Advancing Excellence in Health Care • www.ahrq.gov

Agency for Healthcare Research and Quality

U.S. Department of 

Health and Human Services

Agency for Healthcare Research and Quality

540 Gaither Road

Rockville, MD 20850

AHRQ Publication No. 11-0005

March 2011

www.ahrq.gov/qual/qrdr10.htm
(NIH-NCI), Wilma Tilson (HHS-ASPE), Benedict Truman (CDC), Joan Van Nostrand (HRSA), Barbara Wells (NIH-NHLBI), Valerie

Welsh (HHS-OMH), Odies Williams (HHS-OCR), Lee Wilson (HHS-ASPE), and Susan Yanovski (NIH-NIDDK).

AHRQ NHQR/NHDR Team: Roxanne Andrews, Barbara Barton, Doreen Bonnett, Xiuhua Chen, Frances Chevarley, Cecilia

Rivera Casale, Katherine Crosson, Denise Dougherty, William Freeman, Darryl Gray, Paul Gorrell, Karen Ho, Ernest Moy, Atlang

Mompe, William Munier, Janet Pagán-Sutton, and Judy Sangl.

HHS Data Experts: Roxanne Andrews (AHRQ), Frances Chevarley (AHRQ), Steven Cohen (AHRQ), James Colliver (SAMHSA),

Mark Eberhardt (CDC-NCHS), Paul Eggers (NIH), Alyson Essex (CDC-NCHS), John Fleishman (AHRQ), Elizabeth Goldstein

(CMS), Erin Grace (AHRQ), Janey Hsiao (CDC-NCHS), Susan Jack (CDC-NCHS), Deepthi Kandi (CDC-NCHS), David Keer (EDOSERS), Kenneth Kochanek (CDC-NCHS), Stan Lehman (CDC), Tracy Matthews (HRSA), Diane Meier (HHS-ASPE), William

Mosher (CDC-NCHS), Ryan Mutter (AHRQ), Shaleah Patzer (CDC-NCHS), Arlene Siller (CDC-NCHS), Jack Vaughn (CDCNCHS), Reda Wilson (CDC-NPCR), and Marc Zodet (AHRQ) and members of the Interagency Subcommittee on Disability

Statistics.

Other Data Experts: Stephen Connor (NHPCO), Stephen Edge (Rosewell Park Cancer Institute), Michael Halpern (American

Cancer Society), Bryan Palis (American College of Surgeons), Allison Petrilla (NHPCO), Carol Spence (NHPCO), Andrew Stewart

(American College of Surgeons),.

Other AHRQ Contributors: James Battles, Jeff Brady, Cindy Brach, Judi Consalvo, Chris Crofton, James Cleeman, Noel Eldridge,

Karen Fleming-Michael, Christine Heidenrich, Biff LeVee, Morgan Liscinsky, Corey Mackison, Gerri Michael-Dyer, Karen Migdail,

Laura Nawrocki, Mary Nix, Pamela Owens, Mamatha Pancholi, Larry Patton, Wendy Perry, Mary Rolston, Scott Rowe, Randie

Siegel, Christine Williams, and Phyllis Zucker. 

Data Support Contractors: CHD-Fu, Social and Scientific Systems, Thomson Reuters Healthcare, and Westat.

In memory of Ms. Beatrice Rouse, SAMHSA, a member of the Interagency Work Group, 2003-2010.
Supportive and Palliative Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

3. Patient Safety. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

4. Timeliness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

5. Patient Centeredness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

6. Care Coordination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189

7. Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203

8. Health System Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217

9. Access to Health Care. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

10. Priority Populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

Appendixes:

Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr10/datasources/index.html

Detailed Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr10/methods/index.html

Measure Specifications . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr10/measurespec/index.html

Data Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr10/index.html

in the quality of health care provided to the American people” (42 U.S.C. 299b-2(b)(2)) while 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)).

The 2010 reports and this summary incorporate a number of recommendations made by the Institute of

Medicine (IOM). The IOM first provided guidance to AHRQ on the NHQR and NHDR in 2002. In 2008,

AHRQ again asked the IOM to offer suggestions for enhancing future reports and associated products to

ensure that these reports raise awareness of the performance of the U.S. health care system. In April 2010,

AHRQ received advice from the IOM Committee on Future Directions for the National Healthcare Quality

and Disparities Reports.ii

In the past, separate Highlights were produced for each report. This year, we have integrated findings from

the 2010 NHQR and 2010 NHDR to produce a single summary document. This is intended to reinforce the

need to consider simultaneously the quality of health care and disparities across populations when assessing

our health care system. The National Healthcare Reports Highlights seeks 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?

● Where is the need to improve health care quality and reduce disparities greatest?

i The HHS Interagency Work Group represents 18 HHS agencies and offices.

ii The full report of this committee’s recommendations can be found at www.ahrq.gov/research/iomqrdrreport.

National Healthcare Disparities Report, 2010 1
 Two are improving in quality: (1) Palliative and End-of-Life Care and (2) Patient and Family

Engagement. 

• Three are lagging: (3) Population Health, (4) Safety, and (5) Access.

• Three require more data to assess: (6) Care Coordination, (7) Overuse, and (8) Health System

Infrastructure.

• All eight priority areas showed disparities related to race, ethnicity, and socioeconomic status.

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.

Despite the data limitations, our analyses indicate that health care quality in America is suboptimal. The gap

between best possible care and that which is routinely delivered remains substantial across the Nation.

In the reports, measures are classified as either process measures or outcome measures. Process measures are

further subdivided, when possible, into preventive care, acute treatment, and chronic disease management. 

On average, people received the preventive services tracked in the reports two-thirds of the time. Moreover,

wide variation was found in receipt of different types of preventive services. For instance, 20% of high-risk

adults ages 18-64 ever received pneumococcal vaccination, but 94% of children ages 19-35 months received

3 doses of polio vaccine. 

National Healthcare Disparities Report, 2010 2
National Healthcare Disparities Report, 2010 3

group. Differences that are not statistically significant or are smaller than 10% are labeled as the same

between the selected group and the reference group.

iii A list of core measures can be found in the Introduction and Methods chapter. Analyses of disparities presented in these

Highlights focus on core measures and are so labeled. Other analyses use the entire measure set.
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.

● Disparities in quality of care are common:

• Blacks and American Indians and Alaska Natives received worse care than Whites for about 40% of

core measures.

• Asians received worse care than Whites for about 20% of core measures.

• Hispanics received worse care than non-Hispanic Whites for about 60% of core measures.

• Poor people received worse care than high-income peopleiv for about 80% of core measures.

iv Throughout these highlights and reports, unless otherwise specified, poor indicates individuals whose household income is

below the Federal poverty level and high income indicates individuals whose household income is at least four times the

Federal poverty level.

National Healthcare Disparities Report, 2010 4
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.

● Disparities in access are also common, especially among Hispanics and poor people:

• Blacks had worse access to care than Whites for one-third of core measures.

• Asians and American Indians and Alaska Natives had worse access to care than Whites for 1 of 5

core measures.

• Hispanics had worse access to care than non-Hispanic Whites for 5 of 6 core measures.

• Poor people had worse access to care than high-income people for all 6 core measures.

Quality Is Improving; Access 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 the reports is to examine change over time. To track the

progress of health care quality and access in this country, the reports present annual rates of change, which

represent how quickly quality of and access to services delivered by the health care system are improving or 

National Healthcare Disparities Report, 2010 5
National Healthcare Disparities Report, 2010 6

Improving = Quality or access is going in a positive direction at an average annual rate greater than 1% per year.

No Change = Quality or access is not changing or is changing at an average annual rate less than 1% per year.

Worsening = Quality or access is going in a negative direction at an average annual rate greater than 1% per year.

● Quality is improving slowly. Across all 179 measures of health care quality tracked in the reports,

almost two-thirds showed improvement. However, median rate of change was only 2.3% per year.

● Access is not improving. Across the 22 measures of health care access tracked in the reports, about

70% did not show improvement and 40% were headed in the wrong direction. Median rate of change

was -0.6% per year, indicating no change over time.
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.

● Few disparities in quality of care are getting smaller.

• Fewer than 20% of disparities faced by Blacks, American Indians and Alaska Natives, Hispanics, and

poor people showed evidence of narrowing.

• The Asian-White gap was narrowing for about 30% of core measures, the largest proportion of any

group, but most disparities were not changing.

National Healthcare Disparities Report, 2010 7
Key: AI/AN = American Indian or Alaska Native.

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.

● Almost no disparities in access to care are getting smaller.

• Among disparities in core access measures, only one showed reduction.

Urgent Attention Is Warranted To Ensure Improvements in 

Quality and Progress on Reducing Disparities

The third key function of the reports is to identify which areas are in greatest need of improvement. Potential

problem areas can be defined in terms of types of services, parts of the country, and populations at risk.

Variation Across Types of Services

Pace of improvement varies across preventive services, acute treatment, and chronic disease management.

National Healthcare Disparities Report, 2010 8
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.

● Measures of acute treatment are improving; measures of preventive care and chronic disease

management are lagging.

• While both process and outcome measures are improving, rates of improvement are faster among

processes of care. Median rate of improvement of process measures was 2.6% per year compared

with 1.6% per year for outcome measures.

• Among process measures, the highest rate of improvement was in measures related to treatment of

acute illnesses or injuries. Of the 21 process of care measures related to acute treatment, about 80%

showed improvement.

• In contrast, of the 35 process measures related to preventive services, only 60% showed

improvement. Of the 22 process measures related to chronic disease management, about 70%

showed improvement. This may reflect the high proportion of hospital measures included in acute

treatment, many of which are tracked by the Centers for Medicare & Medicaid Services and publicly

reported.

National Healthcare Disparities Report, 2010 9
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

examined variation across States in the State Snapshots tool (http://statesnapshots.ahrq.gov). 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.

The 2010 reports introduce a new method for examining variation across States and benchmarking quality of

care. For measures with State data, we calculate the benchmark as the average for the top 10% of States; this

average is referred to as the “achievable benchmark.” Achievable benchmarks are believed to be more

actionable because they represent a level of performance that has been demonstrated in the real world. Here,

we examine the frequency with which States perform in the top 10% of States and contribute to the

achievable benchmark.

Data are not available for all States for all measures. Thus, States that have less health care data, either

because it is not collected or because samples are too small to generate reliable estimates, have fewer

opportunities to be in the top 10%. In addition, State data are more readily available from vital statistics and

from hospitals, nursing homes, and home health agencies, while State data are much more limited for

important topics such as quality of HIV or mental health care and care coordination. Policies that improve

data collection at the State level would allow benchmarking across a broader array of measures. It is hoped

that as health information technologies continue to expand, more information will become available for finer

geographic units as well as for more granular subpopulations.

National Healthcare Disparities Report, 2010 10
● Two parts of the country led in performance. While every State was in the top 10% for some

measure and was part of a benchmark, States in the New England (CT, MA, ME, NH, RI, VT) and

Pacific (AK, CA, HI, OR, WA) census divisions were benchmark States most often and States in the

East North Central (IL, IN, MI, OH, WI), East South Central (AL, KY, MS, TN), and West South

Central (AR, LA, OK, TX) divisions were benchmark States less often.

Table H2. States most often contributing to the top 10%

Chronic Disease 

Preventive Care Acute Treatment Management Outcome

Delaware Maine Hawaii Arizona

Massachusetts New Hampshire Minnesota District of Columbia

New Hampshire New Jersey New Hampshire Hawaii

Vermont South Carolina Utah

● New England did best on preventive care and acute treatment; western States did best on outcomes of

care.

National Healthcare Disparities Report, 2010 11
National Healthcare Disparities Report, 2010 12
Key: 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: Number of measures varies for each group because for some measures, data for some groups were not available.

● Residents of the inner-city and rural areas sometimes receive worse quality of care. For most

measures of quality of health care, differences across the urban-rural continuum were small. However,

some disparities are noted. Compared with residents of large city suburbs, residents of large inner cities

received worse care for about a quarter of quality measures tracked in the reports. Residents of

micropolitan and noncore areas (areas typically regarded as “rural”) received worse care for about 30%

of measures.

● Disparities related to preventive care were common across urban and rural areas while disparities

related to diabetes were largest for residents of large inner cities and noncore rural areas.

National Healthcare Disparities Report, 2010 13
Key: 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 poorer quality of care than reference group.

Note: Number of measures varies for each group because for some measures, data for some groups were not available.

● Disparities in access to care across the urban-rural continuum tended to be more common than

disparities in quality of care. Compared with residents of large city suburbs, residents of large inner

cities had worse access to care for about 35% of access measures tracked in the reports. Residents of

micropolitan areas had worse access to care for 50% of access measures. Residents of noncore areas

had worse access to care for about 40% of access measures.

The NHDR focuses on disparities related to race, ethnicity, and socioeconomic status. Table H.3 summarizes

the largest disparities for each major group tracked in the reports that are either getting larger or staying the

same. The table shows that many groups experience disparities related to preventive services and access to

care.

National Healthcare Disparities Report, 2010 14
White

Poor compared People under age 65 with health insurance 4.7

with High Female Medicare beneficiaries age 65 and over who reported ever being 

Income screened for osteoporosis with a bone mass or bone density measurement 3.6

People with a specific source of ongoing care 2.9

Key: RR indicates rate relative to reference group.

Note: To compare RRs, measures were framed negatively. Hence, an RR greater than 1 indicates that a group is receiving poorer

quality of care or facing larger problems with access to care compared with the reference group. For example, an RR of 1.3 indicates

that Asians are 1.3 times more likely than Whites not to have a usual primary care provider.

Progress Is Uneven With Respect to Eight National Priority

Areas

A key IOM recommendation was that AHRQ highlight progress in selected priority areas that are expected to

yield the greatest gains in health care quality. These priorities include six areas identified by the National

Priorities Partnership (NPP), a coalition representing 48 key health care organizations, as well as two areas

proposed by the IOM. In this section, we report on progress in each of these priority areas. Findings are

organized around key goals for each priority and include information from both the NHQR and NHDR.

In addition, the IOM encouraged the reports to go beyond problem identification and to include information

that might help users address the quality and disparities concerns we identify. To that end, we present novel

strategies for improving quality and reducing disparities, gathered from the AHRQ Health Care Innovations

Exchange (HCIE). The HCIE is a repository of more than 1,500 quality improvement tools and more than

500 quality improvement stories. For each priority area, stories of successful innovations were searched.

National Healthcare Disparities Report, 2010 15
National Priority: Population Health

Population health is influenced by many factors, including genetics, lifestyle, health care, and the physical

and social environment. The reports focus on health care and counseling about lifestyle modification and do

not address biological and social determinants of health that are currently not amenable to alteration through

health care services. Nonetheless, it is important to acknowledge that the fundamental purpose of health care

is to improve the health of populations. Acute care is needed to treat injuries and illnesses with short courses,

and chronic disease management is needed to minimize the effects of persistent health conditions. But

preventive services that avert the onset of disease, foster the adoption of healthy lifestyles, and help patients

to avoid environmental health risks hold the greatest potential for maximizing population health.

The NPP envisioned “communities that foster health and wellness as well as national, state, and local

systems of care fully invested in the prevention of disease, injury, and disability.” Key goals include

promoting effective preventive services, adopting healthy lifestyle behaviors, and developing a national index

of health.

V Identification numbers of items from the HCIE are included to help users find more information. To access detailed

information about each novel strategy, insert the identification numbers at the end of this link and copy it into your browser

window: http://www.innovations.ahrq.gov/content.aspx?id=

National Healthcare Disparities Report, 2010 16
National Healthcare Disparities Report, 2010 17

percentage of children who received the 4:3:1:3:3 vaccine series

peaked in 2004 and has fallen

since that time. There are few racial or ethnic disparities in childhood immunization, but incomerelated disparities persist.

● Healthy lifestyles: The NHQR and NHDR track five measures related to obesity, diet, and exercise;

four measures related to nicotine and other substance addictions; and four measures related to

transportation safety for children.viii Across these measures, most showed no improvement. Median rate

of improvement was 0.9% per year. Most disparities did not change, but the Hispanic-non-Hispanic

White and poor-high income gaps in counseling about smoking cessation narrowed.

● National index of health: The NHQR and NHDR track eight mortality measures.ix Across these

measures, most showed improvement. Median rate of improvement was 1.3% per year. Most disparities

did not change; the Black-White gap in prostate cancer mortality narrowed while education-related

disparities in lung cancer mortality widened.

vi Screening: Mammogram, Pap test, colonoscopy/sigmoidoscopy; late-stage breast, cervical, and colorectal cancer screening;

blood pressure, cholesterol, and osteoporosis screening; and vision check. Adult immunizations: Influenza and pneumococcal

vaccine among elderly, high-risk, and diabetic patients; patients hospitalized for pneumonia; and long-stay and short-stay

nursing home residents. Childhood immunizations: 4 doses of diphtheria-tetanus-acellular pertussis (DTaP), 3 doses of polio,

1 dose of measles-mumps-rubella (MMR), 3 doses of Haemophilus influenzae B (Hib), and 3 doses of hepatitis B vaccines,

and 1 dose of varicella vaccine.

vii Number of children ages 19-35 months receiving first five childhood immunizations listed above.

viii Screening, diet counseling, exercise counseling for children and obese adults; smoking cessation and treatment for alcohol

and other substance abuse; car seat, booster seat, seat belt, and bicycle helmet use.

ix Breast, colorectal, prostate, and lung cancer; HIV; suicide; and infant and maternal mortality.
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.

Successful Strategies From AHRQ Health Care Innovations Exchange

El Rio Health Center, AZ (2252)

● Intervention: Ongoing immunization training for pediatricians and nurses; nurse-run immunization

clinics offered at the center and in the community; computerized data system tracking immunizations

and reminders for both patients and providers.

● Impact: Program tripled childhood immunization rates, exceeding Federal standards.

Wayne Action Teams for Community Health (WATCH), NC (2929)

● Intervention: Created new processes to identify and provide individuals in need of colorectal cancer

screening and smoking cessation education by forming partnerships with community-based

organizations and providers. Patients participated in ongoing performance monitoring and evaluation.

● Impact: Over 1 year, colorectal cancer screening rose from 16% to 98%. Smokers receiving cessation

education increased from 66% to 98%.

National Healthcare Disparities Report, 2010 18
gy 

● Relief of suffering: Among patients receiving home health care and nursing home care, management of

symptoms, such as shortness of breath or pressure sores, is improving. However, most quality of care

measures are far below achievable benchmarks, and considerable disparities persist related to age,

gender, race, and ethnicity.

● Help with emotional support: Among hospice patients, fewer than 10% do not receive the right amount

of help for feelings of anxiety or sadness. However, considerable disparities related to age, race, and

ethnicity are observed.

● Communication about dying: Among family caregivers of hospice patients, about one in six wanted

more information about what to expect while the patient was dying. In addition, considerable disparities

related to age, gender, race, and ethnicity are observed.

● Palliative care and hospice services: Among hospice patients, few received care inconsistent with their

stated end-of-life wishes. However, considerable disparities related to age, race, ethnicity, and education

are observed. Availability of nonhospice palliative care providers also is a problem; roughly half of U.S.

hospitals have yet to develop palliative care programs.

National Healthcare Disparities Report, 2010 19
National Healthcare Disparities Report, 2010 20

ggy , 

between different facilities and between caregivers. Avoidable medical errors account for an immense number

of deaths annually. Even if patients do not die from a medical error, they will often have longer and more

expensive hospital stays. Clearly, some risk can be reduced and some cannot, but research has shown that

large numbers of errors and adverse events can be markedly reduced if addressed with appropriate

interventions and efforts.

The NPP’s vision is “a healthcare system that is relentless in continually reducing the risks of care, aiming

for a ‘zero’ harm wherever possible—a system that can promise absolute care, guaranteeing that every

patient, every time, receives the benefits of care based solidly on science.” The vision sees health care leaders

and professionals as leading this effort and being resolute in eliminating defects and errors in care, regardless

of their current safety performance levels. Key goals are reducing healthcare-associated infections (HAIs)

and serious adverse events (SAEs), reducing preventable and premature hospital-level mortality rates, and

improving 30-day mortality rates following hospitalization for selected conditions (acute myocardial

infarction, heart failure, pneumonia).

Progress Toward Key Goals

Figure H.11 shows progress in measures related to patient safety:

● Reducing HAIs and SAEs: The reports track 36 safety measures related to HAIs and other SAEs that

can occur during hospitalization. Of these measures, most showed improvement. Across all measures,

median improvement was 3.6% per year. By comparison, among 14 hospital quality measures not 
National Healthcare Disparities Report, 2010 21

Key: HAI = healthcare-associated infection; SAE = serious adverse event.

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.
National Priority: Patient and Family Engagement

In order to effectively navigate the complicated health care system, providers need to ensure that patients can

access culturally and linguistically appropriate tools. Strategies to support patient and family engagement

enable patients to understand all treatment options and to make decisions consistent with their values and

preferences.

The vision of the NPP is health care “that honors each individual patient and family, offering voice, control,

choice, skills in self-care, and total transparency, and that can and does adapt readily to individual and family

circumstances, and to differing cultures, languages, and social backgrounds.” Key goals include enabling

patients to effectively navigate and manage their care and enabling patients to make informed decisions about

their treatment options.

Progress Toward Key Goals

● Effectively navigating and managing care: More than 90% of U.S. adults were able to easily read

their prescription instructions. However, disparities were observed among groups varying by insurance

status, English proficiency, education, and income. Ethnicity, income, and education also were

associated with the need for language assistance when navigating the health care system.

● Making informed decisions about treatment options: Most adults felt it was easy to understand

written instructions from a doctor’s office but nearly one-fifth of adults were sometimes or never asked

to help with decisions on treatment. Disparities were observed related to insurance status, English

proficiency, education, and race/ethnicity.

National Healthcare Disparities Report, 2010 22
● Impact: Program reduced patient waiting time for an interpreter; 86% of patients waited 15 minutes or

less. The number of languages in which interpreter services are available increased from 51 in 2007 to

75 in 2009.

National Priority: Care Coordination

Care coordination is a conscious effort to ensure that all key information needed to make clinical decisions is

available to patients and providers. Health care in the United States was not designed to be coordinated.

Patients commonly receive medical services, treatments, and advice from multiple providers in many

different care settings, each scrutinizing a particular body part or system. Attending to the patient as a whole

is rare. Less than sufficient provider-provider and provider-patient communication is common and may lead

to delays in treatment and inaccuracies in medical information. Enhancing teamwork and increasing use of

health information technologies to facilitate communication among providers and patients can improve care

coordination.

The NPP envisioned health care that “guides patients and families through their healthcare experience, while

respecting patient choice, offering physical and psychological supports, and encouraging strong relationships

between patients and the healthcare professionals accountable for their care.” Key goals include coordinating

transitions of care, communicating medication information, and reducing hospital readmissions and

preventable emergency department visits.

National Healthcare Disparities Report, 2010 23
discharge to help them understand and manage their complex postdischarge needs and ensure continuity

of care across settings.

● Impact: The program reduced hospital readmissions and costs.

Aurora Health Care, WI (1766)

● Intervention: A communitywide medication collaborative, involving health care consumers, providers,

pharmacists, and community stakeholders, to give elderly patients and their providers the tools and

education needed to assemble and verify accurate medication lists, and communicate effectively to

prevent medication errors.

● Impact: The rate of accurate medication lists among patients improved from 55 to 72%.

National Priority: Overuse of Services

Some diagnostic tests, procedures, and other services are performed even when they are unlikely to benefit

the patient. These instances represent overuse of health services. Apart from causing discomfort and distress

for patients, overuse can be harmful to the patient’s health and increase costs.

The NPP’s vision is “healthcare that promotes better health and affordable care by continually and safely

reducing the burden of unscientific, inappropriate, and excessive care including tests, drugs, procedures, 

National Healthcare Disparities Report, 2010 24
MaineHealth AH! (Asthma Health) Program, ME (2476)

● Intervention: Initiative uses hospital-based educators to support providers and other caregivers in

providing quality asthma care. Asthma educators meet one on one with patients and their families to

promote better asthma self-management.

● Impact: Asthma-related hospitalizations declined from 23.8% to 0% after the education sessions, and

the percentage of children and parents who missed school or work declined from 49.4 to 7.8%.

Summa Health System Care Coordination Network, OH (2162)

● Intervention: Ensures smooth transitions between the hospitals and 37 local skilled nursing facilities.

The network uses a simplified transfer form, an electronic referral system, regular meetings, and other

communication tools to boost patients’ discharge to a facility that meets their medical needs. The

network also works to ensure smooth transitions when patients need to return to a hospital for surgery

or testing.

● Impact: Program has led to fewer patients being readmitted to hospitals, lower hospital length of stay

for patients transferred to skilled nursing facilities (which increased the bed capacity to an additional

130 inpatient admissions each year), and fewer cancellations of tests and surgeries for patients

transferred from skilled nursing facilities.

National Healthcare Disparities Report, 2010 25
care. Minority children were also less likely than White children to have a usual source of care.

● Financial burden: Individuals with private nongroup insurance were nearly three times as likely as

individuals with private employer-sponsored insurance to have high health insurance premiums and outof-pocket medical expenses. Poor individuals were five times as likely as high-income individuals to

have high health care expenses. Overall in 2007, 1 in 10 individuals reported that they were unable to

receive or were delayed in receiving needed medical care, dental care, or prescription medicines due to

financial or insurance reasons. Poor people were twice as likely as high-income people to report that

they had this problem.

Successful Strategies From AHRQ Health Care Innovations Exchange

CarePartners, ME (1689)

● Intervention: Program matches uninsured Maine residents with local primary care physicians,

specialists, and hospitals that are willing to provide free care and helps patients access free or low-cost

drugs through prescription assistance programs.

● Impact: Program has helped to reduce emergency department visits, hospitalizations, and costs among

participants to levels that are well below the average for Medicaid patients.

MinuteClinic, MN (1772)

● Intervention: Walk-in primary care clinics are located within retail stores. Staffed by nurse practitioners

and physician assistants, clinics use electronic health records and decision-support tools to provide lowNational Healthcare Disparities Report, 2010 26
lowest percentage of positive response. This observation was consistent across hospitals, even after

controlling for teaching status, ownership, size, and geographic region.

● HIT: Currently, less than half of office-based providers have fully implemented e-prescribing.

Physicians practicing in urban areas, the western United States, and larger groups had the highest

adoption rates, as did younger physicians. Among hospitals, size, location, ownership, and teaching

status were shown to be determinants of the adoption of e-prescribing. Larger hospitals, hospitals in

urban areas, government-owned hospitals, and hospitals that were members of the Council of Teaching

Hospitals (COTH) had higher rates of adoption.

● Workforce: Previous reports have examined the physician and nursing workforce; this year, the focus is

on pharmacists. The pharmacy workforce is distributed in proportion to population across all four

regions of the United States. In contrast, relative to population, Hispanics and non-Hispanic Blacks are

underrepresented in the pharmacy workforce while non-Hispanic Whites and Asians are

overrepresented.

