Chapter 9. Access to Health Care

National Healthcare Disparities Report, 2011

Many Americans have good access to health care that enables them to benefit fully from the Nation's health care system. Others face barriers that make it difficult to obtain basic health care services. As shown by extensive research and confirmed in previous National Healthcare Disparities Reports (NHDRs), racial and ethnic minorities and people of low socioeconomic status (SES)i are disproportionately represented among those with access problems.

Previous findings from the National Healthcare Quality Report (NHQR) and NHDR showed that health insurance was the most significant contributing factor to poor quality of care for some of the core measures, and many are not improving. Uninsured people were less likely to get recommended care for disease prevention, such as cancer screening, dental care, counseling about diet and exercise, and flu vaccination. They also were less likely to get recommended care for disease management, such as diabetes care management.

Poor access to health care comes at both a personal and societal cost. For example, if people do not receive vaccinations, they may become ill and spread disease to others. This increases the burden of disease for society overall in addition to the burden borne individually.

Components of Health Care Access

Access to health care means having "the timely use of personal health services to achieve the best health outcomes" (IOM, 1993) Attaining good access to care requires three discrete steps:

  • Gaining entry into the health care system.
  • Getting access to sites of care where patients can receive needed services.
  • Finding providers who meet the needs of individual patients and with whom patients can develop a relationship based on mutual communication and trust.

Health care access is measured in several ways, including:

  • Structural measures of the presence or absence of specific resources that facilitate health care, such as having health insurance or a usual source of care.
  • Assessments by patients of how easily they can gain access to health care.
  • Utilization measures of the ultimate outcome of good access to care (i.e., the successful receipt of needed services).

Facilitators and Barriers to Health Care

Facilitators and barriers to health care discussed in this section include health insurance, usual source of care (including having a usual source of ongoing care and a usual primary care provider), and patient perceptions of need.

Findings

Health Insurance

Health insurance facilitates entry into the health care system. Uninsured people are less likely to receive medical care and more likely to have poor health status. The cost of poor health among uninsured people was almost $125 billion in 2004 (Hadley & Holahan, 2004).

The financial burden of uninsurance is also high for uninsured individuals; almost 50% of personal bankruptcy filings are due to medical expenses (Jacoby, et al., 2000). Uninsured individuals report more problems getting care, are diagnosed at later disease stages, and get less therapeutic care. They are sicker when hospitalized and more likely to die during their stay (Hadley & Holahan, 2004).

 

Figure 9.1. People under age 65 with health insurance, by race and income, 1999-2009

Figure 9.1. People under age 65 with health insurance, by race and income, 1999-2009 . For details, go to [D] Text Description below.     Figure 9.1. People under age 65 with health insurance, by race and income, 1999-2009. For details, go to [D] Text Description below.

[D] Select for Text Description.

Key: AI/AN = American Indian or Alaska Native; NHOPI = Native Hawaiian or Other Pacific Islander.
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey (NHIS), 1999-2009.
Denominator: Civilian noninstitutionalized population under age 65.
Note: NHIS respondents are asked about health insurance coverage at the time of interview. Respondents are considered insured if they have private health insurance, Medicare, Medicaid, State Children's Health Insurance Program, a State-sponsored health plan, other government-sponsored health plan, or a military health plan. If their only coverage is through the Indian Health Service, they are not considered insured. Estimates are not adjusted.

  • Overall, there was no statistically significant change from 1999 to 2009 in the percentage of people with health insurance. In 2009, about 83% of people under age 65 had health insurance (data not shown).
  • In 2009, Blacks under age 65 were less likely than Whites to have health insurance (81% compared with 83%), and American Indians and Alaska Natives (AI/ANs) under age 65 were less likely than Whites to have health insurance (68% compared with 83%). There were no statistically significant differences for other racial groups.
  • In 2009, Hispanics under age 65 were less likely than non-Hispanic Whites to have health insurance (data not shown; 67% compared with 87%).
  • From 1999 to 2009, while the percentage of people with health insurance increased for poor people (from 66% to 70%), the percentage decreased for middle-income people (from 86% to 82%). In 2009, the percentage of people with health insurance was significantly lower for poor, low-income, and middle-income people than for high-income people (70%, 70%, and 82%, respectively, compared with 94%).
  • In 2009, the percentage of people ages 25-64 with health insurance was about one-third lower for people with less than a high school education than for people with at least some college education in the same group (data not shown, 56% compared with 88%).

