higher was 0.51 (95% CI = 0.33, 0.81; P < .01).

CONCLUSIONS

Children aged 1 to 5 years during 2005 to 2012 who were living in HUD-assisted housing had lower BLLs than expected given their demographic, socioeconomic, and family characteristics.

Impact of Medicare Part D on Racial Disparities in Adherence to Cardiovascular Medications Among the Elderly

Medicare Part D improved medication adherence among the elderly, but to date, its effect on disparities in adherence remains unknown. We estimated Part D impact on racial/ethnic disparities in adherence to cardiovascular medications among seniors, using pooled data from the Medical Expenditure Panel Survey (2002-2010) on 14,221 Medicare recipients (65+ years) and 3,456 near-elderly controls (60-64 years). Study sample included White, Black, or Hispanic respondents who used at least one cardiovascular medication. Twelve-month adherence was measured as having an overall proportion of days covered ≥80%. Adherence disparities were defined according to the Institute of Medicine framework. Using difference-in-differences logistic regression, we found Part D to be associated with a 16-percentage-point decrease in the White-Hispanic disparity in overall adherence among seniors, net of the change among controls. Black-White disparities worsened only among men, by 21 percentage points. Increasing access and improving quality of medication use among disadvantaged seniors should remain a policy priority.

Relationship Between General Illness and Mental Health Service Use and Expenditures Among Racially-Ethnically Diverse Adults ≥65 Years

OBJECTIVES

The association of general medical illness and mental health service use among older adults from racial-ethnic minority groups is an important area of study given the disparities in mental health and general medical services and the low use of mental health services in this population. The purpose of this report is to describe the impact of comorbid general medical illness on mental health service use and expenditures among older adults and to evaluate disparities in mental health service use and expenditures in a racially-ethnically diverse sample of older adults with and without comorbid general medical illness.

METHODS

Data were obtained from the Medical Expenditure Panel Survey (years 2004-2011). The sample included 1,563 whites, 519 African Americans, and 642 Latinos (N=2,724) age ≥65 with probable mental illness. Two-part generalized linear models were used to estimate and compare mental health service use among adults with and without a comorbid general medical illness.

RESULTS

Mental health service use was more likely for older adults with comorbid general medical illness than for those without it. Once mental health services were accessed, no differences in mental health expenditures were found. Comorbid general medical illness increased the likelihood of mental health service use by older whites and Latinos. However, the presence of comorbidity did not affect racial-ethnic disparities in mental health service use.

CONCLUSIONS

This study highlighted the important role of comorbid general medical illness as a potential contributor to using mental health services and suggests intervention strategies to enhance engagement in mental health services by older adults from racial-ethnic minority groups.

Are Partial Workplace Smoking Bans as Effective as Complete Smoking Bans? A National Population-Based Study of Smoke-Free Policy Among Japanese Employees

INTRODUCTION

Although complete workplace smoking bans are generally recommended rather than partial bans, the latter are widespread in many countries, especially Japan. Our objective was to compare complete workplace smoking bans and partial bans for associations with employee smoking and secondhand smoke (SHS)-related discomfort/ill-health. We also evaluated complete bans versus no ban and partial bans versus no ban.

METHODS

Eleven thousand ninety eligible employees (weighted number: 34 353 241) aged 20-64 years in 2011 (response rate: 62.5%) were analyzed using a nationally-representative, population-based cross-sectional study. Adjusted prevalence ratios for self-reported current smoking and SHS-related discomfort/ill-health according to workplace smoke-free policies were calculated, using conventional regression and propensity score (PS) weighting (targeting population of average treatment effect among both treated [TET] and untreated [TEU]).

RESULTS

Both conventional regressions and PS weighting analyses showed complete bans were significantly associated with lower prevalence of current smoking and perceived SHS-related discomfort/ill-health among nonsmokers than partial or no ban. In contrast, partial bans were not significantly associated with either outcome compared with no ban. Using several PS trimming levels, we found interesting differences between TET and TEU in a comparison between partial and no ban: that is, significant associations in TET estimations, but none in TEU estimations.

CONCLUSIONS

Although complete smoking bans were associated with lower levels of employee smoking and SHS-related discomfort/ill-health compared with no smoking ban, partial bans were not. Findings from PS weighting of TEU suggest that partial workplace bans may not be any more effective for Japanese employees than no ban. Therefore, complete bans may be strongly recommended for future implementation, but careful interpretation of the data is necessary because of the cross-sectional study design.

