Implementing health reform: improved data collection and the monitoring of health disparities

Health Equity in the Care of Adult Critical Illness Survivors

There is evidence that people who fare worse in recovery do so, not only because of their illness, but also because of social and structural determinants. For example, food insecurity and poor nutrition, unemployment, poverty, social isolation and loneliness, limited social support, and poor access to medical care represent marked obstacles to recovery. Those who experience social or structural disadvantage have a poor start to their critical illness journey and are more vulnerable to adverse material conditions that contribute to and worsen their health outcomes.

Contextualized race and ethnicity annotations for clinical text from MIMIC-III

Observational health research often relies on accurate and complete race and ethnicity (RE) patient information, such as characterizing cohorts, assessing quality/performance metrics of hospitals and health systems, and identifying health disparities. While the electronic health record contains structured data such as accessible patient-level RE data, it is often missing, inaccurate, or lacking granular details. Natural language processing models can be trained to identify RE in clinical text which can supplement missing RE data in clinical data repositories. Here we describe the Contextualized Race and Ethnicity Annotations for Clinical Text (C-REACT) Dataset, which comprises 12,000 patients and 17,281 sentences from their clinical notes in the MIMIC-III dataset. Using these sentences, two sets of reference standard annotations for RE data are made available with annotation guidelines. The first set of annotations comprise highly granular information related to RE, such as preferred language and country of origin, while the second set contains RE labels annotated by physicians. This dataset can support health systems' ability to use RE data to serve health equity goals.

Cardiovascular Disease Mortality Among Native Hawaiian and Pacific Islander Adults Aged 35 Years or Older, 2018 to 2022

BACKGROUND

Native Hawaiian and Pacific Islander (NHPI) adults have historically been grouped with Asian adults in U.S. mortality surveillance. Starting in 2018, the 1997 race and ethnicity standards from the U.S. Office of Management and Budget were adopted by all states on death certificates, enabling national-level estimates of cardiovascular disease (CVD) mortality for NHPI adults independent of Asian adults.

OBJECTIVE

To describe CVD mortality among NHPI adults.

DESIGN

Race-stratified age-standardized mortality rates (ASMRs) and rate ratios were calculated using final mortality data from the National Vital Statistics System for 2018 to 2022.

SETTING

Fifty states and the District of Columbia.

PARTICIPANTS

Adults aged 35 years or older at the time of death.

MEASUREMENTS

CVD deaths were identified from International Classification of Diseases, 10th Revision codes indicating CVD (I00 to I99) as the underlying cause of death.

RESULTS

From 2018 to 2022, 10 870 CVD deaths (72.6% from heart disease; 19.0% from cerebrovascular disease) occurred among NHPI adults. The CVD ASMR for NHPI adults (369.6 deaths per 100 000 persons [95% CI, 362.4 to 376.7]) was 1.5 times higher than for Asian adults (243.9 deaths per 100 000 persons [CI, 242.6 to 245.2]). The CVD ASMR for NHPI adults was the third highest in the country, after Black adults (558.8 deaths per 100 000 persons [CI, 557.4 to 560.3]) and White adults (423.6 deaths per 100 000 persons [CI, 423.2 to 424.1]).

LIMITATION

Potential misclassification of underlying cause of death or race group.

CONCLUSION

NHPI adults have a high rate of CVD mortality, which was previously masked by aggregation of the NHPI population with the Asian population. The results of this study support the need for continued disaggregation of the NHPI population in public health research and surveillance to identify opportunities for intervention.

PRIMARY FUNDING SOURCE

National Institute of General Medical Sciences, National Institutes of Health.

Measuring disability among U.S. adolescents and young adults: A survey measurement experiment

Objective

Disability is identified in surveys using various question sets, with little understanding of reliability across these measures, nor how these estimates may vary across age groups, including adolescents and young adults (AYA). The purpose of this study was to assess AYA prevalence of disability using two disability question sets and reliability of these measures.

