2012 National Healthcare Disparities Report

Highlights From the National Healthcare Quality and Disparities Reports

The U.S. health care system is designed to improve the physical and mental well-being of all Americans by preventing, diagnosing, and treating illness and by supporting optimal function. Across the lifespan, health care helps people stay healthy, recover from illness, live with chronic disease or disability, and cope with death and dying. Quality health care delivers these services in ways that are safe, timely, patient centered, efficient, and equitable.

Unfortunately, Americans too often do not receive care they need, or they receive care that causes harm. Care can be delivered too late or without full consideration of a patient's preferences and values. Many times, our system of health care distributes services inefficiently and unevenly across populations. Some Americans receive worse care than others. These disparities may occur for a variety of reasons, including differences in access to care, social determinants, provider biases, poor provider-patient communication, and poor health literacy.

Each year since 2003, the Agency for Healthcare Research and Quality (AHRQ) has reported on progress and opportunities for improving health care quality and reducing health care disparities. As mandated by the U.S. Congress, the National Healthcare Quality Report (NHQR) focuses on "national trends in the quality of health care provided to the American people" (42 U.S.C. 299b-2(b)(2)). The National Healthcare Disparities Report (NHDR) focuses on "prevailing disparities in health care delivery as it relates to racial factors and socioeconomic factors in priority populations" (42 U.S.C. 299a-1(a)(6)).

As in previous years, we have integrated findings from the 2012 NHQR and NHDR to produce a single summary chapter. This is intended to reinforce the need to consider concurrently the quality of health care and disparities across populations when assessing our health care system. The National Healthcare Reports Highlights seek to address three questions critical to guiding Americans toward the optimal health care they need and deserve:

  • What is the status of health care quality and disparities in the United States?
  • How have health care quality and disparities changed over time?i
  • Where is the greatest need to improve health care quality and reduce disparities?

Three themes from the 2012 NHQR and NHDR emphasize the need to accelerate progress if the Nation is to achieve higher quality and more equitable health care in the near future:

  • Health care quality and access are suboptimal, especially for minority and low-income groups.
  • Overall quality is improving, access is getting worse, and disparities are not changing.
  • Urgent attention is warranted to ensure continued improvements in:
    • Quality of diabetes care, maternal and child health care, and adverse events.
    • Disparities in cancer care.
    • Quality of care among states in the South.

Health Care Quality and Access Are Suboptimal, Especially for Minority and Low-Income Groups

A key function of the reports is to summarize the state of health care quality, access, and disparities for the Nation. This undertaking is difficult, as no single national health care database collects a comprehensive set of data elements that can produce national and state estimates for all population subgroups each year. Rather, data come from more than three dozen databases that provide estimates for different population subgroups and data years. While most data are gathered annually, some data are not collected regularly or are old. The full set of measures tracked in the reports includes measures of access to health care (e.g., having health insurance and having a regular provider) and measures of quality of health care delivered (e.g., receipt of specific services needed to treat or prevent a medical condition and outcomes of treatment).

Despite the data limitations, our analyses indicate that access to health care and quality of health care in America are suboptimal. On average, in 2009, 26% of Americans reported barriers that restricted their access to care. Entry into the health care system did not ensure high-quality care. On average, in 2009, Americans received 70% of indicated health care services and failed to receive 30% of the care they needed to treat or prevent particular medical conditions. The gap between best possible care and what is routinely delivered remains substantial across the Nation.

All Americans should have equal access to high-quality care. Instead, we find that racial and ethnic minorities and poor people often face more barriers to care and receive poorer quality of care when they can get it. In previous years, we assessed disparities using a set of core measures. This year, we analyze disparities using the full set of measures tracked in the reports. We observe few differences in results from the core and full measure sets and present findings from the full measure set here.

