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

Identifying Sources of Inter-Hospital Variation in Episode Spending for Sepsis Care

OBJECTIVE

To evaluate inter-hospital variation in 90-day total episode spending for sepsis, estimate the relative contributions of each component of spending, and identify drivers of spending across the distribution of episode spending on sepsis care.

DATA SOURCES/STUDY SETTING

Medicare fee-for-service claims for beneficiaries (n=324,694) discharged from acute care hospitals for sepsis, defined by MS-DRG, between October 2014 and September 2018.

RESEARCH DESIGN

Multiple linear regression with hospital-level fixed effects was used to identify average hospital differences in 90-day episode spending. Separate multiple linear regression and quantile regression models were used to evaluate drivers of spending across the episode spending distribution.

RESULTS

The mean total episode spending among hospitals in the most expensive quartile was $30,500 compared with $23,150 for the least expensive hospitals ( P <0.001). Postacute care spending among the most expensive hospitals was almost double that of least expensive hospitals ($7,045 vs. $3,742), accounting for 51% of the total difference in episode spending between the most expensive and least expensive hospitals. Female patients, patients with more comorbidities, urban hospitals, and BPCI-A-participating hospitals were associated with significantly increased episode spending, with the effect increasing at the right tail of the spending distribution.

CONCLUSION

Inter-hospital variation in 90-day episode spending on sepsis care is driven primarily by differences in post-acute care spending.

Examining Racial/Ethnic Differences in Patterns of Opioid Prescribing: Results from an Urban Safety-Net Healthcare System

Prescription opioids still account for a large proportion of overdose deaths and contribute to opioid use dependence (OUD). Studies earlier in the epidemic suggest clinicians were less likely to prescribe opioids to racial/ethnic minorities. As OUD-related deaths have increased disproportionately amongst minority populations, it is essential to understand racial/ethnic differences in opioid prescribing patterns to inform culturally sensitive mitigation efforts. The purpose of this study is to estimate racial/ethnic differences in opioid medication use among patients prescribed opioids. Using electronic health records and a retrospective cohort study design, we estimated multivariable hazard models and generalized linear models, assessing racial/ethnic differences in OUD diagnosis, number of opioid prescriptions, receiving only one opioid prescription, and receiving ≥18 opioid prescriptions. Study population (N=22,201) consisted of adult patients (≥18years), with ≥3 primary care visits (ensuring healthcare system linkage), ≥1 opioid prescription, who did not have an OUD diagnoses prior to the first opioid prescription during the 32-month study period. Relative to racial/ethnic minority patients, White patients, in both unadjusted and adjusted analyses, had a greater number of opioid prescriptions filled, a higher proportion received ≥18 opioid prescriptions, and a greater hazard of having an OUD diagnosis subsequent to receiving an opioid prescription (all groups p<0.001). Although opioid prescribing rates have declined nationally, our findings suggest White patients still experience a high volume of opioid prescriptions and greater risk of OUD diagnosis. Racial/ethnic minorities are less likely to receive follow-up pain medications, which may signal low care quality. Identifying provider bias in pain management of racial/ethnic minorities could inform interventions seeking balance between adequate pain treatment and risk of opioid misuse/abuse.

The level of countries' preparedness to health risks during Covid-19 and pre-pandemic: the differential response to health systems building blocks and socioeconomic indicators

The global health security (GHS) Index assesses countries' level of preparedness to health risks. However, there is no evidence on how and whether the effects of health systems building blocks and socioeconomic indicators on the level of preparedness differ for low and high prepared countries. The aim of this study was to examine the contributions of health systems building blocks and socioeconomic indicators to show differences in the level of preparedness to health risks. The study also aimed to examine trends in the level of preparedness and the World Health Organization (WHO) regional differences before and during the Covid-19 pandemic. We used the 2021 GHS index report data and employed quantile regression, log-linear, double-logarithmic, and time-fixed effects models. As robustness checks, these functional form specifications corroborated with one another, and interval validity tests confirmed. The results show that increases in effective governance, supply chain capacity in terms of medicines and technologies, and health financing had positive effects on countries' level of preparedness to health risks. These effects were considerably larger for countries with higher levels of preparedness to health risks. The positive gradient trends signaled a sense of capacity on the part of countries with higher global health security. However, the health workforce including doctors, and health services including hospital beds, were not statistically significant in explaining variations in countries' level of preparedness. While economic factors had positive effects on the level of preparedness to health risks, their impacts across the distribution of countries' level of preparedness to health risks were mixed. The effects of Social Development Goals (SDGs) were greater for countries with higher levels of preparedness to health risks. The effect of the Human Development Index (HDI) was greatest for countries whose overall GHS index lies at the midpoint of the distribution of countries' level of preparedness. High-income levels were associated with a negative effect on the level of preparedness, especially if countries were in the lower quantiles across the distributions of preparedness. Relative to poor countries, middle- and high-income groups had lower levels of preparedness to health risks, an indication of a sense of complacency. We find the pandemic period (year 2021) was associated with a decrease in the level of preparedness to health risks in comparison to the pre-pandemic period. There were significant WHO regional differences. Apart from the Eastern Mediterranean, the rest of the regions were more prepared to health risks compared to Africa. There was a negative trend in the level of preparedness to health risks from 2019 to 2021 although regional differences in changes over time were not statistically significant. In conclusion, attempts to strengthen countries' level of preparedness to health shocks should be more focused on enhancing essentials such as supply chain capacity in terms of medicines and technologies; health financing, and communication infrastructure. Countries should also strengthen their already existing health workforce and health services. Together, strengthening these health systems essentials will be beneficial to less prepared countries where their impact we find to be weaker. Similarly, boosting SDGs, particularly health-related sub-scales, will be helpful to less prepared countries. Moreover, there is a need to curb complacency in preparedness to health risks during pandemics by high-income countries. The negative trend in the level of preparedness to health risks would suggest that there is a need for better preparedness during pandemics by conflating national health with global health risks. This will ensure the imperative of having a synergistic response to global health risks, which is understood by and communicated to all countries and regions.

Trends and Racial/Ethnic Differences in Health Care Spending Stratified by Gender among Adults with Arthritis in the United States 2011-2019

The purpose of this study was to determine if there were racial/ethnic differences and patterns for individual office-based visit expenditures by gender among a nationally representative sample of adults with arthritis. We retrospectively analyzed pooled data from the 2011 to 2019 Medical Expenditure Panel Survey of adults who self-reported an arthritis diagnosis, stratified by gender (men = 13,378; women = 33,261). Our dependent variable was office-based visit expenditures. Our independent variables were survey year (categorized as 2011-2013, 2014-2016, 2017-2019) and race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian, non-Hispanic other/multiracial). We conducted trends analysis to assess for changes in expenditures over time. We utilized a two-part model to assess differences in office-based expenditures among participants who had any office-based expenditure and then calculated the average marginal effects. The unadjusted office-based visit expenditures increased significantly across the study period for both men and women with arthritis, as well as for some racial and ethnic groups depending on gender. Differing racial and ethnic patterns of expenditures by gender remained after accounting for socio-demographic, healthcare access, and health status factors. Delaying care was an independent driver of higher office-based expenditures for women with arthritis but not men. Our findings reinforce the escalating burden of healthcare costs among U.S. adults with arthritis across genders and certain racial and ethnic groups.