Translating disparities research to policy: a qualitative study of state mental health policymakers' perceptions of mental health care disparities report cards

Report cards have been used to increase accountability and quality of care in health care settings, and to improve state infrastructure for providing quality mental health care services. However, to date, report cards have not been used to compare states on racial/ethnic disparities in mental health care. This qualitative study examines reactions of mental health care policymakers to a proposed mental health care disparities report card generated from population-based survey data of mental health and mental health care utilization. We elicited feedback about the content, format, and salience of the report card. Interviews were conducted with 9 senior advisors to state policymakers and 1 policy director of a national nongovernmental organization from across the United States. Four primary themes emerged: fairness in state-by-state comparisons; disconnect between the goals and language of policymakers and researchers; concerns about data quality; and targeted suggestions from policymakers. Participant responses provide important information that can contribute to making evidence-based research more accessible to policymakers. Further, policymakers suggested ways to improve the structure and presentation of report cards to make them more accessible to policymakers, and to foster equity considerations during the implementation of new health care legislation. To reduce mental health care disparities, effort is required to facilitate understanding between researchers and relevant stakeholders about research methods, standards for interpretation of research-based evidence, and its use in evaluating policies aimed at ameliorating disparities.

Risk adjustment and observation time: comparison between cross-sectional and 2-year panel data from the Medical Expenditure Panel Survey (MEPS)

Background

Risk adjustment models were used to estimate health care consumption after adjusting for individual characteristics or other factors. The results of this technique were not satisfying. One reason could be that the length of time to document consumption might be associated with the mean and variance of observed health care consumption. This study aims to use a simplified mathematical model and real-world data to explore the relationship of observation time (one or two years) and predictability.

Methods

This study used cross-sectional (one-year) and 2-year panel data sets of the Medical Expenditure Panel Survey (MEPS) from 1996 to 2008. Comparisons of the health care consumption (total health expenditure, emergency room (ER) and office-based visits) included ratios of means and standard errors (SEs). Risk adjustment models for one- and two-year data used generalized linear model.

Results

The ratios of mean health care consumption (two-year to one-year total expenditure, ER and office-based visits) seemed to be two in most age groups and the ratios of SEs varied around or above two. The R-squared of two-year models seemed to be slightly better than that of one-year models.

Conclusions

We find health expenditure and ER or office-based visits observed in two consecutive years were about twice those observed in a single year for most age, similar to the ratios predicted in mathematical examples. The ratios of mean spending and visits varied across age groups. The other finding is that the predictability of two-year consumption seems better than that of one-year slightly. The reason is not clear and we will continue studying this phenomenon.

Electronic supplementary material

The online version of this article (doi:10.1186/2047-2501-2-5) contains supplementary material, which is available to authorized users.

Quality of follow-up after hospitalization for mental illness among patients from racial-ethnic minority groups

OBJECTIVE

Outpatient follow-up after hospitalization for mental health reasons is an important indicator of quality of health systems. Differences among racial-ethnic minority groups in the quality of service use during this period are understudied. This study assessed the quality of outpatient treatment episodes following inpatient psychiatric treatment among blacks, whites, and Latinos in the United States.

METHODS

The Medical Expenditure Panel Survey (2004-2010) was used to identify adults with any inpatient psychiatric treatment (N=339). Logistic regression models were used to estimate predictors of any outpatient follow-up or the beginning of adequate outpatient follow-up within seven or 30 days following discharge. Predicted disparities were calculated after adjustment for clinical need variables but not for socioeconomic characteristics, consistent with the Institute of Medicine definition of health care disparities as differences that are unrelated to clinical appropriateness, need, or patient preference.

RESULTS

Rates of follow-up were generally low, particularly rates of adequate treatment (<26%). Outpatient treatment prior to inpatient care was a strong predictor of all measures of follow-up. After adjustment for need and socioeconomic status, the analyses showed that blacks were less likely than whites to receive any treatment or begin adequate follow-up within 30 days of discharge.

CONCLUSIONS

Poor integration of follow-up treatment in the continuum of psychiatric care leaves many individuals, particularly blacks, with poor-quality treatment. Culturally appropriate interventions that link individuals in inpatient settings to outpatient follow-up are needed to reduce racial-ethnic disparities in outpatient mental health treatment following acute treatment.