Methods

AYA participants in the Policy and Communication Evaluation (PACE) Vermont Study completed a single-item disability question used in the National Survey on Health and Disability (NSHD) and Urban Institute's Health Reform Monitoring Survey (HRMS) and a six-item set on functioning (Washington Group-Short Set, WG-SS) from the National Health Interview Survey (NHIS) and National Survey on Drug Use and Health (NSDUH) in 2021. Prevalence was estimated for any disability and each disability domain in adolescents (ages 12-17) and young adults (ages 18-25) and compared with U.S. national estimates in NHIS and NSDUH.

Results

Using the WG-SS, the prevalence of any disability was 17.0 % in PACE Vermont adolescents and 22.0 % in young adults, consistent with the national prevalence of adolescents in NSDUH (17.9 %) but higher than estimates of young adults in NHIS (3.9 %) and NSDUH (12.9 %). The single-item question provided lower estimates of disability (adolescents: 6.9 %; young adults: 18.5 %) than the WG-SS, with low positive agreement between measures.

Discussion

The prevalence of disability in AYAs varies depending on measures used. To improve disability surveillance, it may be necessary to validate new disability questions, including among AYAs, to capture a broader range of disability domains.

Documenting language barriers in a general hospital psychiatry setting

Previous research has demonstrated that without the use of professional interpreters, language barriers interfere with patient care. The literature recommends documenting the presence of language barriers in medical charts. To our knowledge, this mixed methods study is the first to examine language documentation practices in a Canadian inpatient psychiatry setting. The research team interviewed 122 patients admitted to a tertiary care psychiatry ward in Montreal, Canada between 2016-2017 to assess their ability to communicate in the healthcare establishment's languages (English/French). Nineteen participants identified as having a language barrier were selected for a qualitative analysis of the retrospective audit of their medical charts. The presence of a language barrier was reflected in 68% of these charts. When a language barrier was documented, professional interpreters were never used. Our qualitative analysis, informed by literature on medical discourse, aimed to provide clinical, administrative, and organizational recommendations to optimize the utilization of interpreting services in psychiatric wards. Documentation of language data was inconsistently collected, often vague, and shed light on the clinical challenges involved in differentiating language barriers from psychopathology. Normalization of limited care for language diverse patients was reflected in the clinical notes. Findings show that a change of organizational culture is imperative to provide optimal care to language diverse patients. We recommend clinician education and standardization of documentation practices, along with institutional policies supporting the systematic use of professional interpreters in mental healthcare settings, to maximize human rights and patient safety, and to bring medical practices to an acceptable standard of care.

Race: How the Post-Genomic Era Has Unmasked a Misconception Promoted by Healthcare

The term "race" has been employed to categorize human beings into distinct groups based on some perceived biological distinctions. This concept was debunked with the completion of the Human Genome Project and its revolutionary findings that all humans are >99% genetically identical, subsequently making the term "race" obsolete. Unfortunately, the previous misconception is being propagated by the continued use of the term to capture demographic information in healthcare in an attempt to improve equity. This paper seeks to review the history of the term "race", analyze the current policy, and discuss its limitations. It is important to note that our analysis was exclusively focused on the United States healthcare system and the Affordable Care Act; as such, it may not reflect other regions' policies, including those in Africa, Asia, and the Middle East. However, we feel that this policy analysis may serve as a model to recommend alterations that mirror the post-genomic era. The need for this policy change was recently highlighted in the 2022 ASHG presidential address, One Human Race: Billions of Genomes, and will reflect the knowledge gleaned by the scientific community through the conclusions of the Human Genome Project.

Screening for Social Determinants of Health in the Pediatric Intensive Care Unit: Recommendations for Clinicians

Social determinants of health (SDoH) play a significant role in the health and well-being of children in the United States. Disparities in the risk and outcomes of critical illness have been extensively documented but are yet to be fully explored through the lens of SDoH. In this review, we provide justification for routine SDoH screening as a critical first step toward understanding the causes of, and effectively addressing health disparities affecting critically ill children. Second, we summarize important aspects of SDoH screening that need to be considered before implementing this practice in the pediatric critical care setting.