Successful Strategies From AHRQ Health Care Innovations Exchange

HealthSpring, TN (2080)

● Intervention: Program offers financial bonuses to selected medical practices, onsite practice

coordinators, and dedicated disease management support. Bonuses equal to 20% of health plan

payments are awarded if physicians meet clinical care improvement goals.

National Healthcare Disparities Report, 2010 27
● Palliative and End-of-Life Care: Quality generally high; more problems with access to palliative care.

● Patient and Family Engagement: Quality generally high; most measures improving.

● Population Health: Most measures improving slowly; healthy lifestyles not improving.

● Safety: Most measures improving but more slowly than other hospital measures.

● Access: Not improving.

● Care Coordination, Overuse, Health System Infrastructure: Measures and data are limited; more

information is needed to assess performance.

● Disparities: Present in all national priorities with little evidence of improvement.

Conclusion

Improving quality and reducing disparities require measurement and reporting, but these are not the ultimate

goals. The fundamental purpose of improvement in health care is to make all patients’ and families’ lives

better. The NHQR and NHDR concentrate on tracking 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. 

It makes a difference in people’s lives when breast cancer is diagnosed early; when a patient suffering from a

heart attack is given 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.

National Healthcare Disparities Report, 2010 28
National Healthcare Disparities Report, 2010 29
National Healthcare Disparities Report, 2010 30
With support from a Department of Health and Human Services (HHS) Interagency Work Group and

AHRQ’s National Advisory Council, AHRQ has designed and produced the NHQR and NHDR since 2003.

This is the eighth in the series of reports. Over the years, the NHQR and NHDR have introduced refinements

to the measure set and methodology, which has led to a focus on a subset of the most important and

scientifically supported measures. These are referred to as the core measure set and are again the focus of the

reports this year. 

Refinements include the addition in 2004 of a second critical goal of the report series: tracking the Nation’s

quality improvement progress. The 2005 reports introduced a set of core measures and a variety of new

composite measures. The 2006 reports continued to improve data, measures, and methods, adding databases

and measures and refining methods for quantifying and tracking changes in health care. The 2007 reports

launched a new chapter on health care efficiency. The 2008 reports included an expanded chapter on patient

safety, while the 2009 reports included new sections on lifestyle modification, healthcare-associated

infection, and care coordination.

From the beginning, the Institute of Medicine (IOM) has helped shape these reports. Early planning for the

first NHQR benefited from the IOM reports Crossing the Quality Chasm and To Err Is Human. Similarly,

early planning for the first NHDR profited from the extensive literature review included in the IOM report

Unequal Treatment. Moreover, before the publication of the first reports, AHRQ specifically requested that

the IOM assist the Agency in meeting its congressionally mandated charge. The IOM was tasked with 

i 42 U.S.C. 299b-2(b)(2).

ii 42 U.S.C. 299a-1(a)6).

National Healthcare Disparities Report, 2010 31
g 

The 2010 reports begin the process of incorporating suggestions from the IOM about how to maximize the

utility of the reports and related products. AHRQ received recommendations from the IOM in April 2010.

These recommendations guided the redesign of the 2010 NHQR and NHDR and are reflected throughout

these reports. Some of the key recommendations from the IOM Committee are discussed below. 

Identify Priority Areas for Quality Improvement

The IOM recommended that AHRQ report on progress in selected priority areas. These priority areas are

expected to yield the greatest gains in health care quality. Priorities include six areas identified by the

National Priorities Partnership (NPP),v as well as two areas proposed by the IOM Committee. Measures

selected for reporting reflect concepts captured in the priority areas, as listed below:

Priority areas designated by the NPP

● Patient and family engagement

● Population health

iii The committee’s report is available at: www.ahrq.gov/research/iomqrdrreport.

iv In addition to guidance specific to the reports, the IOM provided recommendations about standardizing collection and

coding of data on race, ethnicity, and language in the report Race, Ethnicity, and Language Data. We continue to seek

opportunities to show data in the reports on disparities related to granular ethnicity and language preference, but such health

care data are rare.

v The NPP is a partnership of public and private health care stakeholders who have come together to establish priorities and

goals to eliminate harm to patients, eliminate health care disparities, and reduce disease burden and health system waste.

More information on the National Priorities Partnership is available at: www.nationalprioritiespartnership.org/Partners.aspx.

National Healthcare Disparities Report, 2010 32
throughout both existing reports. Hence, performance on population health measures is not included as a

separate chapter in this report. As appropriate, population health performance measures are reported in

relevant chapters. For example, the population measure “adults with obesity who ever received advice from a

health provider to exercise” is reported in Chapter 2, “Effectiveness,” in the Lifestyle Modification section.

The concept of population health is also presented as an important focus of the Highlights. 

Adopt Updated Quality Framework

Measures selected for inclusion in the NHQR and NHDR examine performance in each of the priority areas

listed above and are organized along the elements of a quality framework developed by the IOM Committee.

The framework guiding the 2009 NHQR was focused around five dimensions of quality: (1) effectiveness,

(2) patient safety, (3) timeliness, (4) patient/family centeredness, and (5) efficiency. The 2010 reports retain

these quality dimensions and, in keeping with the suggestions offered by the IOM, introduce three others:

access, care coordination, and health system infrastructure. 

National Healthcare Disparities Report, 2010 33
Source: Ulmer C, Bruno M, Burke S, eds. Future directions for the National Healthcare Quality and Disparities Reports. Committee on

Future Directions of the National Healthcare Quality and Disparities Reports, Institute of Medicine. Washington, DC: National

Academies Press; 2010. 

The revised quality framework posits that care coordination and health system infrastructure are foundational

components that must be in place to achieve quality objectives in each of the other quality areas. Measures

corresponding to elements of this quality framework are further described below in the section titled

“Measure Set for NHQR and NHDR.” 

Use Subnational Data

National data to assess performance and the presence of disparities in health care are unavailable for several

key measures of quality. In many cases, these data are simply not being collected. The IOM recommends the

use of subnational data (e.g., State-level data) to construct performance measures when national data are

unavailable. For example, national data on the quality of care rendered to people with HIV/AIDS are

generally unavailable. Data from the HIV Research Network, which represents 18 medical practices across

the United States treating more than 14,000 patients with HIV/AIDS, were used in both the NHQR and

NHDR to gather information on the care received by this population. Although not nationally representative,

the data provide some insight into the care received by people with HIV/AIDS and may serve as a catalyst to

expanded data collection at the national level.

National Healthcare Disparities Report, 2010 34
available to estimate performance for each State, the 10% criterion was used only when data for a minimum

of 30 States were reported.

Create Action-Oriented Products

The NHQR and NHDR and related products should guide or support action. These reports may be made

more actionable by including priority areas and benchmarks. Including examples of “best practices” would

further emphasize the opportunities available to improve quality and reduce disparities. 

Track Access Better

The NHDR has traditionally included a chapter on access to care, identifying the facilitators and barriers to

care and health care utilization experiences of subgroups defined by race and ethnicity, income, education,

and type of health insurance. Pursuant to the IOM’s recommendations, a chapter on access to care, which

has not been specifically tracked in the NHQR, has been added to the 2010 NHQR. 

How This Report Is Organized

NHQR and NHDR chapters are organized along the elements of the quality framework. Several of the

proposed priority areas that are reflected in this framework have been monitored in previous quality and

disparities reports; however, labels and organization of measures within chapters slightly differed. Measures

that reflect the concepts underlying the newly defined priority list have been carried over to the 2010 reports 

National Healthcare Disparities Report, 2010 35
2010 report is organized around eight clinical areas: cancer, diabetes, end stage renal disease (ESRD),

heart disease, HIV and AIDS, maternal and child health, mental health and substance abuse, and

respiratory diseases. Three types of health care services that typically cut across clinical conditions are

also examined: lifestyle modification, functional status preservation and rehabilitation, and supportive

and palliative care. 

● Chapter 3: Patient Safety tracks measures of safety, including healthcare-associated infections,

postoperative and other hospital complications, and preventable hospital deaths. 

● Chapter 4: Timeliness examines the delivery of time-sensitive clinical care and patient perceptions of

how quickly they receive care.

● Chapter 5: Patient Centeredness examines patients’ experiences with care in an office or clinic

setting, as well as during a hospital stay. Measures reported in this chapter focus on perceptions of

communication with providers and satisfaction with the physician-patient relationship. 

● Chapter 10: Priority Populations continues to be unique to the NHDR. This chapter summarizes quality

and disparities in care for populations identified as particularly significant to quality improvement efforts:

• Racial and ethnic minorities.

• Low-income groups.

• Women.

• Children.

• Older adults.

• Residents of rural areas and inner cities.

• Individuals with disabilities or special health care needs.

National Healthcare Disparities Report, 2010 36
efficiency, which capture information on how well the health care system promotes quality, affordable

care, and appropriate use of services, have typically been reported in the NHQR but not the NHDR. 

For the first time, the 2010 NHDR includes a chapter focusing on efficiency measures. These measures

capture information on overuse, underuse, and misuse of health care among population subgroups.

Efficiency measures reported in the 2010 NHDR are:

• Rates of potentially avoidable hospitalizations.

• Hospitalizations for conditions covered in AHRQ’s Prevention Quality Indicators (PQIs).

• Potentially avoidable hospitalizations among home health and nursing home patients.

• Unnecessary services and costs, as measured by the percentage of males over age 75 who had a

prostate-specific antigen test or a digital rectal exam within the previous year.

● Chapter 8: Health Systems Infrastructure, which explores the capacity of health care systems to

support high-quality care, is new to both reports. The IOM recommended including health system

infrastructure as a priority area because measuring performance in terms of health care infrastructure

capacity can “[i]mprove the foundation of health care systems (including infrastructure for data and

quality improvement; communication across settings for coordination of care; and workforce capacity

and distribution...to support high-quality care.” 

National Healthcare Disparities Report, 2010 37
Appendixes are available online for both the NHQR and NHDR at www.ahrq.gov/qual/qrdr10.htm. These

appendixes include: 

● Data Sources, which provides information about each database analyzed for the reports, including data

type, sample design, and primary content.

● Measure Specifications, which provides information about how measures are generated and analyzed

for the reports. Measures highlighted in the report are described, as well as other measures that were

examined but not included in the text of the report.

● Detailed Methods, which provides detailed methodological and statistical information about selected

databases analyzed for the reports.

● Data Tables, which contains detailed data tables for most measures analyzed for the reports, including

measures highlighted in the report text and measures examined but not included in the text. A few

measures cannot support detailed tables and are not included in the appendix.

Theme of 2010 Reports

This year’s focus on health care performance in rural and inner-city areas required the identification of a

standardized approach to identifying communities by level of urbanization. With input from the Interagency

Work Group, AHRQ selected the National Center for Health Statistics (NCHS) Urban-Rural Classification

Scheme to guide analyses involving geographic location. The 2006 NCHS classification system is derived

from data gathered from three sources: the OMB metropolitan and nonmetropolitan designations, the RuralUrban Continuum and Urban Influence coding systems, and the U.S. Census. NCHS includes six

urbanization categories, including four metropolitan and two nonmetropolitan county designations.

Definitions of metropolitan and nonmetropolitan designations are shown in Table 1.1.

National Healthcare Disparities Report, 2010 38
p

Large fringe metropolitan Counties in a metropolitan statistical area of 1 million or more population 

that do not qualify as large central

Medium metropolitan Counties in a metropolitan statistical area of 250,000 to 999,999 population

Small metropolitan Counties in a metropolitan statistical area of 50,000 to 249,999 population

Nonmetropolitan

Micropolitan Counties with urban population of 20,000 to 49,999, adjacent to metro area 

Noncore Counties that are neither metropolitan nor micropolitan

Source: Ingram D, Franco S. 2006 Rural-Urban Classification Scheme for Counties. Centers for Disease Control and Prevention,

NCHS, 2006. Available at www.cdc.gov/nchs/data_access/urban_rural.htm. 

Table 1.2. NSDUH data classification and modified classification for metropolitan and nonmetropolitan

communities

NSDUH Rural/Urban Classification Modified NSDUH Classification for NHQR and NHDR

Metropolitan

Large metropolitan Large central and fringe metropolitan

Small metropolitan 250K-1,000,000 Medium metropolitan

Small metropolitan <250K Small metropolitan

Nonmetropolitan

Urbanized = 20,000 or more Excluded from analyses

Less urbanized = 2,500-20,000 Excluded from analyses

Completely rural = 2,500 or less Excluded from analyses

National Healthcare Disparities Report, 2010 39
The NHQR and NHDR track a broad array of health care measures and have added measures each year. The

2010 reports continue to focus on a consistent subset of measures, the “core” measures, which includes the

most important and scientifically supported measures in the full measure set. In 2005, the Interagency Work

Group selected the core measures from the full measure set. For most core measures, findings are presented

each year. A subset of the core measure group is presented on an alternating basis, typically rotating across

odd or even years of the report. All alternating core measures are included in trend analyses. “Noncore”

measures are included in summary statistics and may be presented to complement core measures in key areas. 

Examples of alternating measures include the set of measures focusing on breast cancer and colorectal

cancer. While measures are annually tracked, breast cancer measures are presented in odd calendar years;

these measures were contained in the 2009 reports. Colorectal cancer measures are also tracked annually, but

results are presented in even calendar years, such as in the 2010 quality and disparities reports.

Composite Measures

Policymakers and others have voiced their support for composite measures of quality because they can be

used to facilitate understanding of information from many different measures. A composite measure

summarizes care that is represented by individual measures that are often related in some way, such as

components of care for a particular disease or illness. Composite measures are composed of two or more

processvi or outcomevii measures that have been recommended or identified as a “best practice” in the 

vi “Receipt of three recommended diabetes services” is one example of a composite process measure. This composite was

formed by combining information on adults with diabetes who received the following clinical preventive services:

hemoglobin A1c measurement, a dilated eye exam, and a foot exam. 

vii “Adults with ambulatory visits who reported poor communication with health providers” is an example of a composite

outcome measure. This composite was formed by combining information on patient perceptions of their providers, including

the extent to which the provider listened to the patient, respect shown by the provider, time spent with the patient, and

explanations offered by providers.

National Healthcare Disparities Report, 2010 40
The composite measure of recommended hospital care for heart failure is an example of the use of the

opportunities model. The total number of patients who receive treatments represented by individual

components of the composite measure (e.g., evaluation of left ventricular ejection fraction and use of

angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) among patients with

left ventricular systolic dysfunction) is divided by the sum of all of the opportunities to receive appropriate

care.

The CAHPS® (Consumer Assessment of Healthcare Providers and Systems) surveys have their own method

for computing composite measures that has been in use for many years. These composite measures average

individual components of patient experiences of care and are presented as the proportion of respondents who

indicate that providers sometimes or never, usually, or always performed well.

Composite measures that relate to rates of complications of hospital care are postoperative complications and

complications of central venous catheters. For these complication rate composites, an additive model is used

that sums individual complication rates. Thus, for these composites, the numerator is the sum of individual

complications and the denominator is the number of patients at risk for these complications. The composite

rates are presented as the overall rate of complications. The postoperative complications composite is a good

example of this type of composite measure: if 50 patients had a total of 15 complications among them

(regardless of their distribution), the composite score would be 30%.

National Healthcare Disparities Report, 2010 41
In addition, detecting health problems at an early stage increases the chances of effectively treating

them, often reducing suffering and costs. Many of the preventive measures tracked in the reports come

from the U.S. Preventive Services Task Force and the Centers for Disease Control and Prevention

Advisory Committee on Immunization Practices.

● Treatment. Even when preventive care is ideally implemented, it cannot entirely avert the need for

acute care. Delivering optimal treatment for acute illness can help reduce the effects of illness and

promote the best recovery possible.

● Management. Some diseases, such as diabetes and ESRD, are chronic, which means they cannot

simply be treated once; they must be managed across a lifetime. Management of chronic disease often

involves lifestyle changes and regular contact with a provider to monitor the status of the disease. For

patients, effective management of chronic disease can mean the difference between healthy living and

frequent medical problems.

A list of core measures included in the 2010 NHQR and NHDR is shown in Table 1.3 at the end of this

chapter. Measures are identified according to the priorities addressed, dimension or type of care, and focus

on structure (access), process (prevention, acute care, chronic care), or outcome of care. The table also notes

whether a measure is a composite measure. 

Analyses

In the NHQR, measures are tracked for different groups, such as age, gender, and geographic location. In the

NHDR, comparisons are made across groups defined by race, ethnicity, income, education, activity

limitations, and geographic location. In general, either the largest subgroup or the best performing subgroup 

National Healthcare Disparities Report, 2010 42
For all measures for which reliable trend data are available, analyses are conducted to assess the annual rate

of change. The 2010 reports use regression analysis to estimate average annual rate of change. Regression

models were specified as follows:

ln(M) = β0 +β1(Y), where

ln(M) = natural logarithm of the measure value (M)

β0 = intercept or constant

β1(Y) = coefficient corresponding to year (Y)

Using regression results, the average annual rate of change was calculated as 100 x (exp(β1) – 1).

Data in the NHQR/NHDR are unavailable at the person level and aggregated estimates are used throughout

analyses. The regression-estimated annual rate of change was reported only when at least three data points—

or 3 years of aggregated data—were available for a measure. 

For inclusion as either improving or getting worse, the average annual rate of change must be at least 1% per

year when the measure is framed positively as a favorable outcome or negatively as an adverse outcome.

Progress on individual measures is reported as follows: 

● Progress on a measure is deemed to be improving or getting better if the annual rate of change is 1% or

greater, in the desirable direction.

● Progress on a measure is deemed to be getting worse when the annual rate of change is 1% or greater,

in the undesirable direction.

● Progress has remained the same if the annual rate of change is ≤1% in either the desirable or

undesirable direction.

National Healthcare Disparities Report, 2010 43
● Change in quality and access over time, by type of service (preventive care, acute care, chronic disease

management) and outcomes.

This process is more complicated because data on all measures are not collected each year. In the summary

trend analyses, we obtain all available data points between the year 2000 and the current data year for each

measure. For most measures, trends include data points from 2001/2002 to 2007/2008. Composite measures

are included in the core measure category. To avoid duplication of estimates within the other categories,

composite measures are not included in other categories where estimates from their component measures are

used. For example, the diabetes composite measure (which includes hemoglobin A1c measurement, eye exam,

and foot exam) contributes to the overall rate for the core measures group but not to the diabetes group rate,

which uses the estimates from the three noncore component measures.

Using the analytic approach previously described, we calculated the sum of measures that were identified as

better, worse, or the same (when considering subgroup differences) or that were improving, worsening, or

remaining the same over time (when considering trend data). The distribution of measures by subpopulation,

type of service, or type of measure (i.e., quality or access) are presented as a way to summarize the status of

health care quality and disparities in the United States.

Standardization of language to describe differences in the value of a measure across time and subgroups is

part of the effort by HHS and AHRQ to provide information on where the Nation is—and is not—making

progress in reducing disparities in health care. Furthermore, as detailed below, the use of benchmarks, or

“best known level of attained performance,” provides an additional way to monitor progress. It also offers an

approach to measuring disparities by projecting the amount of time that would be needed for selected groups

to achieve the benchmarks.

National Healthcare Disparities Report, 2010 44
National Health Interview Survey (NHIS). For these measures of colorectal cancer screening, diabetes care,

and pneumococcal vaccination, almost identical data were available from Behavioral Risk Factor

Surveillance Survey (BRFSS) State data. However, BRFSS sampling and mode of administration differ from

MEPS and NHIS. Hence, to calculate a benchmark for these measures, we first calculated the ratio of the

top 10% achievable benchmark to the overall national estimate from BRFSS. We then applied this ratio to

the overall national estimates from MEPS or NHIS. For example, if the BRFSS benchmark to national

estimate for a measure was 1.5, we would multiply the national estimate for that measure from MEPS by 1.5

to obtain a corresponding benchmark.

Time To Achieve Benchmark

Also new to the 2010 reports are projections of the time expected for population subgroups to achieve the

designated benchmark, based on past performance. Using standard linear regression of the actual values over

time and extrapolating to future years, we calculated the time required for the population, or population

subgroup, to perform at the level of the top-performing States. Since projections of future performance were

based on past performance data, it was necessary to ensure reliability by limiting estimates to those cases in

which at least three data points were available. 

An important caveat to consider in using information on time to achieve benchmarks is that the linear

estimation approach used to derive these estimates assumes that characteristics of the population, technology,

and health care infrastructure remain constant. Changes in the characteristics of the population or health care

system may be expected to alter achievement of benchmarks. Advancements in medical science, changes in

the organization of health services, or reductions in the uninsured population following implementation of

the Patient Protection and Affordable Care Act (P.L. 11-148) would be expected to alter the performance

trajectory. In some cases, the time to achieve the benchmark will drop, while in other cases it may increase. 

National Healthcare Disparities Report, 2010 45
example, much less information is available for income groups than for racial and ethnic groups. Rates

relative to standard reference groups are used to quantify the magnitude of disparities and to identify the

largest disparities specific groups face. For each group, the group rate was divided by the reference group

rate to calculate the relative rate for each core measure, with each core measure framed negatively (e.g., for

immunization, the likelihood of not receiving the vaccine). Relative rates of selected core measures are

presented in the Highlights chapter of the reports.

Presentation of Reports

As in past reports, the NHQR and its companion NHDR continue to be formatted as chartbooks. Each

chapter begins with a description of the importance of the topic. After introductory text, charts and

accompanying findings highlight a small number of measures relevant to the topic. Where applicable, key

findings from the NHDR are included in the NHQR, and NHQR findings are reported in the text of the

NHDR. Readers should refer to the report from which results have been drawn to gather additional details

on the data presented. 

Unless otherwise stated, only those findings that meet the “meaningfulness criteria,” as previously described,

are presented in the bullets that accompany each figure. When these data are available and relevant, the

NHQR charts show contrasts by:

● Age.viii

● Gender. 

● Insurance status.

● Geographic location (rural versus urban). 

viii Unless otherwise specified, the NHQR and NHDR define children as individuals under the age of 18; adults include people

age 18 and over. 

National Healthcare Disparities Report, 2010 46
National Healthcare Disparities Report, 2010 47

Defining Individuals With Disabilities

For the purpose of the NHDR, people with disabilities are those with physical, sensory, and/or mental health

conditions who also have an associated decrease in functioning in such day-to-day activities as bathing,

walking, doing everyday chores, and/or engaging in work or social activities. This is consistent with the

Americans With Disabilities Act (ADA) of 1990,xii which defines disability to include “a physical or mental

impairment that substantially limits one or more major life activities of such individual” as well as with

Federal program definitions based on the ADA.

In displaying the 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 constraints encountered when people, in interaction with

their environment, attempt to participate in community life.

ix Asian includes the former category of Asian or Pacific Islander prior to Office of Management and Budget guidelines, when

information was not collected separately by group.

x Not all data sources used in the NHDR collect information by race and ethnicity separately. In such cases, comparisons are

made by combining racial/ethnic group categories (e.g., comparing non-Hispanic Blacks and Hispanics with non-Hispanic

Whites.)

xi Unless otherwise indicated, throughout this report, poor is defined as having family income less than 100% of the Federal

poverty level (FPL); near poor refers to incomes between 100% and 200% of the FPL; middle income refers to incomes

between 200% and 400% of the FPL, and high income includes incomes 400% or more of the FPL. These are based on U.S.

Census poverty thresholds for each data year, which are used for statistical purposes.

xii 42 U.S.C. 12102.
Diabetes

Hospital admissions for lower ✓

extremity amputations per 1,000 

adult patients with diagnosed 

diabetes

Adults age 40 and over with ✓ ✓

diagnosed diabetes who received 

all three recommended services 

for diabetes in the calendar year 

(hemoglobin A1c measurement, 

dilated eye examination, and foot 

examination)

End Stage Renal Disease

Adult hemodialysis patients with ✓ ✓

adequate dialysis (urea reduction 

ratio 65% or greater)

Dialysis patients under age 70 ✓

who were registered on a waiting 

list for transplantation

xiii Cancer measures alternate by year. Data on colorectal cancer are presented in “even year” reports, and data on breast

cancer are presented in “odd year” reports.

National Healthcare Disparities Report, 2010 48
population age 13 and over

Maternal and Child Health

Women who completed a pregnancy✓

in the last 12 months who first 

received prenatal care in the first 

trimester*

Children ages 19-35 months who ✓✓

received all recommended vaccines

Children ages 3-6 who ever had ✓

their vision checked by a health 

provider (alternating measure)

Children ages 2-17 for whom a ✓

health provider ever gave advice 

about the amount and kind of 

exercise, sports, or physically active 

hobbies they should have

Children ages 2-17 for whom a✓

health provider ever gave advice 

about healthy eating

Infant deaths per 1,000 live births, ✓

birth weight less than 1,500 g*

*No new data

National Healthcare Disparities Report, 2010 49
are now taking preventive medicine 

daily or almost daily (either oral 

or inhaler)

Hospital patients with pneumonia ✓✓

who received recommended hospital

care (initial antibiotics within 6 hours 

of hospital arrival; antibiotics 

consistent with current 

recommendations; blood culture 

before antibiotics are administered; 

influenza vaccination status 

assessment/vaccine provision; and 

pneumococcal vaccination status 

assessment/vaccine provision

Patients with tuberculosis who ✓✓

completed a curative course of 

treatment within 1 year of initiation 

of treatment

National Healthcare Disparities Report, 2010 50
activities increased

Supportive and Palliative Care

Adult home health care patients ✓ ✓

with shortness of breath

High-risk long-stay nursing home ✓ ✓

residents with pressure sores

Short-stay nursing home residents ✓ ✓

with pressure sores

Long-stay nursing home residents ✓

with physical restraints

Patient Safety

Adult surgery patients who received ✓✓

appropriate timing of antibiotics 

(prophylactic antibiotics begun at 

the right time and ended at the 

right time)

Adults age 65 and over who ✓✓

received potentially inappropriate 

prescription medications

Adult surgery patients with ✓

postoperative complications

National Healthcare Disparities Report, 2010 51
Children with ambulatory visits ✓ ✓

whose parents reported poor 

communication with health providers

Adults with ambulatory visits who ✓ ✓

reported poor communication with 

health providers

Access

People under age 65 with health ✓

insurance

People under age 65 who were ✓

uninsured all year

People with a usual primary care ✓

provider

People without a usual source of ✓

care who indicated a financial or 

insurance reason for not having 

a source of care

People with a specific source of ✓

ongoing care

People who were unable to get or ✓✓

delayed in getting needed medical 

care, dental care, or prescription 

medicines in the last 12 months

National Healthcare Disparities Report, 2010 52
Caring for healthy people is an important component of health care. Educating people about health and

promoting healthy behaviors can help postpone or prevent illness and disease. In addition, detecting health

problems at an early stage increases the chances of effectively treating them, often reducing suffering and costs.

Treatment

Even when preventive care is ideally implemented, it cannot entirely avert the need for acute care. Delivering

optimal treatments for acute illness can help reduce the consequences of illness and promote the best

recovery possible. 

Management

Some diseases, such as diabetes and end stage renal disease, are chronic, which means they cannot simply be

treated once; they must be managed over time. Management of chronic disease often involves promotion and

maintenance of lifestyle changes and regular contact with a provider to monitor the status of the disease. For

patients, effective management of chronic diseases can mean the difference between normal, healthy living

and frequent medical problems. 