Also, in the NHQR:

  • From 1999 to 2009, the percentage of children ages 0-17 who had health insurance improved. However, for adults ages 18-44 and 45-64, the percentage decreased.
  • In 2009, adults ages 18-44 and 45-64 were less likely than children ages 0-17 to have health insurance.
  • Females were more likely to have health insurance than males throughout this period.

Asian Subgroups

To show differences within racial groups, this year's NHDR includes information from the California Health Interview Survey (CHIS) on Asians in California. The geographic distribution of Asian subpopulations allows such comparisons in California using CHIS data.

In 2010, an estimated 5.6 million Asian people, or about 32% of the Asian population in the United States, lived in California (U.S. Census Bureau, 2011). The proportion of many Asian subpopulations in California is also greater than the proportion in the overall U.S. population. For example, in 2010, the Vietnamese population was 1.6% of California's population compared with only 0.4% of the U.S. population, and the Filipino population was 3.2% of California's population compared with only 0.7% of the U.S. population (U.S. Census Bureau, 2010). This finding is especially important when examining data for these relatively smaller groups, as most national data sources do not have sufficient data to report estimates for these groups.

Uninsurance

Prolonged periods of uninsurance can have a particularly serious impact on a person's health and stability. Uninsured people often postpone seeking care, have difficulty obtaining care when they ultimately seek it, and may have to bear the full brunt of health care costs. Over time, the cumulative consequences of being uninsured compound, resulting in a population at particular risk for suboptimal health care and health status.

 

Figure 9.2. People under age 65 who were uninsured all year, by ethnicity and income, 2002-2008

Figure 9.2. People under age 65 who were uninsured all year, by ethnicity and income, 2002-2008. For details, go to [D] Text Description below.  Figure 9.2. People under age 65 who were uninsured all year, by ethnicity and income, 2002-2008. For details, go to [D] Text Description below.     
[D] Select for Text Description.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2008.
Denominator: Civilian noninstitutionalized population under age 65.
Note: For this measure, lower rates are better.

  • Overall, from 2002 to 2008, the percentage of people under age 65 who were uninsured all year increased (from 13% to 15%; data not shown).
  • In 2008, there was no statistically significant difference between Blacks and Whites or between Asians and Whites. AI/ANs were more likely than Whites to be uninsured all year (28% compared with 15%; data not shown).
  • In 2008, Hispanics were much more likely than non-Hispanic Whites to be uninsured all year (29% compared with 12%; Figure 9.2).
  • The percentage of poor people and low-income people who were uninsured all year was about four times as high as that for high-income people (27% and 25%, respectively, compared with 7%). The percentage of middle-income people uninsured all year was more than twice as high as that for high-income people (15% compared with 7%).
  • People with less than a high school education and people with a high school education were more likely to be uninsured all year than people with at least some college education (36% and 22%, respectively, compared with 11%; data not shown).
  • From 2002 to 2008, the percentage of people who were uninsured all year was nearly three times as high for people who spoke another language at home as that for people who spoke English at home (in 2008, 34% compared with 12%; data not shown).

Also, in the NHQR:

  • From 2002 to 2008, children ages 0-17 were least likely to be uninsured all year, while adults ages 18-44 were most likely to be uninsured all year.
  • Females were less likely to be uninsured all year than males.

Figure 9.3. Predicted percentages of adults ages 18-64 who were uninsured all year, by race, age, gender, family income, and education, 2002-2008

Figure 9.3. Predicted percentages of adults ages 18-64 who were uninsured all year, by race, age, gender, family income, and education, 2002-2008. For details, go to [D] Text Description below.
[D] Select for Text Description.