Application of quantile mixed-effects model in modeling CD4 count from HIV-infected patients in KwaZulu-Natal South Africa

BACKGROUND

The CD4 cell count signifies the health of an individual's immune system. The use of data-driven models enables clinicians to accurately interpret potential information, examine the progression of CD4 count, and deal with patient heterogeneity due to patient-specific effects. Quantile-based regression models can be used to illustrate the entire conditional distribution of an outcome and identify various covariates effects at the respective location.

METHODS

This study uses the quantile mixed-effects model that assumes an asymmetric Laplace distribution for the error term. The model also incorporated multiple random effects to consider the correlation among observations. The exact maximum likelihood estimation was implemented using the Stochastic Approximation of the Expectation-Maximization algorithm to estimate the parameters. This study used the Centre of the AIDS Programme of Research in South Africa (CAPRISA) 002 Acute Infection Study data. In this study, the response variable is the longitudinal CD4 count from HIV-infected patients who were initiated on Highly Active Antiretroviral Therapy (HAART), and the explanatory variables are relevant baseline characteristics of the patients.

RESULTS

The analysis obtained robust parameters estimates at various locations of the conditional distribution. For instance, our result showed that baseline BMI (at [Formula: see text] 0.05: [Formula: see text]), baseline viral load (at [Formula: see text] 0.05: [Formula: see text] [Formula: see text]), and post-HAART initiation (at [Formula: see text] 0.05: [Formula: see text]) were major significant factors of CD4 count across fitted quantiles.

CONCLUSIONS

CD4 cell recovery in response to post-HAART initiation across all fitted quantile levels was observed. Compared to HIV-infected patients with low viral load levels at baseline, HIV-infected patients enrolled in the treatment with a high viral load level at baseline showed a significant negative effect on CD4 cell counts at upper quantiles. HIV-infected patients registered with high BMI at baseline had improved CD4 cell count after treatment, but physicians should not ignore this group of patients clinically. It is also crucial for physicians to closely monitor patients with a low BMI before and after starting HAART.

Who determines United States Healthcare out-of-pocket costs? Factor ranking and selection using ensemble learning

PURPOSE

Healthcare out-of-pocket (OOP) costs consist of the annual expenses paid by individuals or families that are not reimbursed by insurance. In the U.S, broadening healthcare disparities are caused by the rapid increase in OOP costs. With a precise forecast of the OOP costs, governments can improve the design of healthcare policies to better control the OOP costs. This study designs a purely data-driven ensemble learning procedure to achieve a collection of factors that best predict OOP costs.

METHODS

We propose a voting ensemble learning procedure to rank and select factors of OOP costs based on the Medical Expenditure Panel Survey dataset. The method involves utilizing votes from the base learners forward subset selection, backward subset selection, random forest, and LASSO.

RESULTS

The top-ranking factors selected by our proposed method are insurance type, age, asthma, family size, race, and number of physician office visits. The predictive models using these factors outperform the models that employ the factors commonly considered by the literature through improving the prediction error (test MSE of the OOP costs' log-odds) from 0.462 to 0.382.

CONCLUSION

Our results indicate a set of factors which best explain the OOP costs behavior based on a purely data-driven solution. These findings contribute to the discussions regarding demand-side needs for containing rapidly rising OOP costs. Instead of estimating the impact of a single factor on OOP costs, our proposed method allows for the selection of arbitrary-sized factors to best explain OOP costs.

US Health Care Spending by Race and Ethnicity, 2002-2016

Importance

Measuring health care spending by race and ethnicity is important for understanding patterns in utilization and treatment.

Objective

To estimate, identify, and account for differences in health care spending by race and ethnicity from 2002 through 2016 in the US.

Design, Setting, and Participants

This exploratory study included data from 7.3 million health system visits, admissions, or prescriptions captured in the Medical Expenditure Panel Survey (2002-2016) and the Medicare Current Beneficiary Survey (2002-2012), which were combined with the insured population and notified case estimates from the National Health Interview Survey (2002; 2016) and health care spending estimates from the Disease Expenditure project (1996-2016).

Exposure

Six mutually exclusive self-reported race and ethnicity groups.

Main Outcomes and Measures

Total and age-standardized health care spending per person by race and ethnicity for each year from 2002 through 2016 by type of care. Health care spending per notified case by race and ethnicity for key diseases in 2016. Differences in health care spending across race and ethnicity groups were decomposed into differences in utilization rate vs differences in price and intensity of care.

Results

In 2016, an estimated $2.4 trillion (95% uncertainty interval [UI], $2.4 trillion-$2.4 trillion) was spent on health care across the 6 types of care included in this study. The estimated age-standardized total health care spending per person in 2016 was $7649 (95% UI, $6129-$8814) for American Indian and Alaska Native (non-Hispanic) individuals; $4692 (95% UI, $4068-$5202) for Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals; $7361 (95% UI, $6917-$7797) for Black (non-Hispanic) individuals; $6025 (95% UI, $5703-$6373) for Hispanic individuals; $9276 (95% UI, $8066-$10 601) for individuals categorized as multiple races (non-Hispanic); and $8141 (95% UI, $8038-$8258) for White (non-Hispanic) individuals, who accounted for an estimated 72% (95% UI, 71%-73%) of health care spending. After adjusting for population size and age, White individuals received an estimated 15% (95% UI, 13%-17%; P < .001) more spending on ambulatory care than the all-population mean. Black (non-Hispanic) individuals received an estimated 26% (95% UI, 19%-32%; P < .001) less spending than the all-population mean on ambulatory care but received 19% (95% UI, 3%-32%; P = .02) more on inpatient and 12% (95% UI, 4%-24%; P = .04) more on emergency department care. Hispanic individuals received an estimated 33% (95% UI, 26%-37%; P < .001) less spending per person on ambulatory care than the all-population mean. Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals received less spending than the all-population mean on all types of care except dental (all P < .001), while American Indian and Alaska Native (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 90% more; 95% UI, 11%-165%; P = .04), and multiple-race (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 40% more; 95% UI, 19%-63%; P = .006). All 18 of the statistically significant race and ethnicity spending differences by type of care corresponded with differences in utilization. These differences persisted when controlling for underlying disease burden.

Conclusions and Relevance

In the US from 2002 through 2016, health care spending varied by race and ethnicity across different types of care even after adjusting for age and health conditions. Further research is needed to determine current health care spending by race and ethnicity, including spending related to the COVID-19 pandemic.

Does digital technology reduce health disparity? Investigating difference of depression stemming from socioeconomic status among Chinese older adults

Background

Prior studies on health disparity have shown that socioeconomic status is critical to inequality of health outcomes such as depression. However, two questions await further investigation: whether disparity in depression correlated with socioeconomic status will become larger when depression becomes severer, and whether digital technology will reduce the disparity in depression correlated with socioeconomic status. Our study aims to answer the above two questions.

Methods

By using the dataset from China Health and Retirement Longitudinal Study 2015, we use quantile regression models to examine the association between socioeconomic status and depression across different quantiles, and test the moderating effect of digital technology.

Results

Our study obtains four key findings. First, the negative effects of socioeconomic status on depression present an increasing trend at high quantiles. Second, Internet usage exacerbates the disparity in depression associated with education level on average, but reduces this disparity associated with education level at high quantiles. Third, Internet usage reduces the disparity in depression associated with income on average and at high quantiles. Fourth, mobile phone ownership has almost no moderating effect on the relationship between socioeconomic status and depression.

Conclusions

Our findings suggest the potential use of digital technology in reducing disparity in depression correlated with socioeconomic status among middle-aged and aged individuals in developing countries.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02175-0.