For each measure, we examine the relative difference between a selected group and its reference group. Differences that are statistically significant, are larger than 10%, and favor the reference group are labeled as indicating worse quality or access for the selected group. Differences that are statistically significant, are larger than 10%, and favor the selected group are labeled as indicating better quality or access for the selected group. Differences that are not statistically significant or are smaller than 10% are labeled as the same for the selected and reference groups.

Figure H.1. Number and proportion of all quality measures for which members of selected groups experienced better, same, or worse quality of care compared with reference group

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Key: AI/AN = American Indian or Alaska Native; NHW = non-Hispanic White; n = number of measures.
Better = Population received better quality of care than reference group.
Same = Population and reference group received about the same quality of care.
Worse = Population received worse quality of care than reference group.
Note: For each measure, the most recent data available to our team were analyzed; for the vast majority of measures, this represents data from 2008, 2009, or 2010.

  • Disparities in quality of care are common:
    • Blacks received worse care than Whites, and Hispanics received worse care than non-Hispanic Whites for about 40% of quality measures (Figure H.1).
    • American Indians and Alaska Natives (AI/ANs) received worse care than Whites for one-third of quality measures.
    • Asians received worse care than Whites for about one-quarter of quality measures but better care than Whites for a similar proportion of quality measures.
    • Poor and low-income people received worse care than high-income peopleii for about 60% of quality measures; middle-income people received worse care for more than half the measures.

 

Figure H.2. Number and proportion of all access measures for which members of selected groups experienced better, same, or worse access to care compared with reference group

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Key: AI/AN = American Indian or Alaska Native; NHW = non-Hispanic White; n = number of measures.
Better = Population had better access to care than reference group.
Same = Population and reference group had about the same access to care.
Worse = Population had worse access to care than reference group.
Note: For each measure, the most recent data available to our team were analyzed; for the vast majority of measures, this represents data from 2008, 2009, or 2010.

  • Disparities in access are also common, especially among AI/ANs, Hispanics, and poor people:
    • Blacks had worse access to care than Whites for one-third of measures, and AI/ANs had worse access to care than Whites for about 40% of access measures (Figure H.2).
    • Asians had worse access to care than Whites for about 20% of access measures but better access to care than Whites for a similar proportion of access measures.
    • Hispanics had worse access to care than non-Hispanic Whites for about 70% of measures.
    • Poor people had worse access to care than high-income people for all measures; low-income people had worse access to care for more than 80% of measures, and middle-income people had worse access to care for about 70% of measures.

Overall Quality Is Improving, Access Is Getting Worse, and Disparities Are Not Improving

Suboptimal health care is undesirable, but we may be less concerned if we observe evidence of vigorous improvement. Hence, the second key function of these reports is to examine change over time. New this year, we assess changes in average performance through 2009 across a fixed panel of quality of care process measures and access to care measures.

Figure H.3. Average performance across a panel of quality of care process measures and access to care measures, 2002-2009

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  • Problems with quality of care are decreasing while problems with access to care are increasing:
    • In 2005, Americans failed to receive about 34% of health care services they should have received; by 2009, this had fallen to 30% of services (Figure H.3).
    • In 2002, 24% of Americans encountered difficulties accessing health care; by 2009, this had increased to 26% of Americans.

Another way to track the progress of health care quality and access presented in these reports is to calculate annual rates of change, which represent how quickly quality of and access to services delivered by the health care system are improving or declining. As in past reports, regression analysis is used to estimate annual rate of change for each measure. Annual rate of change is calculated only for measures with at least 4 years of data. For most measures, trends include data points from 2000-2002 to 2008-2010.

Weighted least squares regression is used to assess whether trends are statistically significant. Measures that are going in a favorable direction at a rate that exceeds 1% per year and is statistically significant are considered to be improving. Measures going in an unfavorable direction at a rate that exceeds 1% per year and is statistically significant are considered to be worsening. Measures that are changing at a rate that is less than 1% per year or is not statistically significant are considered to be static. Because of the addition of significance testing, this year's results cannot be compared with results in previous reports.