Key: NHOPI = Native Hawaiian or Other Pacific Islander; AI/AN = American Indian or Alaska Native.
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, pooled 2002-2008 Full Year files.
Note: For this measure, lower rates are better. Predicted percentages are predicted marginals from a logistic regression model that includes the covariates race, age, gender, family income, education, health insurance, and residence location. Predicted percentages for Asians, multiple races, and metropolitan areas did not meet criteria for data reliability and are not reported.

  • In the multivariate model used, after adjustment, about 16% of Blacks and 8% of NHOPIs would have been uninsured all year compared with 17% of Whites (Figure 9.3). AI/ANs would have been more likely than Whites to be uninsured all year (about 21% compared with 17%).
  • After adjustment, people ages 18-44 would have been more likely than people ages 45-64 to be uninsured all year (18% compared with 15%).
  • After adjustment, about 32% of poor, 30% of low-income, and 17% of middle-income individuals would have been uninsured all year compared with 7% of those with high income.
  • After adjustment, 24% of people with less than a high school education and 18% of high school graduates would have been uninsured all year compared with 13% of those with any college education.

Figure 9.4. People under age 65 who were uninsured all year, Hispanic only, California, 2009

Figure 9.4. People under age 65 who were uninsured all year, Hispanic only, California, 2009. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2009.
Denominator: Hispanic civilian noninstitutionalized population ages 0-64 in California.
Note: For this measure, lower rates are better. Data for Puerto Ricans and South Americans did not meet criteria for statistical reliability. The English proficiency of respondents is characterized by the following categories: English Only, English Well/Very Well, and English Not Well/Not at All. The preferred language of respondents is characterized as either English Preferred or Spanish Preferred for Hispanic respondents shown here.

  • In 2009, Mexicans (18%) and Central Americans (27%) were more likely than non-Hispanic Whites (8%) to be uninsured all year in the past year in California (Figure 9.4).
  • Among Hispanics in California, poor people (23%) and low-income people (22%) were more likely than high-income people (10%) to be uninsured all year in the past year.
  • Among Hispanics in California, those who spoke English well or very well were more than twice as likely as those who were English-only speakers to be uninsured all year in the past year (24% compared with 11%). Hispanics who did not speak English well or did not speak English at all were more than three times as likely as those who were English-only speakers to be uninsured all year in the past year (38% compared with 11%).
  • Among Hispanics in California, those who preferred Spanish were more than twice as likely as those who preferred English to be uninsured all year in the past year (36% compared with 17%).
  • Among Hispanics in California, those who were not born in the United States were three times as likely as those born in the United States to be uninsured all year in the past year (30% compared with 10%).

New! Figure 9.5. People under age 65 who were uninsured all year, Asian only, California, 2009

Figure 9.5. People under age 65 who were uninsured all year, Asian only, California, 2009. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2009.
Denominator: Asian civilian noninstitutionalized population ages 0-64 in California.
Note: For this measure, lower rates are better. Data for Filipinos, Japanese people, and South Asians did not meet criteria for statistical reliability. The English proficiency of respondents is characterized by the following categories: English Only, English Well/Very Well, and English Not Well/Not at All. The preferred language of respondents is characterized as English Preferred, Vietnamese Preferred, or Korean Preferred for Asian respondents shown here.

  • In California, in 2009, there was no statistically significant difference between Asians and Whites in the percentage of people who were uninsured all year in the past year (9% compared with 7.5%; Figure 9.5).
  • Among Asians in California, Koreans were more than three times as likely as Whites to be uninsured all year in the past year (24% compared with 7.5%).
  • Among Asians in California, poor people (22%) and low-income people (22%) were nearly eight times as likely and middle-income people (9%) were three times as likely as high-income people (3%) to be uninsured all year in the past year.
  • Among Asians in California, people who did not speak English well or did not speak English at all were almost four times as likely as English-only speakers to be uninsured all year in the past year (24% compared with 6.5%).
  • Among Asians in California, people who preferred to speak Korean were about seven times as likely as those who preferred to speak English to be uninsured all year in the past year (50% compared with 7%). Those who preferred to speak Vietnamese were more than twice as likely as those who preferred to speak English (17.5% compared with 7%) to be uninsured all year in the past year.
  • Among Asians in California, those who were not born in the United States were three times as likely as those who were born in the United States to be uninsured all year in the past year (12% compared with 4%).