Outcomes

Many factors other than health care influence health outcomes, including a person’s genes, lifestyle, and

social and physical environment. However, for many individuals, appropriate preventive services, timely

treatment of acute illness and injury, and meticulous management of chronic disease can positively affect

mortality, morbidity, and quality of life.

National Healthcare Disparities Report, 2010 53
Total costi (2010 est.).......................................................................................................................$263.8 billion4

Direct costsii (2010 est.)...................................................................................................................$102.8 billion4

Indirect costs (2010 est.)..................................................................................................................$161.0 billion4

Cost-effectivenessiii of colorectal cancer screening.....................................................$35,000-$165,000/QALY5

Measures

Evidence-based consensus defining good quality care and how to measure it currently exists for only a few

cancers and a few aspects of care. Breast and colorectal cancers have high incidence rates and are highlighted

in alternate years of the report. The 2009 National Healthcare Disparities Report (NHDR) highlighted breast

cancer; this year’s focus is on colorectal cancer. The core report measures are:

● Colorectal cancer screening.

● Colorectal cancer first diagnosed at advanced stage.

i Throughout this report, total cost equals cost of medical care (direct cost) and economic costs of morbidity and mortality

(indirect cost).

ii Direct costs are defined as “personal health care expenditures for hospital and nursing home care, drugs, home care, and

physician and other professional services.” 

iii Cost-effectiveness is measured here by the average net cost of each quality-adjusted life year (QALY) that is saved by the

provision of a particular health intervention. QALYs are a measure of survival adjusted for its value: 1 year in perfect health is

equal to 1.0 QALY, while a year in poor health would be something less than 1.0. A lower cost per QALY saved indicates a

greater degree of cost-effectiveness. 

National Healthcare Disparities Report, 2010 54
National Healthcare Disparities Report, 2010 55
● In all 4 years, the percentage of non-Hispanic Whites who ever received colorectal cancer screening

was significantly higher than that of Hispanics.

● In all 4 years, the percentage of high-income individuals who ever received colorectal cancer screening

was significantly higher than the percentage of poor, low-income, and middle-income individuals.

● The top 5 State achievable benchmark was 67.1%.iv At the current annual rate of increase of

approximately 1.5%, the benchmark could be achieved overall in 4.6 years. 

● Whites could reach the benchmark in 4.3 years while Blacks and Asians could reach the benchmark in

about 10 years. Non-Hispanic Whites could reach the benchmark in 2.7 years but Hispanics would not

reach the benchmark for 25 years.

● Middle-income adults could reach the benchmark in about 7 years and low-income adults in

approximately 8 years. High-income adults have already achieved the benchmark. There is no

indication that poor adults are progressing toward the benchmark. 

Also, in the National Healthcare Quality Report (NHQR):

● In all available data years, the percentage of adults age 50 and over residing in large fringe metropolitan

areas who ever received colorectal cancer screening was significantly higher than it was for adults

residing in large central metropolitan and noncore areas.

Racial and ethnic minorities, as well as people with low incomes, have disproportionate rates of individuals

with public insurance or no insurance. To distinguish the effects of race, ethnicity, and income on cancer

screening, this measure is stratified by insurance status.

iv The top 5 States contributing to the achievable benchmark are Delaware, Maine, Maryland, Massachusetts, and New

Hampshire.

National Healthcare Disparities Report, 2010 56
Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health Interview Survey

(NHIS), 2000, 2003, 2005, and 2008.

Denominator: Adults ages 50-64 in the civilian noninstitutionalized

population.

National Healthcare Disparities Report, 2010 57

Source:

Center for Health Statistics, National Health Interview Survey

(NHIS), 2000, 2003, 2005, and 2008.

Denominator:

population.

Source:

(NHIS), 2000, 2003, 2005, and 2008.

Denominator:

population.
Differences in rates may vary across racial and ethnic groups due to differences in underlying prevalence of

colorectal cancer. 

National Healthcare Disparities Report, 2010 58
Key: API = Asian or Pacific Islander; AI/AN = American Indian or Alaska Native.

Source: National Cancer Institute, Surveillance, Epidemiology, and End Results Program (SEER), 2000-2007.

Denominator: Adults age 50 and over in the civilian noninstitutionalized population.

Note: Advanced stage colorectal cancer is defined as local stage with tumor size greater than 2 cm diameter, regional stage, or

distant stage. Data are SEER 2000-2007 limited-use database, 17 registries, released April 2010, based on the November 2009

submission. The 2005 data were adjusted for areas impacted by Hurricanes Katrina and Rita. 

● From 2000 to 2007, the rate of advanced stage colorectal cancer was significantly lower for Asians and

Pacific Islanders (APIs) and American Indians and Alaska Natives (AI/ANs) than for Whites (Figure

2.3).

● From 2000 to 2007, Blacks had significantly higher rates of colorectal cancer diagnosed at advanced

stage compared with Whites. During the same period, Hispanics had significantly lower rates of

advanced stage colorectal cancer compared with non-Hispanic Whites.

Also, in the NHQR:

● From 2000 to 2007, the rate of advanced stage colorectal cancer in adults ages 50-64 significantly

decreased, from 45.7 to 40.1 per 100,000 population. 

● During the same period, adults age 65 and over also saw a significant decrease, from 154.2 to 119.2 per

100,000 population. 

● In all years, adults age 65 and over had significantly higher rates of advanced stage colorectal cancer

than adults ages 50-64. 

National Healthcare Disparities Report, 2010 59
Key: AI/AN = American Indian or Alaska Native.

Source: Commission on Cancer, American College of Surgeons and American Cancer Society, National Cancer Data Base, 2003-

2007.

Denominator: U.S. population age 50 and over.

● The overall percentage of adults diagnosed with colorectal cancer who received recommended care

significantly increased from 51.7% in 2003 to 77.0% in 2007 (data not shown). Similar improvement

was observed among all racial and ethnic groups during this period (Figure 2.4).

Also, in the NHQR:

● From 2003 to 2007, the percentage of colorectal cancer patients who received recommended care

significantly increased in all residence locations. The percentage of large metropolitan colorectal cancer

patients who received recommended care was significantly higher in all years than that of micropolitan

patients and noncore patients. 

National Healthcare Disparities Report, 2010 60
New cases (age 20 and over, 2007)......................................................................................................1.6 million7

Cost

Total cost (2007 est.)...........................................................................................................................$174 billion7

Direct medical costs (2007 est.) .........................................................................................................$116 billion7

Measures

Routine monitoring of blood glucose levels with hemoglobin A1c (HbA1c)v tests and dilated eye and foot

examinations have been shown to help prevent or mitigate complications of diabetes, such as diabetic

neuropathy, retinopathy, and vascular and kidney disease.8 With more than half a million discharges in 2006,

diabetes is one of the leading causes of hospitalization in the United States.9 However, with appropriate and

timely ambulatory care, it may be possible to prevent many hospitalizations for diabetes and related

complications. 

The core measure reported in this section examines the extent to which individuals with diabetes receive care

needed to prevent complications or slow the disease’s progression:

● Receipt of three recommended diabetes services. 

v HbA1c, or glycosylated hemoglobin, is a measure of average levels of glucose in the blood.

National Healthcare Disparities Report, 2010 61
Figure 2.5. Composite measure: Adults age 40 and over with diagnosed diabetes who received three

recommended services for diabetes in the calendar year (hemoglobin A1c test, dilated eye examination,

and foot examination), by race, ethnicity, family income, and education, 2002-2007

vi More information on the PQIs is available at: www.qualityindicators.ahrq.gov/downloads/pqi/word/pqi_guide_v31.doc.

National Healthcare Disparities Report, 2010 62
Benchmark is derived from the Behavioral Risk Factor Surveillance System (BRFSS); see Introduction and Methods for details.

● Between 2002 and 2007, Blacks showed a significant decrease in the percentage of adults diagnosed

with diabetes who received recommended care (42.8% to 31.7%; Figure 2.5).

● With the exception of 2003, when results were not statistically significant, across all years, the

percentage of adults with diabetes who received recommended services was significantly lower for

Hispanics than for non-Hispanic Whites. 

● An association was noted between income and receipt of diabetes services. Relative to those with a high

income, the percentage of adults with diabetes who received all recommended services was

significantly lower among poor, near-poor, and middle-income individuals. Among near-poor

individuals, this finding was observed in all years; among middle-income people, lower percentages

were found except in 2003 and 2006. 

● In all years, the percentage of adults age 40 and over with diabetes who received three recommended

services was significantly lower for people with less than a high school education compared with adults

with at least some college education.

● In 2007, 74.2% of high-income adults diagnosed with diabetes had their feet examined in the calendar

year compared with only 62.1% of near-poor adults. Between 2002 and 2007, the percentage of nearpoor individuals who had their feet examined in the calendar year significantly decreased from 73.4%

to 62.1% (data not shown). 

● Between 2002 and 2007, Hispanic, poor, and near-poor adults diagnosed with diabetes all had

significant decreases in the percentage of adults who received HbA1c measurement in the calendar year

(data not shown).

National Healthcare Disparities Report, 2010 63
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, pooled 2002-2007.

Note: Adjusted percentages are predicted marginals from a statistical model that includes the covariates race/ethnicity, family income,

education, health insurance, and residence location. Chapter 1, Introduction and Methods, provides more information.

vii The top 4 States contributing to the achievable benchmark are Alaska, New Hampshire, Vermont, and the District of

Columbia.

National Healthcare Disparities Report, 2010 64
hyperosmolar nonketotic coma (HNC), lactic acidosis (LA), and hypoglycemia.

Patients with DKA, HNC,

and LA require hospitalization for treatment, which results in the use of significant health care resources with

increased health care costs. Patients with hypoglycemia often do not require hospitalization but can still incur

costs for treatment in an ambulatory setting, as well as loss of productivity. Prevention is an important

component in reducing health care costs for these disorders10 and helping people with diabetes maintain

optimal function. 

National Healthcare Disparities Report, 2010 65
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases (SID)

disparities analysis file, 2004-2007.

Denominator: U.S. resident population age 18 and over.

Note: Short-term complications include ketoacidosis, hyperosmolarity, or coma and exclude obstetric admissions and transfers from

other institutions. White, Black, and API are non-Hispanic. Data are adjusted for age, gender, and diagnosis-related group clusters. 

● In all years, the rate of hospital admissions for short-term complications was significantly higher for

Blacks than for Whites. Blacks had an admission rate more than three times the rate of Whites in all

years (Figure 2.7).

● With the exception of 2007, Hispanics had significantly higher rates of hospital admissions for shortterm complications compared with Whites.

● In all years, the rate of hospital admissions for short-term complications was significantly higher for

adults living in communities with median household incomes in the first quartile than for people living

in communities with median household incomes in the fourth quartile. In all years, the rates of

admission were about 2.5 times as high for adults living in communities with median household

incomes in the first quartile compared with adults living in communities with median household

incomes in the fourth quartile.

● The 2007 top 4 State achievable benchmark was 37.8 per 100,000 population.viii At the current annual

rate of increase of 1.7, there is no overall progress toward the benchmark. 

● Adults living in communities with a median income in the fourth quartile and APIs have already

achieved the benchmark. Whites, Blacks, Hispanics, and adults living in communities with median

incomes in the first, second, and third quartiles indicate no progress toward the benchmark.

viii The top 4 States contributing to the achievable benchmark are Hawaii, Nebraska, Utah, and Vermont.

National Healthcare Disparities Report, 2010 66
ix Blood pressure control guidelines were updated in 2005. Previously, having a blood pressure reading of <140/90 mm Hg

was considered under control. For this measure, the new threshold of <140/80 mm Hg has been applied to historic data for the

sake of consistency and comparability.

National Healthcare Disparities Report, 2010 67
, pg

level under control (Figure 2.8). This figure is significantly higher than for Mexican Americans; only

43.9% had their HbA1c under control. Comparing these results to those for 2001-2004 shows a similar

pattern. Almost 60% of non-Hispanic Whites with diabetes had their HbA1c under control compared

with only 36.8% of Mexican Americans. 

● In 2001-2004, 47.7% of non-Hispanic Whites had their cholesterol at optimal levels compared with

51.9% of Mexican Americans. In 2005-2008, the percentage of non-Hispanic Whites who had their

cholesterol at optimal levels had increased to 69.3% and the percentage of Mexican Americans with

optimal control had increased to only 56.5%, significantly less than non-Hispanic Whites.

● In 2001-2004, 63.6% of non-Hispanic Whites had their blood pressure under optimal control, which

was significantly higher than the percentage of non-Hispanic Blacks (47.8%). However, in 2005-2008,

the percentage of non-Hispanic Whites who had their blood pressure under optimal control had

decreased to 57.1% and the percentage of non-Hispanic Blacks with optimal control had increased to

58.2%. There was no statistically significant difference between the two groups.

Also, in the NHQR:

● In 2005-2008, only 54.1% of adults age 40 and over with diabetes had achieved control of their HbA1c

level, 65.2% had control over their cholesterol level, and 58.6% had their blood pressure under control.

Although the percentage of adults with controlled HbA1c and blood pressure does not differ markedly

from that in the 2001-2004 period, a significant increase in the percentage who had their cholesterol

levels under control was observed over time, from 48.5% in 2001-2004 to 65.2% in 2005-2008.

National Healthcare Disparities Report, 2010 68
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Discharge Survey and

National Health Interview Survey.

Denominator: Civilian noninstitutionalized population 18 years and over who report they have ever been told they have diabetes.

Note: Data are age adjusted to the 2000 standard population using three age groups: 0-64, 65-74, and 75 and over.

● From 1999-2001 to 2005-2007, Whites, males, and females all had significant decreases in the

hospitalization rate for lower extremity amputation (Figure 2.9).

● In 2002-2004 and 2005-2007, Blacks had significantly higher rates of hospitalization for lower

extremity amputation compared with Whites. 

● In all years, males had significantly higher rates of admission, about twice the rate of females. 

Also, in the NHQR:

● In all years, adults ages 18-44 had significantly lower rates of hospital admission for lower extremity

amputation than the overall population and adults ages 45 and over. The rate of admission for adults age

65 and over was twice the rate of adults ages 18-44 in all years. 

National Healthcare Disparities Report, 2010 69
x Of potentially eligible AI/ANs, 74% sought health care in 2004 at an IHS or tribally contracted facility, according to IHS

estimates published by the Office of Public Health Support, Division of Program Statistics.

National Healthcare Disparities Report, 2010 70
Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: Indian Health Service (IHS), Tribal, and contract hospitals:IHS, Office of Information Technology/National Patient Information

Reporting System, National Data Warehouse, Workload and Population Data Mart; community hospitals: Agency for Healthcare

Research and Quality, Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) disparities analysis file, 2004-

2007.

Note: White, Black, and API are non-Hispanic populations. Data are adjusted for age and gender. The HCUP SID disparities analysis

file is designed to provide national estimates using weighted records from a sample of hospitals from 25 States that have 66% of the

U.S. resident population. 

● From 2004 to 2007, the age-adjusted rate of total hospitalizations for uncontrolled diabetes significantly

decreased for AI/AN patients in IHS, Tribal, and contract hospitals (from 31.4 per 100,000 to 23.8 per

100,000; Figure 2.10).

● For all years, White patients in community hospitals had significantly fewer admissions for

uncontrolled diabetes compared with AI/AN patients in IHS hospitals. Compared with AI/AN patients

in IHS hospitals, Blacks had significantly more admissions in all years and Hispanics had significantly

more admissions in 3 of 4 years.

National Healthcare Disparities Report, 2010 71
Measures

The NHDR tracks several measures of ESRD management to assess the quality of care provided to renal

dialysis patients. The two core report measures and one noncore measure highlighted here are:

● Adequacy of hemodialysis (core).

● Registration for transplantation (core).

● Use of arteriovenous fistula (AVF) at first outpatient dialysis (supporting).

Findings

Outcome: Adequate Hemodialysis

Dialysis removes harmful waste and excess fluid buildup in the blood that occurs when kidneys fail to

function. Hemodialysis is the most common method used to treat advanced and permanent kidney failure.

The adequacy of dialysis is measured by the percentage of hemodialysis patients with a urea reduction ratio

equal to or greater than 65%; this measure indicates how well urea, a waste product, is eliminated by the

dialysis machine.

National Healthcare Disparities Report, 2010 72
Key: AI/AN = American Indian or Alaska Native.

Source: University of Michigan Kidney Epidemiology and Cost Center, 2009 Dialysis Facility Report.

Denominator: End stage renal disease hemodialysis patients age 20 and over.

● In 2008, the overall percentage of adult hemodialysis patients receiving adequate dialysis was 95.8%

(data not shown). 

● The percentage of Asian and AI/AN adult hemodialysis patients receiving adequate dialysis was higher

than for Whites (97.8% and 96.7%, respectively, compared with 95.9%; Figure 2.11).

● In 2008, the top 5 State achievable benchmark was 98.1%.xi The available data were not sufficient to

calculate time to benchmark.

Also, in the NHQR:

● In 2008, the percentage of male adult hemodialysis patients receiving adequate dialysis was lower than

that of females. 

● The percentage of adult hemodialysis patients receiving adequate dialysis was lower for those age 65

years and over than for those ages 20 to 64 years.

xi The top 5 States contributing to the achievable benchmark are Colorado, Connecticut, Hawaii, Rhode Island, and Texas.

National Healthcare Disparities Report, 2010 73
Key: AI/AN = American Indian or Alaska Native.

Source: National Institute of Diabetes and Digestive and Kidney Diseases, U.S. Renal Data System, 2000-2006.

Denominator: End stage renal disease hemodialysis patients and peritoneal dialysis patients under age 70.

● From 2000 to 2006, the percentage of dialysis patients who were registered on a waiting list for

transplantation increased from 14.5% to 17.1% (data not shown). Improvements were observed among

all racial and ethnic groups (Figure 2.12).

● In 2006, Blacks and AI/ANs were less likely to be registered on a waiting list than Whites (13.1% and

11.9%, respectively, compared with 18.6%). However, Asians (30.6%) were more likely to be registered

on a waiting list than Whites. 

National Healthcare Disparities Report, 2010 74
Although there is consensus that AVF should be the primary method of vascular access, incidence rates of

AVF have historically been very low. Therefore, the Centers for Medicare & Medicaid Services (CMS) has

sought to increase rates of AVF for primary access across the country by forming a nationwide initiative and

collaborative effort to increase overall use of AVF. In 2005, this effort, called the Fistula First Breakthrough

Initiative, set the goal for national prevalence at 66%.

xii The top 5 States contributing to the achievable benchmark are California, Minnesota, New Hampshire, Pennsylvania, and

South Dakota.

National Healthcare Disparities Report, 2010 75
Key: AI/AN = American Indian or Alaska Native; NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Medicare eligibility forms (Centers for Medicare & Medicaid Services [CMS] Form 2728) (2008-2009), Fistula First Incident AVF

Dataset, CMS.

Denominator: New end stage renal disease hemodialysis patients.

● From 2008 to 2009, the percentage of dialysis patients who used an AVF at first dialysis improved from

13.7% to 14.3% (data not shown). 

● In 2009, a higher percentage of Asians than Whites used AVF at first dialysis, but a lower percentage of

Blacks than Whites used AVF at first dialysis (17.6%, 14.7%, and 13.1%, respectively; Figure 2.13).

● Also in 2009, Hispanics had lower rates of AVF at first dialysis than non-Hispanic Whites (11.6%

compared with 14.8%).

● The 2009 top 5 State achievable benchmark was 26.7%.xiii

Also, in the NHQR:

● In 2009, female dialysis patients had substantially lower rates of AVF at first dialysis than males. 

xiii The top 5 States contributing to the achievable benchmark are Hawaii, Maine, Montana, New Hampshire, and Oregon.

National Healthcare Disparities Report, 2010 76
Number of new cases of heart failure (2004).........................................................................................550,00018

Cost

Total cost of cardiovascular disease (2010 est.).............................................................................$503.2 billion4

Total cost of heart failure (2010 est.) ..............................................................................................$39.2 billion17

Direct costs of cardiovascular disease (2010 est.) .........................................................................$324.1 billion4

Cost-effectiveness of hypertension screening ...............................................................$14,000-$35,000/QALY5

Measures

The NHDR tracks several quality measures for preventing and treating heart disease, including the following

three core report measures:

● Receipt of angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) for

heart attack. 

● Inpatient deaths following heart attack. 

● Receipt of recommended care for heart failure.

Several measures related to heart disease are also presented in other chapters of this report. Timeliness of

cardiac reperfusion for heart attack patients is tracked in Chapter 4, Timeliness, and receipt of complete

written discharge instructions by patients with heart failure is tracked in Chapter 6, Care Coordination.

National Healthcare Disparities Report, 2010 77
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2005-2008.

Denominator: Patients hospitalized with a principal diagnosis of acute myocardial infarction and left ventricular systolic dysfunction.

National Healthcare Disparities Report, 2010 78
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2004-2007. 

Denominator: Adults age 18 and over admitted to a non-Federal community hospital in the United States with acute myocardial

infarction as principal discharge diagnosis.

Note: White, Black, and Asian groups are non-Hispanic. Rates are adjusted by age, gender, age-gender interactions, and all payer

refined-diagnosis related group scoring of risk of mortality. 

xiv The top 5 States contributing to the achievable benchmark are Alaska, Minnesota, New Hampshire, North Dakota, and

Oregon.

National Healthcare Disparities Report, 2010 79
Treatment: Receipt of Recommended Care for Heart Failure

The NHDR tracks the national percentages of receipt of the following services (found in the Data Tables

appendix):

● Recommended test for heart functioning (heart failure patients having evaluation of left ventricular

ejection fraction). 

● Recommended medication treatment (patients with left ventricular systolic dysfunction prescribed ACE

inhibitor or ARB at discharge).

In addition, an overall composite measure describes the percentage of all episodes in which heart failure

patients receive recommended care.

xv The top 4 States contributing to the achievable benchmark are Arizona, Florida, Maryland, and Michigan.

National Healthcare Disparities Report, 2010 80
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2005-2008. 

Denominator: Patients hospitalized with a principal diagnosis of acute heart failure.

● From 2005 to 2008, the overall percentage of patients with heart failure who received recommended

care improved from 87.7% to 95% (Figure 2.16). In addition, the percentage of Asian patients who

received recommended care for heart failure improved (from 86.6% to 96.6%).

● The 2008 top 5 State achievable benchmark for patients with heart failure who received recommended

hospital care was 97.2%.xvi At the current rate of improvement, Whites, Blacks, Asians, and nonHispanic Whites could attain the achievable benchmark in less than a year.

● Although the other racial and ethnic groups could attain the benchmark in less than 1 year, AI/ANs and

Hispanics could not attain the benchmark until later (about 3 years and about 1.5 years, respectively).

Also, in the NHQR:

● The percentage of patients with heart failure who received recommended care improved for those age

85 years and over.

● At their current rates of improvement, all age and gender groups could attain the achievable benchmark

in about 1 year. 

xvi The top 5 States contributing to the achievable benchmark are Connecticut, Maine, New Hampshire, New Jersey, and South

Carolina.

National Healthcare Disparities Report, 2010 81
HIV is a virus that kills or damages cells of the body’s immune system. AIDS is the most advanced stage of

HIV infection. HIV is spread through unprotected sex with an infected person and by sharing drug needles or

through contact with the blood of an infected person. In addition, women with HIV can give it to their babies

during pregnancy, childbirth, or breastfeeding.

The impact of HIV infection and AIDS is disproportionately higher for racial and ethnic minorities and

people of lower income and education levels. Although access to care has improved, research shows that

Blacks, Hispanics, women, and uninsured people with HIV remain less likely to have access to care and less

likely to have optimal patterns of care.21

According to the Centers for Disease Control and Prevention, HIV and AIDS disproportionately affect

African Americans in the United States. In 2008, African Americans accounted for 52% of all diagnoses of

HIV infection and had a rate of 73.7 per 100,000 population compared with 8.2 per 100,000 for Whites.22

The spread of HIV is linked to complex social and economic factors, including poverty, concentration of the

virus in specific geographic areas and smaller sexual networks, sexually transmitted co-infections, stigma

(negative attitudes, beliefs, and actions directed at people living with HIV/AIDS or directed at people who

engage in behaviors that might put them at risk for HIV), and injection and noninjection drug use and

associated behaviors.23

The HIV/AIDS epidemic is also a serious threat to the Hispanic community. Hispanics accounted for 15% of

the population but had an estimated 17% of the new HIV infections in 2006, which was 2.5 times the rate of

Whites.24 In addition to being seriously affected by HIV, Hispanics continue to face challenges in accessing

health care, especially preventive services, and HIV treatment. 

National Healthcare Disparities Report, 2010 82
● Adult HIV patients who received two or more CD4 tests during the year.

● Adult HIV patients who received highly active antiretroviral therapy (HAART).

Findings

Management: HIV Patients Receiving Care

Management of chronic HIV disease includes outpatient and inpatient services. Without adequate treatment,

as HIV disease progresses, CD4 cell counts fall and patients become increasingly susceptible to opportunistic

infections.

HIV/AIDS core clinical performance measures are indicators for use in monitoring the quality of care

provided to adults and adolescents living with HIV. Based on the set of quality measures developed by the

HIV/AIDS Bureau of the Health Resources and Services Administration (HRSA), performance can be

measured for various HIV prevention and treatment services. Services indicated for patients with HIV include: 

1. Two or more CD4 cell counts performed in the measurement year.

2. HAART for patients with AIDS.

3. Two or more medical visits in an HIV care setting in the measurement year.28

4. PCP prophylaxis for patients with CD4 cell count below 200.

National Healthcare Disparities Report, 2010 83
Key: HAART = highly active antiretroviral therapy; PCP = Pneumocystis pneumonia; MAC = Mycobacterium avium complex.

Source: Agency for Healthcare Research and Quality, HIV Research Network, 2007.

Note: For HAART measure, adult HIV patients had to be enrolled in an HIV network clinic and receive at least one CD4 test and have

at least one outpatient visit in addition to having at least one CD4 test result of 350 or less. 

● Overall, in 2007, Black patients with HIV were less likely than White patients to receive the minimum

care for HIV, except in the receipt of MAC and PCP prophylaxis (Figure 2.17).

● In 2007, female patients with HIV were more likely to have had two or more outpatient visits than male

patients but were less likely to receive HAART and MAC prophylaxis.

● There were no statistically significant differences in other recommended care.

National Healthcare Disparities Report, 2010 84

HAART = highly active antiretroviral therapy; PCP = Pneumocystis pneumonia; MAC = Mycobacterium avium complex.
National Healthcare Disparities Report, 2010 85
● From 1999 to 2007, HIV infection death rates improved for all groups. The HIV infection death rate

decreased for Blacks (from 23.6 per 100,000 population to 17.3 per 100,000 population) but remains

significantly higher than the rate for Whites (which decreased from 2.9 per 100,000 population to 1.9;

Figure 2.18). 

● From 1999 to 2007, the HIV infection death rate decreased for Hispanics (from 6.9 per 100,000 to 4.1

per 100,000) but remains more than twice as high as the rate for non-Hispanic Whites (which decreased

from 2.3 per 100,000 population to 1.5). 

