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National Healthcare Disparities Report, 2013

Chapter 11. Priority Populations

To examine the issue of disparities in health care, Congress directed the Agency for Healthcare Research and Quality (AHRQ) to produce an annual report to track disparities related to "racial factors and socioeconomic factors in priority populations."i Although the emphasis is on disparities related to race, ethnicity, and socioeconomic status, this directive includes a charge to examine disparities in "priority populations," which are groups with unique health care needs or issues that require special attention.

Integrated throughout the Highlights in both the National Healthcare Disparities Report (NHDR) and the National Healthcare Quality Report (NHQR) and Chapters 2 through 10 of this report are racial, ethnic, socioeconomic, sex, geographic location, and age differences in quality of and access to health care in the general U.S. population. Subpopulation data for Asians and Hispanics are also integrated into these chapters where data are available.

Chapter 11 of the NHDR addresses the congressional directive on priority populations in addition to what is presented throughout the NHDR and in the NHQR this year.ii This chapter summarizes findings from data available on differences for racial, ethnic, and low-income populations, as well as for residents of rural areas and people with disabilities (activity limitations).

This year the NHDR displays prevalence of multiple chronic conditions (MCC) among Medicare beneficiaries. According to the Centers for Medicare & Medicaid Services (CMS), Medicare beneficiaries with MCC are at increased risk for poor outcomes such as mortality and functional limitations and associated high-cost services such as hospitalizations and emergency room visits.

The NHDR also continues to feature health care data on lesbian, gay, bisexual, and transgender (LGBT) populations using data from the California Health Interview Survey (CHIS). This section will continue to be an evolving part of the reports as the Department of Health and Human Services (HHS) and other organizations develop health care measures and data relevant to LGBT populations.

The approach taken in this chapter may help policymakers understand the impact of racial, ethnic, and socioeconomic differences on specific populations and target quality improvement programs toward groups in greatest need. The online data tables include detailed data that allow examination of racial, ethnic, and socioeconomic disparities both in the general population and across priority populations for most measures.

AHRQ's Priority Populations

AHRQ's priority populations, specified by Congress in the Healthcare Research and Quality Act of 1999 (Public Law 106-129), are:

  • Racial and ethnic minority groups.iii
  • Low-income groups.iv
  • Women.
  • Children (under age 18).
  • Older adults (age 65 and over).
  • Residents of rural areas.v
  • Individuals with special health care needsvi  including individuals with disabilities and individuals who need chronic care or end-of-life care.

Although not mandated, other populations, such as LGBT and people with MCC, are also included.

How This Chapter Is Organized

This chapter provides the most recent information available on racial, ethnic, and income differences in quality and access for priority populations. It is presented in the following order:

  • Racial and ethnic minorities.
  • Low-income groups.
  • Residents of rural areas.
  • Individuals with disabilities or special health care needs.
  • Individuals with MCC.
  • LGBT individuals.

Measures related to women, children, and older adults are integrated into other chapters of this report and the online data tables and include comparisons by sex and age. A list of where this information for these populations can be found in the reports is provided in the online Priority Populations appendix.

This chapter does not provide a comprehensive assessment of health care differences in each priority population. In general, most of the measures tracked in the NHQR and NHDR were selected to be applicable across many population groups to fulfill the purpose of these reports, which is to track quality and disparities at the national level.

These general measures overlook some important health care problems specific to particular populations. For example, people with disabilities may face barriers in getting access to care and experience differences in quality of care that are not captured by data because of the limitations in the survey instruments and other data collection instruments.

Racial and Ethnic Minorities

In 2012, the total minority population of the United States, which includes all racial and ethnic groups except for non-Hispanic Whites, was 116 million (37% of the U.S. population; Census Bureau, 2012c). By 2050, it is projected that these groups will account for almost half of the U.S. population (Census Bureau, 2012a).

Racial and ethnic minorities are more likely than non-Hispanic Whites to be poor or near poor (Lillie-Blanton, et al., 2003). In addition, Hispanics, Blacks, and some Asian subgroups are less likely than non-Hispanic Whites to have a high school education (Aud, et al., 2010).

Previous chapters of the NHDR describe health care differences by racial and ethnic categories as defined by the Office of Management and Budget (OMB) and used by the U.S. Census Bureau (Executive Office of the President, 1997). In this section, quality of and access to health care for each minority group are summarized to the extent that statistically reliable data are available for each group.

Criteria for importance are that the difference be statistically significant at the alpha ≤0.05 level (two-tailed test) and that the relative difference from the reference group be at least 10% when framed positively as a favorable outcome or negatively as an adverse outcome. Access measures focus on facilitators and barriers to health care and exclude health care utilization measures.

Changes Over Time

This section also examines changes over time in differences related to race and ethnicity. For each measure, racial, ethnic, and socioeconomic groups are compared with a designated comparison group. The time periods range from 2000-2003 to 2005-2012, depending on the data source.

Consistent with Healthy People 2020, disparities are measured in relative terms as the percentage difference between each group and a comparison group. A linear regression model is used to estimate the difference in the annual rate of change for the comparison group relative to the reference group. Determinations of whether subgroup differences have grown, narrowed, or remained the same were based on estimated differences in annual rate of change as specified below:

  • Subgroup differences are deemed to be narrowing if the change in disparities is less than −1 and p <0.10.
  • Subgroup differences are deemed to be growing if the change in disparities is greater than 1 and p <0.10.
  • Subgroup differences are deemed to have remained the same if the change in disparities is between −1 and 1, or p >0.10.