Financial Burden of Health Care Costs

Health insurance is supposed to protect individuals from the burden of high health care costs. However, even with health insurance, the financial burden for health care can still be high and is increasing (Banthin & Bernard, 2006). High premiums and out-of-pocket payments can be a significant barrier to accessing needed medical treatment and preventive care (Alexander, et al., 2003). According to one study, uninsured families can afford to pay for only 12% of hospitalizations that they experience (HHS, 2011). One way to assess the extent of financial burden is to determine the percentage of family income spent on a family's health insurance premium and out-of-pocket medical expenses.

 

Figure 9.6. People under age 65 whose family's health insurance premium and out-of-pocket medical expenses were more than 10% of total family income, by race, ethnicity, and family income, 2008

Figure 9.6. People under age 65 whose family's health insurance premium and out-of-pocket medical expenses were more than 10% of total family income, by race, ethnicity, and family income, 2008. For details, go to [D] Text Description below.

[D] Select for Text Description.

Key: AI/AN = American Indian or Alaska Native.
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2008.
Denominator: Civilian noninstitutionalized population under 65.
Note: Total financial burden includes premiums and out-of-pocket costs for health care services. Data do not meet the criteria for statistical reliability, data quality, or confidentiality for Native Hawaiians and Other Pacific Islanders.

  • Overall, in 2008, 17% of people under age 65 had health insurance premium and out-of-pocket medical expenses that were more than 10% of total family income (Figure 9.6).
  • In 2008, the percentage of people under age 65 whose family's health insurance premium and out-of-pocket medical expenses were more than 10% of total family income was lower for Blacks than for Whites (15% compared with 18%). The percentage was also lower for Hispanics than for non-Hispanic Whites (14% compared with 19%).
  • The percentage of people under age 65 whose family's health insurance premium and out-of-pocket medical expenses were more than 10% of total family income was more than four times as high for poor individuals (29%), more than three times as high for low-income individuals (25%), and more than twice as high for middle-income individuals (20%) compared with high-income individuals (7%).

Also, in the NHQR:

  • The percentage of people under age 65 whose family's health insurance premium and out-of-pocket medical expenses were more than 10% of total family income was nearly three times as high for individuals with private nongroup insurance as for individuals with private employer-sponsored insurance.
  • Adults ages 45-64 were more likely to have family's health insurance premium and out-of-pocket medical expenses that were more than 10% of total family income.

Usual Source of Care

People with a usual source of care (a provider or facility where one regularly receives care) experience improved health outcomes and reduced disparities (smaller differences between groups) (Starfield & Shi, 2004) and costs (De Maeseneer, et al., 2003). Evidence suggests that the effect on quality of the combination of health insurance and a usual source of care is additive (Phillips, et al., 2004). In addition, people with a usual source of care are more likely to receive preventive health services (Ettner, 1996).

Specific Source of Ongoing Care

The term "specific source of ongoing care" accounts for patients who may have more than one source of care, such as women of childbearing age and older people, who tend to have more than one doctor. A specific source of ongoing care can include an urgent care/walk-in clinic, doctor's office, clinic, health center facility, hospital outpatient clinic, health maintenance organization/preferred provider organization, military or other Veterans Affairs health care facility, or some other similar source of care (however, hospital emergency rooms are excluded).

 

Figure 9.7. People with a specific source of ongoing care, by ethnicity and income, 1999-2009

Figure 9.7. People with a specific source of ongoing care, by ethnicity and income, 1999-2009. For details, go to [D] Text Description below.     Figure 9.7. People with a specific source of ongoing care, by ethnicity and income, 1999-2009. For details, go to [D] Text Description below.

[D] Select for Text Description.

Key: AI/AN = American Indian or Alaska Native.
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 1999-2009.
Denominator: Civilian noninstitutionalized population of all ages.
Note: Measure is age adjusted. A hospital emergency room is not included as a specific source of primary care.

