Advancing Excellence in Health Care • www.ahrq.gov

Agency for Healthcare Research and Quality

National

Healthcare

Disparities

Report

2008
Chapter 1

National Healthcare Disparities Report, 2008

Introduction and Methods
U.S. Department of

Health and Human Services

Agency for Healthcare Research and Quality

540 Gaither Road

Rockville, MD 20850

AHRQ Publication No. 09-0002

March 2009

www.ahrq.gov/qual/qrdr08.htm

2 0 0 8

National

Healthcare

Disparities Report
National Quality Report, 2000

Staying Healthy Acknowledgments

National Healthcare Disparities Report, 2008

The NHDR is the product of collaboration among agencies across the Department of Health and Human Services

(HHS). Many individuals guided and contributed to this report. Without their magnanimous support, this report would

not have been possible.

Specifically, we thank:

Primary AHRQ Staff: Carolyn Clancy, William Munier, Katherine Crosson, Ernest Moy, Karen Ho, and Jeffrey

Brady.

HHS Interagency Workgroup for the NHQR/NHDR: Roxanne Andrews (AHRQ), Hakan Aykan (ASPE), Rachel

Ballard-Barbash (NCI), Douglas Boenning (HHS-ASPE), Jeffrey Brady (AHRQ-CQuIPS), Miriam Campbell (CMS),

Cecelia Casale (AHRQ-OEREP), Fran Chevarley (AHRQ-CFACT), Steven Clauser (NCI), Rameicha Cooks (HRSA),

Agnes Davidson (OPHS), Denise Dougherty (AHRQ-OEREP), Brenda Evelyn (FDA), Yvette Fryar (HRSA), Edward

Garcia (CMS), Olinda Gonzalez (SAMHSA), Tanya Grandison (HRSA), Miryam Granthon (OPHS-OMH), Darryl

Gray (AHRQ-CQuIPS), Saadia Greenberg (AoA), Kirk Greenway (IHS), Lein Han (CMS), Linda Harlan (NCI),

Debbie Hattery (CMS), Karen Ho (AHRQ-CQuIPS), Deloris Hunter (NIH), Memuna Ifedirah (CMS-OCSQ),

Padmini Jagadish (AHRQ-OEREP), Linda Johnston-Lloyd (HRSA), Jackie Shakeh Kaftarian (AHRQ-OEREP), Ruth

Katz (ASPE), Sophia Kazakova (CDC-CCID-OD), Richard Klein (CDC-NCHS), Lisa Koonin (CDC-NCHS), Onelio

Lopez (OCR), Leopold Luberecki (ASPE), Diane Makuc (CDC-NCHS), Marty McGeein (HHS-ASPE), Richard

McNaney (CMS), Nancy Miller (NIH), Carmen Moten (NIH-NIMH), Ernest Moy (AHRQ-CQuIPS), Leo Nolan

(IHS), Cynthia Ogden (CDC-NCHS), Anna Maria Padian (HRSA), Judith Peres (ASPE), Susan Polniaszek (ASPE),

Susan Queen (HRSA), Michael Rapp (CMS), Georgetta Robinson (CMS), Rochelle Rollins (OMH), Susan Rossi

(NIH), Beatrice Rouse (SAMHSA), Asel Ryskulova (CDC-NCHS), Judy Sangl (AHRQ-CQuIPS), Michael

Schoenbaum (NIMH), Adelle Simmons (HHS-ASPE), Alan E. Simon (CDC-NCHS), Sunil Sinha (CMS), Jane Sisk

(CDC-NCHS), Phillip Smith (IHS), Nancy Sonnenfeld (CDC/NCHS), Caroline Taplin (HHS-ASPE), Emmanuel

Taylor (NCI), Wilma Tilson (HHS-ASPE), Benedict Truman (CDC), Joan Van Nostrand (HRSA), Nadarajen A.

Vydelingum (NIH), Barbara Wells (NHLBI), Valerie Welsh (OPHS/OMH), Odies Williams (OCR), Lee Wilson

(ASPE-OS), and Susan Yanovski (NIH/NIDDK).

AHRQ NHQR/NHDR Team: Roxanne Andrews, Jeffrey Brady, Denise Burgess, Fran Chevarley, Cecilia Rivera

Casale, Katherine Crosson, Denise Dougherty, Darryl Gray, Karen Ho, Alan Hsu, Jackie Shakeh Kaftarian, Stephanie

Klapper, Laura McKenzie Phelps, Oscar Mensah, Ernest Moy, William Munier, Ryan Mutter, Daniel Pak, Judy Sangl,

Barbara Slivers, and, Marc Zodet.

HHS Data Experts: Barbara Altman (CDC-NCHS), Roxanne Andrews (AHRQ), Frances Chevarley (AHRQ),

Steven Cohen (AHRQ), James Colliver (SAMHSA), Paul Eggers (NIH), David Keer (ED-OSERS), William Mosher

(CDC-NCHS), Cynthia Ogden (CDC-NCHS), Asel Ryskulova (CDC-NCHS), Alan E. Simon (CDC-NCHS), Jane

Sisk (CDC-NCHS), and Marc Zodet (AHRQ) and members of the Interagency Subcommittee on Disability Statistics.

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

(American Cancer Society), Ronald Kessler (Harvard Medical School), Bryan Palis (NCBD, American College of

Surgeons), Florentina R. Salvail (Hawaii Department of Health), Allison Petrilla (NHCPO), Hardy Spoehr (Papa Ola

Lokahi), Andrew Stewart (NCBD, American College of Surgeons), and Jo Ann Tsark (Papa Ola Lokahi).

Other AHRQ Contributors: Doreen Bonnett, Cindy Brach, Xiuhua Chen, Marybeth Farquhar, Karen FlemingMichael, William Freeman, Amy Galifianakis, Paul Gorrell, Biff LeVee, Corey Mackison, Gerri Michael-Dyer, Karen

Migdail, Laura Nawrocki, Pamela Owens, Mamatha Pancholi, Larry Patton, Wendy Perry, Deborah Queenan, Mary

Rolston, Scott Rowe, Bruce Seeman, Randie Siegel, Christine Williams, and Phyllis Zucker.

Data Support Contractors: CHD-Fu, Social and Scientific Systems, Thomson Reuters Healthcare, and Westat.
National Quality Report, 2000

Introduction and Methods Staying Healthy

National Healthcare Disparities Report, 2008

Chapter 1

Contents

Chapter Page

Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1 Introduction and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2. Quality of Health Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Effectiveness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Diabetes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

End Stage Renal Disease (ESRD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Heart Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

HIV and AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Mental Health and Substance Abuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Respiratory Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Nursing Home, Home Health, and Hospice Care. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Patient Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Timeliness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Patient Centeredness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Summary Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

3. Access to Health Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

Facilitators and Barriers to Health Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140

Health Care Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

Summary Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

4. Priority Populations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

Racial and Ethnic Minorities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

Low-Income Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

Older Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248

Residents of Rural Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256

Individuals With Disabilities and Special Health Care Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268

List of Core Measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287

Appendixes:

A. Data Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr08/datasources/index.html

B. Detailed Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr08/methods/index.html

C. Measure Specifications . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr08/measurespec/index.html

D. Data Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.ahrq.gov/qual/qrdr08/index.html

National Healthcare Disparities Report, 2008
National Quality Report, 2000

Staying Healthy
National Quality Report, 2000

Highlights Staying Healthy

National Healthcare Disparities Report, 2008

1

Key Themes and Highlights From the

National Healthcare Disparities Report

Examining health care disparities is an integral part of improving health care quality. Health care disparities

are the differences or gaps in care experienced by one population compared with another population. As the

National Healthcare Quality Report (NHQR) shows, Americans too often do not receive care that they need

or they receive care that causes harm. The National Healthcare Disparities Report (NHDR) shows that

moreover, some Americans receive even worse care than other Americans. The quality of health care is

different for different people. Within the scope of health care delivery, these disparities are due to differences

in access to care, provider biases, poor provider-patient communication, poor health literacy, and other factors.

The purpose of the NHDR, as mandated by Congress,i is to identify the differences or gaps where some

populations receive poor or worse care than others and to track how these gaps are changing over time.

Although the emphasis is on disparities related to race, ethnicity, and socioeconomic status, this directive also

includes a charge to examine disparities in “priority populations.” These include groups with unique health

care needs or issues that require special attention. Among the priority populations addressed in the NHDR

are women, children, older adults, residents of rural areas, and individuals with disabilities or special health

care needs.

The NHDR uses the same 220 measures used in the NHQR categorized across four dimensions of quality:

effectiveness, patient safety, timeliness, and patient centeredness. This year’s report focuses on the state of

health care disparities for a group of 45 core measuresii that represent the most important and scientifically

credible measures of health care quality for the Nation, as selected by the Department of Health and Human

Services (HHS) Interagency Work Group.iii By focusing on core measures, the 2008 report provides a more

readily understandable summary and explanation of the key results derived from the data.iv While the

measures selected for inclusion in the NHDR are derived from the most current scientific knowledge, this

knowledge base is not evenly distributed across the dimensions of health care quality, nor across racial, ethnic,

and other priority populations. The analysis in the following pages centers on measures for which data are

available and that fit within the framework provided by the Institute of Medicine.1

Three key themes emerge in the 2008 NHDR:

◆ Disparities persist in health care quality and access.

◆ Magnitude and pattern of disparities are different within subpopulations.

◆ Some disparities exist across multiple priority populations.

i This 2008 report is the sixth National Healthcare Disparities Report (NHDR) mandated by the U.S. Congress (42 U.S.C.

299a-1(a)(6)). It is produced by the Agency for Healthcare Research and Quality (AHRQ) on behalf of the U.S.

Department of Health and Human Services (HHS) and in collaboration with an HHS-wide Interagency Work Group.

ii Not all core measures have data for all subgroups for analyses.

iii The HHS Interagency Work Group, which represents 18 HHS agencies and offices, was formed to provide advice and

support to AHRQ and the National Reports team.

iv Data on all NHDR measures are available in the Data Tables appendix at http://www.ahrq.gov/qual/measurix.htm.
Disparities Persist in Health Care Quality and Access

All population groups should receive equally high quality of care. Getting into the health care system

(access to care) and receiving appropriate health care in time for the services to be effective (quality of

care) are key factors in ensuring good health outcomes.

Both categories of measures, quality of care and access to care, show that disparities persist for all

populations. Measures of quality include effectiveness (the percentage of patients with a disease or

condition who get recommended care), patient safety, and timeliness. The NHDR includes the added

dimension of access to care to measure differences in health insurance coverage, utilization of general

health services, and other barriers to care. Below are figures that illustrate for each population how

disparities in quality and access have changed in the past 5 years.

Figure H.1 shows that for Blacks, Asians, American Indians/Alaska Natives (AI/ANs), Hispanics, and

poor people, at least 60% of measures of quality of care are not improving (either stayed the same or

worsened).

Figure H.1. Change over time in racial, ethnic, and socioeconomic disparities for selected core

quality measures, 2000-2001 to 2005-2006

Improving = Population-reference group difference becoming smaller at an average annual rate of greater than or equal to 1%.

Same = Population-reference group difference changing at less than an average annual rate of 1%.

Worsening = Population-reference group difference becoming larger at an average annual rate of greater than or equal to 1%.

Key: AI/AN = American Indian or Alaska Native.

Note: “Asian” includes Asian or Pacific Islander when information is not collected separately for each group. Data presented are the

most recent data available. Measures presented here for racial and ethnic minority groups are a subset of the core measure set that

has data for all groups. Some measures for poor populations are different from the measures used for racial and ethnic groups.

National Quality Report, 2000

Staying Healthy Highlights

National Healthcare Disparities Report, 2008

2

0

10

20

30

40

50

60

70

80

90

100

Percent

Same Worsening

Black vs.

White (n=17)

3 3

8

11

5 5 7

3

6

5

3

8

9

7

5

Improving

Asian vs.

White (n=17)

AI/AN vs.

White (n=17)

Hispanic vs.

Non-Hispanic White (n=17)

Poor vs.

High Income (n=20)
Many Americans have access to primary and hospital care. For many populations, however, barriers exist

to getting needed health care, such as having no health insurance or having trouble getting appointments.

Reducing disparities in access to health care is an important step to improving overall quality.

Figure H.2 is a summary of trends in the core measures of access.

◆ For AI/ANs, 75% of the core measures that could be tracked over time improved (gap decreased).

◆ For Blacks and Asians, 60% of the core measures used to track access remained unchanged (gap

stayed the same) or got worse (gap increased).

◆ For Hispanics, 80% of core access measures remained unchanged or got worse.

◆ For poor populations, 57% of core access measures remained unchanged or got worse.

Figure H.2. Change over time in racial, ethnic, and socioeconomic disparities for selected core

access measures, 2000-2001 to 2005-2006*

* The most recent data year for AI/ANs is 2003.

Improving = Population-reference group difference becoming smaller at an average annual rate of greater than or equal to 1%.

Same = Population-reference group difference changing at an average annual rate of less than 1%.

Worsening = Population-reference group difference becoming larger at an average annual rate of greater than or equal to 1%.

Key: AI/AN = American Indian or Alaska Native.

Note: “Asian” includes Asian or Pacific Islander when information is not collected separately for each group. Data presented are the

most recent data available.

National Quality Report, 2000

Highlights Staying Healthy

National Healthcare Disparities Report, 2008

3

0

10

20

30

40

50

60

70

80

90

100

Percent

Same Worsening

Black vs.

White (n=5)

2 2

1 1

3

1

3

2 2 2 3

2

1

Improving

Asian vs.

White (n=5)

AI/AN vs.

White (n=4)

Hispanic vs.

Non-Hispanic White (n=5)

Poor vs.

High Income (n=7)

1
Making Patient’s and Families’ Lives Better

Providing data through the NHDR is only one of many efforts to reduce health care disparities in the United

States. As multiple individual, community, social, and health system factors contribute to health care

disparities, multiple strategies exist to address these factors. Efforts have focused on training health care

professionals, raising awareness among health professionals and patients, and changing health systems at

the hospital, provider, and community level.

Cultural expectations, assumptions, and language affect the quality of care patients receive. Some efforts

have focused on training health care personnel to deliver culturally and linguistically competent care for

diverse populations:

• The Think Cultural Health Web site (http://www.thinkculturalhealth.org) is sponsored by the Office of

Minority Health (OMH). This Web site offers the latest resources and tools to promote cultural

competency in health care. Users can access free online courses accredited for continuing education

credit. The site also provides supplementary tools to help providers and organizations promote

respectful, understandable, and effective care to an increasingly diverse patient population. This Web

site provides access to online courses such as “A Physician’s Practical Guide to Culturally Competent

Care” and “Culturally Competent Nursing Care,” as well as interactive tools such as the “Health Care

Language Services Implementation Guide.”

• The Unified Health Communication Web-Based Training Program is sponsored by the Health

Resources and Services Administration (HRSA). This interactive Web-based training course introduces

a unified health communication concept called “Unified Health Communication (UHC) 100/101:

Addressing Health Literacy, Cultural Competency, and Limited English Proficiency.” The UHC 100/101

course explores three crucial areas that can affect provider-patient communication: health literacy,

cultural competency, and limited English proficiency. Each of these three components can influence

various aspects of health communication. In combination, they can have an even greater impact on

improving health care delivery, reducing health disparities, and empowering patients to become more

involved in their own health management to enhance their quality of life. This course is currently used

across a variety of health care delivery venues. Its use underscores the importance of clear health

communication through the discussion of innovative approaches by health care providers.

• The Office for Civil Rights (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. This law 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. OCR’s Title VI enforcement activities aim to decrease

health disparities by increasing access to health care and human services. OCR enforces Title VI by

investigating race, color, and national origin discrimination complaints filed by individuals and advocacy

groups; and by resolving those complaints through voluntary compliance agreements and corrective

action monitoring. OCR, for example, recently entered into a voluntary compliance agreement with the

Hawaii Department of Human Services (DHS), which administers a $1.7 billion annual budget, including

the State’s Medicaid, health, and long-term care programs. To comply with Title VI, Hawaii DHS has

agreed to improve language assistance services for limited-English-proficient individuals, including

translating vital documents and providing timely, competent interpreters.

National Quality Report, 2000

Staying Healthy Highlights

National Healthcare Disparities Report, 2008

4
Making Patient’s and Families’ Lives Better

Other efforts to address health care disparities leverage key partnerships to raise awareness of disparities

by using data and research:

• The Health Disparities Roundtable was convened in 2006 under cosponsorship by OMH and AHRQ

and in partnership with the Institute of Medicine (IOM). The purpose of the IOM roundtable is to

generate action and engage interested parties from academia, industry, government, philanthropy, the

corporate sector, and the community to reduce racial and ethnic health disparities. It fills an important

role as a focus for public-private partnerships on research and policy discussions to address various

topics. These include ways to bring together health care-focused and broader community-based

approaches to address disparities more effectively; strategies to expand and strengthen research to

develop effective treatments for those diseases that disproportionately affect minority populations, as

well as research that focuses on the complex interactions of biologic and social factors as

determinants of health; effective cultural competency techniques and cross-cultural education in health

care settings; educational strategies to end health disparities; development and promotion of effective

strategies to increase minority representation in medicine and health professions; and understanding of

the causes of health and health care disparities and best solutions.

• The Federal Collaboration on Health Disparities Research (FCHDR) was developed by the Centers

for Disease Control and Prevention (CDC) in collaboration with OMH and cosponsored by AHRQ.

FCHDR was developed to identify and support research priorities for cross-agency collaboration to

hasten the elimination of health disparities. This collaboration is led by the HHS Health Disparities

Council and the Interagency Committee on Disability Research of the Department of Education.

Through FCHDR, Federal partners have formed subject matter expert workgroups around four initial

research topic areas for collaboration: obesity, built environment (homes, schools, workplaces, parks

and recreation areas, business areas, transportation systems, etc.), mental health care, and

comorbidities. These priorities represent opportunities for Federal agencies and other partners to

collaborate on innovative research.

• The Disparity Reducing Advances Project is a multiyear, multistakeholder project cosponsored by

AHRQ and others, including CDC, the National Cancer Institute, the American Cancer Society, a Florida

hospital agency, the Robert Wood Johnson Foundation, and the University of Texas Medical Branch.

This project identifies the most promising strategies for bringing health gains to poor and underserved

populations and accelerating the development and deployment of these strategies to reduce health

care disparities.