Figure H.4. Number and proportion of all quality measures that are improving, not changing, or worsening, overall and for select populations

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Key: AI/AN = American Indian or Alaska Native; n = number of measures.
Improving = Quality is going in a positive direction at an average annual rate greater than 1% per year.
No Change = Quality is not changing or is changing at an average annual rate less than 1% per year.
Worsening = Quality is going in a negative direction at an average annual rate greater than 1% per year.
Note: For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents trend data from 2000-2002 to 2008-2010.

  • Quality is improving slowly for all groups:
    • Across all measures of health care quality tracked in the reports, almost 60% showed improvement (Figure H.4).
    • Improvement occurred among all racial, ethnic, and income groups.

Figure H.5. Number and proportion of all access measures that are improving, not changing, or worsening, overall and for select populations

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Key: AI/AN = American Indian or Alaska Native; n = number of measures.
Improving = Access is going in a positive direction at an average annual rate greater than 1% per year.
No Change = Access is not changing or is changing at an average annual rate less than 1% per year.
Worsening = Access is going in a negative direction at an average annual rate greater than 1% per year.
Note: For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents trend data from 2000-2002 to 2008-2010.

  • Access is getting worse for most groups:
    • Across the measures of health care access tracked in the reports, only one showed improvement and almost half were getting worse (Figure H.5).
    • For most racial, ethnic, and income groups, the number of access measures that were getting worse exceeded the number that were improving.

Weighted least squares regression was also used to assess change in disparities. When a selected group's rate of change is at least 1% higher than the reference group's rate of change and this difference in rates of change is statistically significant, we label the disparity as improving. When a selected group's rate of change is at least 1% lower than the reference group's rate of change and this difference in rates of change is statistically significant, we label the disparity as worsening. When the difference is less than 1% or is not statistically significant, we label the disparity as static.

Figure H.6. Number and proportion of all quality measures for which disparities related to race, ethnicity, and income are improving, not changing, or worsening

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Key: AI/AN = American Indian or Alaska Native; NHW = non-Hispanic White; n = number of measures.
Improving = Disparity is getting smaller at a rate greater than 1% per year.
No Change = Disparity is not changing or is changing at a rate less than 1% per year.
Worsening = Disparity is getting larger at a rate greater than 1% per year.
Note: For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents data on change in disparities from 2000-2002 to 2008-2010.

  • Few disparities in quality of care are improving (getting smaller):
    • Few disparities in quality of care related to race, ethnicity, or income showed significant improvement, although the number of disparities that were getting smaller typically exceeded the number of disparities that were getting larger (Figure H.6).
    • Disparities that were getting smaller include differences between Hispanics and non-Hispanic Whites in rates of admission for congestive heart failure. Disparities that were getting larger include differences between Blacks and Whites in rates of advanced stage breast cancer.

Figure H.7. Number and proportion of all access measures for which disparities related to race, ethnicity, and income are improving, not changing, or worsening

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Key: AI/AN = American Indian or Alaska Native; NHW = non-Hispanic White; n = number of measures.
Improving = Disparity is getting smaller at a rate greater than 1% per year.
No Change = Disparity is not changing or is changing at a rate less than 1% per year.
Worsening = Disparity is getting larger at a rate greater than 1% per year.
Note: For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents data on change in disparities from 2000-2002 to 2008-2010.

  • Almost no disparities in access to care are improving (getting smaller):
    • The gap in access between Asians and Whites improved (grew smaller) for one measure (people without a usual source of care who indicate a financial or insurance reason for not having a source of care). No other disparities in access to care showed improvement (Figure H.7).