Assessing incentives for service-level selection in private health insurance exchanges

Even with open enrollment and mandated purchase, incentives created by adverse selection may undermine the efficiency of service offerings by plans in the new health insurance Exchanges created by the Affordable Care Act. Using data on persons likely to participate in Exchanges drawn from five waves of the Medical Expenditure Panel Survey, we measure plan incentives in two ways. First, we construct predictive ratios, improving on current methods by taking into account the role of premiums in financing plans. Second, relying on an explicit model of plan profit maximization, we measure incentives based on the predictability and predictiveness of various medical diagnoses. Among the chronic diseases studied, plans have the greatest incentive to skimp on care for cancer, and mental health and substance abuse.

Assessing racial/ethnic disparities in treatment across episodes of mental health care

OBJECTIVE

To investigate disparities in mental health care episodes, aligning our analyses with decisions to start or drop treatment, and choices made during treatment.

STUDY DESIGN

We analyzed whites, blacks, and Latinos with probable mental illness from Panels 9-13 of the Medical Expenditure Panel Survey, assessing disparities at the beginning, middle, and end of episodes of care (initiation, adequate care, having an episode with only psychotropic drug fills, intensity of care, the mixture of primary care provider (PCP) and specialist visits, use of acute psychiatric care, and termination).

FINDINGS

Compared with whites, blacks and Latinos had less initiation and adequacy of care. Black and Latino episodes were shorter and had fewer psychotropic drug fills. Black episodes had a greater proportion of specialist visits and Latino episodes had a greater proportion of PCP visits. Blacks were more likely to have an episode with acute psychiatric care.

CONCLUSIONS

Disparities in adequate care were driven by initiation disparities, reinforcing the need for policies that improve access. Many episodes were characterized only by psychotropic drug fills, suggesting inadequate medication guidance. Blacks' higher rate of specialist use contradicts previous studies and deserves future investigation. Blacks' greater acute mental health care use raises concerns over monitoring of their treatment.

Propensity-score matching in economic analyses: comparison with regression models, instrumental variables, residual inclusion, differences-in-differences, and decomposition methods

This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.

Generalizing observational study results: applying propensity score methods to complex surveys

OBJECTIVE

To provide a tutorial for using propensity score methods with complex survey data.

DATA SOURCES

Simulated data and the 2008 Medical Expenditure Panel Survey.

STUDY DESIGN

Using simulation, we compared the following methods for estimating the treatment effect: a naïve estimate (ignoring both survey weights and propensity scores), survey weighting, propensity score methods (nearest neighbor matching, weighting, and subclassification), and propensity score methods in combination with survey weighting. Methods are compared in terms of bias and 95 percent confidence interval coverage. In Example 2, we used these methods to estimate the effect on health care spending of having a generalist versus a specialist as a usual source of care.

PRINCIPAL FINDINGS

In general, combining a propensity score method and survey weighting is necessary to achieve unbiased treatment effect estimates that are generalizable to the original survey target population.

CONCLUSIONS

Propensity score methods are an essential tool for addressing confounding in observational studies. Ignoring survey weights may lead to results that are not generalizable to the survey target population. This paper clarifies the appropriate inferences for different propensity score methods and suggests guidelines for selecting an appropriate propensity score method based on a researcher's goal.

Differences in diffusion of FDA antidepressant risk warnings across racial-ethnic groups

OBJECTIVE Numerous articles have identified that medical technologies diffuse more rapidly among non-Latino whites compared with other racial-ethnic groups. However, whether health risk warnings also diffuse differentially across racial-ethnic minority groups is uncertain. This study assessed racial-ethnic variation in children's antidepressant use before and after the 2004 black-box warning concerning risks of antidepressants for youths. METHODS Data consisted of responses for white, black, and Latino youths ages five through 17 from the 2002-2008 Medical Expenditure Panel Survey (N=44,422). The dependent variable was any antidepressant use in the prior year. Independent variables were race-ethnicity, year, psychological impairment, income, insurance status, region, and parents' education level. Logistic regression models were used to assess antidepressant use conditional on race-ethnicity, time, interaction between race-ethnicity and time, need, socioeconomic status, and Institute of Medicine-concordant estimates of disparities in predicted antidepressant use before and after the warning. RESULTS The warnings affected antidepressant use differentially for whites, blacks, and Latinos. Usage rates among whites decreased from 3.3 to 2.1 percentage points between prewarning and postwarning, whereas usage rates remained steady among Latinos and increased among blacks. Findings were significant in multiple regression analyses, in which predictions were adjusted for need. CONCLUSIONS The findings indicate that health safety information on antidepressant usage among children diffused faster among whites than nonwhites, suggesting the need to improve infrastructure for delivering important health messages to racial-ethnic minority populations.