● In 2007, the HIV infection death rate for males was more than twice that of females (5.4 per 100,000

population compared with 2.1).

Also, in the NHQR:

● From 1999 to 2007, the rate of HIV infection deaths decreased for adults ages 45-64 but was still

highest among all age groups.

● In 2007, the rates of HIV infection deaths were highest for residents in large central metropolitan areas

and lowest in noncore areas.

National Healthcare Disparities Report, 2010 86
g ,Q

Cost-effectiveness of childhood immunization seriesxviii....................................................................Cost saving5

Measures

The NHQR and NHDR track several prevention and treatment measures related to maternal and child health

care. The core report measures highlighted in this section are:

● Receipt of recommended immunizations by young children. 

● Vision checks for children. 

● Counseling of children or parents about physical activity.

● Counseling of children or parents about healthy eating.

In addition, two supporting measures are presented:

● Obstetric trauma.

● Weight monitoring of overweight children.

xvii In this report, children are defined as individuals under age 18.

xviii The childhood immunization series includes vaccinations for diphtheria-tetanus-pertussis, measles-mumps-rubella,

inactivated polio virus, Haemophilus influenzae type B, hepatitis B, and varicella. “Cost saving” indicates that childhood

immunizations are one of very few services that save more money than they cost.

National Healthcare Disparities Report, 2010 87
Key: API = Asian or Pacific Islander; Q = Quartile; Q1 indicates the lowest area income quartile while Q4 indicates the highest area

income quartile.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, State Inpatient Databases disparities

analysis file, 2001-2007, and Nationwide Inpatient Sample, 2004-2007. 

Denominator: All patients hospitalized for vaginal delivery without indication of instrument assistance.

Note: Rates are adjusted by age and comorbidities.

● Declines were observed among all racial/ethnic and area income groups (Figure 2.19).

● In all years, Blacks and Hispanics had lower rates than Whites and residents of the lower two area

income quartiles had lower rates than residents of the highest area income quartile. 

● In all years, APIs had higher rates than Whites.

National Healthcare Disparities Report, 2010 88
vaccine or vaccines added to the recommended schedule after 1998.

Figure 2.20. Children ages 19-35 months who received the 4:3:1:3:3 vaccine series, by race, ethnicity,

and household income, 2000-2008 

xix The top 3 States contributing to the achievable benchmark are Massachusetts, Utah, and Wyoming.

National Healthcare Disparities Report, 2010 89
was significant for Whites, Blacks, Asians, Hispanics, and all income groups. The fall between 2004

and 2008 was only significant for Whites and the two higher income groups.

● In almost all years, Black children were less likely than White children and poor, low-income, and

middle-income children were less likely than high-income children to receive the 4:3:1:3:3 vaccine

series. 

● From 2002 to 2006, Hispanic children were less likely than non-Hispanic White children to receive

these vaccines. In 2007, rates were comparable, and in 2008, Hispanic children had achieved the higher

rate.

● The 2008 top 5 State achievable benchmark was 84%.xx All racial, ethnic, and income groups are

moving away from the benchmark.

Also, in the NHQR:

● From 2000 to 2004, the percentage of children ages 19-35 months who received the 4:3:1:3:3 vaccine

series increased. From 2004 to 2008, the percentage of children with these vaccines fell. 

● Since 2004, the overall rate and rates for boys and girls have been moving away from the achievable

benchmark.

xx The top 5 States contributing to the achievable benchmark are Louisiana, Massachusetts, New Hampshire, Tennessee, and

Wisconsin.

National Healthcare Disparities Report, 2010 90
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2007. 

Denominator: U.S. civilian noninstitutionalized population ages 3-6.

● From 2002 to 2007, significant improvements were observed among non-Hispanic Whites and Blacks

and among residents of poor and middle-income neighborhoods (Figure 2.21).

● Hispanic children tended to be less likely to receive vision checks than non-Hispanic White children,

but this was statistically significant in only 3 of 6 years.

● Poor, low-income, and middle-income children tended to be less likely to receive vision checks than

high-income children, but again this was statistically significant in only about half of the years.

Also, in the NHQR:

● From 2002 to 2007, the percentage of children ages 3-6 who ever had their vision checked by a health

provider increased.

● Children in large central metropolitan areas tended to be less likely to receive vision checks. 

● Children with special health care needs tended to be more likely to receive vision checks.

National Healthcare Disparities Report, 2010 91
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health and Nutrition Examination

Survey, 2001-2004 and 2005-2008. 

Denominator: U.S. civilian noninstitutionalized population ages 2-19 who were overweight.

Note: Overweight children are identified using age- and sex-specific reference data from the 2000 Centers for Disease Control and

Prevention body mass index (BMI) for age growth charts. Children with BMI values at or above the 95th percentile of the sex-specific

BMI growth charts are categorized as overweight. 

● Between the two time periods, only non-Hispanic Blacks ages 2-19 who were overweight experienced

an increase in being told by a health provider they were overweight (Figure 2.22). 

● In 2005-2008, overweight non-Hispanic Blacks were more likely than overweight non-Hispanic Whites

to report being told by a health provider that they were overweight.

xxi For children ages 2-15, a parent or guardian reported this information.

National Healthcare Disparities Report, 2010 92
National Healthcare Disparities Report, 2010 93
● Significant improvements were observed among Whites, Hispanics, all income groups, and all

insurance groups (Figure 2.23).

● In all years, poor, low-income, and middle-income children were less likely than high-income children

and uninsured children were less likely than privately insured children to receive advice about exercise.

Also, in the NHQR:

● From 2002 to 2007, the percentage of children for whom a health provider ever gave advice about the

amount and kind of exercise, sports, or physically active hobbies they should have improved.

● In all years, children in micropolitan and noncore areas were less likely than children in large fringe

metropolitan areas and children with special health care needs were more likely than children without

such needs to receive advice about exercise.

Prevention: Counseling for Children About Healthy Eating

Physicians play an important role in encouraging children’s healthy eating. Overweight and obesity during

childhood often persist into adulthood, with consequences that are numerous and costly. Unfortunately,

overweight and obesity among children under age 18 have risen dramatically in the past two decades.38 The

American Academy of Pediatrics recommends that pediatricians discuss and promote healthy diets with all

children and their parents or guardians, both those who are overweight and those who are not.38

National Healthcare Disparities Report, 2010 94
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2007.

Denominator: U.S. civilian noninstitutionalized population ages 2-17.

National Healthcare Disparities Report, 2010 95
National Healthcare Disparities Report, 2010 96
past year (2008).....................................................................................................................14.3 million (6.4%)41

Adults with at least one major depressive episode in their lifetime (2006).....................30.4 million (13.9%)42

Cost

National expenditures for treatment of mental health and substance abuse

disorders (2003 est.) ..........................................................................................................................$121 billion43

Cost-effectiveness of screening and brief counseling for problem drinking.........................$0-$14,000/QALY5

Measures 

The NHDR and NHQR track measures of the quality of treatment for major depression and substance abuse.

Mental health treatment includes counseling, inpatient care, outpatient care, and prescription medications.

This section highlights three core measures of mental health and substance abuse treatment:

● Receipt of treatment for depression.

● Suicide deaths.

● Receipt of needed treatment for illicit drug use or alcohol problem. 

In addition, one supporting measure is discussed:

● Completion of substance abuse treatment.

National Healthcare Disparities Report, 2010 97
health insurance benefits for mental health care. Lack of coverage often occurs because small employers and

individual purchasers dominate the rural health insurance marketplace. Therefore, insurance policies are

more likely to have limited or no mental health coverage. 

For racial and ethnic populations in rural areas, these problems are compounded by the lack of culturally and

linguistically competent providers. And as of September 2009, the number of federally designated mental

health professional shortage areas reached 3,291.47

Findings

Treatment: Receipt of Treatment for Depression

It has been estimated that about 1 out of 7 individuals in the United States will have a major depressive

episode in their lifetime.42 Treatment can be very effective in reducing symptoms and associated illnesses and

returning individuals to a productive lifestyle. 

xxii The Office for Civil Rights (OCR) (http://www.hhs.gov/ocr/) is the sole HHS agency with the authority to enforce Title VI

of the Civil Rights Act of 1964, 42 U.S.C. 2000d, which prohibits discrimination based on race, color, or national origin in

programs and activities that receive Federal financial assistance, including most health care providers and human service

agencies. Individuals and advocacy groups may file complaints with OCR to remedy such discrimination.

National Healthcare Disparities Report, 2010 98
Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2008.

Denominator: U.S. population age 18 and over who had a major depressive episode in the last 12 months.

Note: Major depressive episode is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of

interest or pleasure in daily activities and had a majority of the symptoms of depression described in the fourth edition of the

Diagnostic and Statistical Manual of Mental Disorders. Treatment for depression is defined as seeing or talking to a medical doctor or

other professional or using prescription medication in the past year for depression. 

National Healthcare Disparities Report, 2010 99

Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2008.
Figure 2.26. Suicide deaths per 100,000 population, by race and ethnicity, 19992007

Key: API = Asian and Pacific Islander; AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System—Mortality.

Denominator: Civilian noninstitutionalized population.

Note: Estimates are age adjusted to the 2000 standard population. 

National Healthcare Disparities Report, 2010 100
increases the risk of death from car crashes and other injuries.61 Treatment for illicit drug use or an alcohol

problem at a specialty facility is an effective way to reduce the chances of future illicit drug use or alcohol

problems.

xxiii Illicit drugs included in this measure are marijuana/hashish, cocaine (including crack), inhalants (e.g., inhalation of various

substances other than for intended use, such as toluene), hallucinogens, heroin, and prescription-type psychotherapeutic drugs

(nonmedical use).

National Healthcare Disparities Report, 2010 101
Key: API = Asian or Pacific Islander; AI/AN = American Indian or Alaska Native.

Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2003-2008.

Denominator: Civilian noninstitutionalized population age 12 and over who needed treatment for illicit drug use or an alcohol problem

in the last 12 months.

Note: Treatment refers to treatment at a specialty facility, such as a drug and alcohol inpatient and/or outpatient rehabilitation facility,

inpatient hospital setting, or a mental health center. Data not statiscally reliable for all races in all years.

National Healthcare Disparities Report, 2010 102
last 12 months.

National Healthcare Disparities Report, 2010 103
Source: Substance Abuse and Mental Health Services Administration, Treatment Episode Data Set, Discharge Data Set, 2005-2007.

Denominator: Discharges age 12 and over from publicly funded substance abuse treatment facilities.

● From 2005 to 2007, there were no statistically significant changes in the percentage of people age 12

and over treated for substance abuse who completed the treatment course (data not shown).

● In 2007, non-Hispanic Blacks who were treated for substance abuse were significantly less likely than

non-Hispanic Whites to have completed treatment (41.0% compared with 46.6%; Figure 2.28).

● In 2007, Hispanics who were treated for substance abuse were significantly less likely than nonHispanic Whites to have completed treatment (45.8% compared with 46.6%).

● People with less than a high school education and people with a high school education who were

treated for substance abuse were significantly less likely than people with at least some college to

complete treatment (40.6% and 46.1%, respectively, compared with 50.7%).

Also, in the NHQR:

● In 2007, people ages 12-19 were less likely than those age 20 and over and females were significantly

less likely than males to complete treatment.

National Healthcare Disparities Report, 2010 104
Number of discharges attributable to pneumonia (2007)..................................................................1.2 million66

Incidence

Annual number of pneumonia cases due to Streptococcus pneumoniae ..............................................500,00067

New cases of tuberculosis (2008)..............................................................................................................12,89868

Cost

Total cost of lung diseases (2009 est.)...........................................................................................$177.4 billion69

Direct medical costs of lung diseases (2009 est.).........................................................................$113.6 billion69

Total cost of upper respiratory infections (annual est.) .....................................................................$40 billion70

Total cost of asthma (2007 est.).......................................................................................................$19.7 billion71

Direct medical costs of asthma (2007 est.).....................................................................................$14.7 billion71

Cost-effectiveness of influenza immunization .......................................................................$0-$14,000/QALY5

xxiv Chronic lower respiratory diseases include emphysema and chronic bronchitis.

National Healthcare Disparities Report, 2010 105
ethnicity, and income, 2000-2008 

National Healthcare Disparities Report, 2010 106
● In 2008, the percentage of adults age 65 and over who reported ever having pneumococcal vaccination

was significantly lower for Blacks and Asians than for Whites. 

● In 2008, the percentage of Hispanic adults age 65 and over who reported ever having pneumococcal

vaccination continued to be significantly lower, almost half that of non-Hispanic Whites.

● In 2008, the percentage was significantly lower for poor older adults than for high-income older adults

(46.2% compared with 64.9%).

● The 2008 top 5 State achievable benchmark was 66.4%.xxv At the current 1.2% annual rate of increase,

this benchmark could be attained overall in about 9 years.

● Whites could attain the benchmark in about 6 years, while Blacks and Asians would not attain the

benchmark for 14 years and 25 years, respectively. Hispanics would not attain the benchmark for about

54 years.

Also, in the NHQR:

● From 2000 to 2008, the overall percentage of adults age 65 and over who reported ever having

pneumococcal vaccination increased. 

xxv The top 5 States contributing to the achievable benchmark are Colorado, Delaware, Maine, New Hampshire, and

Oklahoma.

National Healthcare Disparities Report, 2010 107
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Quality Improvement Organization Program, 2008.

Denominator: Patients hospitalized with a principal discharge diagnosis of pneumonia or a principal discharge diagnosis of either

septicemia or respiratory failure and secondary diagnosis of pneumonia.

Note: Composite is calculated by averaging the percentage of opportunities for care in which the patient received all five components

of care. 

● In 2008, the percentage of patients with pneumonia who received recommended hospital care was

significantly lower for Blacks (87.6%; Figure 2.30), Asians (87.6%), AI/ANs (84.8%), and Hispanics

(85.2%) compared with Whites (90.7%). 

National Healthcare Disparities Report, 2010 108

Key: AI/AN = American Indian or Alaska Native.
Key: API = Asian or Pacific Islander.

Source: Centers for Disease Control and Prevention, National Tuberculosis Surveillance System, 1999-2006.

Denominator: Foreign-born U.S. resident population with verified tuberculosis, all ages.

● In 2006, among the foreign-born population, Blacks and APIs were more likely than foreign-born

Whites to complete tuberculosis therapy within 1 year (85.7% and 84.3%, respectively, compared with

81.7%; Figure 2.31).

xxvii The top 5 States contributing to the achievable benchmark are Iowa, Maine, New Hampshire, New Jersey, and Vermont.

National Healthcare Disparities Report, 2010 109

Key: API = Asian or Pacific Islander.
contributing to symptom exacerbation, pharmacotherapy, and education for partnership in care.77

Daily long-term controller medication is necessary to prevent exacerbations and chronic symptoms for all

patients with persistent asthma. Appropriate controller medications for people with mild persistent 

asthma78, xxviii include inhaled corticosteroids, cromolyn, nedocromil, theophylline, and leukotriene

modifiers.79

xxvii The top 5 States contributing to the achievable benchmark are Alaska (tie), Indiana (tie), Kansas, Maryland, and Oregon.

xxviii “Mild persistent asthma” refers to cases in which people experience asthma symptoms more than 2 days per week and

more than 2 nights per month, as well as other clinical indicators.

National Healthcare Disparities Report, 2010 110
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2003-2007. 

Denominator: Noninstitutionalized population with asthma, as defined below.

Note: People with current asthma report they still have asthma or had an asthma attack in the last 12 months. 

National Healthcare Disparities Report, 2010 111
The data show that disparities for Asians exist not only in comparison with Whites but also between Asian

subgroups (Chinese, Filipino, Japanese, Korean, Vietnamese, and South Asian) and across Asian subgroups

by income and insurance status. Differences in English proficiency and place of birth are also significant.

The following section shows only some of the significant disparities for these groups in California from

California Health Interview Survey data. 

National Healthcare Disparities Report, 2010 112
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

Denominator: Civilian noninstitutionalized population in California.

● In California, there were no statistically significant differences by ethnicity in the percentage of people

with current asthma who took prescription medication to control asthma during the past 12 months

(Figure 2.33). This is due to relatively large standard errors for many of the subpopulations.

National Healthcare Disparities Report, 2010 113
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

Denominator: Civilian noninstitutionalized population in California.

Note: Data were not statistically reliable for Whites who did not speak English well or did not speak English at all and for Filipinos who

spoke English only and Filipinos who did not speak English well or did not speak English at all.

● Overall, there were no statistically significant differences in the percentage of people with current

asthma who were taking prescription medication to control asthma during the past 12 months in

California between people who spoke English only and those who spoke English well or very well and

those who did not speak English well or did not speak English at all (data not shown).

● Among people who spoke English only at home in California, Asians were less likely than nonHispanic Whites to take prescription medication to control asthma during the past 12 months (31.2%

compared with 47.2%; Figure 2.34).

● Also, among people who spoke English only at home in California, Hispanics and Mexicans were less

likely than non-Hispanic Whites to take prescription medication to control asthma during the past 12

months (37.7% and 35.2%, respectively, compared with 47.2%).

National Healthcare Disparities Report, 2010 114
Measures

Unhealthy behaviors place many Americans at risk for a variety of diseases. Lifestyle practices account for

more than 40% of the differences in health among individuals.84 A recent study examined the effects on

incidence of coronary heart disease, stroke, diabetes, and cancer of four healthy lifestyles: never smoking,

not being obese, engaging in at least 3.5 hours of physical activity per week, and eating a healthy diet (higher

consumption of fruits, vegetables, and whole grain bread and lower consumption of red meat). Engaging in

one healthy lifestyle compared with none cut the risk of developing these diseases in half while engaging in

all four cut risk by 78%.85 Unfortunately, healthy lifestyle practices have declined over the past two decades.85

Helping patients choose and maintain healthy lifestyles is a critical role of health care professionals. The

NHDR tracks several quality measures for modifying unhealthy lifestyles, including the following three core

report measures:

● Counseling smokers to quit smoking. 

● Counseling obese adults about exercise.

● Counseling obese adults about healthy eating. 

In addition, one supporting measure is presented:

● Counseling obese adults about overweight.

National Healthcare Disparities Report, 2010 115
National Healthcare Disparities Report, 2010 116
● In 2007, only 66.2% of current adult smokers overall who had a checkup in the last 12 months were

advised to quit smoking (data not shown).

● There were no statistically significant differences by race and ethnicity in the percentage of current

adult smokers who received advice to quit smoking (Figure 2.35).

● From 2002 to 2007, there were no statistically significant changes overall and for all groups in the

percentage of current adult smokers with a checkup in the last 12 months who received advice to quit

smoking, except for poor patients (from 57.9% to 67.9%). 

● In 2007, near-poor current adult smokers were significantly less likely than high-income current adult

smokers to receive advice to quit smoking (58.8% compared with 67.8%).

● There were no statistically significant differences in the percentage of current adult smokers with a

checkup in the last 12 months who received advice to quit smoking by language spoken at home.

Also, in the NHQR:

● There were no statistically significant differences between adult current smokers living in metropolitan

areas and those living in nonmetropolitan areas with a checkup in the last 12 months who received

advice to quit smoking. Among metropolitan areas, residents of small metropolitan areas who were

current smokers were least likely to receive advice to quit smoking.

● From 2002 to 2007, female current adult smokers continued to be more likely than males to receive

advice to quit smoking.

National Healthcare Disparities Report, 2010 117
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

Denominator: Civilian noninstitutionalized adult current smokers under age 65 who had a checkup in the last 12 months.

Note: Adjusted percentages are predicted marginals from a statistical model that includes the covariates race/ethnicity, family income,

education, health insurance, and residence location.

● In the multivariate model used, after adjustment, 54.7% of Hispanic adult smokers ages 18-64 received

advice to quit smoking compared with 64.8% of White adults (Figure 2.36).

● After adjustment, male adult smokers ages 18-64 were less likely than females to receive advice to quit

smoking (60.7% compared with 66.5%).

● After adjustment, compared with adult smokers ages 18-64 with any private insurance (65.2%), adults

with public insurance were more likely (70.7%) and adults with no insurance were less likely (52.3%)

to receive advice to quit smoking. 

● After adjustment, adult smokers ages 18-64 who lived in metropolitan areas (64.6%) were more likely

than adults in nonmetropolitan areas (60.5%) to receive advice to quit smoking.

National Healthcare Disparities Report, 2010 118
National Healthcare Disparities Report, 2010 119
professional that they were overweight (data not shown).

● Non-Hispanic Black and Mexican-American obese adults were less likely than non-Hispanic White

obese adults to report being told by a doctor that they were overweight (61.4% and 59.9%, respectively,

compared with 67.2%; Figure 2.37).

● Poor (60.8%), near-poor (61.6%), and middle-income (65.1%) obese adults were less likely than highincome (72.8%) obese adults to report being been told by a doctor that they were overweight.

● Obese adults with less than a high school education (59.7%) and those with a high school education

(65.4%) were less likely than obese adults with at least some college (71.5%) to report being told by a

doctor that they were overweight.

Also, in the NHQR:

● Obese adults ages 45-64 and age 65 and over were more likely than obese adults ages 20-44 to report

being told by a doctor that they were overweight.

● Female obese adults age 20 and over were more likely than males to report being told by a doctor or

health professional that they were overweight.

Prevention: Counseling Obese Adults About Exercise

Physician-based exercise and diet counseling is an important component of effective weight loss

interventions,91 and it has been shown to produce increased levels of physical activity among sedentary

patients.93 Although every obese person may not need counseling about exercise and diet, many would likely

benefit from improvements in these activities. Regular exercise and a healthy diet aid in maintaining normal

blood cholesterol levels, weight, and blood pressure, reducing the risk of heart disease, stroke, diabetes, and

other comorbidities of obesity.

National Healthcare Disparities Report, 2010 120
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population age 18 and over.

Note: Obesity is defined as a body mass index of 30 or higher. 

National Healthcare Disparities Report, 2010 121
Prevention: Counseling Obese Adults About Healthy Eating

Figure 2.39. Adults with obesity who ever received advice from a health provider about eating fewer

high-fat or high-cholesterol foods, by race/ethnicity, income, education, and language spoken at home,

2002-2007 

National Healthcare Disparities Report, 2010 122
Note: Obesity is defined as a body mass index of 30 or higher.

● Overall, in 2007, about 51.6% of adults with obesity received advice from a health provider about

healthy eating. This percentage improved from 2002, when 48.9% said they received this advice (data

not shown).

● From 2002 to 2007, the percentage of non-Hispanic Black adults with obesity who received advice

from a health provider about healthy eating increased (from 45.8% to 51.2%; Figure 2.39). There was

no statistically significant difference for non-Hispanic Whites.

● From 2002 to 2007, the percentage of Hispanic adults with obesity who received advice from a health

provider about healthy eating increased (from 35.6% to 44.6%). In 2007, Hispanics were less likely to

receive this advice than non-Hispanic Whites (44.6% compared with 53.4%).

● In 2007, the percentage of obese adults who received advice about eating fewer high-fat or highcholesterol foods was significantly lower for poor, near-poor, and middle-income adults compared with

high-income adults (45.9%, 46.9%, and 48.3%, respectively, compared with 58.7%).

● In 2007, the percentage of obese adults who were given advice about eating fewer high-fat or highcholesterol foods was significantly lower for people with less than a high school education and people

with a high school education compared with people with at least some college (47.3% and 48.8%,

respectively, compared with 56.1%).

● In 2007, the percentage of adults with obesity who spoke another language at home who received

advice about healthy eating was lower than it was for adults with obesity who spoke English at home

(43.4% compared with 52.4%).

National Healthcare Disparities Report, 2010 123
National Healthcare Disparities Report, 2010 124
at least 3 times a week (data not shown).

● From 2002 to 2007, the percentage of adults with obesity who exercised at least 3 times a week

increased for non-Hispanic Blacks and Hispanics (Figure 2.40). In 2007, Hispanics were less likely than

non-Hispanic Whites to exercise at least 3 times a week.

● In 2007, poor and low-income adults with obesity were less likely than high-income adults to exercise

as least 3 times a week. Obese adults who had less than a high school education were less likely than

adults with at least some college to exercise at least 3 times a week. 

● Obese adults who spoke a language other than English at home were less likely than adults who spoke

English at home to exercise at least 3 times a week (data not shown).

Also, in the NHQR:

● Adults age 65 and over with obesity were least likely of all age groups to exercise at least 3 times a

week.

● Female adults with obesity were less likely than males to exercise at least 3 times a week.

● Among those living in metropolitan areas, adults with obesity in large central metropolitan and small

metropolitan areas were less likely to exercise at least 3 times a week compared with adults with

obesity in large fringe metropolitan areas.

National Healthcare Disparities Report, 2010 125
Medicare payments for outpatient physical therapy (2006 est.).......................................................$3.1 billion96

Medicare payments for outpatient occupational therapy (2006 est.).............................................$747 million96

Medicare payments for outpatient speech-language pathology services (2006 est.)....................$270 million96

Measures

A person’s ability to function can decline with disease or age, but it is not always an inevitable consequence.

Threats to function span a wide variety of medical conditions. Services to maximize function are delivered in

a variety of settings, including providers’ offices, patients’ homes, long-term care facilities, and hospitals.

Some health care interventions can help prevent diseases that commonly cause declines in functional status.

Other interventions, such as physical therapy, occupational therapy, and speech-language pathology services,

can help patients regain function that has been lost or minimize the rate of decline in functioning. 

The NHDR tracks several measures related to functional status preservation and rehabilitation. Three core

report measures are highlighted in this section:

● Osteoporosis screening among older women.

● Improvement in ambulation among home health care patients. 

● Nursing home residents needing more help with daily activities.

xxix ADLs consist of basic self-care tasks, such as bathing, dressing, eating, transferring, using the toilet, and walking.

xxx IADLs consist of tasks needed for a person to live independently, such as shopping, doing housework, preparing meals,

taking medications, using the telephone, and managing money.

National Healthcare Disparities Report, 2010 126

EHABILITATION
National Healthcare Disparities Report, 2010 127

EHABILITATION 
● From 2001 to 2008, the percentage of female Medicare beneficiaries age 65 and over who reported ever

being screened for osteoporosis with a bone mass or bone density measurement increased among all

racial, ethnic, income, and disability groups.

● In all years, the percentage of female Medicare beneficiaries age 65 and over who reported ever being

screened for osteoporosis was significantly lower among Blacks and APIs compared with Whites;

Hispanics compared with non-Hispanic Whites; poor, near-poor, and middle-income beneficiaries

compared with high-income beneficiaries; and beneficiaries with limitations in three or more ADLs

compared with beneficiaries with no functional limitations (Figure 2.41).

Also, in the NHQR:

● From 2001 to 2008, the percentage of female Medicare beneficiaries age 65 and over who reported ever

being screened for osteoporosis with a bone mass or bone density measurement increased overall. 

● Since 2003, the percentage of older female Medicare beneficiaries who reported ever being screened for

osteoporosis was lower among those living in nonmetropolitan areas compared with those living in

metropolitan areas. 