Only those measures with 4 or more years of data were included in the trending analysis. Due to methodological changes in trending analysis, it is not appropriate to compare the annual change or rates of change for measure groups discussed in this year's report with those from prior years. More information regarding the methodology can be found in Chapter 1, Introduction and Methods.

Blacks or African Americans

According to the U.S. Census Bureau, in 2011, the Black population of the United States was 43.9 million, an increase of 1.6% from 2010 (Census Bureau, 2013b). The Black population is projected to be 69.5 million by the year 2050, constituting 17.4% of the U.S. population (Census Bureau, 2012a).

Previous NHDRs showed that Blacks had poorer quality of care and worse access to care than Whites for many measures tracked in the reports. Among all measures of health care quality and access that are tracked in the reports and support trends over time, Blacks had worse care than Whites in the most recent year for 78 measures.

Most of these measures showed no significant change in disparities over time. These include preventive care measures for cancer, children's dental care, and flu vaccinations for adults over age 65; hospital admissions for diabetes complications; hospital admissions for asthma; hospital care for pneumonia; hospital care for heart attack; HIV infection deaths; infant mortality; patient safety events; patient-centered care; and access to care.

For 13 measures, the gap between Blacks and Whites grew smaller, indicating improvement:

  • Prostate cancer deaths per 100,000 male population per year.
  • Cancer deaths per 100,000 population per year.
  • Hospital admissions for congestive heart failure per 100,000 population.
  • Incidence of end stage renal disease (ESRD) due to diabetes per million population.
  • Hospital admissions for uncontrolled diabetes per 100,000 population age 18 and over.
  • New AIDS cases per 100,000 population age 13 and over.
  • HIV infection deaths per 100,000 population.
  • Hospital patients age 65 and over with pneumonia who received pneumococcal screening or vaccination.
  • Long-stay nursing home residents who were assessed for pneumococcal vaccination.
  • Short-stay nursing home residents who were assessed for pneumococcal vaccination.
  • Short-stay nursing home residents with pressure sores.
  • Adults age 65 and over with any private insurance.
  • Deaths per 1,000 elective surgery admissions having developed specified complications of care during hospitalization, ages 18-89 or obstetric admissions.

For 3 measures, the gap grew larger, indicating worsening disparities:

  • Breast cancer diagnosed at advanced stage (regional, distant stage, or local stage with tumor greater than 2 cm) per 100,000 women age 40 and over.
  • Maternal deaths per 100,000 live births.
  • Adults age 40 and over with diagnosed diabetes who received at least two hemoglobin A1c measurements in the calendar year.

Asians

In 2011, U.S. Census Bureau data showed that the Asian population (single or multiple  race) was 18.2 million (Census Bureau, 2013a), which represents a 2.3% increase from 2010. It is projected that the Asian population will reach 21 million by 2020 and 35.7 million by 2050 (Census Bureau, 2012a).

Previous NHDRs showed that Asians had similar or better quality of care than Whites but worse access to care than Whites for many measures that the report tracks. Among all measures of health care quality and access that are tracked in the reports and support trends over time, Asians or Asians and Pacific Islanders in aggregate had worse care than Whites in the most recent year for 38 measures.

Most of these measures showed no significant change in disparities over time. These include measures on preventive care for breast cancer, cervical cancer, and colorectal cancer; obstetric trauma; hospice care; timeliness of care; patient-centered care; and access to care.

For 2 measures, the gap between Asians and Whites grew smaller, indicating improvement:

  • Adults with limited English proficiency and a usual source of care that had language assistance.
  • Hospital patients age 65 and over with pneumonia who received pneumococcal screening or vaccination.

For 2 measures, the gap grew larger, indicating worsening disparities:

  • Adults ages 18-64 at high risk (e.g., chronic obstructive pulmonary disease) who ever received pneumococcal vaccination.
  • Children 0-40 lb for whom a health provider gave advice within the past 2 years about using child safety seats when riding in a car.

Native Hawaiians and Other Pacific Islanders

With a population of 1.2 million, NHOPIs (single or multiple race) are 0.4% of the U.S. population. From 2000 to 2010, the NHOPI population increased more than three times as fast as the total U.S. population (35% compared with 9.7% for the total U.S. population). More than half of the NHOPI population reported being of multiple race (56%). While three-fourths of the NHOPI population lived in the West, the South experienced the fastest growth in the NHOPI population (66%) (Hixson, et al., 2012).

The ability to assess disparities among NHOPIs for the NHDR has been a challenge for two main reasons. First, the NHOPI racial category is relatively new to Federal data collection. Before 1997, NHOPIs were classified as part of the Asian and Pacific Islander racial category and could not be identified separately in most Federal data.

In 1997, OMB promulgated new standards for Federal data on race and ethnicity and mandated that information about NHOPIs be collected separately from information about Asians (Executive Office of the President, 1997). However, these standards have not yet been incorporated into all databases. Second, when information about this population was collected, databases often included insufficient numbers of NHOPIs to allow reliable estimates to be made.

In 2011, HHS released new data standards that more consistently measure race, ethnicity, sex, primary language, and disability status. As part of the Affordable Care Act, Federal data collection efforts require that all health surveys sponsored by HHS include standardized information. This effort is expected to improve the specificity, uniformity, and quality of data available for disparity populations such as NHOPIs.

Due to these challenges, in previous NHDRs, estimates for the NHOPI population could be generated for only a handful of measures. A lack of quality data on this population prevents the NHDR from detailing disparities for this group. HHS is working to implement the new data standards for analyzing data for minority populations, including NHOPIs.