Disparities in mental health service use of racial and ethnic minority elderly adults

OBJECTIVES

To apply the Institute of Medicine definition of healthcare disparities, to measure disparities in different aspects of episodes of mental health care and to identify disparities in types of mental health services used.

DESIGN

Four 2-year longitudinal datasets from Panels 9 to 13 (2004-2009) of the Medical Expenditure Panel Surveys were combined.

SETTING

Large-scale surveys of families and individuals and their medical providers across the United States.

PARTICIPANTS

One thousand six hundred fifty-eight participants (981 white, 303 black, and 374 Latino) aged 60 and older with probable mental healthcare needs.

MEASUREMENTS

Mental healthcare need was defined as a Kessler-6 Scale score >12 and a Patient Health Questionnaire-2 score >2. Five aspects of mental healthcare episodes were analyzed: treatment initiation, adequacy of care, duration of care, number of visits, and expenditures. Whether episodes of care included only prescription drug fills, only outpatient visits, or both was assessed.

RESULTS

Treatment initiation and adequacy were lower for blacks and Latinos than whites. Latinos experienced episodes of longer duration, more visits, and higher expenditures. Blacks and Latinos had significantly lower rates of episodes that consisted of only medication refills. Blacks had significantly greater rates of episodes with only outpatient care visits. Latinos had significantly higher rates of medication plus outpatient visits.

CONCLUSION

Low mental health treatment initiation and poor adequacy suggest the need for culturally appropriate interventions to engage older blacks and Latinos in mental health care. The surprising findings in blacks (higher rates of outpatient care visits) and Latinos (higher rates of medication plus outpatient visits) highlight the complexities of the older adult population and suggest new avenues for disparities research.

Looking to the future: incorporating genomic information into disparities research to reduce measurement error and selection bias

OBJECTIVE

To extend recent conceptual and methodological advances in disparities research to include the incorporation of genomic information in analyses of racial/ethnic disparities in health care and health outcomes.

DATA SOURCES

Published literature on human genetic variation, the role of genetics in disease and response to treatment, and methodological developments in disparities research.

STUDY DESIGN

We present a conceptual framework for incorporating genomic information into the Institute of Medicine definition of racial/ethnic disparities in health care, identify key concepts used in disparities research that can be informed by genomics research, and illustrate the incorporation of genomic information into current methods using the example of HER-2 mutations guiding care for breast cancer.

PRINCIPAL FINDINGS

Genomic information has not yet been incorporated into disparities research, though it has direct relevance to concepts of race/ethnicity, health status, appropriate care, and socioeconomic status. The HER-2 example demonstrates how available genetic information can be incorporated into current disparities methods to reduce selection bias and measurement error. Advances in health information infrastructure may soon make standardized genetic information more available to health services researchers.

CONCLUSION

Genomic information can refine measurement of racial/ethnic disparities in health care and health outcomes and should be included wherever possible in disparities research.

Measuring racial/ethnic disparities in health care: methods and practical issues

OBJECTIVE

To review methods of measuring racial/ethnic health care disparities.

STUDY DESIGN

Identification and tracking of racial/ethnic disparities in health care will be advanced by application of a consistent definition and reliable empirical methods. We have proposed a definition of racial/ethnic health care disparities based in the Institute of Medicine's (IOM) Unequal Treatment report, which defines disparities as all differences except those due to clinical need and preferences. After briefly summarizing the strengths and critiques of this definition, we review methods that have been used to implement it. We discuss practical issues that arise during implementation and expand these methods to identify sources of disparities. We also situate the focus on methods to measure racial/ethnic health care disparities (an endeavor predominant in the United States) within a larger international literature in health outcomes and health care inequality. EMPIRICAL APPLICATION: We compare different methods of implementing the IOM definition on measurement of disparities in any use of mental health care and mental health care expenditures using the 2004-2008 Medical Expenditure Panel Survey.

CONCLUSION

Disparities analysts should be aware of multiple methods available to measure disparities and their differing assumptions. We prefer a method concordant with the IOM definition.

Decomposing racial and ethnic disparities in the use of postacute rehabilitation care

OBJECTIVE

To determine the degree to which racial and ethnic disparities in the use of postacute rehabilitation care (PARC) are explained by observed characteristics.