Disparities Action Plan Priority: Increasing the Availability and Quality of Data Collected and Reported on Racial and Ethnic Minority Populations

Identifying problems, targeting resources, and designing interventions all depend on reliable data. Unfortunately, data on underserved populations are often incomplete. Some data sources do not collect information to identify specific groups. Other data sources collect this information, but the numbers of individuals from specific groups included are too small to allow reliable estimates. The HHS Action Plan To Reduce Racial and Ethnic Health Disparities (Disparities Action Plan; HHS, 2011) includes this priority as part of its goal to advance scientific knowledge and innovation in support of reducing health disparities.

Progress in Disparities Data

In the 2006 NHDR, we presented a chart showing the percentage of core quality measures for which an estimate that met our reliability criteria could not be generated for single-race Asians, Native Hawaiians and Other Pacific Islanders (NHOPIs), AI/ANs, multiple-race individuals, Hispanics, and poor people. Except for one measure related to language assistance,iii all measures provided reliable estimates for Blacks, so they were not shown.

Below we include the percentage of all quality measures in the 2006, 2011, and 2012 reports for which a reliable estimate could not be generated for these same groups. Again, except for the one measure of language assistance, reliable estimates could be generated for Blacks for all other measures, so they are not shown.

Figure H.8. Percentage of quality measures in the 2006, 2011, and 2012 reports for which a reliable estimate could not be generated

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Key: NHOPI = Native Hawaiian or Other Pacific Islander; AI/AN = American Indian or Alaska Native.

  • Data on disparities continue to improve but are still suboptimal:
    • Since 2006, the percentage of quality measures that could not be used to assess disparities has decreased for all groups (Figure H.8).
    • For NHOPIs, reliable estimates were not available for more than three-quarters of the measures, making any assessment of disparities incomplete. Reliable estimates for AI/AN and poor populations also could not be generated for a large percentage of measures.

Nationwide Initiatives Increasing Data on Racial and Ethnic Minority Populations

The Affordable Care Act requires that all federally funded health programs and population surveys collect and report data on race, ethnicity, sex, primary language, and disability and supports use of data to analyze and track health disparities (Andrulis, et al., 2010). To improve the quality of data collected in population surveys, HHS published Data Standards for Race, Ethnicity, Sex, Primary Language, and Disability in October 2011 (Office of Minority Health, 2011). New, more granular standards for race and ethnicity build and expand on the 1997 Office of Management and Budget data collection standards.

To strengthen data collection in Medicaid and Children's Health Insurance Programs, HHS evaluated these programs and recommended improvements in the report, Approaches for Identifying, Collecting, and Evaluating Data on Health Care Disparities in Medicaid and CHIP. Recommendations include aligning the Medicaid Statistical Information System, Medicare Current Beneficiary Survey, and Consumer Assessment of Healthcare Providers and Systems with the new data standards.

Urgent Attention Is Warranted To Ensure Improvements in Quality and Success in Reducing Disparities

The third key function of these reports is to identify areas in greatest need of improvement. Potential problem areas can be defined by types of services and populations at risk. Pace of improvement varies across preventive care, acute treatment, and chronic disease management.

Figure H.9. Number and proportion of measures that are improving, not changing, or worsening, by type of quality measure

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Key: n = number of measures.
Improving = Quality is going in a positive direction at an average annual rate greater than 1% per year.
No Change = Quality is not changing or is changing at an average annual rate less than 1% per year.
Worsening = Quality is going in a negative direction at an average annual rate greater than 1% per year.
Note: Preventive care includes screening, counseling, and vaccinations; acute treatment includes hospital care for cancer, heart attack, and pneumonia; chronic disease management includes ambulatory care for diabetes, arthritis, and asthma and nursing home care for pressure sores and pain. For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents trend data from 2000-2002 to 2008-2010.

  • Measures of acute treatment are improving; other measures are lagging:
    • About half of all process and outcome measures showed improvement (Figure H.9).
    • Of the quality measures related to treatment of acute illness or injury, more than 80% showed improvement. In contrast, only about 40% of quality measures related to preventive care and chronic disease management showed improvement. Acute treatment includes a high proportion of hospital measures, many of which are tracked by the Centers for Medicare & Medicaid Services (CMS) and publicly reported. Hospitals often have more infrastructure to improve quality and to respond to performance measurement compared with providers in other settings.