Currently in the NHDR, some data on NHOPIs are available for some measures throughout the report, such as measures related to cancer treatment, heart disease, home health care, access to care, workforce diversity, patient centeredness, and timeliness. Data sources such as the Medical Expenditure Panel Survey, National Health Interview Survey, and Behavioral Risk Factor Surveillance System may have larger samples of NHOPIs due to efforts to improve sample sizes. However, these data are not necessarily a comprehensive survey of health and health care. Other surveys and data collection efforts, such as vital statistics and hospital administrative data, include more topics but do not identify NHOPIs or have large enough sample sizes to provide data for these populations.

For all national data sources, the relatively small population sizes of many Pacific Islander groups can cause these populations to be overlooked when categorized as NHOPIs. In addition, identifying individuals with chronic conditions or other health conditions within such small populations further reduces the sample sizes. However, as data become available, this information will be included in future reports.

HHS and the Centers for Disease Control and Prevention have launched the Native Hawaiian/Pacific Islanders National Health Interview Survey, which uses the Census Bureau's American Community Survey to collect data from approximately 4,000 households, starting in February 2014. Findings will be available in the summer of 2015. These data will help to address the issue of small sample sizes that often impede research focused on NHOPIs.

This year, the NHDR features findings from a report by the Department of Native Hawaiian Health and its Center for Native and Pacific Health Disparities Research at the John A. Burns School of Medicine of the University of Hawaii. The report is called Assessment and Priorities for Health & Well-Being in Native Hawaiians and Other Pacific Peoples (Look, et al., 2013).

Demographic Profile of NHOPIs in Hawaii

NHOPI is a population classification frequently used in Federal reports. This group includes Native Hawaiians, Samoans, Tongans, Guamanians/Chamorros, Micronesians (people of the Federated States of Micronesia, Palau, Marshall Islands, and the Commonwealth of the Northern Marianas), and Fijians.

  • In the State of Hawaii, the population of Native Hawaiians increased by 21%, Samoans by 33%, Tongans by 35%, and Guamanians and Chamorros by 58% from 2000 to 2010 (Essoyan, 2012; Hawaii State Data Center, 2012).
  • Overall, growth in the NHOPI population represents a 40% increase, compared with 9.7% growth in the U.S. population.
  • More than half (56%) of people who identified themselves as NHOPI reported being of multiple races/ethnicities (Hixson, et al., 2012).

Morbidity and Mortality of NHOPIs in Hawaii

  • Life expectancy for Native Hawaiians, in comparison with other ethnicities, has remained consistently lower than the Hawaii State total, at 74.3 years of age. There has been steady improvement from 1950 to 2000 (Park, et al., 2009).
  • Native Hawaiians have higher death rates compared with all other ethnicities in Hawaii. Native Hawaiians have higher mortality across the lifespan with rates 40% higher when compared with Whites. Similar to Blacks across the Nation, Hawaiians are dying at younger ages, with dramatic differences starting in the midlife age range (Panapasa, et al., 2010; Kaʻopua, et al., 2011).
  • In 2002, the infant mortality rate among Native Hawaiians was second highest of any racial/ethnic group and 66% higher than Whites (Mathews, et al., 2004). There continues to be a large disparity between Native Hawaiians and Whites, with infants born to Native Hawaiian mothers more than twice as likely to die as those born to White mothers in Hawaii (Hirai, et al., 2013).
  • NHOPIs bear a disproportionately higher prevalence of many chronic medical conditions, such as obesity, diabetes, and cardiovascular disease, collectively known as cardiometabolic disorders (Mau, et. al, 2009).
  • Native Hawaiians not only have higher rates of death from diabetes and heart disease but also from cancer and other leading causes of death compared with the overall State population (Johnson, et al., 2004).

Other selected findings from this report on NHOPIs in the State of Hawaii are in Chapter 2, Cancer, Cardiovascular Disease, and Diabetes; Chapter 3, Lifestyle Modification; and Chapter 9, Health System Infrastructure.

American Indians and Alaska Natives

In 2012, the population of AI/ANs (single or multiple race) was about 5.2 million, which represents 1.6% of the population.vii From 2000 to 2010, the AI/AN population increased by 1.1 million, an increase of about 27% (U.S. Census Bureau, 2012b). The projected population of AI/ANs is estimated to be 4.5 million by 2020 and 5.6 million by 2050 (U.S. Census Bureau, 2012a).

There are 566 federally recognized tribes (U.S. Department of the Interior, 2013) and 324 federally recognized American Indian reservations. In 2010, 22% of AI/ANs (single or multiple race) lived in American Indian areas or Alaska Native Village Statistical Areas (Census Bureau, 2012b).

Previous NHDRs showed that AI/ANs had poorer quality of care and worse access to care than Whites for many measures tracked in the reports. Among all measures of health care quality and access that are tracked in the reports and support trends over time, AI/ANs had worse care than Whites in the most recent year for 40 measures.

Most of these measures showed no significant change in disparities over time. Such measures include measures for HIV/AIDS, preventive care for children, care for residents in nursing homes, home health care, hospice care, and access to care.

For one measure, the gap between AI/ANs and Whites grew smaller, indicating improvement:

  • Incidence of ESRD due to diabetes per million population.

For 2 measures, the gap grew larger, indicating worsening disparities:

  • Adults age 50 and over who ever received a colonoscopy, sigmoidoscopy, or proctoscopy.
  • People with difficulty contacting their usual source of care over the telephone.

Hispanics or Latinos

In 2012, the Hispanic population of the United States was 53 million. Hispanics are the largest ethnic or racial minority group, representing 17% of the total population. Between 2011 and 2012, the Hispanic population increased by 1.1 million, a 2.2% increase (Census Bureau, 2013c). The Hispanic population is projected to be 63.8 million in 2020 and 111.7 million in 2050 (Census Bureau, 2012a).