Need for Improved Collection and Harmonization of Rural Maternal Healthcare Data

Representation in data sets is critical to improving healthcare for the largest possible number of people. Unfortunately, pregnancy is a very understudied period of time. Further, the gap in available data is wide between pregnancies in urban areas versus rural areas. There are many limitations in the current data that is available. Herein, we review these limitations and strengths of available data sources. In addition, we propose a new mechanism to enhance the granularity, depth, and speed with which data is made available regarding rural pregnancy.

Perinatal Health Risks And Outcomes Among US Women With Self-Reported Disability, 2011-19

Women with disabilities experience elevated risk for adverse pregnancy outcomes. Most studies have inferred disabilities from diagnosis codes, likely undercounting disabilities. We analyzed data, including self-reported disability status, from the National Survey of Family Growth for the period 2011-19. We compared respondents with and without disabilities on these characteristics: smoking during pregnancy, delayed prenatal care, preterm birth, and low birthweight. A total of 19.5 percent of respondents who had given birth reported a disability, which is a much higher prevalence than estimates reported in US studies using diagnosis codes. Respondents with disabilities were twice as likely as those without disabilities to have smoked during pregnancy (19.0 percent versus 8.9 percent). They also had 24 percent and 29 percent higher risk for preterm birth and low birthweight, respectively. Our findings suggest that studies using diagnosis codes may represent only a small proportion of pregnancies among people with disabilities. Measurement and analysis of self-reported disability would facilitate better understanding of the full extent of disability-related disparities, per the Affordable Care Act.

Health Disparity Measurement Among Asian American, Native Hawaiian, and Pacific Islander Populations Across the United States

Objective:

The aim of this study was to describe current measurement of health disparities for Asian American, Native Hawaiian, and Pacific Islander (AANHPI) populations and subgroups across U.S. states.

Methods:

State department of health websites were searched for publicly available online reports and interactive databases denoted as state health or minority health assessments. Sources were examined to determine whether health metrics stratified by any racial/ethnic groups included the AANHPI aggregate population or subgroups. The number and frequency of AANHPI population designations were tabulated, as were the proportion of states that included AANHPIs in stratified metrics in four domains across the life span and the median number of metrics (1) stratified by any racial/ethnic group and (2) including AANHPI populations. A Pearson correlation coefficient assessed the association between the proportion of AANHPIs in state populations and the proportion of state metrics that included AANHPIs in the stratification.

Results:

States used 17 AANHPI population descriptors. Of 49 states stratifying health metrics by race/ethnicity, 34 included AANHPI populations and 2 included disaggregated AANHPI subgroups in ≥1 metric. The proportion of states that included AANHPI populations in stratification ranged from 57% for maternal–infant health to 69% for adult health, and by metric groups within domains, the proportion ranged from 14% for maternal mortality to 100% for marital or head of household status. The median number of metrics reported for AANHPI populations was lower than the median number reported for other racial/ethnic groups in adult, maternal–infant, and child and adolescent health domains. The proportion of state metrics that included AANHPIs in racial/ethnic stratification was not correlated with the proportion of AANHPIs in state populations (r=0.30).

Conclusions and Implications for Health Equity:

AANHPIs were substantially underrepresented in state health equity data, with rare subgroup disaggregation. Reducing disparities and inequities affecting AANHPI health in the United States requires improved and equitable data.

Achieving Greater Health Equity: An Opportunity for Anesthesiology

Anesthesiology and anesthesiologists have a tremendous opportunity and responsibility to eliminate health disparities and to achieve health equity. We thus examine health disparity and health equity through the lens of anesthesiology and the perspective of anesthesiologists. In this paper, we define health disparity and health care disparities and provide tangible, representative examples of the latter in the practice of anesthesiology. We define health equity, primarily as the desired antithesis of health disparity. Finally, we propose a framework for anesthesiologists, working toward mitigating health disparity and health care disparities, advancing health equity, and documenting improvements in health care access and health outcomes. This multilevel and interdependent framework includes the perspectives of the patient, clinician, group or department, health care system, and professional societies, including medical journals. We specifically focus on the interrelated roles of social identity and social determinants of health in health outcomes. We explore the foundational role that clinical informatics and valid data collection on race and ethnicity have in achieving health equity. Our ability to ensure patient safety by considering these additional patient-specific factors that affect clinical outcomes throughout the perioperative period could substantially reduce health disparities. Finally, we explore the role of medical journals and their editorial boards in ameliorating health disparities and advancing health equity.