The NHQR tracks the pace of change over time for measures with at least 4 years of data. Table H.1 lists the quality measures with the highest rates of improvement and deterioration.

Table H.1. Quality measures with the most rapid pace of improvement and deterioration

Quality ImprovingQuality Worsening
Adult surgery patients who had prophylactic antibiotics discontinued within 24 hours after surgery end timeaChildren ages 19-35 months who received 3 or more doses of Haemophilus influenzae type B vaccineb
Adult surgery patients who received prophylactic antibiotics within 1 hour prior to surgical incisionaMaternal deaths per 100,000 live birthsb
Hospital patients with heart attack who received percutaneous coronary intervention within 90 minutes of arrivalaAdults age 40+ with diagnosed diabetes who had their feet checked for sores or irritation in the calendar yearc
Hospital patients age 65+ with pneumonia who received a pneumococcal screening or vaccinationaPostoperative pulmonary embolism or deep vein thrombosis per 1,000 surgical admissions, age 18+d
Hospital patients age 50+ with pneumonia who received an influenza screening or vaccinationaAdmissions for asthma per 100,000 population, age 65+c
Hospital patients with pneumonia who had blood cultures collected before antibiotics were administeredaAdults age 40+ with diagnosed diabetes who received 2+ hemoglobin A1c measurements in the calendar yearc
Hospital patients with heart failure who were given complete written discharge instructionsaSuicide deaths per 100,000 population
Hospital patients with heart failure and left ventricular systolic dysfunction who were prescribed ACE inhibitor or ARB at dischargeaWomen ages 21-65 who received a Pap smear in the last 3 years
Long-stay nursing home residents who were assessed and given pneumococcal vaccinationaAdmissions with stage III or IV pressure ulcer per 1,000 medical and surgical admissions of length 5+ daysd
Patients with colon cancer who received recommended treatment: surgical resection of colon specimen that had 12+ regional lymph nodes pathologically examinedAdmissions with diabetes with short-term complications per 100,000 population, age 18+c

Key: ACE = angiotensin-converting enzyme; ARB = angiotensin receptor blocker.
Note: a = CMS publicly reported measures; b = maternal and child health measures; c = diabetes measures; d = adverse events. For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents trend data from 2000-2002 to 2008-2010.

  • Quality changes unevenly across measures:
    • Of the 10 quality measures that are improving at the fastest pace, 9 are CMS publicly reported measures (a) (Table H.1).
    • Of the 10 quality measures that are getting worse at the fastest pace, 3 relate to diabetes (c), 2 relate to maternal and child health (b), and 2 relate to adverse events in health care facilities (d).

The NHDR focuses on disparities related to race, ethnicity, and socioeconomic status. Table H.2 summarizes the disparities for each major group tracked in the reports. For each group, it shows the measures where disparities are improving at the fastest rate and the measures where disparities favor the comparison group and are worsening.