Previous NHDRs showed that Hispanics had poorer quality of care and worse access to care than non-Hispanic Whites for many measures that the reports track. Among all measures of health care quality and access that are tracked in the reports and support trends over time, Hispanics had worse care than non-Hispanic Whites in the most recent year for 72 measures.

Most of these measures showed no significant change in disparities over time. Such measures include measures on preventive care for cervical cancer and colorectal cancer; diabetes care; HIV/AIDS; hospital admissions for asthma; quality of care for residents of nursing homes; home health care; timeliness of care; patient-centered care; and access to care.

For 7 measures, the gap between Hispanics and non-Hispanic Whites grew smaller, indicating improvement:

  • Hospital admissions for uncontrolled diabetes per 100,000 population age 18 and over.
  • Children ages 2-17 who had a dental visit in the calendar year.
  • Hospital patients age 65 and over with pneumonia who received pneumococcal screening or vaccination.
  • Short-stay nursing home residents who were assessed for pneumococcal vaccination.
  • Hospital admissions for congestive heart failure per 100,000 population.
  • Hospital admissions for long-term complications of diabetes per 100,000 adults.
  • Adults age 65 and over with any private health insurance.

For 3 measures, the gap between Hispanics and non-Hispanic Whites grew larger, indicating worsening disparities:

  • Adult home health care patients whose ability to walk or move around improved.
  • Adult home health care patients whose shortness of breath decreased.
  • Adult home health care patients whose management of oral medications improved.

Low-Income Groups

In this report, poor populations are defined as people living in families whose household income falls below specific poverty thresholds. These thresholds vary by family size and composition and are updated annually by the U.S. Bureau of the Census (Census Bureau, 2011b). After falling for a decade (1990-2000), the number of poor people in America rose from 31.6 million in 2000 to 48.5 million in 2011. In 2011, 15.9% of the U.S. population had incomes below their respective poverty thresholds (Bishaw, 2012).

Poverty varies by race and ethnicity. In 2012, 13.0% of Whites, 28.1% of Blacks, 29.1% of AI/ANs, 13.0% of Asians, 21.3% of NHOPIs, and 25.4% of Hispanics had incomes below the poverty level.viii People from the lowest SES groups are 2.5 times more likely to have repeat emergency department visits and 2.7 times more likely to have repeat hospitalizations during a 1-year period compared with those from higher SES groups (Chen & Miller, 2013).

In general, poor populations have reduced access to high-quality care. Studies have shown that adults ages 51-61 years old who lack health insurance have higher risk-adjusted rates of decline in their overall health and physical functioning compared with individuals with private insurance. Reduced access to care can have serious consequences for health outcomes via lack of preventive services use, delayed diagnosis of disease, and poor monitoring and control of chronic disease (Sudano & Baker, 2006).

Previous chapters of this report describe health care differences by income. Among all measures of health care quality and access that are tracked in the reports and support trends over time, poorix individuals had worse care than high-incomex individuals in the most recent year for 77 measures. Most of these measures showed no significant change in disparities over time. These measures include measures for preventive care for children, diabetes care, asthma care, obesity prevention, patient safety, and access to care.

For 5 measures, the gap between poor and high-income individuals grew smaller, indicating improvement:

  • Hospital admissions for congestive heart failure per 100,000 population.
  • Children ages 2-17 who had a dental visit in the calendar year.
  • Hospital admissions for asthma per 100,000 population, ages 2-17.
  • People under age 65 whose family's health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income.
  • People under age 65 with private insurance whose family's health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income.

For 4 measures, the gap grew larger, indicating worsening disparities:

  • Adults age 50 and over who ever received a colonoscopy, sigmoidoscopy, or proctoscopy.
  • Hospital admissions for short-term complications of diabetes per 100,000 population, adults.
  • Adolescents ages 16-17 who received 1 or more doses of tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis (Tdap) since the age of 10 years.
  • People without a usual source of care who indicated a financial or insurance reason for not having a source of care.

Residents of Rural Areas

According to 2010 U.S. Census data (Census Bureau, 2010), 19.3 % of the U.S. population lives in a rural area. Compared with their urban counterparts, rural residents are more likely to be older, be poor (Ziller, et al., 2003), be in fair or poor health, and have chronic conditions (IOM, 2005). Rural residents are less likely than their urban counterparts to receive recommended preventive services and are more likely to report having deferred care due to cost (Bennett, et al., 2008).

Although about 19% of Americans live in rural areas, only 11% of physicians in America practice in those settings (Rosenblatt, et al., 2010). Other important providers of health care in those settings include nurse practitioners, nurse midwives, and physician assistants. A variety of programs deliver needed services in rural areas, such as the National Health Service Corps Scholarship Program, Indian Health Service, State offices of rural health, rural health clinics, and community health centers.

Many rural residents depend on small rural hospitals for their care. There are approximately 2,000 rural hospitals throughout the country (AHA, 2011). Most of these hospitals are critical access hospitals that have 25 or fewer beds. Rural hospitals face unique challenges due to their size and case mix. During the 1980s, many were forced to close due to financial losses (AHRQ, 1996). More recently, finances of small rural hospitals have improved and few closures have occurred since 2003.

Language barriers are often greater in rural areas. Through the "Advancing Effective Communication in Critical Access Hospitals Initiative," the HHS Office for Civil Rights (OCR) piloted a multistate compliance review and technical assistance project to support CAHs in providing language access services to limited-English-proficient (LEP) populations in rural and isolated areas. During 2012 and 2013, OCR conducted compliance reviews of 45 CAHs, one hospital in each of the 45 States served by the CAH program (a combined total of more than 1,125 beds). Each CAH established a comprehensive language access program:

  1. A needs assessment of its service area.
  2. Oral language services.
  3. Written translation services.
  4. Written policies and procedures, including grievance and nondiscrimination policies.
  5. Notification of the availability of language assistance at no cost.
  6. Staff training.
  7. An assessment of access and quality.
  8. Stakeholder consultations.
  9. Information management.
  10. Compliance with Title VI of the Civil Rights Act of 1964.