• The Centers for Medicare & Medicaid Services (CMS) Health Disparities Program allows CMS to

develop a health care forum that encompasses public and private partnerships to address health

disparities nationwide through a common message. The focus of this program is to improve health

literacy and outcomes through three overarching functions: (1) align CMS and Federal resources to

provide a solid foundation for messaging on health disparities activities and projects; (2) standardize

elements throughout the Quality Improvement Organization 9th Statement of Work themes for the

health disparities program; and (3) work with internal and external stakeholders to advance health

disparities planning objectives. The Health Disparities Program is achieving these goals by using

several methods such as grants to Historically Black Colleges and Universities and Hispanic Serving

Institutions, health disparities forums, newsletters throughout statewide programs, plenary sessions at

conferences, and collaborations with national organizations such as the Administration on Aging, OMH,

and National Institutes of Health.

National Quality Report, 2000

Highlights Staying Healthy

National Healthcare Disparities Report, 2008

5
Making Patient’s and Families’ Lives Better

• Healthy People 2010 is a comprehensive health promotion and disease prevention agenda. It has two

overarching goals: (1) to increase life expectancy and improve quality of life, and (2) to eliminate health

disparities among population subgroups based on characteristics such as race and ethnicity, gender,

and income. Through a national consensus process, HHS identified specific objectives for improving

the health of the Nation, established baseline values for the objectives, and set specific targets to be

achieved by 2010. The Nation’s Public Health Service agencies and agencies in other Federal

departments are involved in pursuing this agenda. Progress toward the achievement of these goals

and objectives is monitored by CDC’s National Center for Health Statistics.

• AHRQ is a partner in the National Business Group on Health (NBGH) Racial and Ethnic Health

Disparities Advisory Board, an initiative of NBGH and OMH to reduce racial and ethnic health

disparities. Some employers have already developed initiatives to reduce health disparities. The

Disparities Advisory Board will facilitate alliances between business, medicine, and public health

organizations to improve the quality of health care for racial and ethnic minority populations, while

promoting beneficiary health and employee productivity. Products include an issue brief on why

companies are making health disparities their business, including practical strategies and a Webinar to

feature best practices. The brief will be distributed to NBGH members.

Other partnerships leverage both public and private partners to address health care disparities at the

community and provider level:

• The AHRQ National Health Plan Collaborative (NHPC), which has 11 participating health plans with a

total of 87 million enrollees, is cofunded by the Robert Wood Johnson Foundation. NHPC’s purpose is

to identify and implement approaches to reducing racial and ethnic disparities and to improve quality

among health plan enrollees. In Phase II of the collaborative, three task forces addressed primary data

collection and language access and are building the business case for reducing disparities. The

collaborative builds on the continued interest of health plans in reducing disparities and improving

health care for minorities. Members of the collaborative have developed a toolkit that will serve as the

core vehicle to share NHPC’s findings and recommendations. The toolkit will be a Web-based

searchable database of tools, research, statistics, case studies, and lessons learned. Users will be able

to search the tool according to their needs, resulting in a personalized page of information and

resources. The toolkit will enable other health plans or stakeholders to implement interventions or

methods to address disparities and will provide lessons learned and best practices for reducing

disparities.

• An HHS pilot project, Improving Hispanic Elders’ Health: Community Partnerships for EvidenceBased Solutions, is bringing together teams of local leaders from communities with large numbers of

Hispanic elders to develop local plans for addressing health disparities. Teams cut across

organizational boundaries and include representatives from the local area agency on aging, Hispanic

community organizations, the local public health agency, aging services providers, the medical

community, and health service research organizations. AHRQ, the Administration on Aging, CDC,

CMS, and HRSA are assisting teams to develop coordinated strategies for improving the health and

well-being of Hispanic elders. Eight communities with sizable disparities participate in this pilot project:

Chicago, Illinois; Houston, Texas; Los Angeles, California; McAllen, Texas; Miami, Florida; New York,

New York; San Antonio, Texas; and San Diego, California. Information from the NHDR and customized

data created by AHRQ for each community have helped target interventions to specific neighborhoods

in greatest need of particular services.

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Making Patient’s and Families’ Lives Better

• The National Partnership for Action (NPA) To End Health Disparities is a multilevel effort to mobilize

and connect individuals and organizations across the country to create a Nation free of health

disparities, with quality health outcomes for all people. Through a nationwide, comprehensive,

community-driven, sustained approach, NPA seeks to illuminate the compelling issues that affect

health outcomes, identify action steps that partners can adopt and adapt for their target audiences,

highlight promising practices that help eliminate health disparities, and promote tools, programs, and

information sources for stakeholders. Strategic actions have been developed around five core

objectives: increase awareness of health disparities, strengthen leadership at all levels, improve health

care outcomes for racial and ethnic minorities and underserved populations and communities, improve

cultural and linguistic competency in delivering health services, and coordinate and use research and

outcome evaluations more effectively. Six Regional Conversations (meetings) were held to bring

together local, State, Tribal, regional, and Federal experts and practitioners from the private and public

sectors to lay the foundation for a cohesive strategy. The meetings resulted in the development of 10

Regional Blueprints that are forming the basis for improved coordination of regional actions related to

reducing health disparities. The Regional Blueprints are informing the development of a National

Blueprint based on 20 wide-reaching strategies.

Magnitude and Patterns of Disparities Differ Among

Various Populations

Improvements in preventive care, chronic care, and access to care have led to the elimination of

disparities for some priority populations in areas such as mammograms, smoking cessation counseling,

and appropriate timing of antibiotics. At the same time, many of the largest disparities have not changed

significantly. The NHDR can be used to identify the most important gaps in care as well as

improvements for priority populations. The complete picture of disparities is different for each

population. An analysis of each population allows targeting of resources and efforts to improve care and

narrow the gaps in care for racial and ethnic minorities and poor populations.

In 2005, the NHDR reported on the biggest gaps that existed in health care quality in America for Blacks,

Asians, AI/ANs, Hispanics, and poor populations. Some of the largest gaps reported in 2005 remain the

largest gaps in this year’s NHDR.

◆ For Blacks, large disparities remain in new AIDS cases despite significant decreases. The proportion

of new AIDS cases was 9.4 times as high for Blacks as for Whites. Hospital admissions for lower

extremity amputations in patients with diabetes and lack of prenatal care for pregnant women in the

first trimester are the largest disparities for Blacks observed in the 2008 NHDR.

◆ For Asians, disparities remain in timeliness of care. Asians were more likely than Whites to not get

care for illness or injury as soon as wanted.

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◆ For AI/ANs, disparities remain in prenatal care. AI/AN women were twice as likely to lack prenatal

care as White women.v Also, AI/AN adults were less likely than Whites to receive colorectal cancer

screening.

◆ For Hispanics, large disparities also remain in new AIDS cases despite significant decreases. The

rate of new AIDS cases was more than three times as high for Hispanics as for non-Hispanic Whites.

◆ For poor people, disparities remain in communication with health care providers. The percentage of

children whose parents reported communication problems with their health providers was nearly four

times as high for poor children as for high-income children. Poor adults were also more than twice

as likely not to get timely care for an illness or injury.

The “biggest gaps” are defined as those quality measures with the largest relative rates between Whites

and racial and ethnic minorities and between high-income and poor individuals. For example, a relative

rate of 4.0 means that this population was four times as likely as the White population to be hospitalized

for pediatric asthma. This analysis is presented in Table H.1.

v The most recent data for prenatal care (2003-2005) are not comparable to previous data years due to revision of the

U.S. Standard Certificate of Live Birth in 2003. Some States that have not adopted this revision are excluded. See

footnote for Figure 4.26. Table H.1 shows comparison between groups within each data year only.

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Table H.1. Three largest disparities in quality of health care for selected groups: Measure and

rate relative to reference group, 2005 NHDR versus 2008 NHDR (Measures that have the largest

gaps in both the 2005 and 2008 NHDR are in italics.)

2005 NHDR 2008 NHDR

Group Measure Relative Measure Relative

rate rate

Black New AIDS cases per 100,000 10.4 New AIDS cases per 9.4

compared population age 13 and over 100,000 population age 13

with White and over

Hospital admissions for pediatric 4.0 Hospital admissions for 2.3

asthma per 100,000 population lower extremity

ages 2-17a amputations in patients

with diabetes per 100,000

population

Emergency department visits in 1.9 Pregnant women who did 1.6

which patients left without being not receive prenatal care

seen in the first trimesterb

Asian People age 18 and over with serious 1.6 Adults who can sometimes 2.1

compared mental illness who did not receive or never get care for illness

with White mental health treatment or or injury as soon as wanted

counseling in the past yeara

Adults who can sometimes or never 1.6 Children ages 2-17 who did 1.2

get care for illness or injury as soon not receive advice about

as wanted physical activity

Adults age 65 and over who did not 1.5 Adults age 65 and over who 1.6

ever receive pneumococcal did not ever receive

vaccination pneumococcal vaccination

AI/AN Pregnant women who did not 2.1 Pregnant women who did 2.1

compared receive prenatal care in the first not receive prenatal care in

with White trimesterb the first trimesterb

Composite: Adults who reported 1.8 Adults age 50 and over who 1.4

poor communication with health received colorectal cancer

providers screening

Children ages 2-17 who did not 1.3 Home health care patients 1.3

receive advice about physical who were admitted to the

activity hospital

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Table H.1. Three largest disparities in quality of health care for selected groups: Measure and

rate relative to reference group, 2005 NHDR versus 2008 NHDR (Measures that have the largest

gaps in both the 2005 and 2008 NHDR are in italics.)

2005 NHDR 2008 NHDR

Group Measure Relative Measure Relative

rate rate

Hispanic New AIDS cases per 100,000 3.7 New AIDS cases per 100,000 3.3

compared population age 13 and over population age 13 and over

with non- Adults who can sometimes or never 2.0 Composite: Children whose 2.0

Hispanic get care for illness or injury as soon parents reported poor

White as wanted communication with

health providers

Composite: Children whose parents 1.8 Pregnant women who did 2.0

reported poor communication with not receive prenatal care in

health providers the first trimesterb

Poor Composite: Children whose parents 3.3 Composite: Children whose 3.7

compared reported poor communication with parents reported poor

with high health providers communication with

health providers

Adults who can sometimes or never 2.3 Adults who can sometimes 2.5

get care for illness or injury as soon or never get care for illness

as wanted or injury as soon as wanted

Children ages 2-17 who did not 2.0 Women age 40 and over 2.1

have a dental visit who reported they did not

have a mammogram in the

last 2 years

a This measure was removed from the 2008 NHQR and NHDR core list.

b The most recent data for prenatal care (2003-2005) are not comparable to previous data years due to revision of the U.S. Standard

Certificate of Live Birth in 2003. Some States that have not adopted this revision are excluded. See footnote for Figure 4.26. Table

H.2 shows comparison between groups within each data year only.

Note: Relative rate is used to compare one group with its reference group. It is calculated by dividing the group’s estimate by the

reference group’s estimate. For example, the relative rate of new AIDS cases for Blacks compared with Whites is 9.4 in the 2008

NHDR. This means that Blacks have a rate that is 9.4 times as high as Whites for this measure.

While some disparities have remained the same or have gotten worse, other disparities have shown some

improvement. Some findings demonstrate progress in decreasing disparities, where gaps have actually

decreased.

◆ From 2000 to 2005, for Blacks, the rate of deaths per 1,000 discharges with complications

potentially resulting from care (failure to rescue) improved (from 159.2 to 121.8; in 2005, this rate

was not significantly different from Whites). The gap between Blacks and Whites decreased to the

point that Blacks have better outcomes in this measure (from a relative rate of 1.1 to 0.97).

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◆ From 2000 to 2005, the percentage of Asian women age 40 and over who reported they had a

mammogram within the last 2 years improved (approximately 4.36 million women received effective

screening for breast cancer in 2005). The gap between AI/ANs and Whites who did not receive a

mammogram decreased (from a relative rate of 1.8 to 1.0).

◆ From 2000 to 2005, the percentage of AI/AN adult surgery patients who received appropriate timing

of antibiotics improved (from 52.0% to 80.8%; in 2005, this rate was not significantly different from

Whites). The gap between AI/ANs and Whites not receiving appropriate timing of antibiotics

decreased (from a relative rate of 1.2 to 1.0).

◆ From 2000 to 2005, the percentage of Hispanic children ages 3-6 who ever had their vision checked

by a health provider improved (from 51.6% to 56.6%, or roughly 2.6 million Hispanic children).

The gap between Hispanics and non-Hispanic Whites who did not receive a vision check decreased

(from a relative rate of 1.2 to 1.1).

◆ From 2000 to 2005, the percentage of poor adult smokers who received smoking cessation

counseling while hospitalized improved (from 57.9% to 65.5%; in 2005, this rate was not

significantly different from high-income patients). The gap between poor individuals and highincome individuals who did not receive smoking cessation counseling decreased (from a relative rate

of 1.3 to 1.0).

In addition to highlighting important progress, decreases in disparities that have been observed identify

areas from which lessons might be learned. Each racial and ethnic group showed improvements in some

areas where quality of care had improved overall. However, not all improvements closed the gap between

these groups and reference groups. Innovative approaches that have contributed to reductions in the

magnitude of disparities in care suggest promising practices and effective policies that may also improve

care in other areas.

Some Disparities Exist Across Multiple Priority

Populations

In addition to the variable distribution of disparities evident across priority populations, in some cases

several different populations experience the same gaps in care as other populations due to poor quality

overall or populations experiencing similar barriers. The following measures included in the NHDR

illustrate disparities for two or more populations:

◆ Blacks, Asians, AI/ANs, and Hispanics all experienced disparities in the percentage of adults age 50

and over who received a colonoscopy, sigmoidoscopy, proctoscopy, or fecal occult blood test. For

this measure, between 1999 and 2006, the disparity increased in all four groups (Table H.2).

◆ For Blacks and Hispanics, disparities grew larger in the percentage of adults with a major depressive

episode in the last 12 months who received treatment for depression in the last 12 months.

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◆ Blacks and Asians both had worsened disparities in the receipt of pneumococcal vaccination for

adults age 65 and over.

◆ Blacks and Asians both had worsened disparities in a patient-centeredness measure of patient and

provider communication.

Table H.2. Core measures that are getting worse for more than one racial and ethnic group

compared with reference group

Topic Measure Blacks Asians AI/ANs Hispanics

Cancer Adults age 50 and over who ****

received a colonoscopy,

sigmoidoscopy, proctoscopy,

or fecal occult blood test

Mental health and Adults with a major depressive * *

substance abuse episode in the last 12 months

who received treatment for

depression in the last 12 months

Respiratory diseases Adults age 65 and over who ever * *

received pneumococcal

vaccination

Patient centeredness Adults with poor provider-patient * *

communication

Note: A complete table of the disparities that worsened for specific populations can be found in Chapter 4, Priority Populations.

Low rates of colorectal cancer screening and other cancer screenings may be due to cultural attitudes and

patient perceptions, such as screenings are not necessary. In addition, patients may have problems paying

for followup visits to complete screening, as well as logistical problems getting to the appointment.

Similarly, pneumococcal vaccination rates may be lower for Blacks and Asians because many distrust the

effectiveness of vaccines and perceive that vaccines are not necessary.

Overall, minorities may be less likely to access and use mental health services due to cultural beliefs

related to mental health and the stigma of getting care for mental illnesses, language barriers, and poor

access to mental health services. In addition, data for mental health care are limited. This lack of data is

a challenge in measuring quality of mental health care and disparities among these populations, especially

for small populations.

Patient experience of health care is another important indicator of health care quality. Minorities are

more likely to experience poor provider-patient communication. Minority patients are more likely to

receive care in clinics where providers face workplace challenges and have a more complex patient mix.

Patient and provider interactions encompass various aspects of care, including whether patients can get

appointments in a timely manner, whether they feel respected and listened to, and whether they

understand their care. Poor provider-patient communication can result from a number of complex factors,

including a provider’s lack of familiarity with cultural norms, language barriers, a patient’s low health

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12
literacy, a chaotic work environment, and a lack of time during a visit. Poor provider-patient

communication can lead to inefficient care and medical errors. Addressing these health care disparities

will require special attention to cultural attitudes and perceptions that affect health behaviors and patterns

of health care access and utilization.

Measures that are improving for more than one population group may also provide additional insight

toward understanding disparities. Areas of care where public policy has identified key practices that have

broad and direct impact on populations have shown improvement in reducing the gap between

populations. These include increasing the number of people with health insurance and improving

provider awareness of recommended care and preventive care for specific conditions. Measures that

showed reductions in disparities across more than one select group over time included the following:

◆ Among Asians and Hispanics, children who received recommended vaccines.

◆ Among Blacks, AI/ANs, and Hispanics, new AIDS cases.

◆ Among Hispanics and poor populations, smokers with heart attack who received smoking cessation

counseling while hospitalized.

◆ Among Blacks, AI/ANs, Hispanics, and poor populations, people under age 65 with health

insurance.

Since its initial publication in 2003, the NHDR has provided a broad and detailed examination of

disparities for at-risk priority populations in U.S. health care. The ability to monitor and track changes in

disparities is critical. Growing interest in public reporting for quality improvement activities continues to

be an impetus to improve not only the quality of data but also the quality of care provided.

This 2008 report summarizes the many areas where little to no progress has been achieved in reducing

disparities. However, it also highlights progress that is being made in key conditions that

disproportionately affect priority populations. Many factors contribute to disparities in health care quality

and access, and it is a major challenge to address them. Yet a number of promising programs at HHS,

such as those described here, are doing just that. The activities described are only a few of the many

efforts of HHS organizations that address the challenges in reducing health care disparities. Other HHS

agencies are contributing in many other ways to address disparities in health service delivery, health care

finance, and clinical research, in addition to both Federal and State efforts to expand access. What they

have in common are the focus on multiple stakeholders and the need for tailored solutions depending on

the particular disparities and populations involved. With the publication of this sixth NHDR, AHRQ

stands ready to contribute to efforts such as those above to encourage and support the development of

national, State, Tribal, and community solutions using national data and benchmarks in disparities. We

hope that the progress and gaps outlined in this NHDR will help policymakers ensure that all patients

receive the health care they need to make their lives better.

1. Swift EK, Corrigan JM, Hare HR, et al., eds. Committee on Guidance for Designing a National Healthcare

Disparities Report, Board on Health Care Services. Institute of Medicine. Guidance for the National Healthcare

Disparities Report. Washington, DC: National Academy Press; 2001.

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Chapter 1

National Healthcare Disparities Report, 2008
Chapter 1

National Healthcare Disparities Report, 2008

Introduction and Methods

C h a p t e r 1 .