Outcome: Improvement in Ambulation in Home Health Care Patients

After an illness or injury, many patients receiving home health care may need temporary help to walk safely.

This assistance can come from another person or from equipment, such as a cane. Patients who use a

wheelchair may have difficulty moving around safely, but if they can perform this activity with little

assistance, they are more independent, self-confident, and active. 

National Healthcare Disparities Report, 2010 128

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

Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set (OASIS), 2002-2008.

Denominator: Adult nonmaternity patients completing an episode of skilled home health care and not already performing at the

highest level according to the OASIS question on ambulation at the start of the episode.

● From 2002 to 2008, the percentage of home health care patients who got better at walking or moving

around improved for each racial and ethnic group (Figure 2.42). 

● The 2008 top 5 State achievable benchmark was 53.8%.xxxi At the current 5% annual rate of increase,

this benchmark could be attained overall in about 5 years.

● Rates of improvement varied across racial and ethnic groups. Whites could attain the achievable

benchmark in about 4 years. Asians and NHOPIs could attain the benchmark sooner, while Blacks,

AI/ANs, multiple-race individuals, and Hispanics would not attain the benchmark for between 7 and 11

years.

xxxi The top 5 States contributing to the achievable benchmark are District of Columbia, Hawaii, Kansas, South Carolina, and

Utah.

National Healthcare Disparities Report, 2010 129

EHABILITATION 
Key: API = Asian or Pacific Islander; AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Minimum Data Set, 2000-2008. Data are from the third quarter of each calendar

year.

Denominator: All long-stay residents in Medicare or Medicaid certified nursing home facilities.

● Between 2000 and 2008, the percentage increased among Blacks of long-stay nursing home residents

whose need for help with daily activities increased (Figure 2.43).

National Healthcare Disparities Report, 2010 130

EHABILITATION
xxxii The top 5 States contributing to the achievable benchmark are Alabama, Alaska, New Jersey, Oklahoma, and Oregon.

National Healthcare Disparities Report, 2010 131

EHABILITATION 
Disease cannot always be cured, and disability cannot always be reversed. For patients with long-term health

conditions, managing symptoms and preventing complications are important goals. Supportive and palliative

care cuts across many medical conditions and is delivered by many health care providers. Supportive and

palliative care focuses on enhancing patient comfort and quality of life and preventing and relieving

symptoms and complications. Toward the end of life, hospice care provides patients and families with

practical, emotional, and spiritual support to help cope with death and bereavement. Honoring patient values

and preferences for care is also critical.104

The National Priorities Partnership (NPP) identified palliative and end-of-life care as one of six national

priorities.105 The vision is health care “capable of promising dignity, comfort, companionship, and spiritual

support to patients and families facing advanced illness or dying.” Key goals include relief of suffering, help

with emotional and spiritual needs, effective communication about options for care, and high-quality hospice

services. 

The NHDR tracks several measures of supportive and palliative care delivered by home health agencies,

nursing homes, and hospices. The 5 presented supporting measures are organized around the NPP goals: 

● Relief of suffering

• Shortness of breath among home health care patients

• Pressure sores among nursing home residents

xxxiii Medicare FFS patients represent only a portion of all home health patients.

xxxiv Cost estimates for nursing home and home health services include only costs for freestanding skilled nursing facilities,

nursing homes, and home health agencies and not those that are hospital based.

National Healthcare Disparities Report, 2010 132
p, y y, 

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

Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set, 2002-2008.

Denominator: Adult nonmaternity patients completing an episode of skilled home health care.

National Healthcare Disparities Report, 2010 133
for an extended time and can be very painful. Residents should be assessed by nursing home staff for

presence or risk of developing pressure sores. Nursing homes can help to prevent or heal pressure sores by

keeping residents clean and dry and by changing their position frequently or helping them move around.

Other interventions include making sure residents get proper nutrition and using soft padding to reduce

pressure on the skin. However, some residents may get pressure sores even when a nursing home provides

good preventive care.

xxxv The top 5 States contributing to the achievable benchmark are Georgia, Hawaii, New Jersey, Rhode Island, and South

Carolina.

National Healthcare Disparities Report, 2010 134
Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: Centers for Medicare & Medicaid Services, Minimum Data Set, 2000-2008. Data for long-stay residents are from the third

quarter of each calendar year. Data for short-stay residents are full calendar-year estimates.

Denominator: Short-stay and high-risk long-stay nursing home residents in Medicare or Medicaid certified nursing and long-term care

facilities.

Note: White, Black, API, and AI/AN are non-Hispanic groups. 

● In all years, Blacks and Hispanics were more likely than Whites to have pressure sores (Figure 2.45).

● The 2008 top 5 State achievable benchmark for short-stay residents was 12.0%.xxxvi At the current 2%

annual rate of decrease, this benchmark could be attained overall in about 16 years. APIs, AI/ANs, and

Hispanics would take between 18 and 41 years to attain this benchmark.

● The 2008 top 5 State achievable benchmark for high-risk long-stay residents was 7.1%.xxxvii At the

current 2% annual rate of decrease, this benchmark could be attained overall in about 16 years. Blacks,

APIs, AI/ANs, and Hispanics would take between 18 and 25 years to attain this benchmark.

xxxvi The top 5 States contributing to the achievable benchmark are Colorado, Iowa, Minnesota, Nebraska, and Utah.

xxxvii The top 5 States contributing to the achievable benchmark are Hawaii, Minnesota, Nebraska, New Hampshire, and North

Dakota.

National Healthcare Disparities Report, 2010 135
Management: Right Amount of Emotional Support Among Hospice Patients

Dying is stressful. Patients at the end of life may develop depression or anxiety disorders. Health care

systems and providers need to be attuned to recognizing and responding to the emotional and spiritual needs

of patients with life-limiting illness and their families.

xxxviii Short-stay residents stay fewer than 30 days in a nursing home, typically following an acute care hospitalization.

xxxix Long-stay residents enter a nursing facility typically because they are no longer able to care for themselves at home; they

tend to remain in the facility for several months or years. High-risk residents are those who are in a coma, do not get the

nutrients needed to maintain skin health, or cannot change position on their own. 

xl This survey provides unique insight into end-of-life care and captures information about a large percentage of hospice

patients but is limited by nonrandom data collection and a response rate of about 40%. Survey questions were answered by

family members, who might not be fully aware of the patients’ wishes and concerns. These limitations should be considered

when interpreting these findings.

National Healthcare Disparities Report, 2010 136
Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: National Hospice and Palliative Care Organization, Family Evaluation of Hospice Care, 2008-2009.

Denominator: Adult hospice patients.

National Healthcare Disparities Report, 2010 137
to continuing care regardless of patient treatment decisions.

Figure 2.47. Hospice patients age 18 and over whose family caregivers wanted more information about

what to expect while the patient was dying, by race, ethnicity, education, and gender, 2008-2009

xli The top 5 States contributing to the achievable benchmark are Alabama, Alaska, Arkansas, Kansas, and South Carolina.

National Healthcare Disparities Report, 2010 138
● In all years, family caregivers of API and AI/AN hospice patients were more likely than family

caregivers of White patients, family caregivers of Hispanic hospice patients were more likely than

family caregivers of non-Hispanic White patients, and family caregivers of male patients were more

likely than family caregivers of female patients to want more information about dying. Family

caregivers of hospice patients with less than a high school education and high school graduates were

less likely than family caregivers of patients with some college education to want more information

about dying.

● The 2009 top 5 State achievable benchmark was 11.7%.xlii Data are insufficient to assess progress

toward this goal.

Also, in the NHQR: 

● The proportion of hospice patient family caregivers who reported that they wanted more information

about what to expect while the patient was dying was 15% in 2009. 

● In all years, family caregivers of hospice patients ages 18-44 and ages 45-64 were more likely than

family caregivers of patients age 65 and over to want more information about dying.

xlii The top 5 States contributing to the achievable benchmark are Iowa, Kansas, Kentucky, Nebraska, and West Virginia.

National Healthcare Disparities Report, 2010 139
National Healthcare Disparities Report, 2010 140
● The overall proportion of hospice patients whose families reported that they did not receive end-of-life

care consistent with their stated wishes was 5.4% in 2009 (data not shown).

● In both 2008 and 2009, Blacks, APIs, and AI/ANs were less likely than Whites, Hispanics were less

likely than non-Hispanic Whites, and hospice patients with less than a high school education and high

school graduates were less likely than patients with some college education to receive end-of-life care

consistent with their wishes. 

National Healthcare Disparities Report, 2010 141
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National Healthcare Disparities Report, 2010 147
National Healthcare Disparities Report, 2010 148
g()

Measures

The Institute of Medicine (IOM) defines patient safety as “freedom from accidental injury due to medical

care or medical errors.”1 In 1999, the IOM published To Err Is Human: Building a Safer Health System,

which called for a national effort to reduce medical errors and improve patient safety.1 In response to the

IOM’s report, President George W. Bush signed the Patient Safety and Quality Improvement Act of 2005

(Patient Safety Act).i The act was designed to spur the development of voluntary, provider-driven initiatives to

improve the quality, safety, and outcomes of patient care. The Patient Safety Act addresses many of the

current barriers to improving patient care. 

Central to this effort is the ability to measure and track adverse events. Measuring patient safety is

complicated by difficulties in assessing and ensuring the systematic reporting of medical errors and adverse

events. All too often, adverse event reporting systems are laborious and cumbersome. Health care providers

may also fear that if they participate in the analysis of medical errors or patient care processes, the findings

may be used against them in court or harm their professional reputations. Many factors limit the ability to

aggregate data in sufficient numbers to rapidly identify prevalent risks and hazards in the delivery of patient

care, their underlying causes, and practices that are most effective in mitigating them. These include

difficulties aggregating and sharing data confidentially across facilities or State lines. 

In addition, although To Err Is Human does not mention race or ethnicity when discussing the problem of

patient safety, such data are limited. Any differences that suggest patient race and/or ethnicity might influence

i Patient Safety and Quality Improvement Act of 2005, 42 U.S.C. 299b-21 to 299b-26.

National Healthcare Disparities Report, 2010 149
● Reduction of HAIs: 

• Appropriate timing of antibiotics (core measure).

• Postoperative sepsis.

● Reduction of SAEs:

• Ambulatory care visits due to adverse effects of medical care.

• Mechanical adverse events. 

• Postoperative respiratory failure. 

● Preventable and premature mortality rates: 

• Deaths following complications of care (core measure).

● 30-day mortality rates:

• Pneumonia mortality rates.

Findings

Healthcare-Associated Infections

Infections acquired during hospital care (nosocomial infections) are one of the most serious patient safety

concerns. They are the most common complication of hospital care.10 An estimated 1.7 million HAIs occur 

National Healthcare Disparities Report, 2010 150
Key: AI/AN = American Indian or Alaska Native. 

Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2005-2008.

Denominator: Hospitalized patients having surgery.

Note: Populations not specifically noted as Hispanic are non-Hispanic.

National Healthcare Disparities Report, 2010 151

Key: AI/AN = American Indian or Alaska Native. 
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample,

and AHRQ Quality Indicators, version 3.1, 2004-2007. 

Denominator: All elective hospital surgical discharges, age 18 and over, with length of stay of 4 or more days, excluding patients

admitted for infection, patients with cancer or immunocompromised states, patients with obstetric conditions, and admissions

specifically for sepsis.

Note: White, Black, and Asian are non-Hispanic. Rates are adjusted by age, gender, age-gender interactions, comorbidities, and

diagnosis-related group clusters.

ii The top 5 States that contributed to the achievable benchmark are Hawaii, Maine, New Hampshire, South Dakota, and Vermont.

National Healthcare Disparities Report, 2010 152

Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample,
office-based physicians, hospital outpatient departments, and hospital emergency departments. Events treated

in ambulatory settings may be less severe than those occurring in inpatient settings. Some adverse events,

such as known side effects of appropriately prescribed medications, may be unavoidable, while others may be

considered medical errors. Although the following measure does not distinguish between the two types of

events, it provides an overall sense of the burden these events place on the population.

iii The top 4 States that contributed to the achievable benchmark are Arkansas, Massachusetts, Nebraska, and Rhode Island.

National Healthcare Disparities Report, 2010 153
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Ambulatory Medical Care Survey

and National Hospital Ambulatory Medical Care Survey, 2007-2008.

Denominator: U.S. Census Bureau estimated civilian noninstitutionalized population on July 1, 2007, and July 1, 2008.

Note: Ambulatory care includes visits to office-based physicians, hospital outpatient departments, and hospital emergency

departments.

● In 2007-2008, the rate of ambulatory care visits due to adverse effects of medical care was higher for

females compared with males (Figure 3.3).

Also, in the NHQR:

● In 2007-2008, the rates of ambulatory care visits due to adverse effects of medical care were higher for

residents of metropolitan areas compared with residents of nonmetropolitan areas and for all age groups

compared with the group ages 0-17.

Outcome: Mechanical Adverse Events

Sometimes patients need a central venous catheter inserted into a major vein in the neck, chest, or groin to

administer medication or fluids, obtain blood for tests, and take cardiovascular measurements. Patients who

require a central venous catheter tend to be severely ill. The placement and use of these catheters can result in

mechanical adverse events, including bleeding; hematoma; perforation; pneumothorax; air embolism; and

misplacement, occlusion, shearing, or knotting of the catheter.

National Healthcare Disparities Report, 2010 154
Source: Centers for Medicare & Medicaid Services, Medicare Patient Safety Monitoring System (MPSMS), 2005-2007.

Denominator: Adult hospitalized Medicare fee-for-service discharges from the MPSMS sample with central venous catheter

placement.

Note: Mechanical adverse events include allergic reaction to the catheter, tamponade, perforation, pneumothorax, hematoma,

shearing off of the catheter, air embolism, misplaced catheter, thrombosis or embolism, knotting of the pulmonary artery catheter, and

certain other events.

● From 2005 to 2007, there was no statistically significant change overall or for any race or gender for

medical adverse events associated with central venous catheter placement (Figure 3.4). 

Outcome: Postoperative Respiratory Failure

Respiratory failure is not uncommon after surgery and may necessitate reintubation or prolonged mechanical

ventilation. Causes include oversedation, exacerbation of underlying cardiovascular or respiratory conditions,

and ventilator-associated pneumonia. Although some cases of respiratory failure cannot be prevented, close

attention to risk factors can reduce rates.

National Healthcare Disparities Report, 2010 155
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2004-

2007.

Denominator: All elective hospital surgical discharges age 18 and over, excluding patients with respiratory disease, circulatory

disease, neuromuscular disorders, obstetric conditions, and secondary procedure of tracheostomy before or after surgery or as the

only procedure.

Note: White, Blacks, and Asians are non-Hispanic. Rates are adjusted by gender, age-gender interactions, comorbidities, and

diagnosis-related group clusters. 

● In 2007, the rate of postoperative respiratory failure for all other income groups was higher than for the

highest income group (fourth quartile) (Figure 3.5).

Also, in the NHQR:

● In 2007, there were no statistically significant differences in the rate of postoperative respiratory failure

among patients living in different geographic areas.

Preventable and Premature Mortality Rates

Outcome: Deaths Following Complications of Care

Many complications that arise during hospital stays cannot be prevented. However, rapid identification and

aggressive treatment of complications may prevent these complications from leading to death. The indicator

“deaths following complications of care,” also called “failure to rescue,” tracks deaths among patients whose

hospitalizations are complicated by pneumonia, thromboembolic events, sepsis, acute renal failure,

gastrointestinal bleeding or acute ulcer, shock, or cardiac arrest.14

National Healthcare Disparities Report, 2010 156
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2004-2007.

Denominator: Patients ages 18-74 years from U.S. community hospitals whose hospitalizations are complicated by pneumonia,

thromboembolic events, sepsis, acute renal failure, gastrointestinal bleeding or acute ulcer, shock, or cardiac arrest.

Note: Whites, Blacks, and Asians are non-Hispanic. Rates are adjusted by age, gender, comorbidities, and diagnosis-related group

clusters. 

● From 2004 to 2007, the rate of deaths following complications of care declined from 123.9 to 105.7 per

1,000 admissions of adults ages 18-74 (data not shown). A significant decrease was also seen among all

racial, ethnic, and income groups during the same period (Figure 3.6).

● In 2007, Asians had a significantly higher rate of deaths following complications of care compared with

Whites (130.2 per 1,000 compared with 111.3). 

Also, in the NHQR:

● For those who were uninsured, the rates of deaths following complications of care were higher than for

those with private insurance.

30-Day Mortality Rates

One of the goals for measurement specified by the NPP under the Safety priority is to reduce 30-day hospital

mortality rates for conditions such as pneumonia. While national 30-day mortality rates due to pneumonia

are not currently available for reporting, the in-hospital mortality rates per 1,000 hospital admissions with

pneumonia are reported here. About two-thirds of patients who die within 30 days of hospital admission die

inside the hospital, and the correlation between inpatient and 30-day mortality is high.15

National Healthcare Disparities Report, 2010 157

Sou Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2004-2007.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample,

and AHRQ Quality Indicators, version 3.1. 

Denominator: All discharges age 18 and over with principal diagnosis code of pneumonia, excluding patients transferred to another

short-term hospital and obstetric and neonatal admissions.

Note: Whites, Blacks, and Asians are non-Hispanic. Rates are adjusted by age, gender, age-gender interactions, and all patient

refined-diagnosis related group risk of mortality score. 

● From 2004 to 2007, the overall inpatient pneumonia mortality rate decreased from 55.2 per 1,000

admissions to 40.8 (data not shown). A significant decrease was also seen among all racial, ethnic, and

income groups during the same period (Figure 3.7). 

● In 2007, Blacks and Hispanics had a significantly lower inpatient pneumonia mortality rate than Whites

(35.4 and 36.6 per 1,000 hospital admissions, respectively, compared with 41.7). 

● In 2007, the lowest income group had a significantly higher inpatient pneumonia mortality rate than the

highest income group (43.2 per 1,000 hospital admissions compared with 39.1).

● The 2007 top 4 State achievable benchmark was 27.5 per 1,000 hospital admissions.iv At the current rate

of improvement, this benchmark could be attained in less than 3 years. 

● Rates of improvement varied by race and ethnicity. Blacks could attain the benchmark in just over 1.5

years and Hispanics in just over 2 years. Whites and Asians would not attain the benchmark for almost

3 years.

iv The top 4 States that contributed to the achievable benchmark are Arizona, Colorado, Maryland, and Michigan.

National Healthcare Disparities Report, 2010 158

Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample,
Care 2000;38:261-71.

11. Klevens RM, Edwards JR, Richards CL, et al. Estimating health care-associated infections and deaths in U.S. hospitals, 2002.

Public Hlth Rep 2007;122:160-66.

12. Moore LJ, Moore FA, Todd SR, et al. Sepsis in general surgery: the 2005-2007 National Surgical Quality Improvement

Program perspective. Arch Surg Jul;145(7):695-700.

13. Mayr FB, Yende S, Linde-Zwirble WT, et al. Infection rate and acute organ dysfunction risk as explanations for racial

differences in severe sepsis. Jama 2010 Jun 23;303(24):2495-2503.

14. Guide to Patient Safety Indicators version 3.1. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available

at: http://www.qualityindicators.ahrq.gov/downloads/psi/word/psi_guide_v31.doc. Accessed November 17, 2009.

15. Rosenthal GE, Baker DW, Norris DG, et al. Relationships between in-hospital and 30-day standardized hospital mortality:

implications for profiling hospitals. Health Serv Res 2000 Mar;34(7):1449-68.

National Healthcare Disparities Report, 2010 159
National Healthcare Disparities Report, 2010 160
Cost

● Early care for comorbid conditions has been shown to reduce hospitalization rates and costs for

Medicare beneficiaries.9 Some research suggests that, over the course of 30 years, the costs of treating

diabetic complications can approach $50,000 per patient.10 Early care for complications in patients with

diabetes can reduce overall costs of the disease.11

Timely outpatient care also can reduce admissions for pediatric asthma, which account for $1.25 billion in

total hospitalization charges annually.12

Measures

This report focuses on one core report measure related to timeliness of primary, emergency, and hospital

care: getting care for illness or injury as soon as wanted. In addition, two supporting measures are presented:

emergency department waiting times, and timeliness of cardiac reperfusion for heart attack patients.

Findings

Getting Care for Illness or Injury As Soon As Wanted

A patient’s primary care provider should be the first point of contact for most illnesses and injuries. A patient’s

ability to receive timely treatment for illness and injury is a key element in a patient-centered health care system.

National Healthcare Disparities Report, 2010 161
Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population age 18 and

over.

Note: Data were insufficient for this analysis for Native Hawaiians

and Other Pacific Islanders and for American Indians and Alaska

Natives.

● From 2002 to 2007, the overall percentage of adults who needed care right away for an illness, injury,

or condition in the last 12 months who sometimes or never got care as soon as wanted decreased (from

16.8% to 15.3%; data not shown).

● During the same period, the percentages improved for Whites, Hispanics, and high school graduates

(15.8% compared with 14.3%, 24.5% compared with 19.6%, and 15.3% compared with 13.3%,

respectively; Figure 4.1). 

National Healthcare Disparities Report, 2010 162

over.

Source:

Expenditure Panel Survey, 2002-2007.

Denominator:

Note:

and Other Pacific Islanders and for American Indians and Alaska

Natives.

Source:

Expenditure Panel Survey, 2002-2007.

over.

Note:

and Other Pacific Islanders and for American Indians and Alaska

Natives.
Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population under age 18.

Note: The 2007 data for high-income people did not meet criteria

for statistical reliability, data quality, or confidentiality.

National Healthcare Disparities Report, 2010 163

Source:

Expenditure Panel Survey, 2002-2007.

Denominator: 

Note:

for statistical reliability, data quality, or confidentiality.

Expenditure Panel Survey, 2002-2007.

Denominator: 

Note:

for statistical reliability, data quality, or confidentiality.
● Nonurgent, not requiring care within 2 hours.

National Healthcare Disparities Report, 2010 164
Key: NHOPI = Native Hawaiian or Other Pacific Islander; AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Ambulatory Medical Care

Survey (NHAMCS), 2007-2008.

Denominator (Immediate or Emergent): Visits to U.S. emergency departments with triage assessments of immediate or emergent,

2007-2008.

Denominator (Urgent): Visits to U.S.emergency departments with triage assessments of urgent, 2007-2008.

Note: Race data were missing for 13.3% of total visits included in this chart. Missing race data were imputed. Standard errors were

inflated as described at 2007 NHAMCS Microdata File Documentation

ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHAMCS/. Insurance status shown for patients under age 65

and classified based on all expected payment sources. Public insurance includes Medicare, Medicaid, and State Children’s Health

Insurance Program. Uninsured is defined as having “only self-pay” or “no charge/charity” as payment sources.

● In 2007-2008, among ED visits for immediate/emergent conditions, the percentage that had to wait an

hour or more was higher among Blacks compared with Whites (Figure 4.3). 

● Among visits for urgent conditions, the percentage of patients who had to wait an hour or more was

higher for Blacks compared with Whites and for uninsured patients under age 65 compared with

privately insured patients under age 65.

Also, in the NHQR:

● In 2007-2008, among ED visits for immediate/emergent conditions, there was no significant difference

in the percentage that had to wait an hour or more between patients living in metropolitan and

nonmetropolitan areas. Among visits for urgent conditions, the percentage that had to wait an hour or

more was lower among nonmetropolitan patients compared with metropolitan patients.

● Differences related to age were not significant.

National Healthcare Disparities Report, 2010 165
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2005-2008.

Denominator: Patients hospitalized with a principal diagnosis of acute myocardial infarction who were appropriate candidates for

percutaneous coronary intervention.

Note: Data were insufficient for this analysis for Native Hawaiians and Other Pacific Islanders.

● Among heart attack patients, except for Asians, the percentage of patients receiving timely PCI

improved for all racial/ethnic groups from 2005 to 2008 (Figure 4.4). In 2008, Blacks and American

Indians and Alaska Natives were less likely to receive timely PCI compared with Whites (74.3% and

69.3%, respectively, compared with 82.1%).

● The 2008 top 5 State benchmark was 91.0%.i At the current rate of improvement, the achievable

benchmark could be attained in less than 1 year.

i The top 5 States that contributed to the achievable benchmark are Massachusetts, Minnesota, North Carolina, Rhode Island,

and South Carolina.

National Healthcare Disparities Report, 2010 166

Key: AI/AN = American Indian or Alaska Native.
Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2005-2008.

Denominator: Patients hospitalized with a principal diagnosis of acute myocardial infarction who were appropriate candidates for

fibrinolytic medication.

● Among heart attack patients, the percentage of patients receiving timely fibrinolytic medication

improved for all racial/ethnic groups from 2005 to 2008 (Figure 4.5). In 2008, Blacks were less likely to

receive timely fibrinolytic medication compared with Whites (37.8% compared with 51.0%).

● In 2008, the top 5 State benchmark was 60.7%.ii At the current rate of improvement, the achievable

benchmark could be attained in about 2.5 years.

● At their current rates of improvement, Whites should reach the achievable benchmark in a little over 2

years; however, Hispanics would not reach the benchmark for about 3.5 years, and Asians and Blacks

would not reach the benchmark for about 5.5 years.

ii The top 5 States that contributed to the achievable benchmark are Arkansas, California Georgia, Kentucky, and Tennessee.

National Healthcare Disparities Report, 2010 167
Mar;25(3):476-81.

11. Ramsey SD, Newton K, Blough D, et al. Patient-level estimates of the cost of complications in diabetes in a managed-care

population. Pharmacoecon 1999 Sep;16(3):285-95.

12. Calculated from Web site: Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. Kids’

Inpatient Database. Rockville, MD. Available at: http://hcupnet.ahrq.gov/. Accessed April 24, 2009.

13. Pitts S, Niska R, Xu J, et al. National Hospital Ambulatory Medical Care Survey: 2007 emergency department summary.

National Health Statistics Reports 2008 Aug 6;(7). Available at: www.cdc.gov/nchs/data/nhsr/nhsr026.pdf. Accessed July 7,

2009.

14. McCaig L, Nawar EW. National Hospital Ambulatory Medical Care Survey: 2004 emergency department summary. Adv Data

Vital Health Stat 2006 June 23;(372). Available at: http://www.cdc.gov/nchs/data/ad/ad372.pdf. Accessed January 20, 2011.

15. Kloner RA, Rezkalla SH. Cardiac protection during acute myocardial infarction: where do we stand in 2004? J Am Coll

Cardiol 2004 Jul 21;44(2):276-86.

National Healthcare Disparities Report, 2010 168
and provider-patient communication include:

● Language barriers.

● Racial and ethnic concordance between the patient and provider.

● Effects of disabilities on patients’ health care experiences.

● Providers’ cultural competency.

Efforts to remove these possible impediments to patient centeredness are underway within the Department of

Health and Human Services (HHS). For example, the Office of Minority Health has developed a set of

Cultural Competency Curriculum Modules that aim to equip providers with cultural and linguistic

competencies to help promote patient-centered care.10, ii These modules are based on the National Standards

on Culturally and Linguistically Appropriate Services. The standards are directed at health care organizations

and aim to improve the patient centeredness of care for people with limited English proficiency (LEP).