  • Overall, 86% percent of people had a specific source of ongoing care in 2009 (data not shown).
  • In 2009, the percentage of people with a specific source of ongoing care was lower for Blacks and AI/ANs than for Whites (85% compared with 86%; and 79% compared with 86%; data not shown).
  • In 2009, the percentage of people with a specific source of ongoing care was significantly lower for Hispanics than for non-Hispanic Whites (77% compared with 88%; Figure 9.7).
  • In 2009, the percentage of people with a specific source of ongoing care was significantly lower for poor and low-income people than for high-income people (78% and 80%, respectively, compared with 92%).
  • In 2009, the percentage of people with a specific source of ongoing care was lower for people with less than a high school education and people with a high school education than for people with at least some college education (75% and 83% respectively, compared with 88%; data not shown).

Also, in the NHQR:

  • In 2009, people age 65 and over were most likely to have a specific source of ongoing care, while people ages 18-44 were least likely to have a specific source of ongoing care.
  • Females were more likely to have a specific source of ongoing care than males from 1999 to 2009.
Usual Primary Care Provider

Having a usual primary care provider (a doctor or nurse from whom one regularly receives care) is associated with patients' greater trust in their provider and with good provider-patient communication. These factors increase the likelihood that patients will receive appropriate care. By learning about patients' diverse health care needs over time, a usual primary care provider can coordinate care (e.g., visits to specialists) to better meet patients' needs. Having a usual primary care provider correlates with receipt of higher quality care (Parchman & Burge, 2002; Inkelas, et al., 2004).

A person is determined to have had a primary care provider if his or her usual source of care setting was either a physician's office or a hospital (setting other than an emergency room), and he or she reported going to this usual source of care for new health problems, preventive health services, and physician referrals.

 

Figure 9.8. People with a usual primary care provider, by race and family income, 2002-2008

Figure 9.8. People with a usual primary care provider, by race and family income, 2002-2008. For details, go to [D] Text Description below.  Figure 9.8. People with a usual primary care provider, by race and family income, 2002-2008. For details, go to [D] Text Description below.     

[D] Select for Text Description.

Key: AI/AN = American Indian or Alaska Native.
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2008.
Denominator: Civilian noninstitutionalized population of all ages.
Note: A usual primary care provider is defined as the source of care that a person usually goes to for new health problems, preventive health care, and referrals to other health professionals.

  • In 2008, Blacks and Asians were less likely than Whites to have a usual primary care provider (72% and 72%, respectively, compared with 76%; Figure 9.8).
  • In 2008, the percentage of people with a usual primary care provider was significantly lower for Hispanics than for non-Hispanic Whites (65% compared with 79%; data not shown).
  • In 2008, the percentage of people with a usual primary care provider was significantly lower for poor people, low-income people, and middle-income people than for high-income people (68%, 71%, and 76% respectively, compared with 80%).

Also, in the NHQR:

  • From 2002 to 2008, people ages 18-44 were least likely to have a usual primary care provider.
  • Uninsured people ages 0-64 were much less likely to have a usual primary care provider than people with private or public insurance.

Patient Perceptions of Need

Patient perceptions of need include perceived difficulties or delays in obtaining care and problems getting care as soon as wanted. Although patients may not always be able to assess their need for care, problems getting care when patients perceive that they are ill or injured likely reflect significant barriers to care.

 

Figure 9.9. People who were unable to get or delayed in getting needed medical care, dental care, or prescription medicines in the last 12 months, by race and income, 2002-2008

Figure 9.9. People who were unable to get or delayed in getting needed medical care, dental care, or prescription medicines in the last 12 months, by race and income, 2002-2008. For details, go to [D] Text Description below.     

[D] Select for Text Description.

Key: AI/AN = American Indian or Alaska Native.
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2008.
Denominator: Civilian noninstitutionalized population of all ages.
Note: For this measure, lower rates are better.

  • Overall in 2008, 10% of people were unable to receive or delayed in receiving needed medical care, dental care, or prescription medicines (data not shown).
  • In 2008, Asians (6%) were less likely than Whites (11%) to report that they were unable to receive or delayed in receiving medical care, dental care, or prescription medicines (Figure 9.9). Hispanics (8%) were less likely than non-Hispanic Whites (11%) to report that they were unable to receive or delayed in receiving medical care, dental care, or prescription medicines (data not shown).
  • In 2008, the percentage of people who were unable to get or delayed in getting needed medical care, dental care, or prescription medicines was significantly higher for poor (15%), low-income (13%), and middle-income (9%) people than for high-income people (8%).
  • People with less than a high school education and people with a high school education were more likely than those with any college education to report they were unable to get or delayed in getting needed care (15% and 12%, respectively, compared with 11%; data not shown).