I n t r o d u c t i o n a n d M e t h o d s

In 1999, Congress directed the Agency for Healthcare Research and Quality (AHRQ) to produce an

annual report, starting in 2003, to track “prevailing disparities in health care delivery as it relates to racial

factors and socioeconomic factors in priority populations.” Although the emphasis is on disparities related

to race, ethnicity, and socioeconomic status (SES), this directive includes a charge to examine disparities

in “priority populations”—groups with unique health care needs or issues that require special focus. The

National Healthcare Disparities Report (NHDR) was designed and produced by AHRQ, with support

from the Department of Health and Human Services (HHS) and private-sector partners, to respond to this

legislative mandate.

The first NHDR, released in 2003, was a comprehensive national overview of disparities in health care

among racial, ethnic, and socioeconomici groups in the general U.S. population and within priority

populations. This 2008 NHDR represents the sixth release of this report. It continues to focus on a

subset of core measures that make up the most important and scientifically supported measures in the full

NHDR measure set and reports on trends in health care disparities, as well as the degree to which health

care disparities for racial and ethnic minorities and poor populations have lessened.

This chapter summarizes the methodological approaches taken by AHRQ in producing the 2008 NHDR.

Issues related to changes in measures, additional data sources, and modifications to presentation format

are summarized below. Material that is new in this year’s report is specifically highlighted and includes:

◆ Additional data for breast cancer and colorectal cancer treatment.

◆ A new measure on mental health treatment for depression.

◆ A new measure on daily preventive asthma medication use.

◆ Additional discussion of patient safety measures, including:

• Surgical discharges with catheter-associated urinary tract infection (UTI).

• Accidental puncture or laceration.

• Postoperative wound separation.

i

Socioeconomic disparities include differences in education and income levels.

15

Introduction and Methods

National Healthcare Disparities Report, 2008

Chapter 1
Chapter 1

National Healthcare Disparities Report, 2008

Introduction and Methods

• Iatrogenic pneumothorax.

• Deaths in low-mortality diagnosis-related groups (DRGs).

- A new measure on hospice care for referral to hospice at the right time.

- Additional data on diversity of Licensed Practical Nurses and Licensed Vocational

Nurses (LPNs/LVNs).

- Additional data on Native Hawaiians and Other Pacific Islanders,ii including:

- People without health insurance.

- Influenza vaccination for older adults.

- Pneumococcal vaccination for older adults.

• Continued expanded focus on individuals with disabilities.

As in previous years, the 2008 NHDR was planned and written by AHRQ staff with the support of

AHRQ’s National Advisory Council and the Interagency Work Group for the NHDR, which includes

representatives from every HHS operating component.

How This Report Is Organized

The basic structure of the 2008 NHDR includes the following chapters:

◆ Highlights summarizes key themes and highlights from the 2008 report.

◆ Chapter 1: Introduction and Methods documents the organization, data sources, and methods

used in the 2008 report and describes major changes from previous reports.

◆ Chapter 2: Quality of Health Care examines disparities in quality of health care in the general

U.S. population. Measures of quality of health care used in this chapter are identical to measures

used in the National Healthcare Quality Report (NHQR) except when data to examine disparities are

unavailable. Sections cover four components of health care quality:

• Effectiveness.

• Patient safety.

• Timeliness.

• Patient centeredness.

iiDue to scarcity of health care data for this population, this report has supplemented national estimates (which often do

not meet statistical reliability criteria for reporting) with State-level data. More information can be found in Chapter 4.

16

Introduction and Methods

National Healthcare Disparities Report, 2008

Chapter 1
Chapter 1

National Healthcare Disparities Report, 2008

Introduction and Methods

◆ Chapter 3: Access to Health Care examines disparities in access to health care in the general U.S.

population. Sections cover two components of health care access:

• Barriers and facilitators to health care.

• Health care utilization.

◆ Chapter 4: Priority Populations examines disparities in quality of and access to health care among

AHRQ’s priority populations, including:

• Racial and ethnic minorities.

• Recent immigrant and limited-English-proficient populations.

• Low-income groups.

• Women.

• Children.

• Older adults.

• Residents of rural areas.

• Individuals with disabilities or special health care needs.

Appendixes are available online (www.ahrq.gov) and include:

◆ Appendix A: Data Sources provides information about each database analyzed for the NHDR,

including data type, sample design, and primary content.

◆ Appendix B: Detailed Methods provides detailed methods for selected databases analyzed for the

NHDR.

◆ Appendix C: Measure Specifications provides information about how to generate each measure

analyzed for the NHDR. It includes measures highlighted in the report text as well as other

measures that were examined but not included in the text. It also includes information about the

summary measures used in the report.

◆ Appendix D: Data Tables provides detailed tables for most measures analyzed for the NHDR,

including measures highlighted in the report text as well as other measures that were examined but

not included in the text. A few measures cannot support detailed tables and are not included in the

appendix.iii When data are available:

• Race tables and ethnicity tables are stratified by age, gender, residence location, and one or

more socioeconomic variables (i.e., household income, education, insurance, and/or area income).

• Socioeconomic tables are stratified by age, gender, residence location, race, and ethnicity.

iiiNHDR data can now be accessed through NHDRnet, an online tool that provides Internet users with an opportunity

to specify dimensions of analysis and produce data tables. NHDRnet is available through the AHRQ Web site at

http://nhdrnet.ahrq.gov/nhdr/jsp/nhdr.jsp.

Introduction and Methods

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Chapter 1
Presentation of the Measure Set

Core Measures

For the 2005 NHDR and NHQR, the Interagency Work Group was convened to select a group of

measures from the full measure sets on which the reports would present findings each year. In 2006, the

work group made additional changes to the core measure set. For some topics, the group favored

alternating sets of core measures. These measures, which relate to cancer prevention and childhood

preventive services, are listed in Table 1.1.

Table 1.1. Alternating core measures

Reported in 2007 NHDR and NHQR* Reported in 2008 NHDR and NHQR

Breast cancer screening (mammography) Colorectal cancer screening

Late-stage breast cancers Advanced stage colorectal cancers

Breast cancer mortality Colorectal cancer mortality

Children who received advice about healthy eating Children who received advice about exercise

Children who had dental care Children who had a vision check

*The measures listed in this column will be reported again in the 2009 reports.

All core measures fall into two categories: process measures, which track receipt of medical services,

and outcome measures, which in part reflect the results of medical care (Table 1.2). Not all process and

outcome measures are reported for all conditions due to data limitations and other limitations (see 2005

NHDR Chapter 1 for core report measure selection criteria).

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Chapter 1
Table 1.2. Core process and outcome measures (Measures that include data for all racial and

ethnic groups and that are included in the summary analyses in the Highlights to this report are

in italics.)

Section Process measures Outcome measures

Effectiveness—Cancer • Adults age 50 and over who received • Colorectal cancer

colorectal cancer screening diagnosed at advanced

stage

• Colorectal cancer deaths

per 100,000 population

per year

Effectiveness—Diabetes • Composite: Adults age 40 and over with • Hospital admissions for

diagnosed diabetes who received all three lower extremity amputations

recommended services for diabetes in the per 1,000 population age

calendar year 18 and over with diabetes

Effectiveness—End Stage • Dialysis patients registered on a waiting • Adult hemodialysis patients

Renal Disease list for transplantation with adequate dialysis

Effectiveness— • Adults with obesity who ever received • Deaths per 1,000 adult

Heart Disease advice from a health provider to exercise more hospital admissions with

• Composite: Hospital patients with heart acute myocardial infarction

failure who received recommended (AMI)

hospital care

• Composite: Hospital patients with heart

attacck who received recommended

hospital care

• Adult current smokers with a checkup in the

last 12 months who received advice to

quit smoking

Effectiveness—HIV • New AIDS cases per

and AIDS 100,000 population

age 13 and over

Effectiveness—Maternal • Pregnant women who received prenatal • Infant deaths per 1,000

and Child Health care in the first trimester live births, birth weight

• Composite: Children ages 19-35 months <1,500 g (no new data this

who received all recommended vaccines year)

• Children ages 2-17 for whom a health

provider ever gave advice about

physical activity

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Chapter 1
Table 1.2. Core process and outcome measures (Measures that include data for all racial and

ethnic groups and that are included in the summary analyses in the Highlights to this report are

in italics.)

Section Process measures Outcome measures

• Children ages 3-6 who ever had their

vision checked by a health provider

Effectiveness—Mental • People age 12 and over who needed • Suicide deaths per 100,000

Health and Substance treatment for illicit drug use and population

Abuse who received such treatment at a specialty

facility in the last 12 months

• Adults with a major depressive episode

in the last 12 months who received

treatment for depression in the last

12 months

• People treated for substance abuse who

completed treatment course

Effectiveness—Respiratory • Adults age 65 and over who ever received • Patients with tuberculosis

Diseases pneumococcal vaccination who completed a curative

• Composite: Hospital patients with course of treatment within

pneumonia who received recommended 1 year of initiation of

hospital care treatment

• Visits with antibiotics prescribed for a

diagnosis of common cold

Effectiveness—Nursing • Long-stay nursing home residents with • High-risk, long-stay nursing

Home, Home Health, physical restraints home residents with

and Hospice Care pressure sores

• Short-stay nursing

home residents with

pressure sores

• Adult home health care

patients whose ability to

walk or move around

improved

• Adult home health care

patients who were admitted

to the hospital

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Chapter 1
Table 1.2. Core process and outcome measures (Measures that include data for all racial and

ethnic groups and that are included in the summary analyses in the Highlights to this report are

in italics.)

Section Process measures Outcome measures

Patient Safety • Composite: Adult surgery patients who • Composite: Adult surgery

received appropriate timing of antibiotics patients with postoperative

• Adults age 65 and over who received complications

potentially inappropriate prescription • Composite: Bloodstream

medicines in the calendar year infections or

mechanical adverse events

per 1,000 central venous

catheter placements

• Deaths per 1,000

discharges with

complications potentially

resulting from care (failure

to rescue), adults ages 18-74

Timeliness • Adults who can sometimes

or never get care for illness

or injury as soon as wanted

• Emergency department

visits in which patients

left without being seen

Patient Centeredness • Composite: Adult ambulatory patients

who reported poor communication with

health providers

• Composite: Children with ambulatory visits

whose parents 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 specific source of ongoing care

• 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 who were unable or delayed in

receiving needed medical care, dental care,

or prescription medications due to financial

or insurance reasons

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Chapter 1
Composite Measures

Policymakers and others have voiced their support for composite measures because they can be used to

facilitate understanding of information from many different measures. The effort to develop new

composites is ongoing and, in 2006, a number of new composite measures were added.iv Composite

measures, which now make up about 20% of the core measures, are listed in Table 1.3.

Composite measures in the NHDR and NHQR are created based on two different models—

appropriateness model or opportunities model. When possible, an appropriateness model is used to create

composite measures. It is sometimes referred to as the “all-or-none” approach because it is calculated

based on the number of patients who received all appropriate services. One example of this model is the

diabetes composite, in which a patient who receives only one or two of the three services would not be

counted as having received the recommended care.

In cases where insufficient data are available to apply an appropriateness model, an opportunities model

may be applied. The opportunities model assumes that each patient needs and has the opportunity to

receive one or more processes of care but not all patients need the same care. Composite measures that

use this model summarize the proportion of appropriate care that is delivered. The denominator for an

opportunities model composite is the sum of opportunities to receive appropriate care across a panel of

process measures. The numerator is the sum of the appropriate services that are actually delivered. The

composite measure of recommended hospital care for heart attack is an example where this model is

applied. The total number of patients who actually receive treatments represented by individual

components of the composite measure (e.g., aspirin therapy within 24 hours, beta blocker within 24

hours, smoking cessation counseling) is divided by the sum of all of these opportunities to receive

appropriate care.

ivGo to Chapter 1, Introduction and Methods, in the 2006 NHQR for more detailed information about these and other

methods that are used to calculate composite measures used in the reports.

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Chapter 1
Table 1.3. Composite measures in the 2008 NHQR and NHDR

Composite measure Individual measures forming composite

Receipt of three • Adults age 40 and over with diabetes who received a hemoglobin A1c

recommended diabetes measurement in the calendar year

services • Adults age 40 and over with diabetes who received a dilated eye

examination in the calendar year

• Adults age 40 and over with diabetes who had feet checked for sores

or irritation in the calendar year

Childhood immunization • Children ages 19-35 months who received 4 doses of

diphtheria-tetanus-pertussis vaccine

• Children ages 19-35 months who received 3 doses of polio vaccine

• Children ages 19-35 months who received 1 dose of

measles-mumps-rubella vaccine

• Children ages 19-35 months who received 3 doses of Haemophilus

influenzae type B vaccine

• Children ages 19-35 months who received 3 doses of hepatitis B vaccine

Recommended hospital care • Hospital patients with heart attack who received aspirin within 24 hours

for heart attack of admission

• Hospital patients with heart attack who were prescribed aspirin at

discharge

• Hospital patients with heart attack who received beta blocker within

24 hours of admission

• Hospital patients with heart attack who were prescribed beta blocker

at discharge

• Hospital patients with heart attack and left ventricular systolic

dysfunction who were prescribed ACE inhibitor or ARB at discharge

• Smokers with heart attack who received smoking cessation counseling

while hospitalized

Recommended hospital care • Hospital patients with heart failure who received an evaluation of left

for heart failurea ventricular ejection fraction

• Hospital patients with heart failure and left ventricular systolic dysfunction

who were prescribed ACE inhibitor or ARB at discharge

Recommended hospital care • Hospital patients with pneumonia who received the initial antibiotic

for pneumoniab dose within 4 hours of hospital arrival

• Hospital patients with pneumonia who received the initial antibiotic

consistent with current recommendations

• Hospital patients with pneumonia who had blood cultures collected

before antibiotics were administered

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Table 1.3. Composite measures in the 2008 NHQR and NHDR

Composite measure Individual measures forming composite

• Hospital patients with pneumonia who received influenza screening

or vaccination

• Hospital patients with pneumonia who received pneumococcal

screening or vaccination

Timing of antibiotics to • Adult surgery patients who received prophylactic antibiotics within 1

prevent postoperative hour prior to surgical incision

wound infection • Adult surgery patients who had prophylactic antibiotics discontinued

within 24 hours after surgery end time

Postoperative complicationsc • Adult surgery patients with postoperative pneumonia events

• Adult surgery patients with postoperaive catheter-associated urinary

tract infection

• Adult surgery patients with postoperative venous thromboembolic events

Complications of central • Bloodstream infections per 1,000 central venous catheter placements

venous catheters • Mechanical adverse events per 1,000 central venous catheter placements

Patients’ experience of care • Adults who had a doctor’s office or clinic visit in the last 12 months

whose providers sometimes or never listened carefully to them

• Adults who had a doctor’s office or clinic visit in the last 12 months

whose providers sometimes or never explained things in a way they

could understand

• Adults who had a doctor’s office or clinic visit in the last 12 months

whose providers sometimes or never showed respect for what they

had to say

• Adults who had a doctor’s office or clinic visit in the last 12 months

whose providers sometimes or never spent enough time with them

• Children who had a doctor’s office or clinic visit in the last 12 months

whose health providers sometimes or never listened carefully

• Children who had a doctor’s office or clinic visit in the last 12 months

whose health providers sometimes or never explained things clearly

• Children who had a doctor’s office or clinic visit in the last 12 months

whose health providers sometimes or never showed respect for what

they or their parents had to say

• Children who had a doctor’s office or clinic visit in the last 12 months

whose health providers sometimes or never spent enough time with them

aUse of angiotensin-converting enzyme (ACE) inhibitors in patients with left ventricular systolic dysfunction was

changed to also include angiotensin receptor blockers (ARBs) as an acceptable alternative.

bAppropriate antibiotic selection was changed to exclude patients with health care-associated pneumonia from the

denominator used in the calculation. Collection of samples for blood culture within 24 hours of hospital arrival was

changed so that only those patients who were admitted to the intensive care unit within 24 hours of hospital arrival are

included in the denominator.

cThe individual measure for postoperative urinary tract infection was refined to include only patients with catheterassociated urinary tract infections.

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Presentation of Disparities

The 2008 NHDR and its companion NHQR continue to be formatted as chartbooks. The 2008 reports

have been improved to show charts and data in a more readable format and to provide more concise

summaries of the findings in each chart.

Each section in the 2008 report begins with a description of the importance of the section’s topic in a

standardized format. After introductory text, chart figures and accompanying findings highlight a small

number of core measures relevant to this topic. When data are available, these charts typically show

contrasts by:

◆ Race—Blacks, Asians,v Native Hawaiians and Other Pacific Islanders (NHOPIs), American Indians

and Alaska Natives (AI/ANs), and people of more than one race compared with Whites.

◆ Ethnicity—Hispanics compared with non-Hispanic Whites.vi

◆ Income—Poor, near-poor, and middle-income people compared with high-income people.vii

◆ Education—People with less than a high school education and high school graduates compared with

people with any college education.

Almost all core measures and composite measures have multiple years of data, so figures typically

illustrate trends over time. When data support stratified analyses, a figure showing racial and ethnic

differences stratified by SES is included. These data are summarized in bullet format. Figures include a

note about the reference group for population-based measures and the denominator for measures based on

services or events.

For some measures with supporting data, regression models were run and used to help interpret bivariate

and stratified results. (These are discussed in more detail in “Bivariate and Multivariate Analyses”

below.)viii

v“Asian” includes “Asian or Pacific Islander” when information is not collected separately for each group.

viNot all data sources used in the NHDR collect data by race and ethnicity separately (e.g., allowing for comparisons of

Blacks with Whites and Hispanics with non-Hispanic Whites). When this is the case, comparisons are made by

combined racial/ethnic categories (e.g., comparing non-Hispanic Blacks and Hispanics with non-Hispanic Whites).

viiThroughout this report, “poor” is defined as having family income less than 100% of the Federal poverty level; “near

poor,” between 100% and 199%; “middle income,” between 200% and 399%; and “high income,” 400% or more of the

Federal poverty level. These are based on U.S. Census poverty thresholds for each data year, which are used for

statistical purposes, unlike HHS poverty guidelines used for programmatic purposes.

viiiThe measures are obese adults given advice about exercise and individuals having a usual primary care provider.

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Decades of Work To Reduce

Disparities in Health Care

Produce Limited Success—JAMA
Gaps between priority populations and the reference group are characterized as growing larger, getting

smaller, or not changing. This is done as 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.