Another example, which is being administered by the Health Resources and Services Administration, is

Unified Health Communication, a Web-based course for providers that integrates concepts related to health

literacy with cultural competency and LEP.iii

i For example, Title VI of the Civil Rights Act of 1964, 42 U.S.C. 2000d, may require the practitioner or hospital to provide

language interpreters and translate vital documents for limited-English-proficient persons. Section 504 of the Rehabilitation

Act of 1973, 29 U.S.C. 794, may require the practitioner or hospital to provide sign language interpreters, materials in Braille,

and/or accessible electronic formats for individuals with disabilities.

ii This online program (available at http://www.thinkculturalhealth.org) is accredited for Continuing Medical Education credits

for physicians and Continuing Education Units for nurses and pharmacists.

iii This online program (available at http://www.hrsa.gov/publichealth/healthliteracy/) is accredited for Continuing Medical

Education credits for physicians and Continuing Education Units for nurses, physician assistants, pharmacists, and Certified

Health Education Specialists.

National Healthcare Disparities Report, 2010 169
● Patient centeredness can reduce the strain on system resources and save money by reducing the number

of diagnostic tests and referrals.6

● Although some studies have shown that being patient centered reduces medical costs and use of health

service resources, others have shown that patient centeredness increases providers’ costs, especially in

the short run.13

Measures

The National Healthcare Quality Report (NHQR) and the National Healthcare Disparities Report (NHDR)

track several measures of patients’ experience of care. The reports also include one priority and two goals

recommended by the National Priorities Partnership (NPP). NPP identified patient and family engagement as

one of six national priorities. The vision is health care “...that honors each individual patient and family,

offering voice, control, choice, skills in self-care, and total transparency, and that can and does adapt readily

to individual and family circumstances, and to differing cultures, languages, and social backgrounds.” Key

goals include enabling patients to effectively navigate and manage their care and enabling patients to make

informed decisions about their treatment options.

The core measure presented in this report is adults and children who reported poor communication at the

doctor’s office. This measure is a composite of four measures—patients’ assessments of how often their

provider listened carefully to them, explained things clearly, respected what they had to say, and spent enough

time with them. This measure is presented separately for adults and children.

National Healthcare Disparities Report, 2010 170
Optimal health care requires good communication between patients and providers, yet barriers to providerpatient communication are common. To provide all patients with the best possible care, providers must be

able to understand patients’ diverse health care needs and preferences and communicate clearly with patients

about their care.

Figure 5.1. Adults who had a doctor’s office or clinic visit in the last 12 months who reported poor

communication with health providers, by race, ethnicity, and income, 2002-2007

National Healthcare Disparities Report, 2010 171
● In all years, the percentage of adults who reported poor communication was significantly higher for

poor, near-poor, and middle-income people than for high-income people.

● In all years, Hispanics were significantly more likely than non-Hispanic Whites to report poor

communication.

● In 4 of 6 years, Black patients were more likely than Whites to report poor communication with health

providers; the exceptions were 2006 and 2007.

● In 5 of 6 years, Asians were more likely than Whites to report poor communication; the exception was

2007.

Also, in the NHQR:

● In 5 of 6 years, a significantly lower percentage of adults in large fringe metropolitan areas reported

poor communication with their health providers; 2006 was the exception.

Racial and ethnic minorities are disproportionately of lower education levels. To distinguish the effects of

race, ethnicity, education, and activity limitation on provider-patient communication, this measure is stratified

by education level and activity limitation.

National Healthcare Disparities Report, 2010 172
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

Denominator: Civilian noninstitutionalized population age 18 and over.

Note: Sample sizes were too small to provide estimates for Asians with less than a high school education and Asians with activity

limitations. Patients who report that their health providers sometimes or never listened carefully, explained things clearly, showed

respect for what they had to say, or spent enough time with them are considered to have poor communication.

National Healthcare Disparities Report, 2010 173
Communication in childrens health care can be challenging since the childs experiences are interpreted

through the eyes of a parent or guardian. During a health care encounter, a responsible adult caregiver will be

involved in communicating with the provider and interpreting decisions in an age-appropriate manner to the

patient. Optimal communication in children’s health care can therefore have a significant impact on receipt 

of high-quality care and subsequent health status. This is especially true for children with special health 

care needs.

National Healthcare Disparities Report, 2010 174
Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population under age

18.

Note: Data for Asians (2005 and 2007) and multiple-race children

(2006 only) did not meet criteria for statistical reliability. Parents

who report that their child’s health providers sometimes or never

listened carefully, explained things clearly, showed respect for what

they had to say, or spent enough time with them are considered to

have poor communication.

● Overall, the percentage of children whose parents or guardians reported poor communication with their

health providers significantly decreased from 6.7% in 2002 to 4.9% in 2007 (data not shown).

National Healthcare Disparities Report, 2010 175

Source:

Expenditure Panel Survey, 2002-2007.

Denominator:

18.

Note:

(2006 only) did not meet criteria for statistical reliability. Parents

who report that their child’s health providers sometimes or never

listened carefully, explained things clearly, showed respect for what

they had to say, or spent enough time with them are considered to

have poor communication.

Denominator:

Source:

Expenditure Panel Survey, 2002-2007.

18.

Note:

(2006 only) did not meet criteria for statistical reliability. Parents

who report that their child’s health providers sometimes or never

listened carefully, explained things clearly, showed respect for what

they had to say, or spent enough time with them are considered to

have poor communication.
Figure 5.4. Composite measure: Children with ambulatory visits whose parents reported poor

communication with health providers, by ethnicity, stratified by income, 2007

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

Denominator: Civilian noninstitutionalized population under age 18.

Note: Data were not available for high-income Hispanics. Parents who report that their child’s health providers sometimes or never

listened carefully, explained things clearly, showed respect for what they had to say, or spent enough time with them are considered to

have poor communication.

National Healthcare Disparities Report, 2010 176
National Healthcare Disparities Report, 2010 177
● Overall, 5.9% of adult hospital patients reported poor communication with nurses during their hospital

stay, and 5.3% reported poor communication with doctors (data not shown).

● Compared with Whites, all minority groups were more likely to report poor communication with nurses

(Figure 5.5). Blacks, American Indians and Alaska Natives, and patients of more than one race were

more likely to report poor communication with doctors.

● Compared with non-Hispanic Whites, Hispanics were more likely to report poor communication with

nurses but not with doctors.

● Compared with patients with at least some college education, patients with less than a high school

education were more likely to report poor communication with both nurses and doctors.

● Compared with patients who speak English at home, patients who speak Spanish at home were more

likely to report poor communication with nurses while patients who speak some other language at home

were more likely to report poor communication with both nurses and doctors.

Also, in the NHQR:

● Compared with patients ages 18-44, patients ages 45-64 were more likely to report poor communication

with doctors.

● Patients age 65 and over were less likely to report poor communication with nurses.

National Healthcare Disparities Report, 2010 178
y

Language Assistance

Language barriers in health care are associated with decreases in quality of care, safety, and patient and

clinician satisfaction and contribute to health disparities, even among people with insurance. The Federal

Government has issued 14 culturally and linguistically appropriate services (CLAS) standards. These

standards, which are directed at health care organizations, are also encouraged for individual providers to

improve accessibility of their practices. The 14 standards are organized by themes: Culturally Competent

Care (Standards 1-3), Language Access Services (Standards 4-7), and Organizational Supports for Cultural

Competence (Standards 8-14). For people with limited English proficiency, having CLAS is of particular

importance and may influence the patient’s choice of a usual source of care.

National Healthcare Disparities Report, 2010 179
Key: USC = usual source of care.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

● In 2007, Hispanic adults were significantly more likely than non-Hispanic adults to have a usual source

of care with language assistance (Figure 5.6).

● In 2007, White adults with limited English proficiency were significantly more likely than Asians to

have a usual source of care with language assistance.

Need for a Translator

The ability of providers and patients to communicate clearly with each other can be compromised if they do

not speak the same language. Quality may suffer if patients with limited English proficiency cannot express

their care needs to providers who speak English only or who do not have an interpreter’s assistance.

Communication problems between the patient and provider can lead to lower patient adherence to medication

regimens and decreased participation in medical decisionmaking. It also can exacerbate cultural differences

that impair the delivery of quality health care.

National Healthcare Disparities Report, 2010 180
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

● In 2007, non-Hispanic White patients in California were significantly less likely than Hispanic patients

to need a translator during their last doctor visit (Figure 5.7). Non-Hispanic Whites also were less likely

than Mexicans and Central Americans to need a translator. Asians were significantly more likely than

non-Hispanic Whites to need a translator during their last doctor visit (4.1% compared with 0.7%).

There were however, no statistically significant differences between the overall Asian population and

Chinese or Vietnamese patients. There also were no significant differences between Chinese and

Vietnamese patients.

● Poor (8.9%), low-income (7.0%), and middle-income (3.1%) patients also were significantly more

likely than high-income (0.9%) patients to need a translator.

● Patients in California with less than a high school education and high school graduates were

significantly more likely to need a translator than patients with some college education (12.0% and 2.6,

respectively, compared with 1.1%).

Ability to Read Instructions on a Prescription Bottle

The effectiveness of a prescription is due in large part to the patient’s ability to follow dosing instructions

correctly. If the patient misinterprets the amount of medication to be taken or the dosing schedule, an adverse

event can occur. This is particularly true for patients taking multiple medications that require strict adherence.

This misunderstanding can be due to the patient’s health literacy levels, cognitive abilities, or visual 

National Healthcare Disparities Report, 2010 181
Key: AI/AN = American Indian or Alaska Native.

Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

● Poor patients in California were less likely than high-income patients to find it easy to read the

instructions on a prescription bottle (81.8% compared with 95.6%; Figure 5.8).

● The percentage of patients in California who found it easy to read the instructions on a prescription

bottle was higher for high school graduates and people with at least some college education compared

with patients with less than a high school education. (92.9% and 95.0%, respectively, compared with

80.2%).

● In 2007, patients in California who did not speak English well or at all were less likely than patients

who speak English only to find it easy to read the instructions on a prescription bottle (75.1% compared

with 95.4%).

Also, in the NHQR:

● In California, patients under age 65 with public insurance and uninsured patients were less likely than

patients with private health insurance to find it easy to read the instructions on a prescription bottle.

National Healthcare Disparities Report, 2010 182
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

● In 2007, among different Hispanic ethnic groups in California, there were no statistically significant

differences in patients who found it easy to read the instructions on a prescription bottle (Figure 5.9).

● In 2007, Filipinos, Vietnamese people, and South Asians living in California were significantly more

likely than the overall Asian population to find it easy to read the instructions on a prescription bottle.

● In 2007, Filipinos, Japanese people, Vietnamese people, and South Asians living in California were all

more likely than Chinese people to find it easy to read the instructions on a prescription bottle.

● In California overall, Asians were significantly more likely than Hispanics to find it easy to read the

instructions on a prescription bottle (89.5% compared with 87.2%).

National Healthcare Disparities Report, 2010 183
Key: AI/AN = American Indian or Alaska Native.

Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007.

● Non-Hispanic White patients living in California were more likely than all other racial and ethnic

groups to find it easy to understand information from a doctor’s office (Figure 5.10).

National Healthcare Disparities Report, 2010 184
National Healthcare Disparities Report, 2010 185
● In California in 2007, Asians were significantly more likely than Hispanics to find it easy to understand

written information from a doctor’s office (84.0% compared with 76.0%; Figure 5.11).

● In California in 2007, Central American patients were significantly less likely than the overall Hispanic

population to find it easy to understand written information from a doctor’s office (65.7% compared

with 76.0%)

● In 2007, Mexican patients in California were significantly more likely than Central American patients to

find it easy to understand written information from a doctor’s office (75.9% compared with 65.7%).

South American patients also were more likely than Central American patients to find it easy to

understand information from a doctor’s office.

● In 2007, Filipino and South Asian patients living in California were significantly more likely than the

overall Asian population to find it easy to understand written information from a doctor’s office (93.3%

and 91.2%, respectively, compared with 84.0%).

● In 2007, Chinese patients living in California were significantly less likely than all other Asian ethnic

groups except Koreans to find it easy to understand written information from a doctor’s office.

Providers Asking Patients To Assist in Making Treatment Decisions

The high prevalence of chronic disease has placed more responsibility on patients. Conditions such as

diabetes and hypertension require self-management by patients. It is vital that patients are provided with

information that allows them to make informed decisions and feel engaged in their treatment and that it

incorporates their values and preferences.

National Healthcare Disparities Report, 2010 186
Key: AI/AN = American Indian or Alaska Native.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

● In 2007, Whites were significantly less likely than Blacks, Asians, and people of more than one race to

have a usual source of care sometimes or never ask for the patient’s help to make treatment decisions

(15.1% compared with 18.9%, 22.7%, and 22.3%, respectively; Figure 5.12).

● In 2007, non-Hispanic White patients were significantly less likely than Hispanics to have a usual

source of care sometimes or never ask for the patient’s help to make treatment decisions (14.5%

compared with 18.5%).

● In 2007, patients with some college education were significantly less likely than patients with less than

a high school education to have a usual source of care sometimes or never ask for the patient’s help to

make treatment decisions (15.0% compared with 19.7%).

● In 2007, patients who usually spoke English at home were significantly less likely than patients who

mostly spoke another language at home to have a usual source of care sometimes or never ask for the

patient’s help to make treatment decisions (15.6% compared with 18.5%).

Also, in the NHQR:

● In 2007, patients living in metropolitan areas were significantly more likely than patients living in

nonmetropolitan areas to have a usual source of care not ask for their help in making treatment decisions.

National Healthcare Disparities Report, 2010 187

Key: AI/AN = American Indian or Alaska Native.
gg pggg gppg

47311-02; August 2, 2008. Available at: www.hhs.gov/ocr/civilrights/resources/specialtopics/lep/factsheetguidanceforlep.html.

Accessed April 24, 2009.

12. Berry LL, Seiders K, Wilder SS. Innovations in access to care: a patient-centered approach. Ann Intern Med 2003 Oct

7;139(7):568-74.

13. Bechel DL, Myers WA, Smith DG. Does patient-centered care pay off? Jt Comm J Qual Improv 2000 Jul;26(7):400-9.

14. Hargraves JL, Hays RD, Cleary PD. Psychometric properties of the Consumer Assessment of Health Plans Study (CAHPS) 2.0

adult core survey. Health Serv Res 2003 Dec;38(6 Pt 1):1509-27.

National Healthcare Disparities Report, 2010 188
p

Morbidity and Mortality

● Care coordination interventions have been shown to: 

• Reduce mortality among patients with heart failure. 

• Reduce mortality and dependency among patients with stroke.

• Reduce symptoms among patients with depression and at the end of life.

• Improve glycemic control among patients with diabetes.2

Cost

● Care coordination interventions have been shown to: 

• Reduce hospitalizations among patients with heart failure.

• Reduce readmissions among patients with mental health conditions.

• Be cost-effective when applied to treatment of depression.2

Measures

The National Priorities Partnership (NPP) identified care coordination as one of six national priorities for

health care.4 The vision is health care that “guides patients and families through their healthcare experience, 

National Healthcare Disparities Report, 2010 189
coordination and having a medical home.

Findings

Transitions of Care

Management: Complete Written Discharge Instructions

As health care conditions and needs change, patients often need to move from one setting to another. These

transitions of care place patients at heightened risk of adverse events. Important information may be lost or

miscommunicated as responsibility is delivered to new parties. 

Effective care coordination begins with ensuring that accurate clinical information is available to support

medical decisions by patients and providers. A common transition of care is discharge from the hospital.

Giving patients and caregivers self-management support after discharge has been shown to reduce

readmissions to the hospital and lower costs.5

Discharge from a hospital typically indicates improvement in a patient’s condition so that the patient no

longer requires inpatient care. It also means that the patient and family must resume responsibility for the

patient’s daily activities, diet, medications, and other treatments. The patient also needs to visit his or her

personal doctor and know what to do if his or her condition deteriorates. Written discharge instructions are

critical to help ensure that a patient receives the information needed to stay healthy after leaving the hospital.

National Healthcare Disparities Report, 2010 190
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Quality Improvement Organization Program, 2005-2008.

Denominator: Hospitalized adult patients with a principal discharge diagnosis of heart failure.

Note: Complete written discharge instructions needed to address all of the following: activity level, diet, discharge medications,

followup appointment, weight monitoring, and actions to take if symptoms worsen. 

● From 2005 to 2008, the percentage of hospitalized adult patients with heart failure who were given

complete written discharge instructions improved from 57.5% to 82.0% (data not shown). 

● Improvements were observed among all racial and ethnic groups (Figure 6.1).

● In all years, American Indians and Alaska Natives were less likely to receive complete written discharge

instructions compared with Whites. In 2005 and 2006, Asians and Hispanics were also less likely to

receive written instructions than Whites, but these disparities were eliminated by 2008.

● The 2008 top 5 State benchmark was 88%.i At the current 12% annual rate of increase, this benchmark

could be attained overall and by most racial and ethnic groups in less than a year. American Indians and

Alaska Natives would require almost 3 years to reach the benchmark.

Also, in the NHQR:

● Significant differences in receipt of written instructions by sex were not observed.

i The top 5 States that contributed to the achievable benchmark are Colorado, Delaware, New Hampshire, New Jersey, and

Utah. 

National Healthcare Disparities Report, 2010 191
In previous years, we reported on readmissions with a principal diagnosis of CHF only, so comparisons with

previous reports would not be appropriate. It is also important to note that the figures reported below are not

national estimates. The States in the analysis account for about one-third of all adult discharges for CHF in

the Nation and may provide an indication of patterns in CHF readmissions.

Costs of CHF rehospitalizations were also examined. Total hospital charges were converted to costs using

HCUP cost-to-charge ratios based on hospital accounting reports from the Centers for Medicare & Medicaid

Services. Cost estimates refer to hospital costs and do not include costs of physician services. In these 15

States, the average cost per CHF readmission was almost $13,000 and the total cost was more than $880

million.

National Healthcare Disparities Report, 2010 192
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, State Inpatient Databases, 2007.

Denominator: Patients hospitalized for congestive heart failure.

Note: Some States had insufficient data for this analysis for Blacks, APIs, and Hispanics.

● The percentage of State-level CHF hospitalizations resulting in rehospitalization for CHF ranged from a

low of 14% to a high of 24% (see NHQR).

● Aggregating over all States, Blacks had higher rehospitalization rates than Whites (Figure 6.2). This

was also observed in States B, F, G, and K. 

● Aggregating over all States, no statistically significant differences were observed between APIs and

Whites or between Hispanics and Whites. However, Hispanics had higher rates than Whites in States A,

G, I, and L, and APIs had a higher rate in State B.

Also, in the NHQR:

● Overall, rehospitalization rates did not vary by age. Rates were higher among patients ages 18-64

compared with patients age 65 and over in one State, but the reverse was true in two other States.

Medication Information

Patients often seek care from many providers, and different providers may prescribe medications for the same

patient. Patients are responsible for keeping track of all their medications, but medication information can be

confusing, especially for patients on multiple medications. When care is not well coordinated and each

provider is not aware of all the medications a patient is taking, patients are at greater risk for adverse drug

interactions and adverse events related to overdosing or underdosing. In addition, providers need to

National Healthcare Disparities Report, 2010 193
National Healthcare Disparities Report, 2010 194
Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population who report a usual source of care.

● From 2002 to 2007, the percentage of people with a usual source of care whose health provider usually

asked about prescription medications and treatments from other doctors improved from 75% to 80%

(see NHQR). 

● Improvements were observed among all racial, ethnic, income, and education groups (Figure 6.3).

● Consistent disparities related to race, ethnicity, or income were not observed. In most years, providers of

people with less than a high school education were less likely to ask about medication from other

doctors compared with providers of people with at least some college education.

Also, in the NHQR:

● In most years, health providers of children and older adults were less likely to ask about medications

from other doctors. 

Structure: Electronic Exchange of Medication Information

Ideally, information about medications prescribed for a patient by one provider would be available to all

providers taking care of that patient. One way to exchange this information efficiently is to build this function

into health information technologies. The American Hospital Association recently surveyed hospitals about

their use of health information technologies. Questions about whether a hospital electronically exchanged

patient information on medication history with other providers were included and 1,963 hospitals responded.

National Healthcare Disparities Report, 2010 195
Source: American Hospital Association Annual Survey Information Technology Supplement, 2008.

● Overall, 80% of hospitals electronically exchanged patient information on medication history with other

hospitals in their system, 13% exchanged information with hospitals outside their system, and 36%

exchanged information with ambulatory providers outside their system (Figure 6.4).

● Hospitals with residency programs were more likely than non-teaching hospitals to exchange

information with hospitals in their system.

● Federal hospitals were most likely to exchange information with hospitals in their system and least

likely to exchange information with ambulatory providers outside their system.

Also, in the NHQR:

● Hospitals outside of metropolitan areas were less likely than metropolitan hospitals to exchange

information with hospitals in their system but more likely to exchange information with hospitals

outside their system. Hospitals with <100 or 100-399 beds were less likely than large hospitals to

exchange information with hospitals in their system. 

National Healthcare Disparities Report, 2010 196
National Healthcare Disparities Report, 2010 197
Key: ED = emergency department.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department

Sample, 2007.

Denominator: U.S. population.

Note: Annual rates are adjusted for age and gender.

● Overall, the rate of ED visits for asthma was 498 per 100,000 among adults (Figure 6.5). About 20% of

ED visits for asthma among adults led to hospitalization (97 per 100,000) and 80% had other

dispositions (401 per 100,000).

● Compared with adult residents of high-income neighborhoods, residents of all other income quartiles

had higher rates of both ED visits for asthma that led to hospitalization and ED visits that did not end in

hospitalization.

● Overall, the rate of ED visits for asthma was 876 per 100,000 among children, considerably higher than

the adult rate. Only about 11% of ED visits for asthma among children led to hospitalization and 89%

had other dispositions.

● Compared with children living in high-income neighborhoods, children living in the lower three income

quartiles had higher rates of both ED visits for asthma that led to hospitalization and visits that did not

end in hospitalization.

National Healthcare Disparities Report, 2010 198
Two measures related to care coordination are presented here. One measure focuses on families who needed

extra help arranging or coordinating a child’s health care with two or more providers. Families that reported

that they usually or always got as much help as needed in arranging or coordinating the child’s health care

were considered to have effective care coordination.

The second measure focuses on the medical home. The patient-centered medical home is one approach to

organizing care around a person and helping each person stay as healthy as possible. A key characteristic of a

medical home is a personal physician leading a team of health care professionals. These professionals

collectively take responsibility for providing all the services that a patient needs or arranging for and

coordinating care provided by others. In addition to coordinating care, medical homes provide care that is

accessible, family centered, continuous, comprehensive, compassionate, and culturally effective.8

In the 2007 National Survey of Children’s Health, several questions were asked to determine whether a child

had a medical home: 

● First, a child had to have a personal doctor or nurse. 

● The presence or absence of family-centered, compassionate, and culturally effective care was assessed

through a series of questions about the relationship between the provider and the child and family. 

● Comprehensive and accessible care was assessed by whether the child had a usual source of care (other

than an ED) when sick or when parents needed advice and by the ease of receiving needed referrals. 

National Healthcare Disparities Report, 2010 199
Key: Hispanic, English indicates that child is Hispanic and English is the primary language spoken at home; Hispanic, Spanish

indicates that child is Hispanic and Spanish is the primary language spoken at home.

Source: Health Resources and Services Administration, Maternal and Child Health Bureau; Centers for Disease Control and

Prevention, National Center for Health Statistics, National Survey of Children’s Health, 2007. 

Denominator: Children under age 18.

Note: Analyses performed by the Child and Adolescent Health Measurement Initiative, Data Resource Center for Child and Adolescent

Health (http://childhealthdata.org).

● Overall, among families who needed extra help arranging or coordinating a child’s health care with two

or more providers, only 69% reported receiving effective care coordination (Figure 6.6). Black, Asian,

and Hispanic children were less likely than White children and Hispanic children who speak Spanish at

home were less likely than Hispanic children who speak English at home to receive effective care

coordination. 

● Overall, 58% of children had a medical home. Black, Asian, and Hispanic children were less likely than

White children and Hispanic children who speak Spanish at home were less likely than Hispanic

children who speak English at home to have a medical home.

National Healthcare Disparities Report, 2010 200
5. Coleman EA, Parry C, Chalmers S, et al. The care transitions intervention: results of a randomized controlled trial. Arch Intern

Med 2006 Sep 25;166(17):1822-8.

6. Whittington J, Cohen H. OSF Healthcare’s journey in patient safety. Qual Manag Health Care 2004 Jan-Mar;13(1):53-59.

7. Weighted national estimates from HCUP Nationwide Emergency Department Sample. Agency for Healthcare Research and

Quality; 2008. Available at: http://hcupnet.ahrq.gov. Accessed November 3, 2010.

8. American Academy of Pediatrics, Medical Home Initiatives for Children With Special Health Care Needs Project Advisory

Committee. Policy statement: the medical home. Pediatrics 2002(110):184-6.

9. Child and Adolescent Health Measurement Initiative. Measuring medical home for children and youth: methods and findings

from the National Survey of Children With Special Health Care Needs and the National Survey of Children’s Health. Portland:

Oregon Health & Science University; 2009. Available at: http://medicalhomedata.org/ViewDocument.aspx?item=436. Accessed

November 5, 2010.

National Healthcare Disparities Report, 2010 201
National Healthcare Disparities Report, 2010 202
another report that examined the question of efficiency from the cost-of-waste point of view. In that report,

the authors outline another common typology for efficiency measurement: the tracking of overuse, underuse,

and misuse in the health care system.3

For 2010, this chapter has been realigned around the National Priorities Partnership’s (NPP) concept of

overuse (one of the six national priorities). The vision is a health care system that “promotes better health and

more affordable care by continually and safely reducing the burden of unscientific, inappropriate, and

excessive care, including tests, drugs, procedures, visits, and hospital stays.” The primary goal is to have

“healthcare organizations that continually strive to improve the delivery of appropriate patient care, and

substantially and measurably reduce extraneous services and treatments.” 

The measures this year are presented in the following layout:

● Inappropriate medication use.

• Adults age 65 and over who received potentially inappropriate prescription medications.

● Preventable emergency department visits and hospitalizations.

• Potentially avoidable hospitalization rates for adults.

• Total national costs associated with potentially avoidable hospitalizations.

• Medicare home health patients with potentially avoidable hospitalizations. 

• Nursing home residents with potentially avoidable hospitalizations. 

National Healthcare Disparities Report, 2010 203
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2007.

Denominator: Civilian noninstitutionalized population age 65 and over.

Note: Prescription medications received include all prescribed medications initially purchased or otherwise obtained, as well as any

refills. Whites and Blacks are non-Hispanic.

i Drugs that should always be avoided for older patients include barbiturates, flurazepam, meprobamate, chlorpropamide,

meperidine, pentazocine, trimethobenzamide, belladonna alkaloids, dicyclomine, hyoscyamine, and propantheline. Drugs that

should often or always be avoided for older patients include carisoprodol, chlorzoxazone, cyclobenzaprine, metaxalone,

methocarbamol, amitriptyline, chlordiazepoxide, diazepam, doxepin, indomethacin, dipyridamole, ticlopidine, methyldopa,

reserpine, disopyramide, oxybutynin, chlorpheniramine, cyproheptadine, diphenhydramine, hydroxyzine, promethazine, and

propoxyphene.