Also, in the NHQR:

  • In 2008, a higher percentage of people ages 18-44, 45-64, and 65 and over reported being unable to get or delaying needed medical care compared with those ages 0-17.
  • In 2008, the percentage was more than twice as high for people with no health insurance as for people with private insurance and was also higher for people with public insurance than for people with private insurance.

References

Alexander GC, Casalino LP, Meltzer DO. Patient-physician communication about out-of-pocket costs. JAMA 2003;290(7):953-8.

Banthin JS, Bernard DM. Changes in financial burdens for health care: national estimates for the population younger than 65 years, 1996 to 2003. JAMA 2006;296(22):2712-9.

De Maeseneer J, De Prins L, Gosset C, et al. Provider continuity in family medicine: does it make a difference for total health care costs? Ann Fam Med 2003;(1):144-8.

DP05: ACS demographic and housing estimates; 2010 American Community Survey 1-year estimates. Suitland, MD: U.S. Census Bureau; 2010. Available at: http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_10_1YR_DP05&prodType=table. Accessed February 24, 2012.

Ettner SL. The timing of preventive services for women and children: the effect of having a usual source of care. Am J Pub Health 1996;86(12):1748-54.

Hadley J, Holahan J. The cost of care for the uninsured: what do we spend, who pays, and what would full coverage add to medical spending? Kaiser Issue Update. Washington, DC: The Henry J. Kaiser Family Foundation; May 10, 2004. Available at: http://www.kff.org/uninsured/upload/The-Cost-of-Care-for-the-Uninsured-What-Do-We-Spend-Who-Pays-and-What-Would-Full-Coverage-Add-to-Medical-Spending.pdf [Plugin Software Help]. Accessed May 23, 2011.

Inkelas M, Schuster MA, Olson LM, et al. Continuity of primary care clinician in early childhood. Pediatrics 2004;113(6 Suppl):1917-25.

Institute of Medicine, Committee on Monitoring Access to Personal Health Care Services. Access to health care in America. Washington, DC: National Academy Press; 1993.

Jacoby M, Sullivan T, Warren E. Medical problems and bankruptcy filings. Norton's Bankruptcy Law Advisor 2000 May;5:1-12.
Parchman ML, Burge SK. Continuity and quality of care in type 2 diabetes: a Residency Research Network of South Texas study. J Fam Pract 2002;51(7):619-24.

Phillips R, Proser M, Green L, et al. The importance of having health insurance and a usual source of care. Am Fam Physician 2004 Sep 15;70(6):1035.

Starfield B, Shi L. The medical home, access to care, and insurance: a review of evidence. Pediatrics 2004;113(5 Suppl):1493-8.

U.S. Census Bureau. Facts for Features, May 2011. Available at: http://www.census.gov/newsroom/releases/archives/facts_for_features_special_editions/cb11-ff06.html. Accessed August 24, 2011
The value of health insurance: few of the uninsured have adequate resources to pay potential hospital bills. ASPE Research Brief. Washington, DC: U.S. Department of Health and Human Services; May 2011. at Available at: http://aspe.hhs.gov/health/reports/2011/ValueofInsurance/rb.pdf [Plugin Software Help]. Accessed June 29, 2011.


i. As described in Chapter 1, Introduction and Methods, income and educational attainment are used to measure SES in the NHDR. Unless specified, poor = below the Federal poverty level (FPL), low income = 100-199% of the FPL, middle income = 200-399% of the FPL, and high income = 400% or more of the FPL. The measure specifications and data source descriptions provide more information on income groups by data source.



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Page last reviewed April 2012
Internet Citation: Chapter 9. Access to Health Care: National Healthcare Disparities Report, 2011. April 2012. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/findings/nhqrdr/nhdr11/chap9.html