Table H.2. Disparities that are changing over time

GroupsDisparities ImprovingDisparities Worsening
Black compared with WhiteAdmissions for congestive heart failure per 100,000 population, age 18+bAdvanced stage invasive breast cancer incidence per 100,000 women age 40+c
Adjusted incidence of end stage renal disease due to diabetes per million populationdMaternal deaths per 100,000 live birthse
Short-stay nursing home residents who were assessed and given pneumococcal vaccinationa 
Asian compared with WhiteHospital patients age 65+ with pneumonia who received a pneumococcal screening or vaccinationaAdjusted incidence of end stage renal disease due to diabetes per million populationd
Hospital patients age 50+ with pneumonia who received an influenza screening or vaccinationaHospice patients who received the right amount of help for feelings of anxiety or sadness
Hospital patients with heart failure who were given complete written discharge instructionsbAdults ages 18-64 at high risk (e.g., COPD) who ever received pneumococcal vaccination
American Indian/ Alaska Native compared with WhiteAdjusted incidence of end stage renal disease due to diabetes per million populationdHospital patients with heart failure and left ventricular systolic dysfunction who were prescribed ACE inhibitor or ARB at dischargeb
Children who had their height and weight measured by a health provider within the past 2 yearseAdults age 50+ who ever received a colonoscopy, sigmoidoscopy, or proctoscopyc
Hispanic compared with Non-Hispanic WhiteAdmissions for congestive heart failure per 100,000 population, age 18+bHome health care patients who have less shortness of breath
Hospital patients age 65+ with pneumonia who received a pneumococcal screening or vaccinationaAdults age 40+ with diagnosed diabetes who received 2+ hemoglobin A1c measurements in the calendar yeard
Hospital patients age 50+ with pneumonia who received an influenza screening or vaccinationaHospital patients with heart attack who received fibrinolytic medication within 30 minutes of arrivalb
Poor compared with High IncomeAdmissions for congestive heart failure per 100,000 population, age 18+bPeople without a usual source of care who indicate a financial or insurance reason for not having a source of care
Deaths per 1,000 hospital admissions with abdominal aortic aneurysm repair, age 18+bAdults age 50+ who ever received a colonoscopy, sigmoidoscopy, or proctoscopyc
Children ages 2-17 who had a dental visit in the calendar yeareAdmissions with diabetes with short-term complications per 100,000 population, age 18+d

Key: COPD = chronic obstructive pulmonary disease; ACE = angiotensin-converting enzyme; ARB = angiotensin receptor blocker.
Note: a = CMS publicly reported vaccination measures; b = cardiovascular disease measures; c = cancer measures; d = diabetes measures; e = maternal and child health measures. For each measure, the earliest and most recent data available to our team were analyzed; for the vast majority of measures, this represents data on change in disparities from 2000-2002 to 2008-2010.

  • Disparities also change unevenly across measures:
    • Of the disparities that are improving, 5 are CMS publicly reported vaccination measures (a) and 5 relate to cardiovascular disease (b) (Table H.2).
    • Of the disparities that favor the comparison group and are getting worse, 3 relate to cancer (c).
    • Measures related to diabetes (d) and maternal and child health (e) showed mixed patterns, with some disparities improving and others worsening.

Quality of care varies not only across types of care but also across parts of the country. Knowing where to focus efforts improves the efficiency of interventions. Delivering data that can be used for local benchmarking and improvement is a key step in raising awareness and driving quality improvement.

Since 2005, AHRQ has used the State Snapshots tool (http://statesnapshots.ahrq.gov) to examine variation across states. This Web site helps state health leaders, researchers, consumers, and others understand the status of health care quality in individual states and the District of Columbia.

The State Snapshots are based on more than 100 NHQR measures, each of which evaluates a different aspect of health care performance and shows each state's strengths and weaknesses. Here, we use data from the 2011 State Snapshots to examine variation in quality across states.

Figure H.10. Overall quality of care, preventive care, acute care, and chronic care, by State

Overall Quality of Care
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Preventive Care
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Acute Care
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Chronic Care
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Source: Agency for Healthcare Research and Quality, 2011 State Snapshots.
Note: States are divided into quartiles based on overall health care score

  • Quality of care differs across geographic regions:
    • For overall quality of care, states in the New England (CT, MA, ME, NH, RI, VT) and West North Central (IA, KS, MN, MO, NE, ND, SD) census divisions were most often in the top quartile (Figure H.10). States in the South Atlantic (DC [not shown], DE, FL, GA, MD, NC, SC, VA, WV), East South Central (AL, KY, MS, TN), and West South Central (AR, LA, OK, TX) census divisions were most often in the bottom quartile.
    • States in different parts of the country faced different patterns of health care quality.
      • States in the New England and West North Central divisions performed well on preventive, acute, and chronic care quality measures while states in the East South Central and West South Central divisions performed poorly on all three types of services.
      • States in the Mountain division (AZ, CO, ID, MT, NV, NM, UT, WY) performed poorly on preventive and acute care.
      • States in the East North Central (IL, IN, MI, OH, WI) division performed well on acute care but poorly on chronic care.
      • States in the South Atlantic census division performed well on preventive care but poorly on chronic care.