The medical costs of low leisure-time physical activity among working-age adults: Gender and minority status matter

This study analyzes the direct medical costs of low physical activity by race/ethnicity and gender. Average health expenditures based on physical activity status for Black non-Hispanics (NH), Asian NHs, and Hispanics were compared to White NHs. Data from the National Health Interview Survey were merged with the Medical Expenditure Panel Survey for years 2000-2010 and 2001-2011, respectively, and weights were applied to ensure generalizability to the larger US population. The sample was restricted to non-pregnant adults between the ages of 25 and 64, with a final sample size of 44,953. The multivariate estimates reveal statistically significant lower annual health care expenditures among physically active men and women in five out of eight racial/ethnic groups relative to their inactive counterparts: on average, for men, $1041 less is spent among White NHs, $905 less is spent for Black NHs and $876 less is spent for Asian NHs. Among women, medical expenditures were $956 per year less among active White non-Hispanics relative to their inactive counterparts, and $815 per year among Hispanics. Essentially, the average reduction in health care expenditures is relatively consistent for five out of the eight groups. The absence of any reduction in average health care expenditures for three of the groups, however, suggests that there may be environmental factors at play for certain groups that mitigate the impact of physical activity on health expenditures.

Differences in Health Care Expenditures Among Non-Latino Whites and Asian Subgroups Vary Along the Distribution of the Expenditures

Using a nationally representative sample from the 2013 to 2016 Medical Expenditure Panel Survey, we examined differences among non-Latino Whites and Asian subgroups (Asian Indians, Chinese, Filipinos, and other Asians) across distributions of total health care expenditures and out-of-pocket (OOP) expenditures. For total health care expenditures, differences between Asian and White adults persisted throughout the distribution, but the magnitude of the difference was larger at no or low levels of expenditures than at high expenditure levels. A similar pattern was observed in OOP expenditures, but the magnitude of the difference was substantially larger at low levels of expenditures. The extent of the difference varied by Asian subgroup, but this trend persisted across all the subgroups. Similar trends were observed by nativity and limited English proficiency. Our findings suggest that differences in health care expenditures between Whites and Asians are more pronounced at low expenditure levels.

How did the tobacco ban increase inmates' body weight during incarceration in Canadian federal penitentiaries? A cohort study

OBJECTIVE

This study aimed to determine how inmates' body weight changed during incarceration in Canadian federal penitentiaries, based on their history of tobacco use. Since tobacco was banned from all Canadian federal penitentiaries in 2008, little is known about the unintended health consequences of this ban, especially on inmates' body weight.

DESIGN

Cohort study.

SETTING

Participants were male and female inmates incarcerated for at least 6 months in Canadian federal penitentiaries. We collected data from 10 institutions in two Canadian regions (Ontario and Atlantic).

PARTICIPANTS

We collected data from 754 inmates who volunteered to participate in the study.

INTERVENTION

This study examined weight change in relation to a history of tobacco use. In 2016-2017, anthropometric data were collected and compared with recorded anthropometric data at the beginning of incarceration (mean follow-up of 5.0±8.3 years). Self-reported data on tobacco and substance use were collected. Weight change was compared between inmates with and without a history of tobacco use.

OUTCOMES

The main outcome measures were body weight change (kg), body mass index (BMI) change (kg/m²), annual weight change (kg/year), and BMI and waist circumference (cm) at the time of the interview.

RESULTS

During incarceration, ex-smokers gained more than twice the amount of weight compared with non-smokers (7.5 kg weight gain for smokers vs 3.7 kg weight gain for non-smokers). Once adjusted for covariates in a regression analysis, for inmates who gained the most weight (75th and 90th percentiles), non-smokers had, respectively, 1.64 and 2.3 lower BMI points than ex-smokers.

CONCLUSIONS

During incarceration in Canadian federal penitentiaries, inmates with a history of tobacco use gained significantly more weight than non-smokers. This put them at increased risk of developing obesity-related health problems. This information is important for the prison setting when planning related programmes and regulation.

Heterogeneity in the costs of medical care among people living with HIV/AIDS in the United States

OBJECTIVE

The costs of medical care for people with HIV/AIDS (PWH) vary substantially across demographic groups, stages of disease progression and regionally across the United States. We aimed to estimate medical costs for PWH and examine the heterogeneity in costs within key patient groups typically distinguished in cost-effectiveness analyses.

DESIGN

Retrospective cohort study using health administrative databases for diagnosed PWH in care at 17 HIV Research Network sites across the United States.

METHODS

We estimated mean quarterly costs for key patient groups using multivariable generalized linear mixed effects models. We used quantile regression to highlight differences in the effect of covariates within each patient group (difference between covariate estimates at the mean versus the 90th percentile of quarterly costs), identifying covariates with a larger effect among the highest cost PWH, or generating greater uncertainty in mean cost estimates.

RESULTS

Our sample included 40 022 patients with a median age of 39 years. Mean quarterly costs were highest for people who inject drugs with advanced disease progression and for PWH on antiretroviral treatment (ART). Within patient groups, we found the most heterogeneity at different levels of resource use for PWH on ART and PWH off ART with CD4 cell counts less than 200 cells/μl, people who inject drugs, as well as PWH in the South.

CONCLUSION

The study quantifies heterogeneity in costs both across and within key PWH patient groups. Our results highlight the need for sensitivity analysis on cost estimates and may inform decisions on model structure in cost-effectiveness analyses on HIV/AIDS treatment and prevention strategies.

Unequal Rates of Serious Perioperative Respiratory Adverse Events Between Black and White Children

BACKGROUND

Recent data among pediatric otolaryngology patients showed unexplained higher rates of serious perioperative respiratory adverse events (PRAE) in black children compared to their white peers. We evaluated whether preoperative respiratory comorbidity (PRC) burden contributes to racial disparity in serious PRAE in children undergoing non-otolaryngologic procedures.

METHODS

Rates of serious PRAE (laryngospasm and/or bronchospasm) were compared across racial groups in a retrospective cohort of black and white children (N = 18538; black 10%) who underwent various elective, non-otolaryngologic procedures between 2007 and 2014 at a US tertiary Children's hospital. Self-reported race was the primary exposure while age, gender, recent upper respiratory tract infection, use of endotracheal intubation, PRC burden and an interaction term between PRC and race were covariates.

RESULTS

Serious PRAE occurred in 9.6% of black children and 6.6% of white children. Although there was no significant difference in age between the groups, being black (odds ratio (OR) 1.70; 95% confidence interval (CI) 1.11-2.62) was independently associated with serious PRAE. Similarly, baseline PRC was independently linked (p < 0.001) with serious PRAE. Notably, there was no significant (p = 0.454) interactions between race and PRC and serious PRAE in our subjects.

CONCLUSION

Race and PRC are important considerations in the risk of serious PRAE and black children are especially at risk compared to their white peers. Children, with PRC (particularly those with SDB and asthma) are also at risk suggesting that due consideration should be given to these factors in the perioperative care of children undergoing elective surgical procedures. Mechanisms underlying these associations deserve further evaluation.

An exploration of reported food intake among inmates who gained body weight during incarceration in Canadian federal penitentiaries

Background

Canadian penitentiaries have recently been shown to be obesogenic. However, little is known about the eating habits of inmates who gained weight while living in the prison environment.

Methods

This retrospective cohort study examined the reported food intake of inmates during incarceration in federal penitentiaries. During a face to face interview, anthropometric measures (2016–2017) were taken and compared to anthropometric data at the beginning of incarceration (mean follow-up of 5.0 ± 8.3 years). Self-reported data on food intake were collected via a food frequency questionnaire.