DATA SOURCES

State inpatient databases (SIDs) for 2005 and 2006 from four diverse states were used to identify patients with stays for joint replacement, stroke, or hip fracture.

STUDY DESIGN

Our primary outcomes were use of institutional PARC (versus discharge home) and, conditional on discharge to an institution, skilled nursing facility (versus inpatient rehabilitation facility) care. We modified the Oaxaca-Blinder decomposition method to account for the dichotomous outcome and multilevel nature of the data.

DATA COLLECTION/EXTRACTION METHODS

Discharges from the four SIDs were included if the principal diagnosis (stroke, hip fracture) or procedure (joint replacement) was in the sample inclusion criteria.

PRINCIPAL FINDINGS

Observed characteristics explained roughly half of the unadjusted differences in use of institutional PARC. Patient-level factors (clinical, age) were more explanatory of disparities in institutional PARC use, while hospital-level factors were more explanatory of skilled nursing facility versus inpatient rehabilitation facility care.

CONCLUSIONS

Adjustment for characteristics influencing PARC use both mitigated and exacerbated racial/ethnic disparities in use. The degree to which the characteristics explained the disparity varied across conditions and outcomes.

Racial-ethnic disparities in substance abuse treatment: the role of criminal history and socioeconomic status

OBJECTIVE

Among persons with substance use disorders, those from racial-ethnic minority groups have been found to receive substance abuse treatment at rates equal to or higher than those of non-Latino whites. Little is known about factors underlying this apparent lack of disparities. This study examines racial-ethnic disparities in treatment receipt and mechanisms that reduce or contribute to disparities.

METHODS

Black-white and Latino-white disparities in any and in specialty substance abuse treatment were measured among adult respondents with substance use disorders from the 2005-2009 National Survey on Drug Use and Health (N=25,159). Three staged models were used to measure disparities concordant with the Institute of Medicine definition, assess the extent to which criminal history and socioeconomic indicators contributed to disparities, and identify correlates of treatment receipt.

RESULTS

Treatment was rare (about 10%) for all racial-ethnic groups. Odds ratios for black-white and Latino-white differences decreased and became significantly less than 1 after adjustment for criminal history and socioeconomic status factors. Higher rates of criminal history and enrollment in Medicaid among blacks and Latinos and lower income were specific mechanisms that influenced changes in estimates of disparities across models.

CONCLUSIONS

The greater likelihood of treatment receipt among persons with a criminal history and lower socioeconomic status is a pattern unlike those seen in most other areas of medical treatment and important to the understanding of substance abuse treatment disparities. Treatment programs that are mandated by the criminal justice system may provide access to individuals resistant to care, which raises concerns about perceived coercion.

Crowd-out and exposure effects of physical comorbidities on mental health care use: implications for racial-ethnic disparities in access

OBJECTIVES

In disparities models, researchers adjust for differences in "clinical need," including indicators of comorbidities. We reconsider this practice, assessing (1) if and how having a comorbidity changes the likelihood of recognition and treatment of mental illness; and (2) differences in mental health care disparities estimates with and without adjustment for comorbidities.

DATA

Longitudinal data from 2000 to 2007 Medical Expenditure Panel Survey (n=11,083) split into pre and postperiods for white, Latino, and black adults with probable need for mental health care.

STUDY DESIGN

First, we tested a crowd-out effect (comorbidities decrease initiation of mental health care after a primary care provider [PCP] visit) using logistic regression models and an exposure effect (comorbidities cause more PCP visits, increasing initiation of mental health care) using instrumental variable methods. Second, we assessed the impact of adjustment for comorbidities on disparity estimates.

PRINCIPAL FINDINGS

We found no evidence of a crowd-out effect but strong evidence for an exposure effect. Number of postperiod visits positively predicted initiation of mental health care. Adjusting for racial/ethnic differences in comorbidities increased black-white disparities and decreased Latino-white disparities.

CONCLUSIONS

Positive exposure findings suggest that intensive follow-up programs shown to reduce disparities in chronic-care management may have additional indirect effects on reducing mental health care disparities.