Data Consultations, Racism, and Critiquing Colonialism in Demographic Datasheets

Objective: We consider how data librarians can take antiracist action in education and consultations. We attempt to apply QuantCrit thinking, particularly to demographic datasheets. Methods: We synthesize historical context with modern critical thinking about race and data to examine the origins of current assumptions about data. We then present examples of how racial categories can hide, rather than reveal, racial disparities. Finally, we apply the Model of Domain Learning to explain why data science and data management experts can and should expose experts in subject research to the idea of critically examining demographic data collection. Results: There are good reasons why patrons who are experts in topics other than racism can find it challenging to change habits from Interoperable approaches to race. Nevertheless, the Census categories explicitly say that they have no basis in research or science. Therefore, social justice requires that data librarians should expose researchers to this fact. If possible, data librarians should also consult on alternatives to habitual use of the Census racial categories. Conclusions: We suggest that many studies are harmed by including race and should remove it entirely. Those studies that are truly examining race should reflect on their research question and seek more relevant racial questions for data collection.

Asian American Pacific Islander Representation in Outcomes Research: NSQIP Scoping Review

BACKGROUND

If Asian American and Pacific Islanders (AAPIs) are not recognized within patients in health services research, we miss an opportunity to ensure health equity in patient outcomes. However, it is unknown what the rates are of AAPIs inclusion in surgical outcomes research.

STUDY DESIGN

Through a scoping review, we used Covidence to search MEDLINE, EMBASE, PsycINFO, Web of Science, Scopus, and CINAHL for studies published in 2008-2018 using NSQIP data. NSQIP was chosen because of its national scope, widespread use in research, and coding inclusive of AAPI patients. We examined the proportion of studies representing AAPI patients in the demographic characteristics and Methods, Results, or Discussion section. We then performed multivariable logistic regression to examine associations between study characteristics and AAPI inclusion.

RESULTS

In 1,264 studies included for review, 62% included race. Overall, only 22% (n = 278) of studies included AAPI patients. Of studies that included race, 35% represented AAPI patients in some component of the study. We found no association between sample size or publication year and inclusion. Studies were significantly more likely to represent AAPI patients when there was a higher AAPI population in the region of the first author's institution (lowest vs highest tercile; p < 0.001). Studies with a focus on disparities were more likely to include AAPI patients (p = 0.001).

CONCLUSIONS

Our study is the first to examine AAPI representation in surgical outcomes research. We found < 75% of studies examine race, despite availability within NSQIP. Little more than one-third of studies including race reported on AAPI patients as a separate group. To provide the best care, we must include AAPI patients in our research.

The Effectiveness of Collaborative Care on Depression Outcomes for Racial/Ethnic Minority Populations in Primary Care: A Systematic Review

BACKGROUND

Racial/ethnic minorities experience a greater burden of mental health problems than white adults in the United States. The collaborative care model is increasingly being adopted to improve access to services and to promote diagnosis and treatment of psychiatric diseases.

OBJECTIVE

This systematic review seeks to summarize what is known about collaborative care on depression outcomes for racial/ethnic minorities in the United States.

METHODS

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. Collaborative care studies were included if they comprised adults from at least one racial/ethnic minority group, were located in primary care clinics in the United States, and had depression outcome measures. Core principles described by the University of Washington Advancing Integrated Mental Health Solutions Center were used to define the components of collaborative care.