Results

Inmates who gained the most weight (15.7 kg) during incarceration reported not eating vegetables. They were followed by inmates who gained 14.3 kg and reported not eating fruit. Other inmates who gained a significant amount of weight reported not eating cereal, dairy or legumes. Moreover, inmates’ weight gain was also assessed by special diets: inmates following a religious diet (4.5 kg) or a diet of conscience (-0.3 kg) gained less weight than inmates not following a diet (5.8 kg). In comparison to other types of diets, inmates on a medical diet gained the most weight (7.5 kg). Furthermore, inmates who gained significant weight (8.0 kg) also reported not purchasing healthy foods from the commissary store (or “canteen”), whereas inmates who gained less weight (4.8 kg) reported purchasing healthy foods from the commissary store (or “canteen”). The observed weight gain was positively associated with food purchased from the commissary store (or “canteen”), but was not associated with the feeding system of the penitentiary (tray, cafeteria or meal plan).

Discussion

Food intake during incarceration is a modifiable risk factor that could be the target of weight management interventions with inmates. Our findings suggest that inmates who gained the most weight also reported having low intake of foods deemed healthy (vegetables, fruit, cereal, dairy and legumes) from food services and from the commissary store (or “canteen”) purchases.

Racial disparities in Medicaid home and community-based service utilization and expenditures among persons with multiple sclerosis

BACKGROUND

Medicaid home and community-based services (HCBS) provide services such as personal care, nursing, and home-delivered meals to aging adults and individuals with disabilities. HCBS are available to people across racial and ethnic groups, yet racial disparities in Medicaid HCBS utilization and expenditures have been understudied. Individuals with multiple sclerosis (MS) may be particularly impacted by HCBS, as nearly one-third requires assistance at home. The present study examined whether disparities exist in Medicaid HCBS utilization and expenditures among HCBS users with MS.

METHODS

We used secondary data to conduct a retrospective cohort analyses including 7550 HCBS recipients with MS. Demographic data was obtained from the Medicaid Analytic eXtract Personal Summary file, Medicaid HCBS service utilization and expenditures were obtained from the Other Therapy file, and comorbidities from the Medicare Chronic Condition Warehouse. Univariate and bivariate statistics were used to describe the sample and provide comparisons of characteristic by race. Logistic regression predicted the likelihood of using HCBS type and gamma regression was used to predict Medicaid HCBS expenditures.

RESULTS

Black HCBS users were younger, more likely to be female, and were more impaired than Whites. Multivariate analyses showed that Blacks were less likely to receive case management, equipment, technology and modification services, and nursing services compared to Whites. Additionally, Black men had the lowest Medicaid HCBS expenditures, while White men had the highest.

CONCLUSIONS

Findings shed light on disparities among HCBS users with MS. As Blacks are already disproportionately affected by MS, these results reveal target areas for future research. Future work should examine the factors that contribute to these disparities, as well as determine the extent to which these inequities impact outcomes such as hospitalizations and nursing home admissions.

Examining racial/ethnic differences in patterns of benzodiazepine prescription and misuse

BACKGROUND

Benzodiazepines (BZDs) are widely prescribed during psychiatric treatment. Unfortunately, their misuse has led to recent surges in overdose emergency visits and drug-related deaths.

METHODS

Electronic health record data from a large healthcare system were used to describe racial/ethnic, sex, and age differences in BZD use and dependence. Among patients with a BZD prescription, we assessed differences in the likelihood of subsequently receiving a BZD dependence diagnosis, number of BZD prescriptions, receiving only one BZD prescription, and receiving 18 or more BZD prescriptions. We also estimated multivariate hazard models and generalized linear models, assessing racial/ethnic differences after adjustment for covariates.

RESULTS

In both unadjusted and adjusted analyses, Whites were more likely than Blacks, Hispanics, and Asians to have a BZD dependence diagnosis and to receive a BZD prescription. Racial/ethnic minority groups received fewer BZD prescriptions, were more likely to have only one BZD prescription, and were less likely to have 18 or more BZD prescriptions. We identified greater BZD misuse among older patients but no sex differences.

CONCLUSIONS

Findings from this study add to the emerging evidence of high relative rates of prescription drug abuse among Whites. There is a concern, given their greater likelihood of having only one BZD prescription, that Blacks, Hispanics, and Asians may be discontinuing BZDs before their clinical need is resolved. Research is needed on provider readiness to offer racial/ethnic minorities BZDs when indicated, patient preferences for BZDs, and whether lower prescription rates among racial/ethnic minorities offer protection against the progression from prescription to addiction.

Comparing the Income Elasticity of Health Spending in Middle-Income and High-Income Countries: The Role of Financial Protection

BACKGROUND

As middle-income countries become more affluent, economically sophisticated and productive, health expenditure patterns are likely to change. Other socio-demographic and political changes that accompany rapid economic growth are also likely to influence health spending and financial protection.

METHODS

This study investigates the relationship between growth on per-capita healthcare expenditure and gross domestic product (GDP) in a group of 27 large middle-income economies and compares findings with those of 24 high-income economies from the Organization for Economic Cooperation and Development (OECD) group. This comparison uses national accounts data from 1995-2014. We hypothesize that the aggregated income elasticity of health expenditure in middle-income countries would be less than one (meaning healthcare is a normal good). An initial exploratory analysis tests between fixed-effects and random-effects model specifications. A fixed-effects model with time-fixed effects is implemented to assess the relationship between the two measures. Unit root, Hausman and serial correlation tests are conducted to determine model fit. Additional explanatory variables are introduced in different model specifications to test the robustness of our regression results. We include the out-of-pocket (OOP) share of health spending in each model to study the potential role of financial protection in our sample of high- and middle-income countries. The first-difference of study variables is implemented to address non-stationarity and cointegration properties.

RESULTS

The elasticity of per-capita health expenditure and GDP growth is positive and statistically significant among sampled middle-income countries (51 per unit-growth in GDP) and high-income countries (50 per unit-growth in GDP). In contrast with previous research that has found that income elasticity of health spending in middle-income countries is larger than in high-income countries, our findings show that elasticity estimates can change if different criteria are used to assemble a more homogenous group of middle-income countries. Financial protection differences between middle- and high-income countries, however, are not associated with their respective income elasticity of health spending.

CONCLUSION

The study findings show that in spite of the rapid economic growth experienced by the sampled middleincome countries, the aggregated income elasticity of health expenditure in them is less than one, and equals that of high-income countries.

Impact of a Value-based Formulary on Medication Utilization, Health Services Utilization, and Expenditures

BACKGROUND

Value-based benefit design has been suggested as an effective approach to managing the high cost of pharmaceuticals in health insurance markets. Premera Blue Cross, a large regional health plan, implemented a value-based formulary (VBF) for pharmaceuticals in 2010 that explicitly used cost-effectiveness analysis (CEA) to inform medication copayments.

OBJECTIVE OF THE STUDY

The objective of the study was to determine the impact of the VBF.

DESIGN

Interrupted time series of employer-sponsored plans from 2006 to 2013.

SUBJECTS

Intervention group: 5235 beneficiaries exposed to the VBF.

CONTROL GROUP

11,171 beneficiaries in plans without any changes in pharmacy benefits.

INTERVENTION

The VBF-assigned medications with lower value (estimated by CEA) to higher copayment tiers and assigned medications with higher value to lower copayment tiers.