Conclusion

The NHQR and NHDR track health care quality and disparities at the national level, but the statistics reported in the reports reflect the aggregated everyday experiences of patients and their providers across the Nation. Improving quality and reducing disparities require measurement and reporting, as provided in the NHQR and NHDR. These statistics, however, are only useful to the extent that they inform policies and initiatives and help us track progress toward the ultimate goal of HHS initiatives, which is to improve the lives of patients and families.

It makes a difference in people's lives when breast cancer is diagnosed early; when a patient having a heart attack gets the correct lifesaving treatment in a timely fashion; when medications are correctly administered; and when doctors listen to their patients and their families, show them respect, and answer their questions in a culturally and linguistically skilled manner. All Americans should have access to quality care that helps them achieve the best possible health.

With the publication of this 10th NHQR and NHDR, AHRQ stands ready to contribute to efforts that encourage and support the development of national, state, tribal, and local solutions using national data and achievable benchmarks of care. These documents identify areas where novel strategies have made a difference in improving patients' quality of life, as well as many areas where much more should be done.

We need to improve access to care, reduce disparities, and accelerate the pace of quality improvement, especially in the areas of preventive care and safety. More data are needed to assess progress in care coordination and efficiency. Information needs to be shared with partners who have the skills and commitment to change health care. Building on data in the NHQR, NHDR, and State Snapshots, stakeholders can design and target strategies and clinical interventions to ensure that all patients receive the high-quality care needed to make their lives better.

References

Andrulis DP, Siddiqui NJ, Purtle JP, et al. Patient Protection and Affordable Care Act of 2010: advancing health equity for racially and ethnically diverse populations. Washington, DC: Joint Center for Political and Economic Studies; 2010. Available at: http://www.jointcenter.org/research/patient-protection-and-affordable-care-act-of-2010-advancing-health-equity-for-racially-and. Accessed March 13, 2013.

HHS action plan to reduce racial and ethnic health disparities. Washington, DC: U.S. Department of Health and Human Services; 2011. Available at: http://minorityhealth.hhs.gov/npa/templates/content.aspx?lvl=1&lvlid=33&ID=285. Accessed March 13, 2013.

Office of Minority Health. Explanation of data standards for race, ethnicity, sex, primary language, and disability. Washington, D.C.: U.S. Department of Health and Human Services; 2011, Available at: http://minorityhealth.hhs.gov/templates/content.aspx?ID=9228&lvl=2&lvlID. Accessed March 13, 2013.

U.S. Department of Health and Human Services. 2012 annual progress report to Congress: national strategy for quality improvement in health care. Washington, DC: HHS; 2012. Available at: https://www.ahrq.gov/workingforquality/nqs/nqs2012annlrpt.pdf [Plugin Software Help]. Accessed March 13, 2013.

i. Data years vary across measures. For most measures, trends include data points from 2000-2002 to 2008-2010.
ii. Throughout the Highlights, poor, low income, middle income, and high income indicate individuals whose household income is <100%, 100-199%, 200-399%, and 400% or more of the Federal poverty level, respectively.
iii. The measure is the percentage of adults with limited English proficiency and a usual source of care who had language assistance.

Page last reviewed May 2013
Internet Citation: 2012 National Healthcare Disparities Report: Highlights From the National Healthcare Quality and Disparities Reports. May 2013. Agency for Healthcare Research and Quality, Rockville, MD. http://archive.ahrq.gov/research/findings/nhqrdr/nhdr12/highlights.html