National Healthcare Disparities Report, 2010 204

Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2007.
discharge data. 

A critical caveat should be noted regarding potentially avoidable hospitalizations. Comparatively high rates of

potentially avoidable hospitalizations may reflect inefficiency in the health care system. Therefore, groups of

patients should not be “blamed” for receiving less efficient care. Instead, examining disparities in efficiency

may help make the business case for addressing disparities in care. Investments that reduce disparities in

access to high-quality outpatient care may help reduce rates of avoidable hospitalizations among groups that

have high rates.

National Healthcare Disparities Report, 2010 205
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2004-2007.

Denominator: Civilian noninstitutionalized adults age 18 and over. 

Note: Annual rates are adjusted for age and gender. White, Black, and Asian or Pacific Islander populations are non-Hispanic. Income

quartiles are based on median income of ZIP Code of patient’s residence. 

● In 2007, rates of potentially avoidable hospitalizations were higher among Blacks compared with

Whites (3,164 compared with 1,508 per 100,000 population; Figure 7.2). Rates were lower among

Asians and Pacific Islanders (936 per 100,000 admissions) compared with Whites. 

● Rates of potentially avoidable hospitalizations were higher among residents of areas in the lowest and

second income quartile compared with residents of the highest income quartile (2,341 and 1,766,

respectively, compared with 1,234 per 100,000 population).

● Rates of avoidable hospitalizations for chronic conditions were higher among Blacks and Hispanics

compared with Whites (2,113 and 1,020.6, respectively, compared with 863 per 100,000 population;

data not shown). Rates were lower among Asians and Pacific Islanders (489 per 100,000 population)

compared with Whites (data not shown). 

● Rates of potentially avoidable hospitalizations for chronic conditions were higher among residents of

areas in the lowest and second income quartile compared with residents of the highest income quartile

(1286.3, and 786.8, respectively, compared with 634 per 100,000 population; data not shown).

● Rates of potentially avoidable hospitalizations for acute conditions were higher among Blacks

compared with Whites (840 compared with 645 per 100,000 population; data not shown). 

● There were no significantly different rates of potentially avoidable hospitalizations for acute conditions

among income groups (data not shown).

National Healthcare Disparities Report, 2010 206
conditions, by race/ethnicity, 2007

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, State Inpatient Databases (SID)

disparities analysis file, 2007.

ii The top 4 States that contributed to the achievable benchmark are Hawaii, Oregon, Utah, and Washington. 

National Healthcare Disparities Report, 2010 207
Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project, Nationwide Inpatient Sample, 2007.

● If residents of the neighborhoods in the lowest income quartile had the benchmark rate of preventable

hospitalizations, they would have had more than 680,000 fewer hospitalizations (Figure 7.4). Instead of

costing $8.8 billion in 2007, preventable hospitalization among income quartile 1 residents would have

cost only $3.9 billion, saving $4.9 billion.

National Healthcare Disparities Report, 2010 208

Source:

Cost and Utilization Project, Nationwide Inpatient Sample, 2007.
or near reservations. Because data on AI/ANs obtained from most Federal and State sources are incomplete,

the NHDR addresses the data gap for this measure by examining data submitted to the IHS National Patient

Information Reporting System (NPIRS) by IHS, Tribal, and contract hospitals.

National Healthcare Disparities Report, 2010 209
Source: IHS, Tribal, and contract hospitals: Indian Health Service, NPIRS, National Data Warehouse, Workload and Population Data

Mart, 2004-2007; community hospitals: Agency for Healthcare Research and Quality, HCUP SID disparities analysis file, 2004-2007.

National Healthcare Disparities Report, 2010 210
which should reduce rates of avoidable hospitalization. However, these patients are also more acutely ill, may

become seriously ill when affected by a new illness, and may have multiple comorbidities. Medicare patients

in these settings often have been hospitalized recently. Therefore, an avoidable hospitalization may represent

a return to the hospital, perhaps against the expectation that the patient no longer needed acute care. 

For application to home health and nursing home settings, the potentially avoidable stays are identified

within a defined time period, 30 days, from the home health or nursing home admission date. If a patient is

hospitalized more than once in that period, only the first stay is recognized for the measure. 

Data on home health patients come from Medicare fee-for-service (FFS) home health claims and Outcome

and Assessment Information Set patient assessment information. Data on nursing home patients come from

Medicare skilled nursing facility FFS claims and Minimum Data Set patient assessment information. These

data are linked with Medicare Part A acute care hospital claims to determine hospitalizations for potentially

avoidable conditions.

National Healthcare Disparities Report, 2010 211
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set linked with Medicare Part A claims

(100%), 2001-2008.

Denominator: Adult nonmaternity patients starting an episode of skilled home health care. 

Note: Rates standardized to the 2006 patient population according to Medicare enrollment category. Hispanics could include other

races. All race categories could include Hispanics.

● Between 2001 and 2008, hospitalizations for potentially avoidable conditions within 30 days of home

health episode start declined from 4.7% to 3.8% (data not shown). 

● From 2001 to 2008, among all racial and ethnic groups except Asians, the percentage of potentially

avoidable hospitalizations within 30 days of home health episode start significantly decreased (Figure

7.6).

● In 2001, the costs associated with hospitalizations for potentially avoidable conditions within 30 days of

home health episode start were $675.4 million; by 2008, the costs had risen to $903.9 million.

National Healthcare Disparities Report, 2010 212
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Minimum Data Set, 2000-2007, linked with Medicare Part A claims (100%). 

Denominator: Residents who met the Medicare skilled nursing facility (SNF) criteria for nursing home admission.

Note: American Indians/Alaska Natives, Asian/Pacific Islanders, Blacks, and Whites are non-Hispanic populations. 

● Between 2000 and 2002, potentially avoidable hospitalizations within 30 days of skilled nursing home

episode start increased by about 0.5% for all racial and ethnic groups except Asians and Pacific

Islanders (Figure 7.7). During this time, the percentage for Asians and Pacific Islanders did not change.

● From 2002 to 2007, potentially avoidable hospitalizations within 30 days of skilled nursing home

episode start plateaued for all racial and ethnic groups, except for Asians and Pacific Islanders. This

percentage gradually rose (from 4.1% to 5.2%).

● In 2000, the costs associated with hospitalizations for potentially avoidable conditions within 30 days of

skilled nursing home episode start were $343.7 million; by 2007, the costs had risen to $724.4 million.

Potentially Harmful Preventive Services

This section highlights waste and opportunities to reduce unnecessary costs. Waste includes overuse,

underuse, and misuse of health care services. As it is one of the NPP priorities, the focus of this section is on

overuse. Nevertheless, underuse and misuse are addressed in various sections of this report. Many of the

effectiveness measures relate to people not getting services they need, i.e., underuse. Many of the safety

measures relate to people getting services in a hazardous manner, i.e., misuse.

National Healthcare Disparities Report, 2010 213
National Healthcare Disparities Report, 2010 214
12 months was 73.7% (data not shown).

● In 2008, the percentage of Black and Asian males age 75 and over who had a PSA test or a DRE within

the last 12 months was lower than for White males (Figure 7.8). 

● In 2008, the percentage of poor males age 75 and over who had a PSA test or a DRE within the last 12

months was lower than for high-income males.

● In 2008, the top 5 State benchmark for males age 75 and over who had a PSA or DRE exam was

62.4%.iii There was no evidence of movement toward the benchmark, but Asian males and poor males

had attained the benchmark.

iii The Top 5 States that contributed to this benchmark are California, Hawaii, Louisiana, New Jersey, and Tennessee.

National Healthcare Disparities Report, 2010 215
National Healthcare Disparities Report, 2010 216
need for standardized collection and reporting of racial and ethnic data, the need for more granular detail on

racial and ethnic subgroups has become apparent. This is an area where the adoption and use of health IT

can be beneficial. 

Another area of patient care that could be improved with the adoption and use of health IT is care

coordination. A Commonwealth Fund study found that health IT can facilitate care coordination within a

practice, but a lack of interoperability makes exchange of information between health care facilities difficult.

Evidence has also shown that the adoption and effective use of health IT can help reduce medical errors and

adverse events, enable better documentation and file organization, provide patients with information that

assists their adherence to medication regimens and scheduled appointments, and assist doctors in tracking

their treatment protocol.1

Having an adequate number of providers is an important aspect of the health system infrastructure and can

be an indicator of quality of care. It is also important to have a large enough and appropriately distributed

workforce to respond to expected increases in patient demand. Previous reports have presented data on

diversity in the physician, nursing, and dental professions workforce. This year, the National Healthcare

Quality Report (NHQR) and National Healthcare Disparities Report (NHDR) present data on the geographic

and racial/ethnic distribution of the pharmacy workforce. 

i Available at the National Academies Press Web site at http://www.nap.edu/openbook.php?isbn=030908265X. 

National Healthcare Disparities Report, 2010 217
work safe, blame-free reporting and communication about error, collaboration and teamwork across

disciplines, and adequate resources to prevent adverse events. 

AHRQ developed the Hospital Survey on Patient Safety Culture to help hospitals assess the culture of safety

in their facilities. AHRQ began producing comparative database reports in 2007 to help hospitals assess their

performance relative to similar institutions.

In this NHDR, we present data from the Hospital Survey on Patient Safety Culture: 2010 User Comparative

Database Report.

2 This report is based on survey responses collected in 2009 from more than 330,000

hospital staff in 885 hospitals representing 15% of the Nation’s hospitals. The average hospital response rate

was 56%, with an average of 383 completed surveys per hospital. 

Most hospitals administered Web surveys, which resulted in lower response rates (50%) compared with

response rates from paper (63%) or mixed-mode surveys (56%). In addition, most hospitals administered the

survey to all staff or a sample of all staff from all hospital departments. Nurses accounted for more than onethird of respondents, followed by “other.” More than three-quarters of respondents had direct interaction

with patients.

Results are presented for the 12 patient safety culture composites addressed in the survey, expressed as

average percent positive response. Percent positive refers to the percentage of responses that agree or

strongly agree with a positively worded item (e.g., “People support one another in this work area”) and the

percentage that disagree or disagree strongly with a negatively worded item (e.g., “We have safety problems

in this work area”). Hospitals contributing data to the comparative database mirror the population of U.S.

hospitals as a whole, but participation is entirely voluntary. Thus, it may not be possible to generalize

findings to all types of facilities.

National Healthcare Disparities Report, 2010 218
Source: Agency for Healthcare Research and Quality, Hospital Survey on Patient Safety Culture: 2010 User Comparative Database

Report.

● Nongovernment hospitals had higher percentages of positive response for Teamwork Within Units

(80%; Figure 8.1) compared with government hospitals (79%) but government hospitals had a higher

percentage of positive response for Supervisor Expectations and Actions Promoting Patient Safety

(76%) than nongovernment hospitals (75%). Teamwork Within Units is the extent to which staff

support each other, treat each other with respect, and work together. Supervisor/Manager Expectations

and Actions Promoting Patient Safety refers to the extent to which supervisors/managers consider staff

suggestions for improving patient safety, praise staff for following patient safety procedures, and do not

overlook patient safety problems.

● Government hospitals had higher percentages of positive response for Handoffs and Transitions (47%)

compared with nongovernment hospitals (44%). For Nonpunitive Response to Error, both government

and nongovernment hospitals had 44% positive response. 

● Across all composites, government hospitals had a slightly higher percent positive response than

nongovernment hospitals (64% compared with 63%; data not shown). 

National Healthcare Disparities Report, 2010 219
directed at improving patient care, including computerized reminders and advice regarding drug selection,

dosage, interactions, allergies, and the need for subsequent orders.6 In addition, once an e-prescription is in

the system, it will follow the patient, avoiding many of the “handoff errors.”

Office-Based Physicians With Electronic Prescribing Systems

Populations that often experience health care disparities, including minorities, low-income families, rural

residents, and older adults, can benefit from their health care providers adopting health information

technologies such as e-prescribing. E-prescribing can improve medication therapy by sending prescriptions

directly to pharmacies, alerting physicians to possible adverse drug events, and allowing physicians to select

drugs that are of lower cost but equally effective.

National Healthcare Disparities Report, 2010 220
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Ambulatory Medical Care Survey,

Electronic Medical Record Mail Survey Supplement, preliminary 2009.

Note: Percent non-Hispanic White population for physician office’s ZIP Code tabulation area is estimated from the 2000 U.S. Census.

Adopting Computerized Systems 

● Preliminary estimates from 2009 indicated that office-based physicians ages 35-44 had the highest

percentage of adoption of computerized systems for ordering prescriptions, sending prescriptions

electronically, and warning of drug interactions or contraindications (Figure 8.2). The percentage of the

non-Hispanic White population was not shown to significantly affect adoption. 

Ordering Prescriptions

● Preliminary estimates from 2009 indicate that the percentage of office-based physicians ages 35-44 who

had a computerized system for ordering prescriptions was significantly higher than that of physicians

age 55 and over. 

● The percentage of physicians who had a computerized system for ordering prescriptions was

comparable in areas with populations of less than 50% non-Hispanic Whites and areas with populations

of 50% or more non-Hispanic Whites. 

National Healthcare Disparities Report, 2010 221
metropolitan areas who had a computerized system for ordering prescriptions was significantly higher

than that of physicians in nonmetropolitan areas. 

● Physicians in the West also had a significantly higher percentage of computerized systems for ordering

prescriptions than physicians in the South. 

● Physicians in practices with more than 10 physicians had a significantly higher percentage of

computerized systems for ordering prescriptions than practices with 10 or fewer physicians. 

Medication Management in Hospitals

Patient handoffs and transitions of care have been identified as placing patients at increased risk of adverse

events. Once a patient is admitted to the hospital, medication plays a vital role in his or her recovery. Doses

of patients’ medications may be altered, new drugs added, and others discontinued. Electronic medication

management can aid in the reduction of adverse events by providing accurate, current medication

information as patient care is transferred from one health care team to another. 

Hospitals that are members of the Council of Teaching Hospitals (COTH) consist mainly of not-for-profit

hospitals, including some government hospitals. Many are located in inner-city areas where they serve large

populations that include minorities and Medicaid recipients who experience significant health care

disparities. COTH hospitals provide a substantial portion of care to underserved populations. According to

the Association of American Medical Colleges, in 2007, teaching hospitals constituted just 6% of all

hospitals but incurred 41% of charity care costs. 

National Healthcare Disparities Report, 2010 222
Key: COTH = Council of Teaching Hospitals; CPOE =

computerized physician order entry.

Source: American Hospital Association, 2008 Information

Technology Supplement.

National Healthcare Disparities Report, 2010 223

Key:

computerized physician order entry.

Source:

computerized physician order entry.

Source:
● Hospitals run by the Federal Government also had a much higher percentage (67.4%) of full

implementation of electronic drug decision support systems compared with non-Federal (18.1%), notfor-profit (28.1%), and investor-owned hospitals (19.4%). 

● Nearly 30% of children’s general hospitals and 27.2% of general medical and surgical hospitals had a

fully implemented electronic drug decision support system. 

● Between 11% and 19% of psychiatric, rehabilitation, and acute long-term care hospitals had a fully

implemented electronic drug decision support system. 

CPOE for Medication

● In 2008, 18.4% of hospitals had a fully implemented computerized physician order entry (CPOE)

system. 

● Nearly 20% of COTH member hospitals (18.4%) had a fully implemented CPOE system compared

with 15.9% of nonmember hospitals. 

● Hospitals run by the Federal Government had a much higher percentage (89.1%) of full implementation

of CPOE systems compared with non-Federal (16.0%), not-for-profit (17.7%), and investor-owned

hospitals (14.3%). 

● More than 35% of children’s general hospitals, 21.7% of acute long-term care hospitals, and 21.3% of

rehabilitation hospitals had a fully implemented CPOE system. Nearly 20% of psychiatric hospitals

(19.2%) and 17.8% of general medical and surgical hospitals had full implementation of CPOE

systems. 

National Healthcare Disparities Report, 2010 224
pppy pyg

decision support. In the South, 24.4%, and in the West, 23% of hospitals had a fully implemented

electronic system for drug decision support. 

Workforce Diversity

In 2008, the Nation’s overall minority population was 104.6 million, or 34 percent of the total population.

Nearly half of the Nation’s children younger than 5 were members of a racial or ethnic minority group;

among all children under 18, 44% were part of a racial or ethnic minority group. It is estimated that by

2050, half of Americans will be members of minority groups.7 Minority providers are more likely than their

White colleagues to practice in underserved minority communities.8, 9 Health care workforce diversity also is

considered to be important for health care research, education, administration, and policy, both to provide

role models and to shape a health care system that meets the needs of all individuals. 

In 2007, 15.6% of the U.S. labor force was foreign born. Of the 281 million people age 5 and over in the

United States in 2007, 55.4 million individuals (20%) reported speaking a language other than English at

home. Workforce diversity increases the opportunities for race- and language-concordant health care visits.

It also can improve cultural competency at the system, organization, and provider levels in several ways.

These include appropriate program design and policies, organizational commitment to culturally competent

care, and cross-cultural education of colleagues.10 As such, diversity is an important element of a patientcentered health care encounter.

Previous reports have presented data on diversity in the physician, nursing, and dental professions workforce.

This year, the NHDR presents data on diversity in the pharmacy workforce.

National Healthcare Disparities Report, 2010 225
Key: AI/AN = American Indian or Alaska Native; NHOPI = Native Hawaiian or Other Pacific Islander.

Source: U.S. Census, American Community Survey, 2006-2008.

Note: All populations are non-Hispanic except for the population specifically noted as Hispanic.

● Although the number of pharmacists has increased over time, the racial and ethnic makeup of the

pharmacist population continues to be disproportionate to the U.S. population. In 2008, 74.3% of the

approximately 301,000 pharmacists in the United States were White, 6.2% were Black, 14.4% were

Asian, and 3.7% were Hispanic (Figure 8.4). Compared with the general U.S. population, Whites and

Asians were overrepresented, and Blacks and Hispanics were underrepresented.

National Healthcare Disparities Report, 2010 226
3. Institute of Medicine, Board on Health Care Services. Informing the future: critical issues in health. 3rd ed. Washington, DC:

National Academies Press; 2007.

4. Balfour DC 3rd, Evans S, Januska J, et al. Health information technology—results from a roundtable discussion. J Manag Care

Pharm 2009 Jan-Feb;15(1 Suppl A):10-17.

5. Institute of Medicine, Board on Health Care Services. Preventing medication errors. Quality Chasm Series. Washington, DC:

National Academies Press; 2006.

6. Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on

medication safety: a systematic review. Arch Intern Med 2003 Jun 23;163(12):1409-16.

7. Day JC. Population projections of the United States by age, sex, race, and Hispanic origin: 1995 to 2050. U.S. Bureau of the

Census, Current Population Reports, P25-1130. Washington, DC: Government Printing Office; 1996. Available at:

www.census.gov/prod/1/pop/p25-1130.pdf. Accessed January 12, 2011.

8. Komaromy M, Grumbach K, Drake M, et al. The role of black and Hispanic physicians in providing health care for

underserved populations. N Engl J Med 1996 May 16;334(20):1305-10.

9. Turner CB, Turner BF. Who treats minorities? Cult Divers Ment Health 1996;2(3):175-82.

10. Nickens HW. The rationale for minority-targeted programs in medicine in the 1990s. Jama 1992 May 6;267(17):2390, 5.

11. Altavela JJ, MK, Ritter M. A prospective trial of a clinical pharmacy intervention in a primary care practice in a capitated

payment system. J Manag Care Pharm 2008;14(9):831-43.

National Healthcare Disparities Report, 2010 227
National Healthcare Disparities Report, 2010 228
Access to health care means having “the timely use of personal health services to achieve the best health

outcomes.”1 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.2

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 are able to gain access to health care.

● Utilization measures of the ultimate outcome of good access to care (i.e., the successful receipt of

needed services).

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), near poor = 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.

National Healthcare Disparities Report, 2010 229
National Healthcare Disparities Report, 2010 230
Denominator: Analyses by race, ethnicity, and income performed for civilian noninstitutionalized population under age 65. Analyses

by education performed for civilian noninstitutionalized population ages 25-64.

Note: NHIS respondents are asked about health insurance coverage at the time of interview. Respondents are considered uninsured if

they lack 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, or if their only coverage is through the Indian Health Service. 

● Overall, there was no significant change from 1999 to 2008 in the percentage of people with health

insurance. In 2008, about 83.2% of people under age 65 had health insurance (data not shown).

● In 2008, Asians under age 65 were more likely than Whites to have health insurance (86.1% compared

with 83.3%; Figure 9.1). American Indians and Alaska Natives under age 65 were less likely than

Whites to have health insurance (71.6% compared with 83.3%). There were no statistically significant

differences for other racial groups.

● In 2008, Hispanics under age 65 were less likely than non-Hispanic Whites to have health insurance

(66.7% compared with 87.5%).

● From 1999 to 2008, while the percentage of people with health insurance increased for poor people

(from 66.2% to 71.0%), the percentage worsened for middle-income people (from 86.4% to 83.4%). In

2008, the percentage of people with health insurance was significantly lower for poor, near-poor, and

middle-income people than for high-income people (71.0%, 69.4%, and 83.4%, respectively, compared

with 93.8%).

● In 2008, the percentage of people 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 (56.9% compared

with 89.0%).

National Healthcare Disparities Report, 2010 231
CHIS data. 

In 2008, an estimated 4.6 million people, or about 34% of the Asian population in the United States, lived in

California.10 The proportion of many Asian subpopulations in California is also greater than the proportion in

the overall U.S. population. For example, the Vietnamese population is 1.3% of California’s population

compared with only 0.4% of the U.S. population, and the Filipino population is 2.7% of California’s

population compared with only 0.7% of the U.S. population. 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. 

National Healthcare Disparities Report, 2010 232
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007. 

Denominator: Civilian noninstitutionalized adults under age 65 in California.

Note: Data for Japanese people did not meet criteria for statistical reliability, data quality, or confidentiality.

● In California, Asians overall were less likely than non-Hispanic Whites to have health insurance in the

past year (89.2% compared with 94.2%; Figure 9.2). 

● Among Asians, Koreans were the least likely to have health insurance compared with non-Hispanic

Whites (68.3% compared with 94.2%). This finding was also true across all income groups (data not

shown). 

● Vietnamese people were also less likely than non-Hispanic Whites to have health insurance (87.7%

compared with 94.2%).

Hispanic Subgroups

The Hispanic population in the United States is highly heterogeneous. Almost 60% of all Hispanics in the

country are of Mexican extraction, making this group the largest subpopulation. People originating from

Puerto Rico, Central America, and South America are the next largest subgroups. Variation is seen in access

to care among Hispanics related to country of origin. Findings are presented below on differences among

Hispanic subpopulations on health insurance.

In 2008, California’s Hispanic population was more than twice the percentage in the United States overall

(36.6% in California compared with 15.4% of the U.S. population).10 Almost 30% of the Hispanic population

in the United States lives in California.11

National Healthcare Disparities Report, 2010 233
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007. 

Denominator: Civilian noninstitutionalized adults under age 65 in California.

Note: Data for Puerto Ricans did not meet criteria for statistical reliability, data quality, or confidentiality.

● In California, Hispanics overall were less likely than non-Hispanic Whites to have health insurance in

the past year (82.0% compared with 94.2%; Figure 9.3). 

● Among Hispanics, Central Americans were the least likely to have health insurance compared with nonHispanic Whites (73.6% compared with 94.2%), followed by Mexicans (81.1% compared with 94.2%). 

● Mexicans also were less likely than non-Hispanic Whites to have health insurance across all income

groups (data not shown).

National Healthcare Disparities Report, 2010 234
Source: University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, 2007. 

Denominator: Civilian noninstitutionalized adults under age 65 in California.

● People under age 65 who spoke English well or very well and people who did not speak English well or

did not speak English at all were less likely than native English speakers to have health insurance

(85.4% and 58.5%, respectively, compared with 92.2%; Figure 9.4).

● People under age 65 who were not born in the United States were less likely to have health insurance

than those who were born in the United States (75.4% compared with 93.4%).

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.

National Healthcare Disparities Report, 2010 235
National Healthcare Disparities Report, 2010 236
● In 2007, Asians were less likely than Whites to be uninsured all year (11.9% compared with 15.5%;

Figure 9.5). There was no statistically significant difference between Blacks and Whites.

● In 2007, Hispanics were much more likely than non-Hispanic Whites to be uninsured all year (29.5%

compared with 11.8%).

● The percentage of poor people and near-poor people who were uninsured all year was about four times

as high as that for high-income people (25.2% and 26.4%, respectively, compared with 6.6%). The

percentage of middle-income people uninsured all year was more than twice as high as that for highincome people (15.8% compared with 6.6%).

● 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 (33.6% and 21.6%,

respectively, compared with 10.8%). 

● From 2002 to 2007, 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

2007, 33.7% compared with 12.2%).

Also, in the NHQR:

● Children ages 0-17 were less likely to be uninsured than adults ages 18-44 and age 65 and over.

● From 2002 to 2007, females were less likely to be uninsured all year than males.

● Among metropolitan areas, residents of large fringe metropolitan areas were least likely to be uninsured

all year while residents of large central metropolitan areas were most likely to be uninsured all year.

National Healthcare Disparities Report, 2010 237
Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, pooled 2002-2007 fiscal year files.

Note: Adjusted percentages are predicted marginals from a statistical model that includes the covariates race/ethnicity, family income,

education, health insurance, and residence location.

● In the multivariate model used, after adjustment, 16% of non-Hispanic Blacks and 27% of Hispanics

would have been uninsured all year compared with 14% of non-Hispanic Whites (Figure 9.6).

● After adjustment, about 30% of poor, 28% of near-poor, and 16% of middle-income individuals would

have been uninsured all year compared with 8% of those with high income.

● After adjustment, 21% 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 at least some college

education.

● After adjustment, 18% of people living in nonmetropolitan areas would have been uninsured all year

compared with 17% of those living in metropolitan areas.

National Healthcare Disparities Report, 2010 238

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, pooled 2002-2007 fiscal year files.
Key: AI/AN = American Indian or Alaska Native.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2007.

Denominator: Civilian noninstitutionalized population.

Note: Total financial burden includes premiums and out-of-pocket costs for health care services.

● Overall, in 2007, 16.3% 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 9.7).

● In 2007, the percentage of people under age 65 whose family’s health insurance premium and out-ofpocket medical expenses were more than 10% of total family income was lower for American Indians

and Alaska Natives than for Whites (9.9% compared with 16.8%). The percentage was also lower for

Hispanics than for non-Hispanic Whites (12.8% compared with 17.8%).

● 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 about five times as high for poor

individuals (29.7%), about four times as high for near-poor individuals (23.6%), and about three times

as high for middle-income individuals (18.7%) compared with high-income individuals (6.7%).

National Healthcare Disparities Report, 2010 239
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.