RESULTS

Of 398 titles screened, 169 full-length articles were assessed for eligibility, and 19 studies were included in our review (10 randomized controlled trials, 9 observational). Results show there is potential that collaborative care, with or without cultural/linguistic tailoring, is effective in improving depression for racial/ethnic minorities, including those from low socioeconomic backgrounds.

CONCLUSIONS

Collaborative care should be explored as an intervention for treating depression for racial/ethnic minority patients in primary care. Questions remain as to what elements of cultural adaptation are most helpful, factors behind the difficulty in recruiting minority patients for these studies, and how the inclusion of virtual components changes access to and delivery of care. Future research should also recruit individuals from less studied populations.

Medicaid And Private Insurance Coverage For Low-Income Asian Americans, Native Hawaiians, And Pacific Islanders, 2010-16

To determine how low-income Asian American, Native Hawaiian, and Pacific Islander (AANHPI) adults gained health insurance coverage-specifically, via Medicaid or private insurance-under the Affordable Care Act, we used a difference-in-differences approach to compare uninsurance rates in 2010-13 and 2015-16. In Medicaid expansion states, adjusted Medicaid coverage gains were 9.67 percentage points larger than in nonexpansion states; however, adjusted private coverage gains in expansion states were 10.19 percentage points lower. These results indicate that, in contrast to the case for other racial/ethnic groups, for AANHPI the Medicaid coverage increases in expansion states were of similar magnitude to the private insurance coverage increases in nonexpansion states. Reasons for this may include differences in willingness to enroll in public versus private coverage, barriers related to language or citizenship status, or other factors. Future studies are needed to understand these patterns and promote health equity for this population.

Challenges with quality of race and ethnicity data in observational databases

OBJECTIVE

We sought to assess the quality of race and ethnicity information in observational health databases, including electronic health records (EHRs), and to propose patient self-recording as an improvement strategy.

MATERIALS AND METHODS

We assessed completeness of race and ethnicity information in large observational health databases in the United States (Healthcare Cost and Utilization Project and Optum Labs), and at a single healthcare system in New York City serving a racially and ethnically diverse population. We compared race and ethnicity data collected via administrative processes with data recorded directly by respondents via paper surveys (National Health and Nutrition Examination Survey and Hospital Consumer Assessment of Healthcare Providers and Systems). Respondent-recorded data were considered the gold standard for the collection of race and ethnicity information.

RESULTS

Among the 160 million patients from the Healthcare Cost and Utilization Project and Optum Labs datasets, race or ethnicity was unknown for 25%. Among the 2.4 million patients in the single New York City healthcare system's EHR, race or ethnicity was unknown for 57%. However, when patients directly recorded their race and ethnicity, 86% provided clinically meaningful information, and 66% of patients reported information that was discrepant with the EHR.

DISCUSSION

Race and ethnicity data are critical to support precision medicine initiatives and to determine healthcare disparities; however, the quality of this information in observational databases is concerning. Patient self-recording through the use of patient-facing tools can substantially increase the quality of the information while engaging patients in their health.

CONCLUSIONS

Patient self-recording may improve the completeness of race and ethnicity information.

Trends in Clinical Research Including Asian American, Native Hawaiian, and Pacific Islander Participants Funded by the US National Institutes of Health, 1992 to 2018

Importance

Advancing the health equity agenda for Asian American, Native Hawaiian, and Pacific Islander (AA/NHPI) individuals has become an intersecting priority for federal agencies. However, the impact of federal investments and legislation to ensure systematic processes and resources to eliminate health disparities in AA/NHPI populations is unclear.

Objective

To perform a portfolio review of clinical research funded by the National Institutes of Health (NIH) for AA/NHPI populations and determine the level of NIH investment in serving these populations.

Design, Setting, and Participants

Cross-sectional study in which the NIH Research Portfolio Online Reporting Tools Expenditures and Results system was queried for extramural AA/NHPI-focused clinical research projects conducted in the United States from January 1, 1992, to December 31, 2018. Clinical research funded under research project grants, centers, cooperative awards, research career awards, training grants, and fellowships was included, with an advanced text search for AA/NHPI countries and cultures of origin. Project titles and terms were screened for inclusion and project abstracts were reviewed to verify eligibility. Descriptive analyses were completed.