MEASURES

Primary outcome was medication expenditures from member, health plan, and member plus health plan perspectives. Secondary outcomes were medication utilization, emergency department visits, hospitalizations, office visits, and nonmedication expenditures.

RESULTS

In the intervention group after VBF implementation, member medication expenditures increased by $2 per member per month (PMPM) [95% confidence interval (CI), $1-$3] or 9%, whereas health plan medication expenditures decreased by $10 PMPM (CI, $18-$2) or 16%, resulting in a net decrease of $8 PMPM (CI, $15-$2) or 10%, which translates to a net savings of $1.1 million. Utilization of medications moved into lower copayment tiers increased by 1.95 days' supply (CI, 1.29-2.62) or 17%. Total medication utilization, health services utilization, and nonmedication expenditures did not change.

CONCLUSIONS

Cost-sharing informed by CEA reduced overall medication expenditures without negatively impacting medication utilization, health services utilization, or nonmedication expenditures.

Race and contrast-induced nephropathy in patients undergoing coronary angiography and cardiac catheterization

Contrast-induced nephropathy (CIN) is an acute worsening of renal function after receiving intravascular contrast during a procedure. Some of the predisposing factors include underlying diabetes, chronic kidney disease, congestive heart failure, periprocedural hypotension, anemia, contrast volume, and osmolality of contrast; however, it remains unclear if risk varies for CIN with race and ethnicity. There is evidence in the literature showing the link between race/ethnicity and the discrepancies in the utilization of preventive care services and the resources related to cardiovascular and renal health. While these disparities continue to exist and affect some of the predictors of CIN, this review will explore the extent to which race and ethnicity directly affect CIN.

Racial and ethnic disparities in meeting MTM eligibility criteria among patients with asthma

BACKGROUND

Asthma is one of the most frequently targeted chronic diseases in the medication therapy management (MTM) programs of the Medicare prescription drug (Part D) benefits. Although racial and ethnic disparities in meeting eligibility criteria for MTM services have been reported, little is known about whether there would be similar disparities among adults with asthma in the United States.

METHODS

Adult patients with asthma (age ≥ 18) from Medical Expenditure Panel Survey (2011-2012) were analyzed. Bivariate analyses were conducted to compare the proportions of patients who would meet Medicare MTM eligibility criteria between non-Hispanic Blacks (Blacks), Hispanics and non-Hispanic Whites (Whites). Survey-weighted logistic regression was performed to adjust for patient characteristics. Main and sensitivity analyses were conducted to cover the entire range of the eligibility thresholds used by Part D plans in 2011-2012.

RESULTS

The sample included 4,455 patients with asthma, including 2,294 Whites, 1,218 Blacks, and 943 Hispanics. Blacks and Hispanics had lower proportions of meeting MTM eligibility criteria than did Whites (P < 0.001). According to the main analysis, Blacks and Hispanics had 36% and 32% lower, respectively, likelihood of MTM eligibility than Whites (odds ratio [OR]: 0.64, 95% confidence interval [CI]: 0.45-0.90; OR: 0.68, 95% CI: 0.47-0.98, respectively). Similar results were obtained in sensitivity analyses.

CONCLUSIONS

There are racial and ethnic disparities in meeting Medicare Part D MTM eligibility criteria among adult patients with asthma. Future studies should examine the implications of such disparities on health outcomes of patients with asthma and explore alternative MTM eligibility criteria.

Reducing Young Adults' Health Care Spending through the ACA Expansion of Dependent Coverage

OBJECTIVE

To estimate health care expenditure trends among young adults ages 19-25 before and after the 2010 implementation of the Affordable Care Act (ACA) provision that extended eligibility for dependent private health insurance coverage.

DATA SOURCES

Nationally representative Medical Expenditure Panel Survey data from 2008 to 2012.

STUDY DESIGN

We conducted repeated cross-sectional analyses and employed a difference-in-differences quantile regression model to estimate health care expenditure trends among young adults ages 19-25 (the treatment group) and ages 27-29 (the control group).

PRINCIPAL FINDINGS

Our results show that the treatment group had 14 percent lower overall health care expenditures and 21 percent lower out-of-pocket payments compared with the control group in 2011-2012. The overall reduction in health care expenditures among young adults ages 19-25 in years 2011-2012 was more significant at the higher end of the health care expenditure distribution. Young adults ages 19-25 had significantly higher emergency department costs at the 10th percentile in 2011-2012. Differences in the trends of costs of private health insurance and doctor visits are not statistically significant.

CONCLUSIONS

Increased health insurance enrollment as a consequence of the ACA provision for dependent coverage has successfully reduced spending and catastrophic expenditures, providing financial protections for young adults.

The ACA's Dependent Coverage Expansion and Out-of-Pocket Spending by Young Adults With Behavioral Health Conditions

OBJECTIVE

Young adults with behavioral health conditions (mental or substance use disorders) often lack access to care. In 2010, the Affordable Care Act (ACA) extended eligibility for dependent coverage under private health insurance, allowing young adults to continue on family plans until age 26. The objective of this study was to analyze out-of-pocket (OOP) spending as a share of total health care expenditures for young adults with behavioral health conditions before and after the implementation of the ACA dependent care provision. The study examined the population of young adults with behavioral health conditions overall and by race and ethnicity.

METHODS

The study analyzed 2008-2009 and 2011-2012 nationally representative data from the Medical Expenditure Panel Survey with zero-or-one inflated beta regression models in a difference-in-differences framework to estimate the impact of the ACA's dependent coverage expansion. OOP spending was examined as a share of total health care expenditures among young adults with behavioral health disorders. The study compared the treatment group of individuals ages 19-25 (unweighted N=1,158) with a group ages 27-29 (unweighted N=668).

RESULTS

Young adults ages 19-25 with behavioral health disorders were significantly less likely than the older group to have high levels of OOP spending after the implementation of the ACA's dependent coverage expansion. The reduction was pronounced among young adults from racial-ethnic minority groups.

CONCLUSIONS

The extension of health insurance coverage to young adults with behavioral health disorders has provided them with additional financial protection, which can be important given the low incomes and high debt burden that characterize the age group.

Financial Barriers to Health Care Among Mexican Americans With Chronic Disease and Depression or Anxiety in El Paso, Texas

PURPOSE

To determine the barriers to health care access by chronic disease and depression/anxiety diagnosis in Mexican Americans living in El Paso, TX.

DESIGN

A secondary analysis was conducted using data for 1,002 Hispanics from El Paso, TX (2009-2010). Logistic regression was conducted for financial barriers by number of chronic conditions and depression/anxiety diagnosis. Interaction models were conducted between number of chronic conditions and depression or anxiety.

RESULTS

Depressed/anxious individuals reported more financial barriers than those with chronic conditions alone. There were significant interactions between number of chronic conditions and depression/anxiety for cost, denied treatment because of an inability to pay, and an inability to pay $25 for health care.

CONCLUSION

Financial barriers should be considered to maintain optimal care for both mental and physical health in this population.

IMPLICATIONS FOR PRACTICE

There should be more focus on the impact of depression or anxiety as financial barriers to compliance.