Under this ongoing Initiative, OCR will conduct language assistance compliance reviews in each of the 45 States served by the CAH program.

Similarly, transportation needs are pronounced among rural residents, who must travel longer distances to reach health care delivery sites. Of the nearly 1,000 "frontier counties"xi in the Nation, most have limited health care services and many do not have any (Frontier Education Center, 2000).

One challenge for interpreting research findings for "rural" residents is that the geographic location or "level of urbanization" is classified in different ways depending on the data source. Chapter 1, Introduction and Methods, provides more information on the classifications used. In this chapter, we compare residents of noncoreixii (the most rural) areas with residents of large fringe metropolitan (suburban) areas because residents of suburban areas tend to have higher quality health care and better outcomes than residents of the most rural areas.

Among all measures of health care quality and access that are tracked in the reports and support trends over time, residents of noncore areas had worse care than residents of large fringe metropolitan areas in the most recent year for 32 measures. Most of these measures showed no significant change in disparities over time. These include measures for cancer mortality, obesity prevention, patient-centered care, and access to care.

For 2 measures, the gap grew larger, indicating worsening disparities:

  • Cancer deaths per 100,000 population per year.
  • Deaths per 1,000 adult hospital admissions with pneumonia.

Individuals With Disabilities or Special Health Care Needs

The NHDR tracks many measures of relevance to individuals with disabilities or special health care needs and this year particular focus is placed on the health care Americans with disabilities receive. Data are often limited, and AHRQ has worked with Federal partners to improve reporting on health care quality for individuals with disabilities.

The disability measure for adults used in the 2013 NHDR/NHQR has been used in these reports since 2007 and is based on the work of a subgroup of the NHQR/NHDR Interagency Work Group. This subgroup received assistance from the Interagency Subcommittee on Disability Statistics of the Interagency Committee on Disability Research. The charge to the disabilities subgroup was to advise AHRQ on measures of disabilities from existing data that could track disparities for disabled individuals in quality of and access to care and that would be comparable across national surveys. For this effort, the subgroup focused on measures for adults, a population for which the most survey data are available.

For the 2013 NHDR, AHRQ is again using a broad, inclusive measure of disability for adults. This measure is intended to be consistent with statutory definitions of disability, such as the first criterion of the 1990 Americans With Disabilities Act (ADA) (i.e., having a physical or mental impairment that substantially limits one or more major life activities [Office of the Surgeon General, 2005; LaPlante, 1991]) and other Federal program definitions of disability.

For the purpose of the NHDR, adults with disabilities are those with physical, sensory, and/or mental health conditions that can be associated with a decrease in functioning in such day-to-day activities as bathing, walking, doing everyday chores, and engaging in work or social activities. In displays of data on disability, paired measures are shown to preserve the qualitative aspects of the data:

  • Limitations in basic activities represent problems with mobility and other basic functioning at the person level.
  • Limitations in complex activities represent limitations encountered when the person, in interaction with the environment, attempts to participate in community life.

Limitations inbasicactivities include problems with mobility, self-care (activities of daily living), domestic life (instrumental activities of daily living), and activities that depend on sensory functioning (limited to people who are blind or deaf). Limitations in complex activities include limitations experienced in work and in community, social, and civic life. The use of the subgroup's recommendation of these paired measures of basic and complex activity limitations is conceptually similar to the way others have divided disability (LaPlante, 1991; Altman and Bernstein, 2008) and is consistent with the International Classification of Functioning, Disability, and Health separation of activities and participation domains (WHO, 2001).

These two categories are not mutually exclusive; people may have limitations in basic activities and complex activities. The residual category Neither includes adults with neither basic nor complex activity limitations.

In this year's reports, analyses by activity limitation for adults are presented for selected measures in Chapter 2, Cancer, Cardiovascular Disease, Musculoskeletal Diseases, and Respiratory Diseases; Chapter 3, Lifestyle Modification; Chapter 6, Patient Centeredness; Chapter 7, Care Coordination; and Chapter 10, Access to Health Care in the NHQR. In addition, the online data tables include activity limitations as a stub variable for all National Health Interview Survey and Medical Expenditure Panel Survey tables.

Among all measures of health care quality and access that are tracked in the reports and support trends over time, individuals with basic activity limitations had worse care than individuals with neither basic nor complex activity limitations in the most recent year for 21 measures. Most of these measures showed no significant change in disparities over time. Such measures included measures for patient-centered care and access to care.

For 2 measure, the gap between individuals with basic activity limitations and individuals with neither basic nor complex activity limitations narrowed, indicating improvement:

  • People under age 65 with any private health insurance.
  • People under age 65 whose family's health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income.

For 1 measure, the gap grew larger, indicating worsening disparities:

  • People under age 65 with health insurance.

Individuals with complex activity limitations had worse care than individuals with neither basic nor complex activity limitations in the most recent year for 21 measures. Most of these measures showed no significant change in disparities over time. Such measures included measures for patient-centered care and access to care.

For 1 measure, the gap between individuals with complex activity limitations and individuals with neither basic nor complex activity limitations narrowed, indicating improvement:

  • People under age 65 whose family's health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income.