Main Outcomes and Measures

Outcomes included NIH funding trends and characteristics of funded projects and organizations. The proportions of AA/NHPI-related funding trends were calculated using 2 denominators, total NIH expenditures and clinical research expenditures.

Results

There were 5460 records identified, of which 891 studies were reviewed for eligibility. Of these, 529 clinical research studies focused on AA/NHPI participants composed 0.17% of the total NIH budget over 26 years. Projects studying AA/NHPI individuals in addition to other populations were funded across 17 NIH institutes and centers. The top 5 funders collectively contributed almost 60% of the total funding dollars for AA/NHPI projects and were the National Cancer Institute ($231 584 664), National Institute on Aging ($108 365 124), National Heart, Lung, and Blood Institute ($67 232 910), National Institute on Minority Health and Health Disparities ($62 982 901), and National Institute on Mental Health ($60 072 779). Funding of these projects ($775 536 121) made up 0.17% of the overall NIH expenditures ($451 284 075 000) between 1992 and 2018, and 0.18% ($677 479 468) of the NIH research budget after 2000. Funding for AA/NHPI projects significantly increased over time, but the proportion of the total NIH budget has only increased from 0.12% before 2000 to 0.18% after 2000. Of total funding, 60.8% was awarded to research project grants compared with only 5.1% allocated to research career awards, training grants, and fellowships.

Conclusions and Relevance

Increases in research dollars for AA/NHPI clinical research were not associated with increases in the overall NIH research budget, and underrepresentation of AA/NHPI subgroups still remains. Without overt direction from federal entities and dedicated funds for health disparities research, as well as parallel efforts to increase diversity in the biomedical workforce, investments may continue to languish for AA/NHPI populations.

A patient and family data domain collection framework for identifying disparities in pediatrics: results from the pediatric health equity collaborative

BACKGROUND

By 2020, the child population is projected to have more racial and ethnic minorities make up the majority of the populations and health care organizations will need to have a system in place that collects accurate and reliable demographic data in order to monitor disparities. The goals of this group were to establish sample practices, approaches and lessons learned with regard to race, ethnicity, language, and other demographic data collection in pediatric care setting.

METHODS

A panel of 16 research and clinical professional experts working in 10 pediatric care delivery systems in the US and Canada convened twice in person for 3-day consensus development meetings and met multiple times via conference calls over a two year period. Current evidence on adult demographic data collection was systematically reviewed and unique aspects of data collection in the pediatric setting were outlined. Human centered design methods were utilized to facilitate theme development, facilitate constructive and innovative discussion, and generate consensus.

RESULTS

Group consensus determined six final data collection domains: 1) caregivers, 2) race and ethnicity, 3) language, 4) sexual orientation and gender identity, 5) disability, and 6) social determinants of health. For each domain, the group defined the domain, established a rational for collection, identified the unique challenges for data collection in a pediatric setting, and developed sample practices which are based on the experience of the members as a starting point to allow for customization unique to each health care organization. Several unique challenges in the pediatric setting across all domains include: data collection on caregivers, determining an age at which it is appropriate to collect data from the patient, collecting and updating data at multiple points across the lifespan, the limits of the electronic health record, and determining the purpose of the data collection before implementation.

CONCLUSIONS

There is no single approach that will work for all organizations when collecting race, ethnicity, language and other social determinants of health data. Each organization will need to tailor their data collection based on the population they serve, the financial resources available, and the capacity of the electronic health record.

Collection of Data on Race, Ethnicity, Language, and Nativity by US Public Health Surveillance and Monitoring Systems: Gaps and Opportunities

OBJECTIVE

Despite increasing diversity in the US population, substantial gaps in collecting data on race, ethnicity, primary language, and nativity indicators persist in public health surveillance and monitoring systems. In addition, few systems provide questionnaires in foreign languages for inclusion of non-English speakers. We assessed (1) the extent of data collected on race, ethnicity, primary language, and nativity indicators (ie, place of birth, immigration status, and years in the United States) and (2) the use of data-collection instruments in non-English languages among Centers for Disease Control and Prevention (CDC)-supported public health surveillance and monitoring systems in the United States.