The heterogeneity in financial and time burden of caregiving to children with chronic conditions

We examine the financial and time burdens associated with caring for children with chronic conditions, focusing on disparities across types of conditions. Using linked data from the 2003 to 2006 National Health Interview Survey and 2004-2008 Medical Expenditure Panel Survey, we created measures of financial burden (out-of-pocket healthcare costs, the ratio of out-of-pocket healthcare costs to family income, healthcare costs paid by insurance, and total healthcare costs) and time burden (missed school time due to illness or injury and the number of doctor visits) associated with 14 groups of children's chronic conditions. We used the two-part model to assess the effect of condition on financial burden and finite mixture/latent class model to analyze the time burden of caregiving. Controlling for the influences of other socio-demographic characteristics on caregiving burden, children with chronic conditions have higher financial and time burdens relative to caregiving burdens for healthy children. Levels of financial burden and burden sharing between families and insurance system also vary by type of condition. For example, children with pervasive developmental disorder or heart disease have a relatively low financial burden for families, while imposing a high cost on the insurance system. In contrast, vision difficulties are associated with a high financial burden for families relative to the costs borne by others. With respect to time burden, conditions such as cerebral palsy and heart disease impose a low time burden, while conditions such as pervasive developmental disorder are associated with a high time burden. This study demonstrates that differences exist in caregiving burden for children by type of chronic condition. Each condition has a unique profile of time and financial cost burden for families and the insurance system. These results have implications for policymakers and for families' savings and employment decisions.

Catastrophic medical expenditure risk

We propose a measure of household exposure to particularly onerous medical expenses. The measure can be decomposed into the probability that medical expenditure exceeds a threshold, the loss due to predictably low consumption of other goods if it does and the further loss arising from the volatility of medical expenses above the threshold. Depending on the choice of threshold, the measure is consistent with a model of reference-dependent utility with loss aversion. Unlike the risk premium, the measure is only sensitive to particularly high expenses, and can identify households that expect to incur such expenses and would benefit from subsidised, but not actuarially fair, insurance. An empirical illustration using data from seven Asian countries demonstrates the importance of taking account of informal insurance and reveals clear differences in catastrophic medical expenditure risk across and within countries. In general, risk is higher among poorer, rural and chronically ill populations.

Healthcare Cost Regressions: Going Beyond the Mean to Estimate the Full Distribution

Understanding the data generating process behind healthcare costs remains a key empirical issue. Although much research to date has focused on the prediction of the conditional mean cost, this can potentially miss important features of the full distribution such as tail probabilities. We conduct a quasi-Monte Carlo experiment using the English National Health Service inpatient data to compare 14 approaches in modelling the distribution of healthcare costs: nine of which are parametric and have commonly been used to fit healthcare costs, and five others are designed specifically to construct a counterfactual distribution. Our results indicate that no one method is clearly dominant and that there is a trade-off between bias and precision of tail probability forecasts. We find that distributional methods demonstrate significant potential, particularly with larger sample sizes where the variability of predictions is reduced. Parametric distributions such as log-normal, generalised gamma and generalised beta of the second kind are found to estimate tail probabilities with high precision but with varying bias depending upon the cost threshold being considered.

A spatiotemporal quantile regression model for emergency department expenditures

Motivated by a recent study of geographic and temporal trends in emergency department care, we develop a spatiotemporal quantile regression model for the analysis of emergency department-related medical expenditures. The model yields distinct spatial patterns across time for each quantile of the response distribution, which is important in the spatial analysis of expenditures, as there is often little spatiotemporal variation in mean expenditures but more pronounced variation in the extremes. The model has a hierarchical structure incorporating patient-level and region-level predictors as well as spatiotemporal random effects. We model the random effects via intrinsic conditionally autoregressive priors, improving small-area estimation through maximum spatiotemporal smoothing. We adopt a Bayesian modeling approach based on an asymmetric Laplace distribution and develop an efficient posterior sampling scheme that relies solely on conjugate full conditionals. We apply our model to data from the Duke support repository, a large georeferenced database containing health and financial data for Duke Health System patients residing in Durham County, North Carolina.

Latino Population Growth and Hospital Uncompensated Care in California

OBJECTIVES

We examined the association between the size and growth of Latino populations and hospitals' uncompensated care in California.

METHODS

Our sample consisted of general acute care hospitals in California operating during 2000 and 2010 (n = 251). We merged California hospital data with US Census data for each hospital service area. We used spatial analysis, multivariate regression, and fixed-effect models.

RESULTS

We found a significant association between the growth of California's Latino population and hospitals' uncompensated care in the unadjusted regression. This association was still significant after we controlled for hospital and community population characteristics. After we added market characteristics into the final model, this relationship became nonsignificant.

CONCLUSIONS

Our findings suggest that systematic support is needed in areas with rapid Latino population growth to control hospitals' uncompensated care, especially if Latinos are excluded from or do not respond to the insurance options made available through the Affordable Care Act. Improving availability of resources for hospitals and providers in areas with high Latino population growth could help alleviate financial pressures.

Gender Differences in Mental Health Outcomes before, during, and after the Great Recession

We examined gender differences in mental health outcomes during and post-recession versus pre-recession. We utilized 2005-2006, 2008-2009, and 2010-2011 data from the Medical Expenditure Panel Survey. Females had lower odds of depression diagnoses during and post-recession and better mental health during the recession, but higher odds of anxiety diagnoses post-recession. Males had lower odds of depression diagnoses and better mental health during and post-recession and lower Kessler 6 scores post-recession. We conducted stratified analyses, which confirmed that the aforementioned findings were consistent across the four different regions of the U.S., by employment status, income and health care utilization. Importantly, we found that the higher odds of anxiety diagnoses among females after the recession were mainly prominent among specific subgroups of females: those who lived in the Northeast or the Midwest, the unemployed, and those with low household income. Gender differences in mental health in association with the economic recession highlight the importance of policymakers taking these differences into consideration when designing economic and social policies to address economic downturns. Future research should examine the reasons behind the decreased depression diagnoses among both genders, and whether they signify decreased mental healthcare utilization or increased social support and more time for exercise and leisure activities.

Health care spending and utilization by race/ethnicity under the Affordable Care Act's dependent coverage expansion

OBJECTIVES

We estimated the effect of the ACA expansion of dependents' coverage on health care expenditures and utilization for young adults by race/ethnicity.

METHODS

We used difference-in-difference models to estimate the impact of the ACA expansion on health care expenditures, out-of-pocket payments (OOP) as a share of total health care expenditure, and utilization among young adults aged 19 to 26 years by race/ethnicity (White, African American, Latino, and other racial/ethnic groups), with adults aged 27 to 30 years as the control group.

RESULTS

In 2011 and 2012, White and African American young adults aged 19 to 26 years had significantly lower total health care spending compared with the 27 to 30 years cohort. OOP, as a share of health care expenditure, remained the same after the ACA expansion for all race/ethnicity groups. Changes in utilization following the ACA expansion among all racial/ethnic groups for those aged 19 to 26 years were not significant.

CONCLUSIONS

Our study showed that the impact of the ACA expansion on health care expenditures differed by race/ethnicity.

Chronic conditions and medical expenditures among non-institutionalized adults in the United States

INTRODUCTION

This study sought to examine medical expenditures among non-institutionalized adults in the United States with one or more chronic conditions.

METHOD

Using data from the 2010 Medical Expenditure Panel Survey (MEPS) Household Component (HC), we explored total and out-of-pocket medical, hospital, physician office, and prescription drug expenditures for non-institutionalized adults 18 and older with and without chronic conditions. We examined relationships between expenditure differences and predisposing, enabling, and need factors using recent, nationally representative data.

RESULTS

Individuals with chronic conditions experienced higher total spending than those with no chronic conditions, even after controlling for confounding factors. This relationship persisted with age. Out-of-pocket spending trends mirrored total expenditure trends across health care categories. Additional population characteristics that were associated with high health care expenditures were race/ethnicity, marital status, insurance status, and education.