Findings presented in the text meet report criteria for importanceix; comparisons not discussed in the text

do not meet these criteria. However, absence of differences that meet criteria for importance should not

be interpreted as absence of disparities. Often, large differences between groups did not meet criteria for

statistical significance because of small sample sizes and limited power. In addition, significance testing

used in this report does not take into account multiple comparisons.

Effectiveness measures for each condition or care setting area are organized further into categories that

reflect the patient’s need for preventive care, treatment of acute illness, or management of chronic

conditions. Further detail on each of these categories and the measures included can be found in Chapter

2, Quality of Health Care.

Trends in Health Care Quality and Access

As in previous NHDRs, the 2008 report uses the earliest and most recent available NHDR data estimates

for each measure to calculate average annual rate of change for the general U.S. population and for each

racial, ethnic, and socioeconomic group. Consistent with Health, United States,1 the geometric rate of

change, which assumes the same rate each year between the two time periods, has been calculated for the

2008 NHDR and NHQR.x

Two criteria are applied to determine whether a significant trend exists:

◆ First, the difference between the oldest and most recent estimates must be statistically significant at

alpha=0.05.

◆ Second, the average annual rate of change must be at least 1% when the measures are framed as a

favorable outcome or as an adverse outcome.

Only changes over time that meet these two criteria are discussed in the 2008 reports. Changes in

disparities are categorized as follows:

◆ Core measures for which the relative differences are changing less than 1% per year are identified as

staying the same.

ixCriteria for importance are that the difference is statistically significant at the alpha=0.05 level, two-tailed test, and

that the relative difference is at least 10% different from the reference group when framed positively as a favorable

outcome or negatively as an adverse outcome.

xThe geometric rate of change assumes that a measure increases or decreases at the same rate during each year between

two time periods. It is calculated using the following formula: [(VY/VZ)1/N−1] × 100, where VY is the most recent

year’s value, VZ is the most distant year’s value, and N is the number of years in the interval. See the entry for Average

Annual Rate of Change in Appendix II, Definitions and Methods, Health, United States, 2007 (available at

http://www.cdc.gov/nchs/hus.htm).

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◆ Core measures for which the relative differences are becoming smaller at a rate of more than 1% per

year are identified as improving.

◆ Core measures for which the relative differences are becoming larger at a rate of more than 1% per

year are identified as worsening.

◆ Changes of greater than 5% per year are also differentiated from changes of between 1% and 5% per

year in some figures.

An additional constraint relates to trends among specific racial and ethnic groups. Different Federal

databases completed transition to the new Federal standards for racial and ethnic data that were required

by 2003 at different times. These new standards created two separate racial categories: “Asian” and

“Native Hawaiian or Other Pacific Islander.” In addition, individuals could report more than one race.

This change results in underestimates for the “American Indian and Alaska Native” category, since a large

proportion of this group identifies as mixed race. In contrast, effects on estimates for Whites, Blacks, and

Hispanics were proportionately much smaller. Therefore, the 2008 NHDR, as in the previous year, shows

shorter trends (i.e., fewer years of data) for groups directly or significantly affected by the new standards,

such as Asian, NHOPI, AI/AN, and multiple-race individuals.

Bivariate and Multivariate Analyses

Bivariate analyses are included for some measures for which data are available to examine the

interrelationship between race/ethnicity and SES. These analyses appear in Chapter 3, Access to Health

Care, and in the section on low-income groups in Chapter 4, Priority Populations. This year, the NHDR

also examines the interrelationship between insurance status and income for quality of care in more depth

for some selected measures through the use of bivariate analyses in Chapter 4, Priority Populations.

In multivariate models, estimates for a measure are controlled for multiple factors, including race,

ethnicity, income, education, insurance, age, gender, and residence location, to show the extent to which

these factors affect an outcome. To account for Medicare, the analyses were done separately for people

under age 65 and age 65 years and over. Finally, to ensure that the findings were not biased by the

sequence in which each factor was entered into the analysis, 12 separate analyses were done for each of

the 12 measures. Adjusted odds ratios are shown to quantify the relative magnitude of disparities after

controlling for a number of confounding factors. Two selected measures—one quality measure (obese

adults given advice about exercise) and one access measure (persons who have a usual primary care

provider)—were selected to conduct multivariate analyses.

Quantifying Disparities

In the Highlights and in Chapter 4, Priority Populations, the extent of disparities across the core measures

is summarized for Blacks, Hispanics, Asians, NHOPIs, AI/ANs, and poor populations. Racial, ethnic,

and socioeconomic groups are compared with a designated reference group for each core measure. Each

group could receive care that is worse than, about the same as, or better than the reference group. For

each group, the percentages of measures for which the group received worse care, similar care, or better

care were calculated.

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Introduction and Methods

Health care utilization measures are difficult to interpret and were excluded when summarizing disparities

in access to care.xi In Chapter 4, Priority Populations, which presents information on each population

separately, all core measures are used when summarizing trends in disparities for each group. However,

in the Highlights, where multiple groups are presented side by side, only core measures with estimates for

all racial and ethnic groups over time are used, to facilitate comparisons across groups. As noted above,

an exception is made for income comparisons of quality measures because much less information is

available for income groups than for racial and ethnic groups.

Beginning with the 2005 NHDR, rates relative to standard reference groups are used to quantify the

magnitude of disparities and to identify the largest disparities faced by specific groups. For each group,

the group rate was divided by the reference group rate to calculate the relative rate for each core measure.

Relative rates of selected core measures are presented in the Highlights section of this report.

Changes to the Measure Set

The measure sets used in the 2008 NHDR and NHQR have been improved in several ways. As in

previous years, a handful of measures were modified to reflect changing standards of care or improved

information about care. Although no core measures were added, some noncore measures are being

presented in the reports for the first time in 2008.

Modifications to Existing Composite Measures

The changes applied to existing measures this year were for individual component measures that make up

composite measures. The changes affect the comparability of data over time to varying degrees for each

measure. Beginning in the 2007 reports, the following core composite measures of effectiveness and

patient safety underwent modifications:

◆ Recommended hospital care received by Medicare patients with acute myocardial infarction

composite. The individual measure on use of angiotensin-converting enzyme (ACE) inhibitors in

patients with left ventricular systolic dysfunction was changed to also include angiotensin receptor

blockers (ARBs) as an acceptable alternative.

◆ Recommended hospital care received by Medicare patients with heart failure. The individual

measure on use of ACE inhibitors in patients with left ventricular systolic dysfunction was changed

to also include ARBs as an acceptable alternative.

xiInterpreting health care utilization data is more complex than analyzing data on patient perceptions of access to care.

Along with access to care, health care utilization is strongly affected by health care need and patient preferences and

values. In addition, greater use of services does not necessarily indicate better care. In fact, high use of some inpatient

services may reflect impaired access to outpatient services. For these reasons, measures of health care utilization are

excluded from summaries of access to health care.

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Introduction and Methods

◆ Recommended hospital care received by Medicare patients with pneumonia. Two component

measures underwent revision:

• The individual measure of appropriate antibiotic selection for community-acquired pneumonia

was changed to exclude patients with health care-associated pneumonia from the denominator

used in the calculation.

• The individual measure for the collection of samples for blood culture within 24 hours of

hospital arrival was changed so that only those patients who were admitted to the intensive

care unit within 24 hours of hospital arrival are included in the denominator.

◆ Postoperative care. The individual measure for postoperative urinary tract infection was refined to

include only patients with catheter-associated urinary tract infections.

New Noncore Measures

Non-core measures are measures identified by the Interagency Work Group to provide additional

information in the NHDR to fill a specific data gap in a particular topic area. Each year, the NHDR

features non-core measures in special focus sections of the report. The following new non-core measures

have been included in the 2008 NHDR to fill identified gaps:

◆ One measure of workforce diversity from the American Community Survey (ACS):

• U.S. LPNs/LVNs by race and ethnicity.

◆ A refined measure of mental health treatment for depression from the Collaborative Psychiatric

Epidemiology Surveys:

• Receipt of minimally adequate treatment by adults with mental disorders.

◆ One measure of hospice care quality from the National Hospice and Palliative Care Organization

Family Evaluation of Hospice Care:

• Referral to hospice at the right time.

◆ Five additional measures of patient safety highlighted from the NHDR noncore measure set:

• Postoperative wound separation.

• Reclosure of postoperative abdominal incisional separation.

• Accidental puncture or laceration during procedures.

• Iatrogenic pneumothorax.

• Deaths per 1,000 admissions in low-mortality DRGs.

Measure revisions were proposed and reviewed in meetings of the Interagency Work Group for the

NHDR, which includes representation from across HHS.

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Introduction and Methods

National Disparities Report, 2008

Chapter 1
Databases Used in the 2008 Reports

Table 1.4 lists the databases used in the 2008 reports. This year the Collaborative Psychiatric

Epidemiology Surveys (CPES) is added to the set of databases that were used in the 2007 reports.

Table 1.4. Databases used in the 2008 reports (new databases in italics)

Survey data collected from populations

• AHRQ, Medical Expenditure Panel Survey (MEPS), 2002-2005

• CAHPS® (Consumer Assessment of Healthcare Providers and Systems) Hospital Survey, 2008

• Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System

(BRFSS), 2001-2006

• CDC-National Center for Health Statistics (NCHS), National Health and Nutrition Examination Survey

(NHANES), 1999-2006

• CDC-NCHS, National Health Interview Survey (NHIS), 1998-2006

• CDC-NCHS/National Immunization Program, National Immunization Survey (NIS), 1998-2006

• Centers for Medicare & Medicaid Services (CMS), Medicare Current Beneficiary Survey (MCBS), 1998-

2004

• National Center for Education Statistics, National Assessment of Adult Literacy (NAAL), Health Literacy

Component, 2003

• National Hospice and Palliative Care Organization, Family Evaluation of Hospice Care (FEHC), 2005-

2007

• National Institutes of Health (NIH), National Institute of Mental Health (NIMH), Collaborative Psychiatric

Epidemiology Surveys (CPES), 2001-2003

• Substance Abuse and Mental Health Services Administration (SAMHSA), National Survey on Drug Use

and Health (NSDUH), 2002-2006

• U.S. Census Bureau, American Community Survey (ACS), 2006

Data collected from samples of health care facilities and providers

• American Cancer Society and American College of Surgeons, National Cancer Data Base (NCDB),

1999-2005

• CDC-NCHS, National Ambulatory Medical Care Survey (NAMCS), 1997-2006

• CDC-NCHS, National Hospital Ambulatory Medical Care Survey-Emergency Department (NHAMCSED), 1997-2006

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• CDC-NCHS, National Hospital Ambulatory Medical Care Survey-Outpatient Department (NHAMCSOPD), 1997-2006

• CDC-NCHS, National Hospital Discharge Survey (NHDS), 1998-2006

• CMS, End Stage Renal Disease Clinical Performance Measures Project (ESRD CPMP), 2001-2006

Data extracted from data systems of health care organizations

• AHRQ, Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases disparities analysis

file,a 2001-2005

• CMS, Home Health Outcomes and Assessment Information Set (OASIS), 2002-2006

• CMS, Hospital Compare, 2006

• CMS, Medicare Patient Safety Monitoring System (MPSMS), 2003-2006

• CMS, Nursing Home Minimum Data Set (MDS), 2002-2006

• CMS, Quality Improvement Organization (QIO) program, Hospital Quality Alliance (HQA) measures,

2002-2006

• HIV Research Network (HIVRN) data, 2003-2005

• Indian Health Service, National Patient Information Reporting System (NPIRS), 2002-2005

• National Committee for Quality Assurance, Health Plan Employer Data and Information Set (HEDIS®),

2001-2005

• NIH, United States Renal Data System (USRDS), 1998-2004

• SAMHSA, Treatment Episode Data Set (TEDS), 2002-2005

Data from surveillance and vital statistics systems

• CDC-National Center for HIV, Viral Hepatitis, STD, and TB Prevention, HIV/AIDS Reporting System,

2000-2004

• CDC-National Center for HIV, STD, and TB Prevention, TB Surveillance System, 1999-2004

• CDC, National Program of Cancer Registries (NPCR), 2000-2005

• CDC-NCHS, National Vital Statistics System (NVSS), 1999-2005

• NIH-National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) program, 2000-2005

aThis file is designed to provide national estimates of disparities in the AHRQ Quality Indicators using weighted

records from a sample of hospitals from the following 23 States: Arizona, Arkansas, California, Colorado, Connecticut,

Florida, Georgia, Hawaii, Kansas, Maryland, Massachusetts, Michigan, Missouri, New Hampshire, New Jersey, New

York, Oklahoma, Rhode Island, South Carolina, Tennessee, Texas, Vermont, and Wisconsin.

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Chapter 1
Expanded Analysis of Trends in Disparities

Starting with the 2007 NHDR, an additional dimension of trends is emphasized in the reports. In

previous years, the NHDR included discussion of change over time for each population from baseline to

most recent data year, where available. The NHDR also reported separately on statistically significant

differences between a comparison group and reference group. The 2008 NHDR continues to combine the

discussion of change over time and differences between groups by focusing on the change over time in

the difference between groups. Thus, the NHDR shows not only where disparities exist in health care

quality and access to health care, but also how disparities have changed over time.

The change over time in the disparity between the comparison group and reference group is reported if

the following two criteria are met:

◆ There is a statistically significant difference between the estimate for the baseline year and the most

recent data year for at least one group.

◆ There is a statistically significant difference between a comparison group and reference group at

baseline year, at most recent data year, or at both baseline year and most recent data year.

The change is reported as increased if the absolute difference in the gap between the comparison group

and reference group in the most recent data year is greater than the gap in the baseline year. The change

is reported as decreased if the absolute difference in the gap between the comparison group and reference

group in the most recent data year is less than the gap in the baseline year. Change is not reported if there

is no change in either the comparison group or the reference group, if both the reference group and the

comparison group show significant differences between the baseline year and the most recent data year,

or if data are not available for more than one data year.

No statistical test was performed on the change from the baseline year to the most recent data year in the

difference between the comparison group and the reference group. Since most differences are relatively

small, performing an additional statistical test would eliminate most reports of change in disparities.

The NHDR continues to report statistically significant differences between the comparison group and

reference group where data are available for the most recent data year. Since the NHDR now contains

estimates for several data years for most of the measures, for simplification in reporting on disparities,

only the most recent data year is discussed.xii

Individuals With Disabilities

The Interagency Work Group Subcommittee on Disability Statistics convened to develop a broad

definition of disabilities that can be applied across different national data sources to obtain data on the

quality of care for adults with disabilities. Beginning with the 2007 NHDR, AHRQ has used a broad,

inclusive measure of disability. This measure is intended to be consistent with statutory definitions of

xiiFor estimates from prior years, go to Appendix D: Data Tables for previous releases of the NHDR.

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Chapter 1
disability, such as the first criterion of the Americans With Disabilities Act of 1990, 42 U.S.C. §§ 12181

et seq., (i.e., having a physical or mental impairment that substantially limits one or more major life

activities) and Federal program definitions based on the Americans With Disabilities Act.

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. 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.

The use of the Subcommittee’s recommendation of these paired measures of basic and complex activity

limitations is conceptually similar to the way others have divided disability. It is also consistent with the

International Classification of Functioning, Disability, and Health (ICF) separation of activities and

participation domains. These two categories are not mutually exclusive; persons may have both

limitations in basic activities and limitations in complex activities. Further information regarding the

definition and methods can be found in the Individuals With Disabilities and Special Health Care Needs

section in Chapter 4, Priority Populations.

Reference

1. National Center for Health Statistics. Health, United States, 2007. Available at http://www.cdc.gov/nchs/hus.htm. Accessed

November 6, 2008.

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C h a p t e r 2 .

Q u a l i t y o f H e a l t h C a r e

As better understanding of health and sickness has led to superior ways of preventing, diagnosing, and

treating diseases, the health of most Americans has improved dramatically. However, ample evidence

indicates that some Americans do not receive the full benefits of high-quality care. Specifically, a

substantial body of public health, social science, and health services research has shown extensive

disparities in health care related to race, ethnicity, and socioeconomic status (SES). These disparities have

been confirmed in previous releases of the National Healthcare Disparities Report.

Components of Health Care Quality

Quality health care means doing the right thing, at the right time, in the right way, for the right people—

and having the best possible results.1 Quality health care is care that is2:

◆ Effective—Providing services based on scientific knowledge to all who could benefit and refraining

from providing services to those not likely to benefit.

◆ Safe—Avoiding injuries to patients from the care that is intended to help them.

◆ Timely—Reducing waits and sometimes harmful delays for both those who receive and those who

give care.

◆ Patient centered—Providing care that is respectful of and responsive to individual patient

preferences, needs, and values and ensuring that patient values guide all clinical decisions.

◆ Equitable—Providing care that does not vary in quality because of personal characteristics such as

gender, ethnicity, geographic location, and SES.

◆ Efficient—Avoiding waste, including waste of equipment, supplies, ideas, and energy.

Health care quality is measured in several ways, including:

◆ Clinical performance measures of how well providers deliver specific services needed by specific

patients, such as whether children get the immunizations they need.

◆ Assessments by patients of how well providers meet health care needs from the patient’s perspective,

such as whether providers communicate clearly.

◆ Outcome measures, such as death rates from cancers preventable by screening, that may be affected

by the quality of health care received.

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Chapter 2
How This Chapter Is Organized

This chapter presents information about disparities in the quality of health care in America, with a

presentation of a subset of core measures. The measures used here are the same as those used in the

National Healthcare Quality Report (NHQR). This chapter is constructed to mirror sections in the

NHQR—effectiveness, patient safety, timeliness, and patient centeredness. Due to constraints on the

length of this report, only a subset of the core measures is presented.

Effectiveness of care is presented in Chapter 2 in eight clinical condition or care setting areas: cancer;

diabetes; end stage renal disease (ESRD); heart disease; HIV and AIDS; mental health and substance

abuse; respiratory diseases; and nursing home, home health, and hospice care. Maternal and child health

is discussed in Chapter 4, Priority Populations.

As in previous NHDRs, this chapter’s discussion of quality of care focuses on disparities in quality related

to race, ethnicity, and SES in the general U.S. population. Disparities in quality of care within specific

priority populations are presented in Chapter 4. This chapter also presents analyses of changes over time

by race, ethnicity, and SES, as well as some stratified analyses.