Figure 9.8. People with a specific source of ongoing care, by race, ethnicity, income, and education,

1999-2008

National Healthcare Disparities Report, 2010 240
008

Denominator: Analyses by race, ethnicity, and income performed for civilian noninstitutionalized population of all ages. Analyses by

education performed for civilian noninstitutionalized population ages 25-64.

Note: Measure is age adjusted.

● Overall, 86.1% percent of people had a specific source of ongoing care in 2008 (data not shown).

● In 2008, the percentage of people with a specific source of ongoing care was lower for Blacks than

Whites (84.7% compared with 86.3%; Figure 9.8) and significantly lower for Hispanics than for nonHispanic Whites (77.1% compared with 88.6%).

● In 2008, the percentage of people with a specific source of ongoing care was significantly lower for

poor people than for high-income people (77.5% compared with 92.1%).

● In 2008, the percentage of people with a specific source of ongoing care was lower for people with less

than a high school education and for people with a high school education than for people with at least

some college education (74.2% and 82.2% respectively, compared with 88.9%).

Also, in the NHQR:

● In 2008, the percentage of people with a specific source of ongoing care was much lower for uninsured

people than for people with private insurance.

● In 2008, for people 65 and over, the percentage of people with a specific source of ongoing care was

lower for people with Medicare only than for people with Medicare and private insurance.

National Healthcare Disparities Report, 2010 241
National Healthcare Disparities Report, 2010 242
Key: AI/AN = American Indian or Alaska Native.

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2007.

Denominator: Analyses by race, ethnicity, and income performed

for civilian noninstitutionalized population of all ages. Analyses by

education performed for civilian noninstitutionalized population age

18 and over.

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 2007, about 76.3% of people had a usual primary care provider (Figure 9.9).

● In 2007, Blacks and Asians were less likely than Whites to have a usual primary care provider (73.3%

and 69.4%, respectively, compared with 77.2%).

National Healthcare Disparities Report, 2010 243

Denominator:

Key:

Source:

Expenditure Panel Survey, 2002-2007.

for civilian noninstitutionalized population of all ages. Analyses by

education performed for civilian noninstitutionalized population age

18 and over.

Note: 

care that a person usually goes to for new health problems,

preventive health care, and referrals to other health professionals. 

Key:

Source:

Expenditure Panel Survey, 2002-2007.

Denominator:

for civilian noninstitutionalized population of all ages. Analyses by

education performed for civilian noninstitutionalized population age

18 and over.

Note: 

care that a person usually goes to for new health problems,

preventive health care, and referrals to other health professionals. 
● Females were more likely to have a usual primary care provider than males.

● In 2007, residents of nonmetropolitan areas were more likely to have a usual primary care provider than

residents of metropolitan areas overall.

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.

National Healthcare Disparities Report, 2010 244
National Healthcare Disparities Report, 2010 245
● In 2007, the percentage of people who were unable to get or delayed in getting needed medical care,

dental care, or prescription medicines was lower for Asians than for Whites (5.5% compared with

10.3%; Figure 9.10).

● In 2007, the percentage of people who were unable to get or delayed in getting needed medical care,

dental care, or prescription medicines was lower for Hispanics than for non-Hispanic Whites (8.9%

compared with 10.6%).

● In 2007, the percentage of people who were unable to get or delayed in getting needed medical care,

dental care, or prescription medicines was significantly worse for poor (14.7%), near-poor (13.2%), and

middle-income (9.7%) people than for high-income people (7.2%).

● People with less than a high school education and people with a high school education were more likely

than those with some college education to report they were unable to get or delayed in getting needed

care (13.7% and 11.8%, respectively, compared with 10.6%).

● In 2007, the percentage of people who were unable to get or delayed in getting needed medical care,

dental care, or prescription medicines was lower for people who spoke a language other than English at

home than for people who spoke English at home (8.0% compared with 10.3%).

Also, in the NHQR:

● For people under age 65, the percentage of people who were unable to get or delayed in getting needed

medical care, dental care, or prescription medicines was more than twice as high for people with no

health insurance as for people with private insurance. The percentage was also worse for people with

public insurance than for people with private insurance.

National Healthcare Disparities Report, 2010 246
11. Facts for Features, Hispanic Heritage Month 2007. Suitland, MD: U.S. Census Bureau; 2007. Available at:

www.census.gov/newsroom/releases/archives/facts_for_features_special_editions/cb07-ff14.html. Accessed August 13, 2009.

12. 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):2712-19.

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

8.

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

98.

15. De Maeseneer J, De Prins L, Gossett 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.

16. 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.

17. Ettner SL. The timing of preventive services for women and children: the effect of having a usual source of care. Am J Public

Health 1996;86(12):1748-54.

18. U.S. Department of Health and Human Services. Healthy People 2010: understanding and improving health. 2nd ed.

Washington, DC: Government Printing Office; November 2000. Available at: www.healthypeople.gov/2010/. Accessed August

17, 2009.

19. Mainous AG, Baker R, Love MM, et al. Continuity of care and trust in one’s physician: evidence from primary care in the

United States and the United Kingdom. Fam Med 2001;33(1):22-27.

20. Starfield B. Primary care: balancing health needs, services and technology. New York: Oxford University Press; 1998.

21. Forrest CB, Starfield B. The effect of first-contact care with primary care clinicians on ambulatory health care expenditures. 

J Fam Pract 1996;43(1):40-48.

National Healthcare Disparities Report, 2010 247
National Healthcare Disparities Report, 2010 248
Quality Report (NHQR) this year.ii Chapters 2 through 9 of this report examine racial, ethnic, socioeconomic,

gender, 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 presented in these chapters where data are

available.

This chapter summarizes differences for each of the racial and ethnic and low-income populations for which

there is relatively more data from multiple sources. For other relatively smaller populations, such as Native

Hawaiians and Other Pacific Islanders (NHOPIs), American Indians and Alaska Natives (AI/ANs), and

people with disabilities, this chapter highlights some unique data and findings.

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 Data Tables appendix includes detailed tables that allow examination of racial, ethnic,

and socioeconomic disparities both in the general population and across priority populations for most

measures.

i Available at: http://origin.www.gpo.gov/fdsys/pkg/USCODE-2000-title42/html/USCODE-2000-title42-chap6A-subchapVIIpartA-sec299a-1.htm.

ii Populations of inner-city areas are also identified as one of AHRQ’s priority populations pursuant to 42 U.S.C. 299(c)(l)(A).

However, no data are available to support findings for this population.

National Healthcare Disparities Report, 2010 249
● Racial and ethnic minorities.

● Low-income groups.

● Residents of rural areas.

● Individuals with disabilities or special health care needs.

Measures related to women, children, and older adults are presented in other chapters of this report and

include comparisons by gender and age.

iii Racial groups are White, Black, Asian, Native Hawaiian or Other Pacific Islander, American Indian and 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, near poor, 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 2009 the Federal poverty threshold for a family of

two adults and two children was $22,050.

v Rural areas can be defined differently depending on the data source. The NHDR uses Office of Management and Budget

revised definitions of metropolitan and micropolitan statistical areas. Noncore areas are rural areas. 

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.

National Healthcare Disparities Report, 2010 250
Whites to be poor or near poor.6 In addition, Hispanics, Blacks, and some Asian subgroups are less likely

than non-Hispanic Whites to have a high school education.7

Previous chapters of the NHDR describe health care differences by racial and ethnic categories as defined by

the Office of Management and Budget and used by the U.S. Census Bureau.8 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.vii Criteria for importance are that the difference is statistically significant at the

alpha ≤ 0.05 level (two-tailed test) and that the relative difference from the reference group is 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 core report

measure, racial, ethnic, and socioeconomic groups are compared with a designated comparison group. The

time periods range from 2000-2002 to 2006-2008, depending on the data source. Consistent with Healthy

People 2010, disparities are measured in relative terms as the percentage difference between each group and

a comparison group. Changes in disparity are measured by subtracting the percentage difference from the

comparison group at the baseline year from the percentage difference from the comparison group at the most

recent year. The change in each disparity is then divided by the number of years between the baseline and

most recent estimate to calculate change in disparity per year.

vii Data are presented for each minority group except for people of multiple races due to unreliable estimates for this group.

National Healthcare Disparities Report, 2010 251
Blacks or African Americans

Previous NHDRs showed that Blacks had poorer quality of care and worse access to care than Whites for

many measures tracked in the reports. Findings based on core report measures (Table 1.3) of quality of and

access to health care are shown below.

National Healthcare Disparities Report, 2010 252
National Healthcare Disparities Report, 2010 253

substance abuse for depression in the last 12 months

People age 12 and over treated for substance abuse who completed treatment course

Respiratory diseases Adults age 65 and over who ever received pneumococcal vaccination

Hospital patients with pneumonia who received recommended hospital care 

Supportive and High-risk long-stay nursing home residents with pressure sores

palliative care Short-stay nursing home residents with pressure sores

Adult home health care patients who were admitted to the hospital

Hospice patients who received the right amount of medicine for pain

Timeliness Adults who needed care right away for an illness, injury, or condition in the last 12 

months who got care as soon as wanted

Emergency department visits where patients left without being seen

Access People with a usual primary care provider

People with a specific source of ongoing care
Worsening = Black-White difference becoming larger at an average annual rate greater than 1%.

Note: The time period for this figure is the most recent and oldest years of data used in the NHDR. Only 53 core report measures

could be tracked over time for Blacks.

Asians

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. Findings based on core report measures of quality

and access to health care that support estimates for either Asians or Asians and Pacific Islanders in aggregate

are shown below.

Table 10.2. Measures for which Asians were worse than Whites for most recent year and their trends

over time

Topic Asians worse than Whites and getting better

Cancer Adults age 50 and over who ever received colorectal cancer screening

Patient safety Adult surgery patients who received appropriate timing of antibiotics

Topic Asians worse than Whites and staying the same

Respiratory diseases Adults age 65 and over who ever received pneumococcal vaccination

Hospital patients with pneumonia who received recommended hospital care

Access People with a usual primary care provider

National Healthcare Disparities Report, 2010 254
Worsening = Asian-White difference becoming larger at an average annual rate greater than 1%.

Note: The time period for this figure is the most recent and oldest years of data used in the NHDR. Only 24 core report measures

could be tracked over time for Asians.

Native Hawaiians and Other Pacific Islanders

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, the Office of Management and Budget promulgated new standards for Federal

data on race and ethnicity and mandated that information about NHOPIs be collected separately from

information about Asians.8 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.

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. This year, the NHDR features data from the Behavioral Risk Factor Surveillance

System (BRFSS) to supplement the NHDR information for the NHOPI population. Preventive care and

access to care measures were selected to highlight quality of care for people who identified themselves as

NHOPI (including people of mixed race who identified primarily as NHOPI). This year, the measures

include cholesterol screening, pneumonia admissions, and cost as a barrier to medical care.

National Healthcare Disparities Report, 2010 255
Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System, 2005, 2007, and 2009.

Denominator: Adults age 18 and over in Hawaii.

Note: These data are self-reported from a survey of adults in a household.

National Healthcare Disparities Report, 2010 256

Key: NHOPI = Native Hawaiian or Other Pacific Islander.
Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Hawaii State Inpatient Databases, 2005-

2007, and AHRQ Quality Indicators, version 3.1.

Denominator: Adults age 18 and over in Hawaii based on the Hawaii Health Survey.

Note: Excludes sickle cell or hemoglobin-S conditions, transfers from other institutions, and obstetric admissions. Rates are adjusted

by age and gender using the total U.S. population for 2000 as the standard population.

● From 2005 to 2007, there was significant improvement among all groups in the rate of hospital

admissions with bacterial pneumonia in Hawaii.

● In 2007, NHOPIs overall had a higher rate of hospital admission with bacterial pneumonia than Whites

in Hawaii (294.4 per 100,000 population compared with 229.1 per 100,000 population; Figure 10.4).

National Healthcare Disparities Report, 2010 257

Key: NHOPI = Native Hawaiian or Other Pacific Islander.
Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System, 2007-2009.

Denominator: Adults age 18 and over in Hawaii.

Note: These data are self-reported from a survey of adults in a household.

● From 2007 to 2009, the percentage of adults who needed to see a doctor in the past year but could not

because of cost in Hawaii worsened overall and for Whites, but improved for NHOPIs (from 16.7% to

15.7%; Figure 10.5).

● In 2007, the percentage of adults who needed to see a doctor in the past year but could not because of

cost in Hawaii was higher for NHOPIs than for Whites (15.7% compared with 13.1%).

National Healthcare Disparities Report, 2010 258
Cancer Adults age 50 and over who ever received colorectal cancer screening 

Patient safety Adult surgery patients who received appropriate timing of antibiotics

Figure 10.6. Change in American Indian or Alaska Native-White disparities over time for all core

measures

Improving = AI/AN-White difference becoming smaller at an

average annual rate greater than 1%.

Same = AI/AN-White difference not changing.

Worsening = AI/AN-White difference becoming larger at an

average annual rate greater than 1%.

Key: AI/AN = American Indian or Alaska Native.

Note: The time period for this figure is the most recent and oldest

years of data used in the NHDR. Only 27 core report measures

could be tracked over time for AI/ANs.

National Healthcare Disparities Report, 2010 259

Improving

average annual rate greater than 1%.

Same

Worsening

average annual rate greater than 1%.

Key:

Note:

years of data used in the NHDR. Only 27 core report measures

could be tracked over time for AI/ANs.

Improving

average annual rate greater than 1%.

Same

Worsening

average annual rate greater than 1%.

Key:

Note:

years of data used in the NHDR. Only 27 core report measures

could be tracked over time for AI/ANs.
Diabetes Adults age 40 and over with diagnosed diabetes who received all three 

recommended services for diabetes in the calendar year 

Heart disease Hospital patients with heart attack and left ventricular systolic dysfunction 

who were prescribed angiotensin-converting enzyme inhibitor or angiotensin 

receptor blocker at discharge

Hospital patients with heart failure who received recommended hospital care 

HIV and AIDS New AIDS cases per 100,000 population age 13 and over

Mental health and substance Adults with a major depressive episode in the last 12 months who received 

abuse treatment for depression in the last 12 months

Respiratory disease Adults age 65 and over who ever received pneumococcal vaccination

Hospital patients with pneumonia who received recommended hospital care 

Lifestyle modification Adults with obesity who ever received advice from a health provider to 

exercise more

Supportive and palliative care Long-stay nursing home residents with physical restraints

High-risk long-stay nursing home residents with pressure sores

Short-stay nursing home residents with pressure sores

Adult home health care patients who were admitted to the hospital

Hospice patients who received the right amount of medicine for pain

National Healthcare Disparities Report, 2010 260
Figure 10.7. Change in Hispanic–non-Hispanic White disparities over time for all core measures

Improving = Hispanic-non-Hispanic White difference becoming smaller at an average annual rate greater than 1%.

Same = Hispanic-non-Hispanic White difference not changing.

Worsening = Hispanic-non-Hispanic White difference becoming larger at an average annual rate greater than 1%.

Note: The time period for this figure is the most recent and oldest years of data used in the NHDR. Only 47 core report measures

could be tracked over time for Hispanics.

National Healthcare Disparities Report, 2010 261

Improving = Hispanic-non-Hispanic White difference becoming smaller at an average annual rate greater than 1%.
Table 10.5. Measures for which poor people were worse than high-income people for most recent year

and their trends over time

Topic Poor worse than high income and getting better

Maternal and child health Children ages 2-17 who had a dental visit in the calendar year

Lifestyle modification Adults with obesity who ever received advice from a health provider about 

healthy eating 

Topic Poor worse than high income and staying the same

Diabetes Hospital admissions for short-term complications of diabetes per 100,000 

population

Heart disease Deaths per 1,000 adult hospital admissions with acute myocardial infarction

Maternal and child health Children ages 2-17 for whom a health provider ever gave advice about exercise

Children ages 2-17 for whom a health provider ever gave advice about healthy 

eating

Children ages 19-35 months who received all recommended vaccines

Mental health and Adults with a major depressive episode in the last 12 months who received 

substance abuse treatment for depression in the last 12 months

viii Household income less than Federal poverty thresholds.

ix Household income 400% of Federal poverty thresholds and higher.

National Healthcare Disparities Report, 2010 262
Access People under age 65 with health insurance

People under age 65 who were uninsured all year

People with a specific source of ongoing care

People with a usual primary care provider

People unable to get or delayed in getting needed care due to financial or 

insurance reasons

People who were unable to get or delayed in getting needed medical care, 

dental care, or prescription medicines in the last 12 months

Topic Poor worse than high income and getting worse

Cancer Women age 40 and over who received a mammogram in the last 2 years

Adults age 50 and over who ever received colorectal cancer screening

Diabetes Adults age 40 and over with diagnosed diabetes who received all three 

recommended services for diabetes in the calendar year 

National Healthcare Disparities Report, 2010 263
Worsening = Poor-high-income difference becoming larger at an average annual rate greater than 1%.

Note: The time period for this figure is the most recent and oldest years of data used in the NHDR. Only 27 core report measures of

quality and access could be tracked over time for poor individuals. No acute care measures reported data for income.

Residents of Rural Areas

About one in five Americans lives in a nonmetropolitan area.16 Compared with their urban counterparts, rural

residents are more likely to be older, be poor,17 and be in fair or poor health, and have chronic conditions.16

Rural residents are less likely than their urban counterparts to receive recommended preventive services and

on average report fewer visits to health care providers.18

Although 20% of Americans live in rural areas,x only 9% of physicians in America practice in those

settings.19 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. Cost-based Medicare reimbursement incentives are also

available for rural health clinics, critical access hospitals, sole community hospitals, and Medicare-dependent

hospitals and physicians in health professional shortage areas.

x Many terms are used to refer to the continuum of geographic areas. For Census 2000, the U.S. Census Bureau’s classification

of “rural” consists of all territory, population, and housing units located outside of urban areas and urban clusters. The Census

Bureau classified as “urban” all territory, population, and housing units located within (1) core census block groups or blocks

that have a population density of at least 1,000 people per square mile and (2) surrounding census blocks that have an overall

density of at least 500 people per square mile.

National Healthcare Disparities Report, 2010 264
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. Micropolitan and noncore areas are typically

regarded as “rural.”

National Healthcare Disparities Report, 2010 265
Children ages 2-17 for whom a health provider ever gave advice about the amount 

and kind of exercise, sports, or physically active hobbies they should have

Children ages 2-17 for whom a health provider ever gave advice about healthy eating

Children who ever had their height and weight measured by a health provider

Children 41-80 lb for whom a health provider ever gave advice about using booster 

seats 

Children ages 2-17 for whom a health provider ever gave advice about using a 

helmet when riding a bicycle or motorcycle

Mental health and Suicide deaths per 100,000 population

substance abuse

Respiratory Hospital admissions for immunization-preventable influenza per 100,000 population 

diseases age 65 and over

Deaths per 1,000 adult hospital admissions with pneumonia

Lifestyle Adults with obesity who ever received advice from a health provider to exercise more

modification

xiii Data were insufficient to assess change over time.

National Healthcare Disparities Report, 2010 266
Better = Noncore area is better than large fringe metropolitan area at a relative rate greater than 10%.

Same = No difference between noncore area and large fringe metropolitan area.

Worse = Noncore area is worse than large fringe metropolitan area at a relative rate greater than 10%.

Note: All measures with data for metropolitan areas are included (core and supporting measures).

xiv Data were insufficient to assess change over time.

National Healthcare Disparities Report, 2010 267
pyg y, ppqp

● 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 in basic activities 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 disability25 and

is consistent with the International Classification of Functioning, Disability, and Health separation of

activities and participation domains.26 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 limitations for adults are presented in the Patient Centeredness

chapter of both the NHQR and NHDR. In addition, the appendix tables include activity limitations as a stub

variable for all National Health Interview Survey and Medical Expenditure Panel Survey tables. 

In summarizing disparities for individuals with disabilities, we present comparisons between adults with

basic or complex activity limitations and adults with neither basic nor complex activity limitations.

National Healthcare Disparities Report, 2010 268
People who were unable to get or delayed in getting needed medical care in the 

last 12 months

People who were unable to get or delayed in getting needed dental care in the 

last 12 months

People who were unable to get or delayed in getting needed prescription medicines 

in the last 12 months

People with a usual source of care, excluding hospital emergency rooms, who 

has office hours nights or weekends

People with difficulty contacting their usual source of care over the telephone

National Healthcare Disparities Report, 2010 269
Adults who had a doctor’s office or clinic visit in the last 12 months whose health

providers spent enough time with them

Rating of health care by adults who had a doctor’s office or clinic visit in the last 

12 months

People with a usual source of care for whom health care providers explained and

provided all treatment options

Access People who were unable to get or delayed in getting needed medical care in the last

12 months

People who were unable to get or delayed in getting needed dental care in the last 

12 months

People who were unable to get or delayed in getting needed prescription medicines 

in the last 12 months

People with a usual source of care, excluding hospital emergency rooms, who has

office hours nights or weekends

People with difficulty contacting their usual source of care over the telephone

Adults who did not have problems seeing a specialist they needed to see in the last 

12 months

National Healthcare Disparities Report, 2010 270
Same = Difference between complex activity limitations and neither basic nor complex activity limitations not changing.

Worsening = Difference between complex activity limitations and neither basic nor complex activity limitations and no limitations

becoming larger at an average annual rate greater than 1%.

Note: The time period for this figure is the most recent and oldest years of data used in the NHDR. Measures include supporting

measures. Only 37 measures of quality and access could be tracked over time for individuals with activity limitations.

National Healthcare Disparities Report, 2010 271
www.census.gov/population/www/socdemo/race/Ombdir15.html. Accessed November 11, 2008.

9. Balabis J, Pobutsky K, Kromer Baker C, et al. The burden of cardiovascular disease in Hawaii 2007. Honolulu, HI: State of

Hawaii Department of Health; 2007.

10. Alexander GC, Casalino LP, Meltzer DO. Patient-physician communication about out-of-pocket costs. Jama 2003 Aug

20;290(7):953-8.

11. 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 Dec 13;296(22):2712-9.

12. Poverty thresholds 2006. Suitland, MD: U.S. Census Bureau; 2008. Available at:

www.census.gov/hhes/www/poverty/data/threshld/thresh06.html. Accessed November 12, 2008.

13. DeNavas-Walt C, Proctor B, Smith J. Income, poverty, and health insurance coverage in the United States: 2008. Suitland, MD:

U.S. Census Bureau, Economics and Statistics Administration; 2009. Available at: www.census.gov/prod/2009pubs/p60-

236.pdf. Accessed March 11, 2010.

14. Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Project Hope) 2002 MarApr;21(2):60-76.

15. Brown AF, Gross AG, Gutierrez PR, et al. Income-related differences in the use of evidence-based therapies in older persons

with diabetes mellitus in for-profit managed care. J Am Geriatr Soc 2003 May;51(5):665-70.

16. Committee on the Future of Rural Health Care, Institute of Medicine. Quality through collaboration: the future of rural health.

Washington, DC: National Academies Press; 2005.

17. Ziller EC, Coburn AF, Loux SL, et al. Health insurance coverage in rural America. Washington, DC: Kaiser Commission on

Medicaid and the Uninsured; 2003. Available at: www.kff.org/uninsured/4093.cfm. Accessed November 14, 2008.

18. Larson SL, Fleishman JA. Rural-urban differences in usual source of care and ambulatory service use: analyses of national data

using Urban Influence Codes. Med Care 2003 Jul;41(7 Suppl):III65-III74.

19. Van Dis J. Where we live: health care in rural vs. urban America. Jama 2002 Jan 2;287(1):108.

National Healthcare Disparities Report, 2010 272
National Healthcare Disparities Report, 2010 273
National Healthcare Disparities Report, 2010 274
Adult dialysis patients registered on a

waiting list for transplantation USRDS ✔ ✔ ✔ ✔

Hemodialysis patients with ESRD

adequate dialysis CPMP ✔ ✔ ✔ ✔

Hospital care for heart attack patients QIO ✔ ✔ ✔ ✔

Hospital care for heart failure patients QIO ✔ ✔ ✔ ✔

Deaths per 1,000 adult hospital admissions

with acute myocardial infarction HCUP ✔ ✔ ✔ ✔

New AIDS cases per 100,000 population CDC AIDS

ages 13 and over Surveillance ✔ ✔ ✔ ✔

Children ages 19-35 months who received 

all recommended vaccines NIS ✔ ✔ ✔ ✔ ✔

✔ Indicates that reliable data on measure are available for this group and included in summary across measures of

quality and access for this group.

Key: API=Asian or Pacific Islander; AI/AN=American Indian or Alaska Native; Poor=individuals with household

incomes <100% of Federal poverty thresholds.

National Healthcare Disparities Report, 2010 275
g

pneumococcal vaccination NHIS ✔ ✔ ✔ ✔

Hospital care for pneumonia patients QIO ✔ ✔ ✔ ✔

Patients with tuberculosis who 

completed a curative course of treatment CDC TB ✔ ✔ ✔ ✔

within 1 year of initiation of treatment Surveillance

Older women screened for osteoporosis MCBS ✔ ✔ ✔ ✔ ✔

Long-stay nursing home residents with CMS

physical restraints MDS ✔ ✔ ✔ ✔

High-risk long-stay nursing home CMS

residents with pressure sores MDS ✔ ✔ ✔ ✔

Short-stay nursing home residents CMS

with pressure sores MDS ✔ ✔ ✔ ✔

Adult home health care patients whose 

ability to walk or move around improved OASIS ✔ ✔ ✔ ✔

Adult home health care patients who were 

admitted to the hospital OASIS ✔ ✔ ✔ ✔

Adult surgery patients with postoperative 

pneumonia or venous thromboembolic MPSMS ✔

event

Adult surgery patients who received 

appropriate timing of antibiotics QIO ✔ ✔ ✔ ✔

✔ Indicates that reliable data on measure are available for this group and included in summary across measures of

quality and access for this group.

Key: API=Asian or Pacific Islander; AI/AN=American Indian or Alaska Native; Poor=individuals with household

incomes <100% of Federal poverty thresholds.

National Healthcare Disparities Report, 2010 276
enough time with them

Access

People under age 65 with health insurance NHIS ✔ ✔ ✔ ✔ ✔

People under age 65 who were 

uninsured all year MEPS ✔ ✔ ✔ ✔ ✔

People with a specific source of ongoing 

care NHIS ✔ ✔ ✔ ✔ ✔

People with a usual primary 

care provider MEPS ✔ ✔ ✔ ✔ ✔

People without a usual source of care who 

indicated a financial or insurance reason MEPS ✔ ✔ ✔ ✔

for not having a source of care

People who were unable to get or delayed MEPS ✔ ✔ ✔ ✔ ✔

in getting needed care

✔ Indicates that reliable data on measure are available for this group and included in summary across measures of

quality and access for this group.

Key: API=Asian or Pacific Islander; AI/AN=American Indian or Alaska Native; Poor=individuals with household

incomes <100% of Federal poverty thresholds.

National Healthcare Disparities Report, 2010 277
National Healthcare Disparities Report, 2010
National Healthcare Disparities Report, 2010
A

AHRQ Publication No. 11-0005

March 2011