CONCLUSIONS

The high costs associated with having one or more chronic conditions indicates a need for more robust interventions to target population groups who are most at risk.

Using quantile regression to examine health care expenditures during the Great Recession

OBJECTIVE

To examine the association between the Great Recession of 2007-2009 and health care expenditures along the health care spending distribution, with a focus on racial/ethnic disparities.

DATA SOURCES/STUDY SETTING

Secondary data analyses of the Medical Expenditure Panel Survey (2005-2006 and 2008-2009).

STUDY DESIGN

Quantile multivariate regressions are employed to measure the different associations between the economic recession of 2007-2009 and health care spending. Race/ethnicity and interaction terms between race/ethnicity and a recession indicator are controlled to examine whether minorities encountered disproportionately lower health spending during the economic recession.

PRINCIPAL FINDINGS

The Great Recession was significantly associated with reductions in health care expenditures at the 10th-50th percentiles of the distribution, but not at the 75th-90th percentiles. Racial and ethnic disparities were more substantial at the lower end of the health expenditure distribution; however, on average the reduction in expenditures was similar for all race/ethnic groups. The Great Recession was also positively associated with spending on emergency department visits.

CONCLUSION

This study shows that the relationship between the Great Recession and health care spending varied along the health expenditure distribution. More variability was observed in the lower end of the health spending distribution compared to the higher end.

Highlighting differences between conditional and unconditional quantile regression approaches through an application to assess medication adherence

The quantile regression (QR) framework provides a pragmatic approach in understanding the differential impacts of covariates along the distribution of an outcome. However, the QR framework that has pervaded the applied economics literature is based on the conditional quantile regression method. It is used to assess the impact of a covariate on a quantile of the outcome conditional on specific values of other covariates. In most cases, conditional quantile regression may generate results that are often not generalizable or interpretable in a policy or population context. In contrast, the unconditional quantile regression method provides more interpretable results as it marginalizes the effect over the distributions of other covariates in the model. In this paper, the differences between these two regression frameworks are highlighted, both conceptually and econometrically. Additionally, using real-world claims data from a large US health insurer, alternative QR frameworks are implemented to assess the differential impacts of covariates along the distribution of medication adherence among elderly patients with Alzheimer's disease.

Health care expenditures among Asian American subgroups

Using two nationally representative data sets, this study examined health care expenditure disparities between Caucasians and different Asian American subgroups. Multivariate analyses demonstrate that Asian Americans, as a group, have significantly lower total expenditures compared with Caucasians. Results also point to considerable heterogeneities in health care spending within Asian American subgroups. Findings suggest that language assistance programs would be effective in reducing disparities among Caucasians and Asian American subgroups with the exception of Indians and Filipinos, who tend to be more proficient in English. Results also indicate that citizenship and nativity were major factors associated with expenditure disparities. Socioeconomic status, however, could not explain expenditure disparities. Results also show that Asian Americans have lower physician and pharmaceutical costs but not emergency department or hospital expenditures. These findings suggest the need for culturally competent policies specific to Asian American subgroups and the necessity to encourage cost-effective treatments among Asian Americans.

Measuring disparities across the distribution of mental health care expenditures

BACKGROUND

Previous mental health care disparities studies predominantly compare mean mental health care use across racial/ethnic groups, leaving policymakers with little information on disparities among those with a higher level of expenditures.

AIMS OF THE STUDY

To identify racial/ethnic disparities among individuals at varying quantiles of mental health care expenditures. To assess whether disparities in the upper quantiles of expenditure differ by insurance status, income and education.

METHODS

Data were analyzed from a nationally representative sample of white, black and Latino adults 18 years and older (n=83,878). Our dependent variable was total mental health care expenditure. We measured disparities in any mental health care expenditures, disparities in mental health care expenditure at the 95th, 97.5 th, and 99 th expenditure quantiles of the full population using quantile regression, and at the 50 th, 75 th, and 95 th quantiles for positive users. In the full population, we tested interaction coefficients between race/ethnicity and income, insurance, and education levels to determine whether racial/ethnic disparities in the upper quantiles differed by income, insurance and education.

RESULTS

Significant Black-white and Latino-white disparities were identified in any mental health care expenditures. In the full population, moving up the quantiles of mental health care expenditures, Black-White and Latino-White disparities were reduced but remained statistically significant. No statistically significant disparities were found in analyses of positive users only. The magnitude of black-white disparities was smaller among those enrolled in public insurance programs compared to the privately insured and uninsured in the 97.5 th and 99 th quantiles. Disparities persist in the upper quantiles among those in higher income categories and after excluding psychiatric inpatient and emergency department (ED) visits.

DISCUSSION

Disparities exist in any mental health care and among those that use the most mental health care resources, but much of disparities seem to be driven by lack of access. The data do not allow us to disentangle whether disparities were related to white respondent's overuse or underuse as compared to minority groups. The cross-sectional data allow us to make only associational claims about the role of insurance, income, and education in disparities. With these limitations in mind, we identified a persistence of disparities in overall expenditures even among those in the highest income categories, after controlling for mental health status and observable sociodemographic characteristics.

IMPLICATIONS FOR HEALTH CARE PROVISION AND USE

Interventions are needed to equalize resource allocation to racial/ethnic minority patients regardless of their income, with emphasis on outreach interventions to address the disparities in access that are responsible for the no/low expenditures for even Latinos at higher levels of illness severity.

IMPLICATIONS FOR HEALTH POLICIES

Increased policy efforts are needed to reduce the gap in health insurance for Latinos and improve outreach programs to enroll those in need into mental health care services.

IMPLICATIONS FOR FURTHER RESEARCH

Future studies that conclusively disentangle overuse and appropriate use in these populations are warranted.

African ancestry protects against Alzheimer's disease-related neuropathology

Previous studies in dementia epidemiology have reported higher Alzheimer's disease rates in African-Americans when compared with White Americans. To determine whether genetically determined African ancestry is associated with neuropathological changes commonly associated with dementia, we analyzed a population-based brain bank in the highly admixed city of São Paulo, Brazil. African ancestry was estimated through the use of previously described ancestry-informative markers. Risk of presence of neuritic plaques, neurofibrillary tangles, small vessel disease, brain infarcts and Lewy bodies in subjects with significant African ancestry versus those without was determined. Results were adjusted for multiple environmental risk factors, demographic variables and apolipoprotein E genotype. African ancestry was inversely correlated with neuritic plaques (P=0.03). Subjects with significant African ancestry (n=112, 55.4%) showed lower prevalence of neuritic plaques in the univariate analysis (odds ratio (OR) 0.72, 95% confidence interval (CI) 0.55-0.95, P=0.01) and when adjusted for age, sex, APOE genotype and environmental risk factors (OR 0.43, 95% CI 0.21-0.89, P=0.02). There were no significant differences for the presence of other neuropathological alterations. We show for the first time, using genetically determined ancestry, that African ancestry may be highly protective of Alzheimer's disease neuropathology, functioning through either genetic variants or unknown environmental factors. Epidemiological studies correlating African-American race/ethnicity with increased Alzheimer's disease rates should not be interpreted as surrogates of genetic ancestry or considered to represent African-derived populations from the developing nations such as Brazil.

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.

Diabetes, its treatment, and catastrophic medical spending in 35 developing countries

OBJECTIVE

To assess the individual financial impact of having diabetes in developing countries, whether diabetic individuals possess appropriate medications, and the extent to which health insurance may protect diabetic individuals by increasing medication possession or decreasing the risk of catastrophic spending.