Categorization of Effectiveness Measures by Health Care

Need

In the effectiveness section of this chapter, measures are organized into categories related to the patient’s

need for preventive care, treatment of acute illness, and chronic disease management. There is sizable

overlap among these categories, and some measures may be considered to belong in more than one

category. Outcome measures are particularly difficult to categorize when prevention, treatment, and

management all play important roles. For the purposes of this report, however, measures are placed into

categories that best fit the general descriptions below:

◆ Prevention—Caring for healthy people is an important component of health care. Educating people

about healthy behaviors can help to postpone and avoid illness and disease. Additionally, detecting

health problems at an early stage increases the chances of effectively treating them, often reducing

suffering and expenditures.

◆ 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 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

normal, healthy living and frequent medical problems.

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Chapter 2
Note that findings for women and children, which parallel those presented in the NHQR for maternal and

child health, are presented in the sections on women and children in Chapter 4. Effectiveness measures

presented in this section are organized within the categories of prevention, treatment, and management.

For findings related to all core measures of effectiveness, go to Tables 2.1a and 2.1b.

Section Measure

Prevention

Cancer Colorectal cancer screening

Cancer Advanced stage colorectal cancer patients*

Heart disease Counseling obese adults about overweight*

Heart disease Counseling obese adults about exercise

Respiratory diseases Pneumococcal vaccination

Maternal and child health (women) Prenatal care/maternal health

Maternal and child health (women) Obese adults advised about exercise

Maternal and child health (children) Early childhood vaccinations

Maternal and child health (children) Counseling about physical activity*

Maternal and child health (children) Vision screening

Treatment

Cancer Recommended care for breast and colorectal cancer*

Heart disease Receipt of recommended hospital care for heart failure

Mental health and substance abuse Receipt of needed treatment for illicit drug use

Mental health and substance abuse Receipt of treatment for depression

Mental health and substance abuse Receipt of minimally adequate treatment for mental

disorders

Respiratory diseases Receipt of recommended care for pneumonia

Maternal and child health (women) Mortality rate for acute myocardial infarction

Maternal and child health (women) Recommended hospital care for heart attack

Management

Diabetes Receipt of three recommended diabetes services

Diabetes Lower extremity amputations

Diabetes Controlled hemoglobin, cholesterol, and blood pressure

End stage renal disease Patients with adequate hemodialysis

End stage renal disease Registration for transplantation

HIV and AIDS New AIDS cases

HIV and AIDS PCP and MAC prophylaxis*

Respiratory diseases Daily asthma medication

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

37

Chapter 2
National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

38

Chapter 2

Section Measure

Nursing home, home health, and hospice care Use of physical restraints on nursing home residents

Nursing home, home health, and hospice care Presence of pressure sores in nursing home residents

Nursing home, home health, and hospice care Improvement by home health care patients in walking

or moving around

Nursing home, home health, and hospice care Acute care hospitalization of home health care patients

Nursing home, home health, and hospice care Hospice care*,i

Maternal and child health (women) New AIDS cases

* Noncore measure.

i

Two noncore measures of hospice care are from the National Hospice and Palliative Care Organization Family

Evaluation of Hospice Care: hospice patients who did not receive the right amount of medicine for pain and hospice

patients who did not receive end-of-life care consistent with their stated wishes.
Effectiveness

Cancer

Number of deaths (2008 est.)..............................................................................................................565,6503

Cause of death rank (2005) ........................................................................................................................2nd4

Number of living Americans who have been diagnosed with cancer (2005 est.) .......................11,098,4505

New cases of cancer (2008 est.) ......................................................................................................1,437,1803

New cases of colorectal cancer (2008 est.) ........................................................................................148,8103

Total costii (2007).......................................................................................................................$219.2 billion6

Direct costsiii (2007) ....................................................................................................................$89.0 billion6

Cost-effectivenessiv of colorectal cancer screening..........................................................$0-$14,000/QALY7

Cost-effectiveness of breast cancer screening .......................................................$35,000-$165,000/QALY7

Cost-effectiveness of cervical cancer screening......................................................$14,000-$35,000/QALY7

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

Prevention: Colorectal Cancer Screening

Ensuring that all populations have access to appropriate cancer screening services is a core element of

reducing cancer health disparities.8 This year the NHDR focuses on colorectal cancer; findings for breast

cancer are found in the 2007 NHDR. Screening for colorectal cancer—including fecal occult blood test

(FOBT), sigmoidoscopy, colonoscopy, and

proctoscopy—is an effective way of reducing

new cases of late-stage disease and mortality

caused by this cancer.

iiTotal cost is composed of the cost of medical care itself (direct cost) and the economic costs of morbidity and

mortality (indirect cost).

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

and physician and other professional services.”6

ivCost-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. For example, the net cost for colorectal cancer screening

ranges from $0 to $14,000 for each QALY saved.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

39

Chapter 2 Cancer

Colorectal cancer is the third most

common cancer in adults.
Figure 2.1. Composite measure: Adults age 50 and over who received colorectal cancer

screening (colonoscopy, sigmoidoscopy, proctoscopy, or fecal occult blood test [FOBT]), by race

(left), ethnicity (top right), and income (bottom left), 2000-2005

Key: AI/AN = American Indian/Alaska Native.

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health Interview Survey,

2000, 2003, and 2005.

Reference population: Civilian noninstitutionalized population

age 50 and over.

Note: Data were insufficient for this analysis for Native Hawaiians

and Other Pacific Islanders.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

40

Chapter 2

0

10

20

30

40

50

60

70

80

90

White

Black

2003

2005

Percent

2000

Asian

Total

>1 Race

AI/AN

0

10

20

30

40

50

60

70

80

90

2003

2005

Percent

2000

Non-Hispanic White

Hispanic

0

10

20

30

40

50

60

70

80

90

2003

2005

Percent

2000

Near Poor High Income

Poor Middle Income

Cancer
National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

41

Chapter 2

◆ Overall, the percentage of adults age 50 and over who received colorectal cancer screening increased

from 2000 to 2005 (49.8% to 55.5%; Figure 2.1).

◆ From 2000 to 2005, the gap between Blacks and Whites in the percentage of adults age 50 and over

who received colorectal cancer screening increased. In 2005, Blacks were less likely than Whites to

receive a colonoscopy, sigmoidoscopy, or proctoscopy or an FOBT (48.6% compared with 56.8%).

◆ The gap between Asians and Whites increased. In 2005, Asians were less likely than Whites to

receive colorectal cancer screening (42.4% compared with 56.8%).

◆ The gap between American Indian/Alaska Natives (AI/ANs) and Whites remained the same. In

2005, AI/ANs were less likely than Whites to receive a colorectal cancer screening (38.1%

compared with 56.8%).

◆ The gap between Hispanics and non-Hispanic Whites increased. In 2005, Hispanics were less likely

than non-Hispanic Whites to receive colorectal cancer screening (37.3% compared with 58.5%).

Racial and ethnic minorities are disproportionately of lower SES. To distinguish the effects of race,

ethnicity, income, and education on cancer screening, this measure is stratified by income (Figure 2.2)

and education level (Figure 2.3).

Figure 2.2. Composite measure: Adults age 50 and over who received colorectal cancer

screening (colonoscopy, sigmoidoscopy, proctoscopy, or fecal occult blood test [FOBT]), by race

(left) and ethnicity (right), stratified by income, 2005

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 2005.

Reference population: Civilian noninstitutionalized population age 50 and over.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

0

10

20

30

40

50

60

70

80

90

100

Percent

White

Black

Poor Near

Poor

Middle

Income

High

Income

0

10

20

30

40

50

60

70

80

90

100

Percent

Non-Hispanic White

Hispanic

Poor Middle

Income

Near

Poor

High

Income

Cancer
Figure 2.3. Adults age 50 and over who received a colonoscopy, sigmoidoscopy, or proctoscopy

or a fecal occult blood test (FOBT), by race (left) and ethnicity (right), stratified by education,

2005

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 2005.

Reference population: Civilian noninstitutionalized population age 50 and over.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

◆ After controlling for income, there were no statistically significant differences between Blacks and

Whites in the percentage of adults age 50 and over who received colorectal cancer screening (Figure

2.2).

◆ There were no statistically significant differences between Blacks and Whites of the same education

level except among college-educated adults. Blacks with at least some college education were less

likely than Whites to receive colorectal cancer screening (57.8% compared with 63.8%; Figure 2.3).

◆ Both before and after controlling for income and education, Hispanics were less likely than nonHispanic Whites to receive colorectal cancer screening at all income and education levels.

Prevention: Advanced Stage Colorectal Cancer

Cancers can be diagnosed at different stages. The rate of cancers that are diagnosed at advanced stages is

a measure of the effectiveness of cancer screening efforts. Differences in rates may vary across racial and

ethnic groups due to differences in prevalence.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

42

Chapter 2

0

20

40

60

80

100 Percent

White

Black

<High

School

At Least

Some

College

High

School Grad

0

20

40

60

80

100

Percent

Non-Hispanic White

Hispanic

<High

School

At Least

Some

College

High

School Grad

Cancer
Figure 2.4. Colorectal cancer diagnosed at advanced stage (tumors diagnosed at regional or

distant stage) per 100,000 population age 50 and over, by race (left) and ethnicity (right),

2000-2005

Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: National Cancer Institute, Surveillance, Epidemiology, and End Results program, 2000-2005.

Reference population: Men and women age 50 and over.

Note: Rates are age adjusted.

◆ From 2000 to 2005, the total rate of diagnosis for advanced stage colorectal cancer decreased (from

95.2 per 100,000 to 80.8 per 100,000; data not shown). The rate decreased for all groups except

AI/ANs, for whom the change was not statistically significant.

◆ From 2000 to 2005, the gap between Blacks and Whites remained the same. In 2005, Blacks were

more likely to be diagnosed at advanced stage with colorectal cancer than Whites (103.8 per 100,000

compared with 80.0 per 100,000).

◆ APIs were less likely than Whites to be diagnosed at advanced stage with colorectal cancer (66.7 per

100,000 compared with 80.0 per 100,000).

◆ From 2000 to 2005, there was no statistically significant change in the rate for AI/ANs, who were

less likely than Whites to be diagnosed at advanced stage with colorectal cancer (42.3 per 100,000

compared with 80.0 per 100,000).

◆ Hispanics were less likely than non-Hispanic Whites to be diagnosed at advanced stage with

colorectal cancer (65.6 per 100,000 compared with 81.5 per 100,000).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

43

Chapter 2

0

20

40

60

80

100

120

140 White

Black

2001

2003

Rate per 100,000

2002

API

AI/AN

2000

2004

2005

0

20

40

60

80

100

120

140

2001

2003

Rate per 100,000

2000

2002

2004

Non-Hispanic White

Hispanic

2005

Cancer
Treatment: Recommended Care for Breast and Colorectal Cancer Patients

Different diagnostic and treatment options exist for various types of cancer. Some aspects of cancer care

are well established as beneficial and are commonly recommended. The appropriateness of

recommended care depends on different factors, such as the stage or the extent of the cancer within the

body (especially whether the disease has spread from the original site to other parts of the body). Other

types of care are important for accurate diagnosis, such as ensuring the adequate examination of lymph

nodes when surgery is performed (e.g., to remove colon cancer).

Among women diagnosed with breast cancer who receive surgical therapy, approximately 63% undergo

breast-conserving surgery.9 Randomized controlled trials have shown that women who undergo breastconserving surgery and postoperative radiation therapy significantly reduce local recurrence rates.10,11,12

Figure 2.5. Women under age 70 treated for breast cancer* with breast-conserving surgery who

received radiation therapy to the breast within 1 year of diagnosis, by race (left) and ethnicity

(right), 1999-2005

* American Joint Committee on Cancer Stage I, II, or III, primary invasive epithelial breast cancer.

Source: Commission on Cancer, American College of Surgeons and American Cancer Society, National Cancer Data Base, 1999-

2005.

Reference population: U.S. population, women.

◆ From 1999 to 2005, the gap between Blacks and Whites remained the same. In 2005, Black patients

with breast cancer were less likely than Whites to receive radiation therapy to the breast within 1

year of diagnosis (68.1% compared with 75.3%; Figure 2.5).

◆ From 1999 to 2005, the gap between Hispanics and non-Hispanic Whites increased. In 2005,

Hispanic patients with breast cancer were less likely than non-Hispanic Whites to receive radiation

therapy to the breast within 1 year of diagnosis (61.5% compared with 76.0%).

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

44

Chapter 2

0

10

20

30

40

50

60

70

80

90

100

White

Black

2001

2003

Percent

2002

Asian

Total

1999

2000

2004

2005

0

10

20

30

40

50

60

70

80

90

100

2001

2002

Percent

Non-Hispanic White

Hispanic

1999

2000

2003

2004

2005

Cancer
Figure 2.6. Women with Stage I-IIb breast cancer who received axillary node dissection or

sentinel lymph node biopsy (SLNB) at the time of surgery (lumpectomy or mastectomy), by race

(left) and ethnicity (right), 1999-2005

Source: Commission on Cancer, American College of Surgeons and American Cancer Society, National Cancer Data Base, 1999-

2005.

Reference population: U.S. population, women.

◆ From 1999 to 2005, overall there was improvement in the percentage of women with Stage I-IIb

breast cancer who received an axillary node dissection or sentinel lymph node biopsy at the time of

surgery (from 75.3% to 86.5%; Figure 2.6).

◆ There were no statistically significant differences by race or ethnicity (Figure 2.6) or income (data

not shown).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

45

Chapter 2

0

10

20

30

40

50

60

70

80

90

100

White

Black

2001

2003

Percent

2002

Asian

Total

1999

2000

2004

2005

0

10

20

30

40

50

60

70

80

90

100

2001

2002

Percent

Non-Hispanic White

Hispanic

1999

2000

2003

2004

2005

Cancer
Lymph nodes must be examined to accurately stage colon cancers and guide adjuvant therapy treatment

decisions.13,14 The quality measure of the percentage of colon cancer patients who have had at least 12

lymph nodes examined is endorsed by the National Quality Forum and is intended to be a benchmark for

hospital quality improvement initiatives.

Figure 2.7. Patients with colon cancer who received surgical resection of colon cancer that

included at least 12 lymph nodes pathologically examined, by race (top left), ethnicity (top right),

and income (bottom left), 2003-2005

Source: Commission on Cancer, American College of Surgeons

and American Cancer Society, National Cancer Data Base, 2003-

2005.

Reference population: U.S. population.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

46

Chapter 2

40

50

60

70

80

90

100

White

Black

2003

Percent

Asian

Total

2004

2005

Z

0

40

50

60

70

80

90

100

Percent

Non-Hispanic White

Hispanic

2003

2004

Z

0

2005

40

50

60

70

80

90

100

Percent

2003

2004

Z

0

2005

Poor

Low Income

Middle Income

High Income

Cancer
◆ From 2003 to 2005, there was improvement among racial and ethnic groups in the percentage of

patients with colon cancer who received recommended care (Figure 2.7).

◆ During this period, the gap between Asians and Whites remained the same. In 2005, Asians with

colon cancer were more likely than Whites to receive recommended care for colon cancer (64.9%

compared with 59.9%).

◆ During this period, the gap between poor people and high-income people increased. In 2005, poor

people with colon cancer were much less likely than high-income people to receive recommended

care for colon cancer (57.1% compared with 66.7%).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

47

Chapter 2 Cancer
Diabetes

Number of deaths (2005)......................................................................................................................75,1194

Cause of death rank (2005).........................................................................................................................6th4

Total number of Americans with diabetes (2007).....................................................................23.6 million15

Number of people with diagnosed diabetes (2007) ..................................................................17.9 million15

Number of people with undiagnosed diabetes (2007) ................................................................5.7 million15

New cases (age 20 and over, 2007)..............................................................................................1.6 million15

Total cost (2007) .........................................................................................................................$174 billion16

Direct medical costs (2007)........................................................................................................$116 billion16

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

Management: Receipt of Three Recommended Diabetes Services

Effective management of diabetes includes hemoglobin A1c (HbA1c)v testing, eye examination, and foot

examination, as well as appropriate influenza immunization and lipid management.17,18,19

vHbA1c is glycosylated hemoglobin and its level provides information about control of blood sugar levels.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

48

Chapter 2 Diabetes

Rate of Hispanic diabetics’ foot

amputations soar—DailyGazette.com

(Schenectady, NY), March 24, 2008
Figure 2.8. Composite measure: Adults age 40 and over with diagnosed diabetes who received

all three recommended services for diabetes in the calendar year, by race (top left), ethnicity (top

right), family income (bottom left), and education (bottom right), 2002-2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population age 40 and over.

Note: Recommended services for diabetes are: (1) HbA1c testing, (2) retinal eye examination, and (3) foot examination. Data include

people with both type 1 and type 2 diabetes. Rate is age adjusted to the 2000 U.S. standard population. Data were insufficient for

this analysis for Native Hawaiians and Other Pacific Islanders and for American Indians and Alaska Natives.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

49

Chapter 2

0

20

40

60

80

100 White

Black

2004

Percent

2002

2003

2005

0

20

40

60

80

100

2004

Percent

Non-Hispanic White

Hispanic

2002

2003

2005

0

20

40

60

80

100

2004

Percent

2002

2003

Near Poor High Income

Poor Middle Income

2005

0

20

40

60

80

100

2004

Percent

2002

2003

High School Grad

<High School Some College

2005

Diabetes
◆ From 2002 to 2005, the gap remained the same between Blacks and Whites in the percentage of

adults age 40 and over with diabetes who received three recommended services (Figure 2.8). In

2005, there were no statistically significant differences between Blacks and Whites for this measure

(37% compared with 41%).

◆ The gap increased between Hispanics and non-Hispanic Whites in the percentage of adults age 40

and over with diabetes who received three recommended services. In 2005, this percentage was

significantly lower for Hispanics than for non-Hispanic Whites (33.8% compared with 42.4%).

◆ From 2002 to 2005, the gap between poor people and high-income people remained the same. In

2005, this percentage was significantly lower for poor (30.3%), near-poor (28.5%), and middleincome people (38.4%) than for high-income people (52.6%).

◆ The gap remained the same between people with less than a high school education and people with

at least some college education. In 2005, the percentage of adults age 40 and over with diabetes

who received three recommended services was lower for people with less than a high school

education (31.5%) and high school graduates (39.9%) than for people with at least some college

(47.7%).