METHODS

We identified CDC-supported surveillance and health monitoring systems in place from 2010 through 2013 by searching CDC websites and other federal websites. For each system, we assessed its website, documentation, and publications for evidence of the variables of interest and use of data-collection instruments in non-English languages. We requested missing information from CDC program officials, as needed.

RESULTS

Of 125 data systems, 100 (80%) collected data on race and ethnicity, 2 more collected data on ethnicity but not race, 26 (21%) collected data on racial/ethnic subcategories, 40 (32%) collected data on place of birth, 21 (17%) collected data on years in the United States, 14 (11%) collected data on immigration status, 13 (10%) collected data on primary language, and 29 (23%) used non-English data-collection instruments. Population-based surveys and disease registries more often collected data on detailed variables than did case-based, administrative, and multiple-source systems.

CONCLUSIONS

More complete and accurate data on race, ethnicity, primary language, and nativity can improve the quality, representativeness, and usefulness of public health surveillance and monitoring systems to plan and evaluate targeted public health interventions to eliminate health disparities.

Health spending among working-age immigrants with disabilities compared to those born in the US

BACKGROUND

Immigrants have disparate access to health care. Disabilities can amplify their health care burdens.

OBJECTIVE/HYPOTHESIS

Examine how US- and foreign-born working-age adults with disabilities differ in their health care spending patterns.

METHODS

Medical Expenditures Panel Survey yearly-consolidated files (2000-2010) on working-age adults (18-64 years) with disabilities. We used three operational definitions of disability: physical, cognitive, and sensory. We examined annual total, outpatient/office-based, prescription medication, inpatient, and emergency department (ED) health expenditures. We tested bivariate logistic and linear regression models to, respectively, assess unadjusted group differences in the propensity to spend and average expenditures. Second, we used multivariable two-part models to estimate and test per-capita expenditures adjusted for predisposing, enabling, health need and behavior indicators.

RESULTS

Adjusted for age and sex differences, US-born respondents with physical, cognitive, sensory spent on average $2977, $3312, and $2355 more in total compared to their foreign-born counterparts (P < 0.01). US-born spending was also higher across the four types of health care expenditures considered. Adjusting for the behavioral model factors, especially predisposing and enabling indicators, substantially reduced nativity differences in overall, outpatient/office-based and medication spending but not in inpatient and ED expenditures.

CONCLUSIONS

Working-age immigrants with disabilities have lower levels of health care use and expenditures compared to their US-born counterparts. Affordable Care Act provisions aimed at increasing access to insurance and primary care can potentially align the consumption patterns of US- and foreign-born disabled working-age adults. More work is needed to understand the pathways leading to differences in hospital and prescription medication care.

Racial and Ethnic Health Disparities and the Affordable Care Act: a Status Update

Persistent racial and ethnic health disparities exist in the USA, despite decades of research and public health initiatives. Several factors contribute to health disparities, including (but not limited to) implicit provider bias, access to health care, social determinants, and biological factors. Disparities in health by race/ethnicity are unacceptable and correctable. The Patient Protection and Affordable Care Act is a comprehensive legislation that is focused on improving health care access, quality, and cost control. This health care reform includes specific provisions which focus on preventive care, the standardized collection of data on race, ethnicity, primary language and disability status, and health information technology. Although some provisions of the Patient Protection and Affordable Care Act have not been implemented, such as funding for the U.S. Public Health Sciences track, which would have addressed the shortage of medical professionals in the USA who are trained to use patient-centered, interdisciplinary, and care coordination approaches, this legislation is still poised to make great strides toward eliminating health disparities. The purpose of this manuscript is to highlight the unprecedented opportunities that exist for the Patient Protection and Affordable Care Act to reduce racial and ethnic disparities in health in the USA.