The Nathan Kline Institute cultural competency assessment scale: psychometrics and implications for disparity reduction

The NKI Cultural Competency Assessment Scale measures organizational CC in mental health outpatient settings. We describe its development and results of tests of its psychometric properties. When tested in 27 public mental health settings, factor analysis discerned three factors explaining 65% of the variance; each factor related to a stage of implementation of CC. Construct validity and inter-rater reliability were satisfactory. In tests of predictive validity, higher scores on items related to linguistic and service accommodations predicted a reduction in service disparities for engagement and retention outcomes for Hispanics. Disparities for Blacks essentially persisted independent of CC scores.

Comparing methods of racial and ethnic disparities measurement across different settings of mental health care

INTRODUCTION

The ability to track improvement against racial/ethnic disparities in mental health care is hindered by the varying methods and disparity definitions used in previous research.

DATA

Nationally representative sample of whites, blacks, and Latinos from the 2002 to 2006 Medical Expenditure Panel Survey. Dependent variables are total, outpatient, and prescription drug mental health care expenditure.

METHODS

Rank- and propensity score-based methods concordant with the Institute of Medicine (IOM) definition of health care disparities were compared with commonly used disparities methods. To implement the IOM definition, we modeled expenditures using a two-part GLM, adjusted distributions of need variables, and predicted expenditures for each racial/ethnic group.

FINDINGS

Racial/ethnic disparities were significant for all expenditure measures. Disparity estimates from the IOM-concordant methods were similar to one another but greater than a method using the residual effect of race/ethnicity. Black-white and Latino-white disparities were found for any expenditure in each category and Latino-white disparities were significant in expenditure conditional on use.

CONCLUSIONS

Findings of disparities in access among blacks and disparities in access and expenditures after initiation among Latinos suggest the need for continued policy efforts targeting disparities reduction. In these data, the propensity score-based method and the rank-and-replace method were precise and adequate methods of implementing the IOM definition of disparity.

There's a reason they call them dummy variables: a note on the use of structural equation techniques in comparative effectiveness research

Many research designs and statistical methodologies will be used to conduct comparative effectiveness research (CER). In particular, it is almost certainly the case that the demand for real-world evidence will drive increased demand for CER analyses of observational data. Although a great deal of progress has been made in the development and application of statistical methods for the analysis of observational data, the ordinary least squares multiple regression model remains, by far, the most widely applied multivariate analysis tool. This article begins with a brief review of the interpretation of treatment effects captured through the use of dummy variables in multiple regression models. This review makes clear just how limited this typical estimator of treatment effect is. Structural equation and decomposition methods for CER analyses of observational data are then reviewed. Although these methods have not been commonly used for outcomes research, they offer the opportunity to extract significantly more information regarding treatment effects than the standard dummy variable approach. I have attempted to make the point that traditional dummy variable methods in regression models provide an extremely limited estimate of treatment effects. Structural equation models and decomposition methods provide considerably more information about treatment effects - in particular, the ability to identify how outcomes may vary differentially with respect to patient characteristics and other factors for alternative treatment cohorts. Such an understanding is fundamental to deciphering the heterogeneity of treatment response among patient subpopulations. Structural equation and decomposition methods may be further enhanced by incorporating propensity score matching prior to the analysis. On the other hand, researchers should be wary of the potential pitfalls associated with parametric sample selection bias models. Although tests for selection bias and other forms of endogeneity are an excellent research practice, it is entirely possible that attempts to correct for endogeneity may introduce more bias than they remove. Nonparametric methods, such as differences in differences, while making strong assumptions of their own, avoid the need to identify instrumental variables that are correlated with treatment selection but uncorrelated with residuals in the outcome equation.

Pathways and correlates connecting Latinos' mental health with exposure to the United States

OBJECTIVES

We examined potential pathways by which time in the United States may relate to differences in the predicted probability of past-year psychiatric disorder among Latino immigrants as compared with US-born Latinos.

METHODS

We estimated predicted probabilities of psychiatric disorder for US-born and immigrant groups with varying time in the United States, adjusting for different combinations of covariates. We examined 6 pathways by which time in the United States could be associated with psychiatric disorders.

RESULTS

Increased time in the United States is associated with higher risk of psychiatric disorders among Latino immigrants. After adjustment for covariates, differences in psychiatric disorder rates between US-born and immigrant Latinos disappear. Discrimination and family cultural conflict appear to play a significant role in the association between time in the United States and the likelihood of developing psychiatric disorders.

CONCLUSIONS

Increased perceived discrimination and family cultural conflict are pathways by which acculturation might relate to deterioration of mental health for immigrants. Future studies assessing how these implicit pathways evolve as contact with US culture increases may help to identify strategies for ensuring maintenance of mental health for Latino immigrants.