Management: Lower Extremity Amputations

Although diabetes is the leading cause of lower extremity amputations, amputations can be avoided

through proper care on the part of patients and providers. Hospital admissions for lower extremity

amputations for patients with diagnosed diabetes reflect poorly controlled diabetes. Better management

of diabetes would prevent the need for lower extremity amputations.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

50

Chapter 2 Diabetes
Figure 2.9. Hospital admissions for lower extremity amputations per 1,000 population age 18 and

over with diabetes, by race, 2001-2003 and 2004-2006

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Hospital

Discharge Survey and National Health Interview Survey,

2001-2003 and 2004-2006.

Note: Data years were combined to create sufficient

sample sizes for this analysis.

◆ While the rate of hospitalizations for lower extremity amputations improved overall from 2001-2003

to 2004-2006, the gap between Blacks and Whites increased. The percentage of hospitalizations for

lower extremity amputations among diabetes patients remained higher for Blacks than Whites (5.7

admissions per 1,000 population with diagnosed diabetes compared with 2.5 admissions per 1,000

population with diagnosed diabetes; Figure 2.9).

◆ Women with diabetes were less likely than men with diabetes to be hospitalized for lower extremity

amputation (2.3 per 1,000 compared with 5.4 per 1,000; data not shown).

◆ The Healthy People 2010 target rate of 2.9 lower extremity amputations in adults with diagnosed

diabetes per 1,000 population has not been met by any group except Whites.

Management: Controlled Hemoglobin, Cholesterol, and Blood Pressure

People with diagnosed diabetes often have other cardiovascular risk factors, such as high blood pressure

and high cholesterol. The combination of these conditions with diabetes increases the likelihood of

complications from diabetes, such as heart disease and stroke. Therefore, in addition to controlling blood

sugar levels, diabetes management often includes treating high blood pressure and high cholesterol.

HbA1c testing determines the average blood sugar level over 2 to 3 months and provides information

about control of blood sugar levels. Checking blood pressure and cholesterol levels is also needed to

assess control of these risk factors.vi

viBlood 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 Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

51

Chapter 2

0

1

2

3

4

5

6

Rate per 1,000 population

White

Black

2001-2003 2004-2005

Total

Healthy People

2010 Target: 2.9

Diabetes
Figure 2.10. Adults age 40 and over with diagnosed diabetes with HbA1c (top left), total

cholesterol (top right), and blood pressure (bottom left) under control, by race/ethnicity and

income, 1988-1994, 1999-2002, and 2003-2006

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health and Nutrition

Examination Survey (NHANES), 1988-1994, 1999-2002, and

2003-2006.

Reference population: Civilian noninstitutionalized population

with diagnosed diabetes, age 40 and over.

Note: Whites and Blacks are non-Hispanic groups; “Mexican

American” is used in place of “Hispanic” because the NHANES

is designed to provide estimates for this group rather than all

Hispanics. Age adjusted to the 2000 U.S. standard population.

Data were insufficient for this analysis for Native Hawaiians and

Other Pacific Islanders and for American Indians and Alaska

Natives.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

52

Chapter 2

White

Percent

1988-1994

1999-2002

Black

Near Poor

Middle Income

Total

Poor

Mexican American

High Income

HbA1c <7%

0

20

40

60

80

100

2003-2006

White

Percent

1988-1994

Black

Near Poor

Middle Income

Total

Poor

Mexican American

High Income

Total Cholesterol <200 mg/dL

1999-2002

2003-2006

0

20

40

60

80

100

White

Percent

1988-1994

Black

Near Poor

Middle Income

Total

Poor

Mexican American

High Income

Blood Pressure <140/80 mm Hg

1999-2002

2003-2006

0

20

40

60

80

100

Diabetes
HbA1c under control

◆ From the 1988-1994 to 2003-2006 periods, the percentage of adults with diagnosed diabetes who

had their HbA1c under optimal control improved (Figure 2.10). However, in 2003-2006, only

54.6% of adults with diagnosed diabetes had their HbA1c under optimal control.

◆ The gap between Blacks and Whites increased. In 2003-2006, the rate was significantly lower for

Blacks than Whites (43.0% compared with 60.5%).

◆ The gap between Mexican Americans and Whites increased. In 2003-2006, the rate was

significantly lower for Mexican Americans than Whites (37.6% compared with 60.5%).

◆ In 2003-2006, there were no statistically significant differences among income groups.

Total cholesterol under control

◆ From the 1988-1994 to 2003-2006 periods, the percentage of adults with diagnosed diabetes who

had their total cholesterol under control increased significantly. However, in 2003-2006, only 54.9%

of adults with diagnosed diabetes had their total cholesterol under control.

◆ In 2006, there were no statistically significant differences across racial groups and income groups.

Blood pressure under control

◆ From the 1988-1994 to 2003-2006 periods, the percentage of adults with diagnosed diabetes who

had their blood pressure under control did not change. In 2003-2006, only 58.5% of adults with

diagnosed diabetes had their blood pressure under control.

◆ The gap between Blacks and Whites decreased. In 2003-2006, there was no significant difference

between Blacks, Mexican Americans, and Whites for this measure.

◆ The gap between poor people and high-income people remained the same. In 2003-2006, the rate

was significantly lower for poor than for high-income people (59.8% compared with 63.3%).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

53

Chapter 2 Diabetes
End Stage Renal Disease (ESRD)

Total ESRD deaths (2005)..................................................................................................................85,79020

Total cases (2005)..............................................................................................................................485,01221

New cases (2005) ..............................................................................................................................106,91221

Total Medicare program expenditure for ESRD (2005)..........................................................$19.3 billion21

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

Management: Patients With 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.

Figure 2.11. Adult hemodialysis patients with adequate dialysis (urea reduction ratio 65% or

greater), by race (left) and ethnicity (right), 2001-2006

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, End Stage Renal Disease (ESRD) Clinical Performance Measures Project, 2001-

2006.

Reference population: ESRD hemodialysis patients age 18 and over.

Note: Data were not available for Native Hawaiians and Other Pacific Islanders, and in 2006 for people of multiple race.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

54

Chapter 2

75

80

85

90

95

100 White

Black

2001

2003

Percent

2002

Asian

AI/AN >1 Race

0

Z

2004

2005

2006

75

80

85

90

95

100

2001

2002

Percent

Non-Hispanic White

Hispanic

2003

Z

0

2004

2005

2006

End Stage Renal Disease (ESRD)
◆ From 2001 to 2006, the gap decreased between Blacks and Whites in hemodialysis patients with

adequate dialysis. However, in 2006 Blacks were less likely than Whites to have adequate dialysis

(85% compared with 88%; Figure 2.11).

◆ From 2001 to 2006, the gap between Asians and Whites remained the same. In 2006, the percentage

with adequate dialysis continued to be higher for Asians than for Whites (94% compared with 88%).

◆ The percentage with adequate dialysis improved for Hispanics (from 87% to 90%) and for nonHispanic Whites (from 85% to 87%).

◆ In 2006, women were more likely than men to have adequate dialysis (92% compared with 83%;

data not shown).

Management: Registration for Transplantation

Kidney transplantation often allows people with ESRD to continue a lifestyle similar to what they had

before their kidney failure.21 It is important that persons with ESRD be registered on the waiting list for

kidney transplantation to increase the likelihood of transplantation. However, the number of people on

the waiting list greatly exceeds the number who receive transplants. Thus, being on the waiting list does

not ensure a transplant.22 In 2006, 70,778 patients were on the Organ Procurement and Transplantation

Network (OPTN) deceased donor kidney transplant waiting list in the United States. Only 10,212

deceased donor kidney transplants were performed.20

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

55

Chapter 2 End Stage Renal Disease (ESRD)
Figure 2.12. Dialysis patients under age 70 who were registered on a waiting list for

transplantation, by race (left) and ethnicity (right), 1998-2004

Key: AI/AN = American Indian or Alaska Native.

Source: U.S. Renal Data System, 1998-2004.

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

Note: Data were not available for Native Hawaiians and Other Pacific Islanders.

◆ From 1998 to 2004, the gap between Blacks and Whites in the percentage of dialysis patients

registered for transplantation remained the same. In 2004, Blacks were still less likely to be

registered for transplantation than Whites (11.8% compared with 16.8%; Figure 2.12).

◆ The gap between AI/ANs and Whites decreased. However, in 2004, AI/ANs were still less likely to

be registered for transplantation than Whites (10.6% compared with 16.8%).

◆ The gap between Asians and Whites registered for transplantation increased. In 2004, this

percentage was higher for Asians than for Whites (30.0% compared with 16.8%).

◆ The gap between Hispanics and non-Hispanic Whites decreased. However, in 2004, this percentage

was still lower for Hispanics than for non-Hispanic Whites (13.9% compared with 17.6%).

◆ From 1998 to 2004, only Asians achieved the Healthy People 2010 target of 30%.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

56

Chapter 2

0

10

20

30

40

50

60

70 White Black

2000

2001

Percent

2002

Asian AI/AN

1998

1999

2003

2004

Healthy People

2010 Target: 25%

0

10

20

30

40

50

60

70

2000

2001

Percent

1998

1999

2002

2003

Healthy People

2010 Target: 25%

2004

Hispanic

Non-Hispanic White

End Stage Renal Disease (ESRD)
Heart Disease

Number of deaths (2005)....................................................................................................................652,0914

Cause of death rank (2005).........................................................................................................................1st4

Number of cases of coronary heart disease (2005)...................................................................16.0 million23

Number of cases of heart failure (2005)......................................................................................5.3 million23

Number of cases of high blood pressure (2005) .......................................................................73.0 million23

Number of heart attacks (2005) ...................................................................................................8.1 million24

Number of new cases of congestive heart failure (2005)................................................................366,81523

Total cost of cardiovascular disease (2008 est.).......................................................................$448.5 billion6

Total cost of congestive heart failure (2008 est.) .....................................................................$34.8 billion23

Direct medical costs of cardiovascular disease (2008 est.) .....................................................$296.4 billion6

Cost-effectiveness of hypertension screening.........................................................$14,000-$35,000/QALY7

Cost-effectiveness of aspirin chemoprophylaxis.....................................................................cost savings7,vii

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

Prevention: Counseling Obese Adults About Overweight

As in the 2005 report, measures related to overweight and obesity are presented in the NHDR. In this

section, measures for counseling obese adults about overweight and exercise are presented. In Chapter 4,

Priority Populations, a measure for counseling children about overweight is presented in the section on

children.

More than 34% of adults age 20 and over in the United States are obese (defined as having a body mass

index of 30 or higher),25,viii putting them at increased risk for many chronic, often deadly, conditions,

such as hypertension, cancer, diabetes, and coronary heart disease.26 Reducing obesity is a major

objective in preventing heart disease and stroke.27 Although physician guidelines recommend that health

care providers screen all adult patients for obesity,28 obesity remains underdiagnosed in U.S. adults.29

The health care system has a central role to play in helping people become aware of the risks of obesity

when they are overweight and suggesting strategies for reducing these risks.

viiUnlike other interventions that often involve greater costs for health benefits, this intervention actually results in net

cost savings to society.

viiiObesity is defined as having a body mass index (BMI) of 30 or higher. It is noteworthy that BMI incorporates both

a person’s weight and height in determining if he or she is overweight or obese.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

57

Chapter 2 Heart Disease
Figure 2.13. Adults with obesity age 20 and over who were told by a doctor they were

overweight, by race/ethnicity, income, and education, 1999-2002 and 2003-2006

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health and

Nutrition Examination Survey (NHANES), 1999-2002 and

2003-2006.

Reference population: Civilian noninstitutionalized

population age 20 and over.

Note: Obesity is defined as a body mass index of 30 or

higher. “Mexican American” is used in place of

“Hispanic” because the NHANES is designed to provide

estimates for this group rather than all Hispanics.

Education groups are for adults age 25 and over only.

Rates other than the total are age adjusted to the 2000

standard population. Data were not available for Asians,

Native Hawaiians and Other Pacific Islanders, and

American Indians and Alaska Natives.

◆ There were no statistically significant changes from 1999-2002 to 2003-2006 in the percentage of

obese adults told that they were overweight.

◆ During this period, trends were different for men and women. The percentage of obese women who

were told they were overweight increased (from 63.1% to 69.8%; data not shown), while the

percentage decreased for men (from 71.9% to 59.6%; data not shown).

◆ The percentage of obese adults told that they were overweight was significantly lower for Blacks

(60.5%) and Mexican Americans (57.1%) compared with Whites (66.4%); for poor (61.5%), nearpoor (62.5%), and middle-income (62.4%) people compared with high-income people (70.6%); and

for adults with less than a high school education (59.2%) and high school graduates (64.2%)

compared with adults with any college education (70.3%) (Figure 2.13).

Prevention: Counseling Obese Adults About Exercise

Exercise counseling within the clinical setting is an important component of effective weight loss

interventions.28 Regular exercise aids in weight loss and blood pressure control efforts, reducing the risk

of heart disease, stroke, diabetes, and other diseases.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

58

Chapter 2

White

Percent

Mexican American

Poor

Near Poor

Middle Income

High Income

Total

<High School

High School Grad

At Least Some College

Black

50

55

60

65

70

75 1999-2002

2003-2006

0

Z

Heart Disease
Figure 2.14. Adults with obesity who ever received advice from a health provider to exercise

more, by race (top left), ethnicity (top right), income (bottom left), and education (bottom right),

2002-2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Obesity is defined as a body mass index of 30 or higher. Data were insufficient for this analysis for Asians, Native Hawaiians

and Other Pacific Islanders, and American Indians and Alaska Natives.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

59

Chapter 2

0

20

40

60

80

100

2002

Percent

2003

White

Black

20042005

0

20

40

60

80

100

Percent

Non-Hispanic White

Hispanic

2002

2003

2004

2005

0

20

40

60

80

100

2004

Percent

2002

2003

Poor

Near Poor

Middle Income

High Income

2005

0

20

40

60

80

100

2004

Percent

2002

<High School

High School Grad

At Least

Some College

2003

2005

Heart Disease
◆ From 2002 to 2005, there were no statistically significant changes in the percentage of obese adults

who were given advice about exercise (Figure 2.14).

◆ During the same period, there was no statistically significant gap between Blacks and Whites on this

measure.

◆ From 2002 to 2005, the gap between Hispanics and non-Hispanic Whites increased. In 2005, this

percentage was significantly lower for Hispanics than for non-Hispanic Whites (44.1% compared

with 61.9%).

◆ The gap between poor people and high-income people remained the same. In 2005, this percentage

was significantly lower for poor people compared with high-income people (49.5% compared with

64.2%).

◆ The gap between people with less than a high school education and people with at least some

college education remained the same. In 2005, the percentage of obese adults who were given

advice about exercise was significantly lower for people with less than a high school education than

for people with at least some college education (50.5% compared with 63.2%).

Each year, multivariate analyses are conducted in support of the NHDR to identify the independent

effects of race, ethnicity, and SES on quality of health care. Past reports have listed some of these

findings. This year, the NHDR presents the results of a multivariate model for one measure: obese adults

who were given advice about exercise. Adjusted odds ratios are shown to quantify the relative magnitude

of disparities after controlling for a number of confounding factors.

To identify the independent effects of socioeconomic factors on obese (BMI of 30 or higher) adults ages

18-64 given advice by a doctor or health professional about exercise, logistic regressions were run using

pooled 2002-2005 MEPS data. The predictive variables included race, ethnicity, income, education, age,

gender, insurance, and residence location. White, non-Hispanic White, high income, some college,

private insurance, ages 45-64, male, and metropolitan were used as reference groups (odds ratio = 1).

The odds ratios estimate the ratios of probability of received advice by each covariate group over the

reference group and are reported in Figure 2.15. A lower odds ratio indicates that the group is less likely

to receive advice.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

60

Chapter 2 Heart Disease

Heart disease is the leading cause

of death in the United States for

both men and women.
Figure 2.15. Adults with obesity who ever received advice from a health provider to exercise

more: Adjusted odds ratios, 2002-2005

Key: = reference group.

Source: Agency for Healthcare

Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Obese civilian

noninstitutionalized population ages

18-64.

Note: Obesity is defined as a body

mass index of 30 or higher. Adjusted

odds ratios are calculated from logistic

regression models controlling for race,

ethnicity, income, education, age,

gender, insurance, and residence

location. White, non-Hispanic White,

male, high income, some college,

metropolitan, and private insurance are

reference groups with odds ratio = 1;

odds ratios <1 indicate that a group is

less likely to receive a service than the

reference group. For example,

compared with obese adults with

private insurance, obese adults with no

insurance had 0.6 times the odds of

receiving advice about exercise after

controlling for other factors. Data were

insufficient for this analysis for Asians,

Native Hawaiians and Other Pacific

Islanders, and American Indians and

Alaska Natives.

◆ In multivariate models controlling for race, ethnicity, income, education, insurance, age, gender, and

residence location, obese Hispanics had 0.7 times the odds of receiving advice about exercise

compared with non-Hispanic Whites (Figure 2.15).

◆ In this multivariate model, poor individuals had 0.8 times the odds compared with high-income

individuals. Individuals with less than a high school education had 0.8 times the odds compared

with individuals with some college education.

◆ Obese individuals with no health insurance had 0.6 times the odds compared with individuals with

private insurance to receive advice about exercise.

◆ In this multivariate model, obese individuals within nonmetropolitan areas had 0.8 times the odds of

being given advice about exercise compared with individuals within metropolitan areas.

◆ In this multivariate model, obese females had 1.5 times the odds of being given advice about

exercise compared with obese males.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

61

Chapter 2

Non-Hispanic White

Odds ratio

Non-Hispanic White

Non-Hispanic Black

Hispanic

Poor

Near Poor

Middle Income

High Income

<High School

High School Grad

Some College

Private Insurance

No lnsurance

Nonmetropolitan

Metropolitan

0.0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Male

Female

Heart Disease
Treatment: Receipt of Recommended Hospital Care for Heart Failure

Recommended hospital care for heart failure includes evaluation of the left ventricular ejection fraction

and receipt of an angiotensin-converting enzyme (ACE) inhibitor for left ventricular systolic dysfunction.

In 2005, the ACE inhibitor measure was modified to include receipt of angiotensin receptor blockers

(ARBs) as an alternative to ACE inhibitors.

Figure 2.16. Composite measure: Hospital patients with heart failure who received

recommended hospital care, Medicare only by race/ethnicity, 2002-2004 (left) and All payer,

2005-2006 (right)

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Medicare Quality Improvement Organization Program, 2002-2006.

Denominator: Patients hospitalized for heart failure, all ages.