In June 2009, HHS created the Community Living Initiative (CLI) to promote Federal partnerships that advance the directive of the Olmstead decision, which develops and implements innovative strategies that increase opportunities for Americans with disabilities and older American to enjoy meaningful community living. Figure 11.1 highlights some characteristics of Americans living with disabilities.

Figure 11.1. People living with disability, by age, sex, 2012, and economic status, 2010 and 2012

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[D] Select for Text Description.

Source: U.S. Census Bureau, American Community Survey 1-year estimates, 2012.
Note: Earnings data are taken from Disability employment 7A. Detailed census occupation by disability status, employment status (employed, total), earnings (8), sex, and race/ethnicity, Total population, number. Universe: civilian population 16 years and over. DOL Disability Employment Tabulation 2008-2010 (3-year ACS data). Available at: http://factfinder2.census.gov/bkmk/table/1.0/en/EEO/10_3YR/DOLALL7AN. Public assistance data are for ages 15-64 in 2010. Detailed data are available in Brault MW. Americans with disabilities: 2010, Current Population Reports, P70-131, Washington, DC: U.S. Census Bureau; 2012. Poverty level data are for people age 16 and over.

  • In 2012, there were 37.6 million civilian noninstitutonalized people (12.2%) living with a disability. About 1% of children under age 5, 5% of children ages 5-17, 10% of adults ages 18-64, and 36% of adults age 65 and over were living with a disability (Figure 11.1).
  • In 2012, about 12% of males and females were living with a disability.
  • In 2012, one-third of adults ages 18-64 living with a disability were employed. Data for 2010 show that about 300,000 of employed individuals with a disability made $100,000 or more.
  • In 2012, the median earnings in the past 12 months for adults with a disability was $20,184 compared with $30,660 for those without a disability (data not shown).
  • In 2010, nearly 60% of people with a severe disability received some type of public assistance, and 22.9% of people with a nonsevere disability received assistance.
  • Twenty-two percent of people with a disability lived below the poverty level and 14.4% were at 100% to 149% of the poverty level compared with 12.7% and 8.3%, respectively, of people without a disability.

Individuals With Multiple Chronic Conditions

Chronic illnesses are conditions that last more than a year and require ongoing medical attention and/or limit activities of daily living (HHS, 2010). Nearly half the adult population is affected by chronic conditions and more than one in four have multiple, concurrent chronic conditions (HHS, 2010; Ward & Schiller, 2013). CMS analyzed 15 common chronic conditions, including high blood pressure, heart failure, diabetes, and chronic kidney disease, for 31 million Medicare beneficiaries who were enrolled continuously in the Medicare fee-for-service (FFS) program in 2010.

Figure 11.2. Medicare FFS beneficiaries by number of chronic conditions, age and sex, and race/ethnicity, 2010

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Key: API = Pacific Islander
Source: Centers for Medicare & Medicaid Services, Chronic conditions and Medicare beneficiaries: chartbook, 2012 edition.
Note: White, Black, and API are non-Hispanic. Hispanic includes all races.

  • In 2010, 32% of Medicare FFS beneficiaries had zero or one chronic condition, 32% had two or three chronic conditions, about one-quarter had four or five chronic conditions, and 14% had six or more (Figure 11.2).
  • In 2010, 9% of adults under age 65 and 9% of adults ages 65-74 had six or more chronic conditions compared with 18% of adults ages 75-84 and 25% of adults age 85 and over.
  • In 2010, 11% of API, 14% of White, and 16% of both Black and Hispanic Medicare beneficiaries had six or more chronic conditions.

MCC increase the risks for poor outcomes such as mortality and functional limitations. They also increase the risk for high-cost services such as hospitalizations and emergency department (ED) visits. Medicare beneficiaries with MCC are the heaviest users of health care services. Hospitalizations are an important driver of health care cost, so it is critical to know the impact chronic conditions have on inpatient admissions. In 2010, about one in five Medicare beneficiaries was admitted to a hospital, costing more than $100 billion (CMS, 2012).

Figure 11.3. Medicare FFS beneficiaries by number of ED visits and number of chronic conditions, 2010

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Source: Centers for Medicare & Medicaid Services, Chronic conditions and Medicare beneficiaries: chartbook, 2012 edition.

  • In 2010, 75% of Medicare FFS beneficiaries with two or three chronic conditions had no ED visits compared with 59% of beneficiaries with four or five and 30% of beneficiaries with six or more (Figure 11.3).
  • In 2010, 17% of Medicare beneficiaries with two or three chronic conditions had one ED visit compared with 24% of beneficiaries with four or five and 26% of beneficiaries with six or more.
  • In 2010, 5% of Medicare beneficiaries with two or three chronic conditions had two ED visits compared with 9% of beneficiaries with four or five and 17% of beneficiaries with six or more.
  • In 2010, only 4% of Medicare beneficiaries with two or three chronic conditions had three or more ED visits compared with 8% of beneficiaries with four or five and 27% of beneficiaries with six or more.

MCC are associated with higher rates of death, disability, adverse effects, institutionalization, use of health care resources, and poorer quality of life (AGS Expert Panel, 2012). Older adults with MCC require considerable health services and complex care. The intensity and complexity of treating people with MCC account for a large proportion of health care costs, including more than 80% of Medicare expenditures. Individuals with MCC typically receive multiple interventions, each of which may affect other coexisting conditions positively or negatively and may interact with other interventions.

Figure 11.4. Hospital admissions with a readmission within 30 days for Medicare FFS beneficiaries, by number of chronic conditions, age, and sex, 2010

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Source: Centers for Medicare & Medicaid Services, Chronic conditions and Medicare beneficiaries: chartbook, 2012 edition.