RESEARCH DESIGN AND METHODS

Using 2002-2003 World Health Survey data (n = 121,051 individuals; 35 low- and middle-income countries), we examined possession of medications to treat diabetes and estimated the relationship between out-of-pocket medical spending (2005 international dollars), catastrophic medical spending, and diabetes. We assessed whether health insurance modified these relationships.

RESULTS

Diabetic individuals experience differentially higher out-of-pocket medical spending, particularly among individuals with high levels of spending (excess spending of $157 per year [95% CI 130-184] at the 95th percentile), and a greater chance of incurring catastrophic medical spending (17.8 vs. 13.9%; difference 3.9% [95% CI 0.2-7.7]) compared with otherwise similar individuals without diabetes. Diabetic individuals with insurance do not have significantly lower risks of catastrophic medical spending (18.6 vs. 17.7%; difference not significant), nor were they significantly more likely to possess diabetes medications (22.8 vs. 20.6%; difference not significant) than those who were otherwise similar but without insurance. These effects were more pronounced and significant in lower-income countries.

CONCLUSIONS

In low-income countries, despite insurance, diabetic individuals are more likely to experience catastrophic medical spending and often do not possess appropriate medications to treat diabetes. Research into why policies in these countries may not adequately protect people from catastrophic spending or enhance possession of critical medications is urgently needed.

A modified measure of health care disparities applied to birth weight disparities and subsequent mortality

We describe how a modified Gini index serves as an improved method of estimating health care disparities. The method, although general, is applied to an example of birth weight disparities and to their effect on subsequent mortality. The method provides the between-group results obtainable from current methods (i.e. how Hispanics generally fare relative to non-Hispanic Whites) but adds measures of within-group disparities (i.e. which specific Hispanics experience the greatest disparate treatment). Our application to birth weights and receipt of prenatal care, which may provide an upper bound because of omitted variables, shows that the time-of-birth disparities are associated with increased infant mortality within the first year of life.

Hypertension and antihypertensive therapy in Hispanics and Mexican Americans living in the United States

Hypertension is a major independent risk factor for cardiovascular diseases, which are the most frequent cause of death worldwide. In addition, the risk of hypertension has been associated with racial and/or ethnic background. Hispanics are the largest and fastest-growing minority population in the United States, currently comprising about 16.3% (50.5 million) of the total population; these numbers will continue to increase into the next 10 years. The rate of uncontrolled hypertension in Hispanics significantly exceeds the rates observed among non-Hispanic blacks and whites. The reasons for these racial and ethnic differences in blood pressure control may include factors such as lack of access to health care, low socioeconomic status, language barriers, degree of acculturation, poor doctor-patient communication, and genetic factors. This article provides an up-to-date summary of epidemiological and treatment aspects of high blood pressure in the US Hispanic population. Because Mexican Americans constitute approximately 66% of US Hispanics, data sources that focus on Mexican Americans are also discussed.

Health expenditure dynamics and years of U.S. residence: analyzing spending disparities among Latinos by citizenship/nativity status

OBJECTIVE

We investigate health expenditure disparities between Latinos and non-Latino whites by years of United States residence and citizenship/nativity status.

DATA SOURCES

We link the Medical Expenditure Panel Survey and the National Health Interview Survey from 2000 to 2007. The sample consists of 31,514 Latinos and 76,021 white adults (18-64 years).

STUDY DESIGN

The likelihood of any health spending, total health expenditure, and the out-of-pocket (OOP) share of health expenditure are our main dependent variables. We use two-part multivariate models to adjust for confounding factors. A stratified analysis by insurance status checks for the results' robustness. The decomposition technique is implemented to estimate the share of disparities that can be explained by observed and unobserved variables.

PRINCIPAL FINDINGS

Latinos are much less likely to have any health spending (68 percent), total health expenditure (57 percent), and more likely to pay OOP (6 percent) compared with the white population. Overall, disparities narrow or disappear for naturalized Latinos the longer they stay in the country. Among noncitizen Latinos, disparities remain constant or decline slightly, but they remain large over time.

CONCLUSIONS

Low-health spending by foreign-born Latinos contributes to health expenditure disparities between Latinos and whites. Our findings provide preliminary evidence on health-spending convergence over time between foreign-born Latinos and that of whites.

Using race as a case-mix adjustment factor in a renal dialysis payment system: potential and pitfalls

BACKGROUND

Racial disparities in health care are widespread in the United States. Identifying contributing factors may improve care for underserved minorities. To the extent that differential utilization of services, based on need or biological effect, contributes to outcome disparities, prospective payment systems may require inclusion of race to minimize these adverse effects. This research determines whether costs associated with end-stage renal disease (ESRD) care varied by race and whether this variance affected payments to dialysis facilities.

STUDY DESIGN

We compared the classification of race across Medicare databases and investigated differences in cost of care for long-term dialysis patients by race.

SETTING & PARTICIPANTS

Medicare ESRD database including 890,776 patient-years in 2004-2006.

PREDICTORS

Patient race and ethnicity.

OUTCOMES

Costs associated with ESRD care and estimated payments to dialysis facilities under a prospective payment system.

RESULTS

There were inconsistencies in race and ethnicity classification; however, there was significant agreement for classification of black and nonblack race across databases. In predictive models evaluating the cost of outpatient dialysis care for Medicare patients, race is a significant predictor of cost, particularly for cost of separately billed injectable medications used in dialysis. Overall, black patients had 9% higher costs than nonblack patients. In a model that did not adjust for race, other patient characteristics accounted for only 31% of this difference.

LIMITATIONS

Lack of information about biological causes of the link between race and cost.

CONCLUSIONS

There is a significant racial difference in the cost of providing dialysis care that is not accounted for by other factors that may be used to adjust payments. This difference has the potential to affect the delivery of care to certain populations. Of note, inclusion of race into a prospective payment system will require better understanding of biological differences in bone and anemia outcomes, as well as effects of inclusion on self-reported race.

Definition and use of the variable "race" by medical students in Salvador, Brazil

CONTEXT AND OBJECTIVE

The lack of a clear definition for human "race" and the importance of this topic in medical practice continue to create doubt among scholars. Here, we evaluate the use of the variable "race" by medical students in Salvador, Brazil.

DESIGN AND SETTING

Cross-sectional study at a Brazilian federal public university.

METHODS

221 randomly selected subjects were included. A semi-structured questionnaire was used for data collection. The results were expressed as means and standard deviations of the mean, proportions and frequencies. The χ2 (chi-square) test was used for the statistical calculations.

RESULTS

Approximately half of the students (45.4%) used the racial group variable in their studies on clinical practice. Of these, 86.8% considered it to be relevant information in the medical records and 92.7%, important for diagnostic reasoning; 95.9% believed that it influenced the cause, expression and prevalence of diseases; 94.9% affirmed that it contributed towards estimating the risk of diseases; 80.5% thought that the therapeutic response to medications might be influenced by racial characteristics; 41.9% considered that its inclusion in research was always recommendable; and 20.3% thought it was indispensable. The main phenotypic characteristics used for racial classification were: skin color (93.2%), hair type (45.7%), nose shape (33.9%) and lip thickness (30.3%).

CONCLUSIONS

Despite the importance of different racial groups in medical practice, the majority of the professionals do not use or know how to classify them. It is necessary to add to and/or expand the discussion of racial and ethnic categories in medical practice and research.