Note: Whites, Blacks, AI/ANs, and Asians are non-Hispanic groups. Composite incorporates the following measures: (1) receipt of

evaluation of left ventricular ejection fraction and (2) receipt of ACE inhibitor for left ventricular systolic dysfunction. Composite is

calculated by averaging the percentage of the population that received each of the two incorporated components of care. For further

details on composite measures, go to Chapter 1, Introduction and Methods. Data for 2002-2004 and 2005-2006 differ due to

modification of the ACE inhibitor measure in 2005 to include receipt of ARBs as an acceptable alternative to ACE inhibitors and the

data collection method change made in 2005 from the abstraction of randomly selected medical records for Medicare beneficiaries to

the receipt of hospital self-reported data for all payer types. Data were not available for Native Hawaiians and Other Pacific Islanders.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

62

Chapter 2

50

60

70

80

90

100

White

Black

2003

2004

Percent

2002

Asian

Total AI/AN

Hispanic

0

Z

50

60

70

80

90

100

White

Black

Percent

Asian

Total AI/AN

Hispanic

0

Z

2005

2006

Heart Disease
◆ In 2006, the percentage of patients with heart failure who received recommended hospital care was

higher for Blacks than for Whites (91.4% compared with 90.0%; Figure 2.16).

◆ In 2006, the percentage of patients with heart failure who received recommended hospital care was

lower for AI/ANs than Whites (86.3% compared with 90.0%).

◆ From 2002 to 2004, the overall percentage of Medicare patients with heart failure who received

recommended hospital care improved from 73.4% to 77.7% (Figure 2.16; 2005-2006 data not

comparable to this time period).

◆ During the same period, this percentage was significantly lower for Hispanics compared with

Whites. In 2004, the percentage was also significantly lower for AI/ANs compared with Whites

(72.3% compared with 77.9%).

◆ From 2002 to 2004, the percentage of Medicare patients with heart failure who received

recommended hospital care improved significantly for the total population and for Whites, Blacks,

and Hispanics.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

63

Chapter 2 Heart Disease
HIV and AIDS

Number of people in the United States living with HIV (2006) . . . . . . . . . . . . . . . . . . . . . . . . . . 226,47730

Number of people in the United States living with AIDS (2006) . . . . . . . . . . . . . . . . . . . . . . . . . 436,69330

Number of deaths among people with AIDS (2006) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,62730

Number of new HIV cases (2006). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56,30031

Number of new AIDS cases (2006). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37,85232

Federal spending on domestic HIV/AIDS care, cash and housing assistance,

and prevention and research (fiscal year 2008 est.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $18.2 billion32

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

Changes in HIV infection rates reflect changes in behavior by at-risk individuals that may only partly be

influenced by the health care system. However, individual and community programs have shown

progress in influencing behavior change. Changes in the incidence of new AIDS cases are affected by

changes in HIV infection rates and by the availability of appropriate treatments for HIV-infected

individuals. Improved treatments that extend life for those with the disease are reflected in the fact that

the number of deaths due to AIDS fell from about 18,000 to 14,600 between 2002 and 2006, after

showing no change for the previous 3 years.33

The impact of human immunodeficiency virus (HIV) infection and its late-stage manifestation, acquired

immune deficiency syndrome (AIDS), is disproportionately higher for racial and ethnic minorities and

persons of lower socioeconomic position. While access to care has improved, research shows that Blacks,

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

to have optimal patterns of care.34

According to the Centers for Disease Control and Prevention, HIV and AIDS disproportionately affect

African Americans in the United States. The spread of HIV is related to factors faced by many African

Americans, including poverty, high-risk behaviors related to sexually transmitted diseases, and stigma

(negative attitudes, beliefs, and actions directed at people living with HIV/AIDS or directed at people

who do things that might put them at risk for HIV).35

The HIV/AIDS epidemic is also a serious threat to the Hispanic/Latino community. According to current

surveillance data, 39% of Latinos who are newly diagnosed with HIV infection progress to an AIDS

diagnosis within 1 year.35 In addition to being a population seriously affected by HIV, Hispanics/Latinos

continue to face challenges in accessing health care, prevention services, and HIV treatment. In 2005,

HIV/AIDS was the fourth leading cause of death among Hispanic/Latino men and women ages 35-44.36

While having Medicaid insurance and a usual source of care decreased the likelihood of delaying care for

HIV, research shows that delay in care is still greater for Latinos and African Americans.37

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

64

Chapter 2 HIV and AIDS
Although the number of cases of HIV and AIDS from 2001 through 2005 decreased (by 1% for men and

19% for women),38 HIV and AIDS are having an increasing impact on women of color, particularly on

African-American women (68.7% of estimated AIDS cases among adult women were Black).39 Women

with HIV and AIDS face particular challenges to accessing care. Women are often the primary caregivers

in their families, thus making their own health a lesser priority. Risk behaviors such as drug use and sex

trading also put HIV-infected women at higher risk for depression, violence, family problems, and

inadequate social support.40

Management: New AIDS Cases

Currently, comprehensive data on HIV infection rates across the Nation are lacking; however, early and

appropriate treatment of HIV disease can delay progression to AIDS. Improved management of chronic

HIV disease has likely contributed to declines in new AIDS cases. For example, as the use of highly

active antiretroviral therapy (HAART) to treat HIV infection became widespread in the mid-1990s, rates

of new AIDS cases declined.41,42

Figure 2.17. New AIDS cases per 100,000 population age 13 and over, by race/ethnicity, 1998-2006

Key: AI/AN = American Indian or Alaska Native;

API = Asian or Pacific Islander.

Source: Centers for Disease Control and

Prevention, National Center for HIV, STD, and TB

Prevention, HIV/AIDS Surveillance System, 1998-

2006.

Reference population: U.S. population age 13

and over.

Note: The source categorizes race/ethnicity as a

single item. White = non-Hispanic White; Black =

non-Hispanic Black. Data are based on hospital

self-reports.

◆ In 2006, the overall rate of new AIDS cases decreased to about 15 cases per 100,000 population

(Figure 2.17).

◆ From 1998 to 2006, the rate of new AIDS cases decreased for Blacks (from 80.7 to 60.3 per

100,000), Hispanics (from 31.3 to 20.8 per 100,000), and Whites (from 8.2 to 6.4 per 100,000).

◆ During this period, the gap between Blacks and Whites decreased. However, in 2006, the rate of

new AIDS cases was still almost 10 times higher (60.3 per 100,000 compared with 6.4 per 100,000)

for Blacks than for Whites.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

65

Chapter 2

0

20

40

60

80

100

White

Black

2001

2003

Number of cases per 100,000 population

2002

API

Total AI/AN

Hispanic

1998

1999

2000

2004

2005

2006

Healthy People

2010 Target: 1.0

HIV and AIDS
◆ From 1998 to 2006, the gap between Hispanics and non-Hispanic Whites decreased. However, in

2006, the rate of new AIDS cases was still more than three times higher for Hispanics than for

Whites (20.8 per 100,000 compared with 6.4 per 100,000).

◆ In 2006, the rate of new AIDS cases was almost three times higher for men compared with women

(22.4 per 100,000 compared with 7.8 per 100,000; data not shown)

◆ No group has reached the Healthy People 2010 target of 1.0 new AIDS case per 100,000 population.

Management: PCP and MAC Prophylaxis

Management of chronic HIV disease includes outpatient and inpatient services. Because national data on

HIV care are not routinely collected,ix HIV measures tracked in the NHDR come from the HIV Research

Network. This network consists of 18 medical practices across the United States that treat large numbers

of HIV patients.

Without adequate treatment, as HIV disease progresses, CD4 cell counts fall and patients become

increasingly susceptible to opportunistic infections. When CD4 cell counts fall below 200, medicine to

prevent development of Pneumocystis pneumonia (PCP) is routinely recommended; when CD4 cell

counts fall below 50, medicine to prevent development of disseminated Mycobacterium avium complex

(MAC) infection is routinely recommended.43

Figure 2.18. Adult patients with HIV and CD4 count <200 who received PCP prophylaxis in the

calendar year, by race/ethnicity, 2003-2005

Source: Agency for Healthcare Research and Quality, Center for

Delivery, Organization, and Markets, HIV Research Network,

2003-2005.

Reference population: HIV patients age 18 and over receiving

care from HIV Research Network providers.

Note: Whites and Blacks are non-Hispanic populations. Data

were not available for Asians, Native Hawaiians and Other Pacific

Islanders, and American Indians and Alaska Natives.

ixAlthough program data are collected from all Ryan White CARE Act HIV/AIDS Program grantees, the aggregate

nature of the data makes it difficult to assess the quality of care provided by the Ryan White HIV/AIDS Program.

National Quality Report, 2000

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66

Chapter 2

50

60

70

80

90

100 Total Black

2003

Percent

2004

2005

Hispanic

0

Z

White

HIV and AIDS
◆ From 2003 to 2005, the overall percentage of HIV patients with CD4 cell count <200 who received

PCP prophylaxis increased. The percentage was not significantly different for any racial or ethnic

group compared with Whites (Figure 2.18).

◆ During this period, the gap between men and women increased for HIV patients with CD4 cell count

<200 who received PCP prophylaxis. In 2005, women were less likely than men to receive PCP

prophylaxis treatment (86.5% compared with 91.9%; data not shown).

Figure 2.19. Adult patients with HIV and CD4 count <50 who received MAC prophylaxis in the

past year, by race/ethnicity, 2003-2005

Source: Agency for Healthcare Research and Quality, Center for

Delivery, Organization, and Markets, HIV Research Network,

2003-2005.

Reference population: HIV patients age 18 and over receiving

care from HIV Research Network providers.

Note: Whites and Blacks are non-Hispanic populations. Data

were not available for Asians, Native Hawaiians and Other Pacific

Islanders, and American Indians and Alaska Natives.

◆ From 2003 to 2005, the overall percentage of HIV patients with CD4 cell count <50 who received

MAC prophylaxis remained the same.

◆ During this period, the gap between Hispanics and non-Hispanic Whites remained the same. In

2005, the percentage of HIV patients with CD4 cell count <50 who received MAC prophylaxis was

higher for Hispanics than for Whites (90.4% compared with 83.4%; Figure 2.19).

◆ From 2003 to 2005, the gap between men and women in the percentage of HIV patients with CD4

cell count <50 who received MAC prophylaxis remained the same. However, in 2005, women were

still less likely than men to receive MAC prophylaxis treatment (85.3% compared with 87.7%; data

not shown).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

67

Chapter 2

50

60

70

80

90

100

2003

Percent

2004

2005

0

Z

Total Black

White Hispanic

HIV and AIDS
Mental Health and Substance Abuse

Highest cause of death rank-suicide (2005).............................................................................................11th4

Adults age 18 and over with any mental disorder or substance disorder

in past year (2001-2003)....................................................................................................................32.4%44,x

Alcohol-related motor vehicle deaths (2006) .....................................................................................17,60245

People age 12 and over with alcohol and/or illicit drug dependence or

abuse (2006)....................................................................................................................22.6 million (9.2%)46

Adults age 18 and over with serious psychological distress (2006).........................................24.9 million46

Youths ages 12-17 with a major depressive episode during the past year (2006).........2.0 million (7.9%)46

Adults age 18 and over with a major depressive episode during the

past year (2006) .............................................................................................................15.8 million (7.2%)46

Adults with history of major depressive disorder (2006)...........................................30.4 million (13.9%)46

Total medical expenditures for substance abuse and mental

disorders (2003 est.)....................................................................................................................$121 billion47

Cost-effectiveness of problem drinking screening and brief counseling.............$ 14,000-$ 35,000/QALY7

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

In 2004, almost one-fourth of all stays in U.S. community hospitals for patients age 18 and over—7.6

million of nearly 32 million stays—involved mental disorders such as depression, bipolar disorder,

schizophrenia, and substance use-related disorders.48 In a cross-national survey of adults in 14 countries

(8 developed, 6 less developed) conducted from 2001 to 2003, the United States had the highest rate of

any mental disorders, including substance abuse.49,x The 12-month prevalence of anxiety disorders in the

United States in 2001-2003 was 19.1%; mood disorders, 9.7%; impulse control disorder, 10.5%; and any

substance disorder (including drug abuse, alcohol abuse, and nicotine dependencexi), 13.4%.

Socioeconomic factors and cultural factors can affect mental health. For example, poverty is both a risk

factor for poor mental health and can be a consequence of poor mental health. Low-income individuals

may be more likely to receive needed substance abuse treatment due to linkages in service delivery

between substance abuse and public assistance services in many States.

xTo some extent, this finding may be attributable to cross-national differences in how people respond to the mental

health assessment tool used.

xiNicotine dependence is a physical addiction to nicotine when delivered by various tobacco products.

National Quality Report, 2000

Staying Healthy Quality of Health Care

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68

Chapter 2 Mental Health and Substance Abuse
Culturally and linguistically appropriate services can decrease the prevalence, incidence, severity, and

duration of certain mental disorders. However, many factors adversely affect the mental health of racial

and ethnic groups and present significant barriers to treatment. These include cost of care, social stigma,

fragmented organization of services, discrimination,xii racism, and mistrust. One way to help meet the

needs of racial and ethnic populations is to engage representatives from the community being served in

the design, planning, and implementation of services. Providing services to meet the cultural and

linguistic needs of more diverse populations may demand more of an initial investment than continuing

services as usual. To date, there are no cost-effectiveness studies that provide information on the benefits

of providing or failing to provide culturally and linguistically appropriate services.50

In rural and remote areas, many people with mental illnesses have inadequate access to care, limited

availability of skilled care providers, lower family incomes, and greater societal stigma for seeking mental

health treatment than their urban counterparts. In addition, rural Americans are less likely to have private

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 dearth of culturally and linguistically competent providers.

Finally, of the 1,669 federally designated mental health professional shortage areas, more than 85% are

rural areas.51

Treatment: Receipt of Needed Treatment for Illicit Drug Use

Illicit drugxiii use is a medical problem that can have a direct toxic effect on a number of bodily organs, as

well as exacerbate numerous health and mental health conditions. Treatment for illicit drug use at a

specialty facility is an effective way to reduce the chances of future illicit drug use.

xiiThe Office for Civil Rights (OCR) (http://www.hhs.gov/ocr/) is the sole 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.

xiiiIllicit drugs included in this measure are marijuana/hashish, cocaine (including crack), inhalants, hallucinogens,

heroin, and prescription-type psychotherapeutic drugs (nonmedical use).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

69

Chapter 2 Mental Health and Substance Abuse
Figure 2.20. People age 12 and over who needed treatment for illicit drug use and who received

such treatment at a specialty facility in the last 12 months, by race (top left), ethnicity (top right),

income (bottom left), and education (bottom right), 2003-2006

Key: AI/AN = American Indian or Alaska Native.

Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2006.

Reference population: U.S. population age 12 and over who needed treatment for illicit drug use in the past year.

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Chapter 2

0

5

10

15

20

25

30

2005

Percent

2003

White

Black

2004

Total

AI/AN

2006

Healthy People 2010

Target: 24%

0

5

10

15

20

25

30

Percent

Non-Hispanic White

Hispanic

2003

2004

2005

2006

Healthy People 2010

Target: 24%

0

5

10

15

20

25

30

35

2004

Percent

2003

2005

Poor

Near Poor

Middle Income

High Income

2006

Healthy People 2010

Target: 24%

0

5

10

15

20

25

30

35

2004

Percent

2005

<High School

High School Grad

Some College

2003

2006

Healthy People 2010

Target: 24%

Mental Health and Substance Abuse
Note: Estimates by education were available only for persons age 18 and over. “Received illicit drug treatment at a specialty facility”

refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental health center to reduce or

stop the nonmedical use of prescription-type psychotherapeutic drugs or for medical problems associated with drug use.

Respondents were classified as needing treatment for an illicit drug problem if they met at least one of these three criteria during the

past year: (1) dependent on any illicit drug; (2) abuse of any illicit drug; or (3) received treatment for an illicit drug problem at a

specialty facility (drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers).

Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and Alaska

Natives.

◆ From 2003 to 2006, the gap between Blacks and Whites decreased. In 2006, the disparity was

eliminated between these groups in the percentage of people age 12 and over who needed treatment

for illicit drug use and received it at a specialty facility in the past year (Figure 2.20); there was no

statistically significant difference.

◆ From 2003 to 2006, the gap between Hispanics and non-Hispanic Whites decreased. In 2006, the

disparity between these groups in those who needed and received treatment for illicit drug use was

eliminated; there was no statistically significant difference.

◆ From 2003 to 2006, the gap between poor and high-income people remained the same. In 2006, a

higher percentage of poor people needed and received treatment for illicit drug use than high-income

people (30.8% compared with 16.5%).

◆ From 2003 to 2006, the gap between people with less than a high school education and people with

some college education decreased. In 2006, people with less than a high school education who

needed treatment were significantly more likely to receive treatment for illicit drug use than people

with some college education (31.7% compared with 15.9%).

◆ In 2006, Blacks, Hispanics, poor people, and people with less than a high school education achieved

the Healthy People 2010 target of 24% of people age 12 and over who needed treatment for illicit

drug use actually receiving such treatment.

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Quality of Health Care Staying Healthy

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71

Chapter 2 Mental Health and Substance Abuse

Nearly 30% of adults with mood,

anxiety, or impulse control disorders

received minimally adequate

treatment.
Treatment: Receipt of Treatment for Depression

Treatment for depression is an effective way to reduce the chances of future major depressive episodes.

However, many people face significant barriers to treatment for depression, such as cost of care, societal

stigma, and fragmented organization of services.50

Figure 2.21. Adults with a major depressive episode in the last 12 months who received

treatment for depression in the last 12 months, by race, ethnicity, income, and education, 2006

Source: Substance Abuse and Mental Health

Services Administration, National Survey on Drug

Use and Health, 2006.

Reference population: U.S. population age 18 and

over who had a major depressive episode in the

past year.

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 for depression described in the 4th

edition of the Diagnostic and Statistical Manual of

Mental Disorders (DSM-IV). 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. Data were insufficient for this analysis

for Asians, Native Hawaiians and Other Pacific

Islanders, and American Indians and Alaska Natives.

◆ The percentage of adults with a major depressive episode in the last 12 months who received any

treatment for depression in the last 12 months was significantly lower for Blacks than for Whites

(58.9% compared with 71.1%) and lower for Hispanics than for non-Hispanic Whites (51.8%

compared with 73.3%; Figure 2.21).

◆ There were no statistically significant differences by income level or education level for this

measure.