  • In 2010, 11% of Medicare FFS beneficiaries under age 65 with zero or one chronic condition had a readmission within 30 days compared with 16% of beneficiaries with two or three, 20% of beneficiaries with four or five, and 32% with six or more (Figure 11.4).
  • Seven percent of Medicare beneficiaries age 65 and over with zero or one chronic condition had a readmission within 30 days compared with 8% of beneficiaries with two or three, 13% of beneficiaries with four or five, and 24% of beneficiaries with six or more.
  • In 2010, 10% of male beneficiaries with zero or one chronic condition had a readmission within 30 days compared with 11% of beneficiaries with two or three, 15% of beneficiaries with four or five, and 27% of beneficiaries with six or more.
  • Eight percent of female beneficiaries with zero or one chronic condition had a readmission within 30 days compared with 9% of beneficiaries with two or three, 13% of beneficiaries with four or five, and 24% of beneficiaries with six or more.

Figure 11.5. Heart failure admissions for Medicare FFS beneficiaries, by number of chronic conditions, age and sex, and race/ethnicity, 2011

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Key: API = Asian or Pacific Islander; AI/AN = American Indian or Alaska Native.
Source: Centers for Medicare & Medicaid Services, Medicare beneficiary enrollment and claims for both institutional and noninstitutional settings available from the CMS Chronic Conditions Data Warehouse (CCW), www.ccwdata.org.
Note: White, Black, API, and AI/AN are non-Hispanic. Hispanic includes all races. Data for AI/ANs with zero or one chronic condition did not meet criteria for statistical reliability.

  • In 2011, the overall rate of hospital admission for heart failure was 1,399 per 100,000 Medicare FFS beneficiaries (data not shown). The rate of admission for beneficiaries with six or more chronic conditions was more than 900 times the rate for beneficiaries with zero or one chronic condition (8,203 per 100,000 beneficiaries compared with 9 per 100,000 beneficiaries; Figure 11.5).
  • In 2011, the rate of hospital admission for heart failure for Medicare beneficiaries under age 65 with six or more chronic conditions was more than 1,000 times the rate for Medicare beneficiaries under age 65 with zero or one chronic condition (8,260 per 100,000 beneficiaries compared with 8 per 100,000 beneficiaries).
  • In 2011, the rate of hospital admission for heart failure for male Medicare beneficiaries with six or more chronic conditions was 1,000 times the rate for Medicare beneficiaries with zero or one chronic condition (9,069 per 100,000 beneficiaries compared with 9 per 100,000 beneficiaries).
  • In 2011, the rate of hospital admission for heart failure for female Medicare beneficiaries with six or more chronic conditions was more than 800 times the rate for female Medicare FFS beneficiaries with zero or one chronic condition (7,584 per 100,000 beneficiaries compared with 9 per 100,000 beneficiaries).
  • In 2011, the rate of hospital admission for heart failure for White Medicare beneficiaries with six or more chronic conditions was more than 800 times the rate for White Medicare beneficiaries with zero or one chronic condition (7,885 per 100,000 beneficiaries compared with 9 per 100,000 beneficiaries).
  • In 2011, the rate of hospital admission for heart failure for Hispanic Medicare beneficiaries with six or more chronic conditions was more than 1,000 times the rate for Hispanic Medicare beneficiaries with zero or one chronic condition (7,384 per 100,000 beneficiaries compared with 7 per 100,000 beneficiaries). Similarly, the rate of hospital admission for heart failure for Black Medicare beneficiaries with six or more chronic conditions was 11,239 per 100,000 beneficiaries compared with 14 per 100,000 for Black Medicare beneficiaries with zero or one chronic condition.

Figure 11.6. Admissions for long-term complications of diabetes for Medicare FFS beneficiaries, by number of chronic conditions, age and sex, and race/ethnicity, 2011

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Key: API = Asian or Pacific Islander; AI/AN = American Indian or Alaska Native.
Source: Centers for Medicare & Medicaid Services, Medicare beneficiary enrollment and claims for both institutional and noninstitutional settings available from the CMS Chronic Conditions Data Warehouse (CCW), www.ccwdata.org.
Note: White, Black, API, and AI/AN are non-Hispanic. Hispanic includes all races. Data for APIs with zero or one chronic condition did not meet criteria for statistical reliability.

  • In 2011, the rate of admission for long-term complications of diabetes for Medicare FFS beneficiaries under age 65 with six or more chronic conditions was nearly 400 times the rate for Medicare beneficiaries under age 65 with zero or one chronic condition (5,141 per 100,000 beneficiaries compared with 13 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for male Medicare beneficiaries with six or more chronic conditions was about 300 times the rate for male Medicare beneficiaries with zero or one chronic condition (2,140 per 100,000 beneficiaries compared with 7 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for female Medicare beneficiaries with six or more chronic conditions was nearly 500 times the rate for female Medicare beneficiaries with zero or one chronic condition (1,486 per 100,000 beneficiaries compared with 3 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for White Medicare beneficiaries with six or more chronic conditions was more than 300 times the rate for White Medicare beneficiaries with zero or one chronic condition (1,350 per 100,000 beneficiaries compared with 4 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for Black Medicare beneficiaries with six or more chronic conditions was more than 300 times the rate for Black Medicare beneficiaries with zero or one chronic condition (3,787 per 100,000 beneficiaries compared with 11 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for AI/AN Medicare beneficiaries with six or more chronic conditions was more than 170 times the rate for AI/AN Medicare beneficiaries with zero or one chronic condition (3,787 per 100,000 beneficiaries compared with 22 per 100,000 beneficiaries).
  • In 2011, the rate of admission for long-term complications of diabetes for Hispanic Medicare beneficiaries with six or more chronic conditions was more than 300 times the rate for Hispanic Medicare beneficiaries with zero or one chronic condition (3,076 per 100,000 beneficiaries compared with 10 per 100,000 beneficiaries).