Measuring racial/ethnic disparities across the distribution of health care expenditures

OBJECTIVE

To assess whether black-white and Hispanic-white disparities increase or abate in the upper quantiles of total health care expenditure, conditional on covariates.

DATA SOURCE

Nationally representative adult population of non-Hispanic whites, African Americans, and Hispanics from the 2001-2005 Medical Expenditure Panel Surveys.

STUDY DESIGN

We examine unadjusted racial/ethnic differences across the distribution of expenditures. We apply quantile regression to measure disparities at the median, 75th, 90th, and 95th quantiles, testing for differences over the distribution of health care expenditures and across income and education categories. We test the sensitivity of the results to comparisons based only on health status and estimate a two-part model to ensure that results are not driven by an extremely skewed distribution of expenditures with a large zero mass.

PRINCIPAL FINDINGS

Black-white and Hispanic-white disparities diminish in the upper quantiles of expenditure, but expenditures for blacks and Hispanics remain significantly lower than for whites throughout the distribution. For most education and income categories, disparities exist at the median and decline, but remain significant even with increased education and income.

CONCLUSIONS

Blacks and Hispanics receive significantly disparate care at high expenditure levels, suggesting prioritization of improved access to quality care among minorities with critical health issues.

Black-White Disparities in Care in Nursing Homes

Nursing homes serve many severely ill poor people, including large numbers of racial/ethnic minority residents. Previous research indicates that blacks tend to receive care from lower quality nursing homes (Grabowski, 2004). Using the Institute of Medicine (IOM) definition of racial-ethnic disparities, this study decomposes nursing home disparities into within and across facility components. Using detailed person-level nursing home data, we find meaningful black-white disparities for one of the four risk-adjusted quality measures, with both within and across nursing home components of the disparity. The IOM approach, which recognizes mediation through payer status and education, has a small effect on measured disparities in this setting. Although we did not find disparities across the majority of quality measures and alternate disparity definitions, this approach can be applied to other health care services in an effort to disentangle the role of across and within facility variation and the role of potential mediators on racial/ethnic disparities.

Measuring trends in racial/ ethnic health care disparities

Monitoring disparities over time is complicated by the varying disparity definitions applied in the literature. This study used data from the 1996-2005 Medical Expenditure Panel Survey (MEPS) to compare trends in disparities by three definitions of racial/ethnic disparities and to assess the influence of changes in socioeconomic status (SES) among racial/ethnic minorities on disparity trends. This study prefers the Institute of Medicine's (IOM) definition, which adjusts for health status but allows for mediation of racial/ethnic disparities through SES factors. Black-White disparities in having an office-based or outpatient visit and medical expenditure were roughly constant and Hispanic-White disparities increased for office-based or outpatient visits and for medical expenditure between 1996-1997 and 2004-2005. Estimates based on the independent effect of race/ethnicity were the most conservative accounting of disparities and disparity trends, underlining the importance of the role of SES mediation in the study of trends in disparities.

Testing for statistical discrimination by race/ethnicity in panel data for depression treatment in primary care

OBJECTIVE

To test for discrimination by race/ethnicity arising from clinical uncertainty in treatment for depression, also known as "statistical discrimination."

DATA SOURCES

We used survey data from 1,321 African-American, Hispanic, and white adults identified with depression in primary care. Surveys were administered every six months for two years in the Quality Improvement for Depression (QID) studies.

STUDY DESIGN

To examine whether and how change in depression severity affects change in treatment intensity by race/ethnicity, we used multivariate cross-sectional and change models that difference out unobserved time-invariant patient characteristics potentially correlated with race/ethnicity.

DATA COLLECTION/EXTRACTION METHODS

Treatment intensity was operationalized as expenditures on drugs, primary care, and specialty services, weighted by national prices from the Medical Expenditure Panel Survey. Patient race/ethnicity was collected at baseline by self-report.

PRINCIPAL FINDINGS

Change in depression severity is less associated with change in treatment intensity in minority patients than in whites, consistent with the hypothesis of statistical discrimination. The differential effect by racial/ethnic group was accounted for by use of mental health specialists.

CONCLUSIONS

Enhanced physician-patient communication and use of standardized depression instruments may reduce statistical discrimination arising from clinical uncertainty and be useful in reducing racial/ethnic inequities in depression treatment.