Lesbian, Gay, Bisexual, and Transgender Populations

LGBT individuals encompass all races and ethnicities, religions, and social classes. Sexual orientation and gender identity questions are not asked on most national or State surveys, making it difficult to estimate the number of LGBT individuals and their health needs. Evidence is emerging that suggests that LGBT people face a variety of personal and structural barriers to obtaining high-quality medical care.

Personal barriers may include disrespectful behavior from staff and providers, perceived threatening environment, and stigma associated with being a sexual minority (IOM, 2011). Discrimination against LGBT individuals has been associated with high rates of psychiatric disorders (McLaughlin, et al., 2010), substance abuse (Ibanez, et al., 2005; Herek & Garnets, 2007), and suicidal behavior (Remafedi, et al., 1998; Haas, et al., 2011).

Structural barriers include difficulty obtaining health insurance, since many employer-sponsored insurance plans do not recognize same-sex unions, and a lack of culturally competent providers (Ash & Badgett, 2006; Heck, et al., 2006). Improving the health, safety, and well-being of LGBT individuals is one of the goals of Healthy People 2020.

National data on mental health and access to care for some underserved populations are not available from the national data sources in the NHDR. These populations include people with limited English proficiency; individuals who speak a language other than English at home; LGBT individuals; and Asian and Hispanic subpopulations. To address some of these data gaps, additional data from the CHIS are shown below. The sampling methods used in CHIS are an example of how important disparities can be examined when data are collected this way.

Figure 11.7. Individuals ages 12 and older seen by their primary care provider or a psychiatrist in the last 12 months for problems with mental health or use of alcohol or drugs, by sexual orientation, insurance status, family income, and English proficiency, California, 2009

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Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2009.
Note: Data for Gay/Lesbian/Bisexual who received treatment is not available for individuals who did not speak English well or at all.

  • Overall, in 2009, among California residents, homosexual or bisexual individuals were significantly more likely than heterosexual individuals to report a perceived need for a health professional for problems with mental health or use of alcohol or drugs (Figure 11.7).
  • Homosexual or bisexual individuals in all income groups were significantly more likely than heterosexual individuals in the same income groups to need a health professional for problems with mental health or use of alcohol or drugs.
  • Overall, in 2009, homosexual or bisexual individuals were significantly more likely than heterosexual individuals to see a health professional for problems with mental health or use of alcohol or drugs.
  • Homosexual or bisexual individuals with all types of insurance were significantly more likely than heterosexual individuals with the same types of insurance to see a health professional for problems with mental health or use of alcohol or drugs.

While members of the LGBT community share similar health care needs as the rest of the population, they often face additional health care barriers, including stigma and a lack of awareness and insensitivity to their unique needs (Pelletier & Tschurtz, 2012). One study found that both men and women in same-sex relationships had significantly lower rates of health insurance coverage and higher rates of unmet medical needs than did individuals in different-sex relationships (Buchmueller & Carpenter, 2010).

Figure 11.8. Delayed in getting medical care due to cost or lack of health insurance, by sexual orientation, insurance status, and residence location, 2009

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Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2009.
Note: Data for uninsured gay/lesbian/bisexual are statistically unreliable.

  • In 2009, among California residents, there were no statistically significant differences between homosexual or bisexual individuals and heterosexual individuals overall, by insurance status, or by residence location in the percentage who reported delaying medical care due to cost or lack of health insurance (Figure 11.8).

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i For statutory requirements, refer to 42 U.S.C. 299a-1(a)(6).
ii Populations of inner-city areas are also identified as one of AHRQ's priority populations pursuant to 42 U.S.C. 299(c)(1)(A). However, no data are available to support findings for this population.
iii Racial groups are White, Black, Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, and more than one race. Ethnic groups are Hispanic or Latino, non-Hispanic White, and non-Hispanic Black.
iv Thresholds for income categories—poor, low income, middle income, and high income—vary by family size and composition and are updated annually by the U.S. Bureau of the Census. For example, in 2012, the Federal poverty threshold for a family of two adults and two children was $23,050.
v Rural areas can be defined in different ways depending on the data source. The NHDR uses the 2006 National Center for Health Statistics (NCHS) Urban–Rural Classification Scheme for Counties, which is built on the Office of Management and Budget definitions of metropolitan and micropolitan Core Based Statistical Areas (2000). The NCHS scheme describes the six "levels of urbanization" on a continuum from the large central metropolitan area (most urban/inner city) to the noncore or "most rural" area.
vi Individuals with special health care needs include children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who also require health and related services of a type or amount beyond that required by children generally.
vii Data taken from the 2012 American Community Survey, available at http://factfinder2.census.gov/bkmk/table/1.0/en/ACS/12_1YR/S0201//popgroup~009.
viii Data taken from the 2012 American Community Survey, available at http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_12_1YR_S1701&prodType=table.
ix Household income less than Federal poverty thresholds.
x Household income 400% of Federal poverty thresholds and higher.
xi "Frontier counties" have a population density of less than 7 people per square mile; thus, residents may have to travel long distances for care.
xii Noncore areas are outside of metropolitan or micropolitan statistical areas and are considered "the most rural" on a "level of urbanization" continuum.


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Page last reviewed May 2014
Page originally created May 2014
Internet Citation: Chapter 11. Priority Populations. Content last reviewed May 2014. Agency for Healthcare Research and Quality, Rockville, MD. https://archive.ahrq.gov/research/findings/nhqrdr/nhdr13/chap11.html

 

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