Treatment: Receipt of Minimally Adequate Treatment for Mental

Disorders

Receipt of any treatment for a major depressive episode is a relatively low standard against which to

assess quality of mental health care. The Collaborative Psychiatric Epidemiology Surveys (CPES) allow

more detailed examination of mental health care. The CPES join together three nationally representative

surveys, the National Comorbidity Survey Replication (NCS-R), the National Survey of American Life

National Quality Report, 2000

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72

Chapter 2

White

Percent

Black

Poor

Non-Hispanic White

Total

<High School

High School Grad

At Least Some College

0

10

20

30

40

50

60

70

80

90

100

Low Income

Middle Income

High Income

Hispanic

Mental Health and Substance Abuse
(NSAL), and the National Latino and Asian American Study (NLAAS). Together, these surveys provide

national estimates of mental disorders and mental health care for majority and minority populations in the

United States in much greater detail than other data sources.

To better assess quality of mental health care, a higher standard of care, minimally adequate treatment,

has been specified using the CPES. This measure defines minimally adequate treatment as

pharmacotherapy, including at least 60 days of an appropriate medication and 4 visits to a physician; or

psychotherapy, including at least 8 visits to a health care or human services professional lasting an

average of 30 minutes or more.52

Figure 2.22. Adults with a mood, anxiety, or impulse control disorder in the last 12 months who

received minimally adequate treatment, by race/ethnicity, income, and education, 2001-2003

Source: National Institute of Mental Health,

Collaborative Psychiatric Epidemiology Surveys,

2001-2003.

Reference population: U.S. population age 18 and

over who had a mood, anxiety, or impulse control

disorder in the past year.

Note: White and Black are non-Hispanic groups.

Data for Asians and Pacific Islanders and American

Indians and Alaska Natives were not statistically

reliable for this analysis. The Composite

International Diagnostic Interview (CIDI) was used to

make psychiatric diagnoses consistent with the 4th

edition of the Diagnostic and Statistical Manual of

Mental Disorders (DSM-IV). “Minimally adequate

treatment” is defined as at least 60 days of an

appropriate medication and 4 visits to a physician

OR at least 8 visits to a health care or human

services professional lasting an average of 30

minutes or more in the past year.

◆ Nearly 30% of adults with mood, anxiety, or impulse control disorders received minimally adequate

treatment (Figure 2.22).

◆ The percentage of adults who received minimally adequate treatment was lower among Blacks and

Hispanics compared with Whites, with Hispanics having the lowest percentage of all groups.

◆ The percentage of adults who received minimally adequate treatment was also lower among

individuals with less than a high school education and high school graduates compared with those

with some college education.

◆ There were no statistically significant differences by household income for this measure.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

73

Chapter 2

White

Percent

Total

Black

Poor

<High School

High School Grad

Some College

0

5

10

15

20

25

30

35

Low Income

Middle Income

High Income

Hispanic

Mental Health and Substance Abuse
Respiratory Diseases

Number of deaths due to lung diseases (2004).................................................................................226,37953

Number of deaths, influenza and pneumonia combined (2005)..........................................................63,0014

Cause of death rank, influenza and pneumonia combined (2005) ............................................................8th4

People age 18 and over with current asthma (2006).....................................................................16 million54

People under age 18 with an asthma attack in past 12 months (2004).......................................5.9 million55

Annual number of cases of the common cold (est.) ......................................................................>1 billion56

Number of discharges attributable to pneumonia (2003 est.)......................................................1.4 million57

Total cost of lung diseases (2007 est.) ......................................................................................$153.6 billion6

Direct medical costs of lung diseases (2007 est.).......................................................................$94.8 billion6

Total approximate cost of upper respiratory infections (annual).................................................$40 billion58

Total cost of asthma (2007)........................................................................................................$19.7 billion53

Direct medical costs of asthma (2007) ......................................................................................$14.7 billion53

Cost-effectiveness of influenza immunization..................................................................$0-$14,000/QALY7

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data

sources.

Prevention: Pneumococcal Vaccination

Vaccination is an effective strategy for reducing illness, death, and disparities associated with

pneumococcal disease and influenza.59,60

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

74

Chapter 2 Respiratory Diseases
Figure 2.23. Adults age 65 and over who ever received pneumococcal vaccination, by race (top

left), ethnicity (top right), and income (bottom left), 1999-2006

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health Interview Survey,

1999-2006.

Reference population: Civilian noninstitutionalized population

age 65 and over.

Note: Data were insufficient for this analysis for Native Hawaiians

and Other Pacific Islanders and for American Indians and Alaska

Natives (see Chapter 4 for data for Native Hawaiians and Other

Pacific Islanders).

◆ From 1999 to 2006, the overall percentage of adults age 65 and over who had received

pneumococcal vaccination improved significantly, from 49.9% to 57.3% (data not shown).

Improvements were observed for Whites, Hispanics (Figure 2.23), and people with less than a high

school education (data not shown).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

75

Chapter 2

0

20

40

60

80

100 White Black

2000

2001

Percent

1999

2002

2003

Asian

2004

2005

2006

Healthy People

2010 Target: 90%

0

20

40

60

80

100

2000

2001

Percent

Non-Hispanic White Hispanic

1999

2002

2003

2004

2005

2006

Healthy People

2010 Target: 90%

0

20

40

60

80

100

2000

2001

Percent

1999

2002

2003

Poor

Near Poor

Middle Income

High Income

2004

2005

2006

Healthy People

2010 Target: 90%

Respiratory Diseases
◆ The gap between Blacks and Whites increased. In 2006, the percentage of adults age 65 and over

who ever had pneumococcal vaccination was significantly lower for Blacks than for Whites (36.8%

compared with 59.9%).

◆ From 1999 to 2006, the gap between Hispanics and non-Hispanic Whites decreased. However, in

2006, the percentage of Hispanic adults age 65 and over who ever had pneumococcal vaccination

was still about half that of non-Hispanic Whites (33.2% compared with 61.9%).

◆ The gap between poor and high-income people remained the same. In 2006, the percentage was

significantly lower for poor older adults than for high-income older adults (45.1% versus 60.9%).

◆ In 2006, as in 2005, no group achieved the Healthy People 2010 target of 90% of adults age 65 and

over having received pneumococcal vaccination.

Racial and ethnic minorities are disproportionately of lower SES. To distinguish the effects of race,

ethnicity, income, and education on pneumococcal vaccination, this measure is stratified by income and

education level.

Figure 2.24. Adults age 65 and over who ever received pneumococcal vaccination, by race (left)

and ethnicity (right), stratified by income, 2006

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 2006.

Reference population: Civilian noninstitutionalized population age 65 and over.

Note: Age adjusted to the 2000 U.S. standard population. Data were insufficient for this analysis for Asians, Native Hawaiians and

Other Pacific Islanders, American Indians and Alaska Natives, and high-income Hispanics.

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National Healthcare Disparities Report, 2008

76

Chapter 2

0

20

40

60

80

100

Percent

White

Black

Poor Near

Poor

Middle

Income

High

Income

0

20

40

60

80

100

Percent

Non-Hispanic White

Hispanic

Poor Near

Poor

Middle

Income

High

Income

Respiratory Diseases
Figure 2.25. Adults age 65 and over who ever received pneumococcal vaccination, by race (left)

and ethnicity (right), stratified by education, 2006

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 2006.

Reference population: Civilian noninstitutionalized population age 65 and over.

Note: Age adjusted to the 2000 U.S. standard population. Data were insufficient for this analysis for Asians, Native Hawaiians and

Other Pacific Islanders, and American Indians and Alaska Natives.

◆ With the exception of the poor group, Blacks at all income levels were less likely than Whites of the

same income level to ever have had a pneumococcal vaccination (Figure 2.24). High-income Blacks

were almost half as likely as Whites of the same income level to receive this preventive care.

◆ Hispanics at all income levels were less likely than non-Hispanic Whites of the same income level to

have ever had a pneumococcal vaccination. Poor Hispanics were less than half as likely as Whites

of the same income level to receive this preventive care.

◆ With the exception of Hispanic high school graduates, Blacks and Hispanics at all education levels

were less likely than Whites to have ever had a pneumococcal vaccination (Figure 2.25).

Treatment: Receipt of Recommended Care for Pneumonia

Older adults are at high risk for pneumonia. The highest rate of hospitalizations for pneumonia occurs in

the population 65 and over—220.4 per 10,000 population for this group in 2004, compared with 45.5 per

10,000 for the overall population.57 The Centers for Medicare & Medicaid Services tracks a set of

measures for quality of pneumonia care for hospitalized patients from the CMS Quality Improvement

Organization (QIO) program. This set of measures has been adopted by the Hospital Quality Alliance

(HQA).

National Quality Report, 2000

Quality of Health Care Staying Healthy

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77

Chapter 2

0

20

40

60

80

100

Percent

White

Black

<High

School

High

School Grad

At Least Some

College

0

20

40

60

80

100

Percent

Non-Hispanic White

Hispanic

High School

Grad

<High

School

At Least Some

College

Respiratory Diseases
Figure 2.26. Composite measure; Hospital patients with pneumonia who received recommended

hospital care, by race/ethnicity, Medicare only, 2002-2004 (left) and All payer, 2005-2006 (right)

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services, Quality Improvement Organization Program, 2002-2006.

Denominator: Patients with pneumonia who are hospitalized, all ages.

Note: Whites, Blacks, Asians, and AI/ANs are non-Hispanic groups. Composite includes the following five measures: (1) receipt of

antibiotics within 4 hours, (2) receipt of appropriate antibiotics, (3) receipt of blood culture before antibiotics, (4) receipt of influenza

screening (i.e., person is assessed as to whether he or she would be a good candidate for vaccination) or vaccination, and (5) receipt

of pneumococcal screening or vaccination. Composite is calculated by averaging the percentage of opportunities for care in which

the patient received all five incorporated components of care. For further details on composite measures, go to Chapter 1,

Introduction and Methods. The denominator used to calculate these measures was refined in 2005 to exclude patients with health

care-associated pneumonia. The percentage of Medicare beneficiaries with blood cultures within 24 hours of hospital arrival was

changed to include in the denominator only patients who were admitted to the intensive care unit within 24 hours of hospital arrival.

◆ In all 3 years, from 2002 to 2004, the percentage of patients with pneumonia who received

recommended hospital carexiv was significantly lower for Blacks and Hispanics compared with

Whites (Figure 2.26). In 2004, the percentage was also significantly lower for Asians compared

with Whites.

◆ In 2006, the percentage was lower for Blacks (76.9%), Asians (75.8%), and Hispanics (74.2%) than

for Whites (81.5%) (Figure 2.26).

◆ From 2002 to 2004 and from 2005 to 2006, the percentage of patients with pneumonia who received

recommended hospital care improved significantly for the total population and for all racial and

ethnic groups.

xiv“Recommended hospital care” is a composite of five separate measures (the note for Figure 2.25 lists these

measures). For further details on composite measures, go to Chapter 1, Introduction and Methods.

National Quality Report, 2000

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78

Chapter 2

White

Black

2003

2004

Percent

2002

Asian

Total AI/AN

Hispanic

0

Z

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

White

Black

2005

2006

Percent

Asian

Total AI/AN

Hispanic

0

Z

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Respiratory Diseases
Management: Daily Asthma Medication

Improving quality of care for people with asthma can reduce the occurrence of asthma attacks and

avoidable hospitalizations. The National Asthma Education and Prevention Program, coordinated by the

National Heart, Lung, and Blood Institute, develops and disseminates science-based guidelines for the

diagnosis and management of asthma.61 These recommendations are built around four essential

components of asthma management critical for effective long-term control of asthma: assessment and

monitoring, control of factors contributing to symptom exacerbation, pharmacotherapy, and education for

partnership in care.62

Daily long-term control medication is necessary to prevent exacerbations and chronic symptoms for all

patients with persistent asthma. Appropriate controller medications for people with mild persistent

asthma63,xv include inhaled corticosteroids, cromolyn, nedocromil, theophylline, and leukotriene

modifiers.64

xv“Mild persistent asthma” refers to cases in which people experience asthma symptoms more than 2 days per week,

more than 2 nights per month, and other clinical indicators.

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

79

Chapter 2 Respiratory Diseases

Blacks with current asthma were

less likely than Whites with current

asthma to take daily preventive

medicine.
Figure 2.27. People with current asthma who are now taking preventive medicine daily or almost

daily (either oral or inhaler), by race (top left), ethnicity (top right), income (bottom left), and

education (bottom right), 2003-2005

Key: Ai/AN = American Indian or Alaska Native.

Reference population: Noninstitutionalized population with asthma as defined below.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2003-2005.

National Quality Report, 2000

Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

80

Chapter 2

0

10

20

30

40

50 Total Black

Percent

2003

2004

2005

White

0

10

20

30

40

50

Percent

2003

2004

Non-Hispanic White

Hispanic

2005

0

10

20

30

40

50

2004

Percent

2003

High School Grad

<High School Some College

2005

0

10

20

30

40

50

2004

Percent

2003

Low Income High Income

Poor Middle Income

2005

Respiratory Diseases
Note: People with current asthma are defined as people who report they either still have asthma or had an episode or attack in the

last 12 months. Data were insufficient for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and Alaska

Natives for this analysis.

◆ From 2003 to 2005, there were no statistically significant changes over time in the percentage of

people with current asthma who are taking daily preventive medicine for any group except for nonHispanic Whites (Figure 2.27).

◆ From 2003 to 2005, the gap between Blacks and Whites remained the same. In 2005, Blacks with

current asthma were less likely than Whites with current asthma to take daily preventive medicine

(27.4% compared with 34.0%).

◆ From 2003 to 2005 the gap between Hispanics and non-Hispanic Whites increased. In 2005,

Hispanics with current asthma were less likely than non-Hispanic Whites with current asthma to take

daily preventive medicine (21.1% compared with 35.9%).

◆ From 2003 to 2005, there were no statistically significant changes overall by income or education

status in the percentage of people with current asthma who took daily preventive medicine (Figure

2.26).

◆ In 2005, people with current asthma who were poor (27.1%), low income (29.3%), and middle

income (30.1%) were less likely than high-income people (38.5%) to take daily preventive medicine.

◆ There were no statistically significant differences by education status in 2005.

National Quality Report, 2000

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National Healthcare Disparities Report, 2008

81

Chapter 2 Respiratory Diseases
Nursing Home, Home Health, and Hospice Care

Number of nursing home residents ever admitted during the calendar year (2006) ...................3,176,11965

Medicare fee-for-service (FFS) admissions to skilled nursing facilities (2005)..........................2,543,13366

Number of Medicare FFS home health patients (2006) ...............................................................3,031,81467

Number of Medicare FFS beneficiaries using Medicare hospice services (2006).........................935,56568

Total costs of nursing home care (2006) ..................................................................................$124.9 billon69

Medicare expenditures for nursing home care (2006) ........................................................$20.8 billion69

Total costs of home health care (2006) .....................................................................................$52.7 billion69

Medicare expenditures for home health care (2006)...........................................................$19.8 billion69

Medicare FFS payments for hospice services (2006).................................................................$9.2 billion70

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources. Cost

estimates for nursing home and home health services include costs only for freestanding skilled nursing facilities, nursing homes, and

home health agencies, and not facilities that are hospital based.

This section highlights two core measures of nursing home quality of care—use of physical restraints and

presence of pressure sores—and two measures of home health care quality—improvement in walking or

moving around and episodes with acute care hospitalization. In addition, this section includes

supplemental measures on management of pain in hospice care, receipt of care consistent with patient’s

stated end-of-life wishes, and referral to hospice at the right time.

Management: Use of Physical Restraints on Nursing Home Residents

Although restraining nursing home residents is sometimes a component of keeping residents safe and

well cared for, residents who are restrained daily can become weak, lose their ability to go to the

bathroom by themselves, and develop pressure sores or other medical complications. Restraints should

be used only when they are necessary as part of medical treatment.

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Chapter 2 Nursing Home, Home Health, and Hospice Care

Use of physical restraints on

patients declines in nursing

homes—Associated Press
Figure 2.28. Long-stay nursing home residents with physical restraints, by race/ethnicity,

1999-2006

Key: AI/AN = American Indian or Alaska Native; API = Asian or

Pacific Islander.

Source: Centers for Medicare & Medicaid Services, Minimum

Data Set, 1999-2006. Data are from the third quarter of each

calendar year.

Denominator: Long-stay nursing home residents, all ages.

Note: White, Black, API, and AI/AN are non-Hispanic groups.

Long-stay residents are people in an extended/permanent nursing

home stay.

◆ From 1999 to 2006, the percentage of residents who were physically restrained decreased from

10.7% to 6.0% (Figure 2.28).

◆ From 1999 to 2006, the gap between APIs and Whites in the percentage of residents who were

physically restrained decreased. However, in 2006 the percentage of residents who were physically

restrained was higher for APIs than for Whites (9.1% compared with 6.0%).

◆ From 1999 to 2006, the gap between Hispanics and Whites decreased. However, in 2006, the

percentage of residents who were physically restrained was still higher for Hispanics than for Whites

(8.1% compared with 6.0%).

Management: Presence of Pressure Sores in Nursing Home Residents

A pressure ulcer, or pressure sore, is an area of broken-down skin caused by sitting or lying in one

position for an extended time. 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, 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.

National Quality Report, 2000

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83

Chapter 2

0

5

10

15

20

25

White

Black

API

1999

2000

2001

AI/AN

Percent

2002

2003

Hispanic

2004

Total

2005

2006

Nursing Home, Home Health, and Hospice Care
Figure 2.29. High-risk, long-stay nursing home residents (left), and short-stay residents (right)

with pressure sores, by race/ethnicity, 1999-2006

Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: Centers for Medicare & Medicaid Services, Minimum Data Set, 1999-2006. 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: Long-stay nursing home residents and short-stay nursing home residents.

Note: White, Black, API, and AI/AN are non-Hispanic groups. Long-stay residents are people in an extended/permanent nursing

home stay. Short-stay residents are people who need skilled nursing care or rehabilitation services following a hospital stay but are

expected to return home.

High-risk, long-stay nursing home residents

◆ From 1999 to 2006, the percentage of high-risk,xvi long-stay residents who developed pressure sores

decreased from 14.3% to 12.5% (Figure 2.29). While improvements were observed for all groups

except for AI/ANs, the gap between Blacks, AI/ANs, and Hispanics compared with Whites remained

the same.

◆ In 2006, the percentage of high-risk, long-stay residents who developed pressure sores was

significantly higher for Blacks (16.3%), AI/ANs (14.4%), and Hispanics (13.5%) than for Whites

(11.9%).

xvi“High-risk” residents are those who are in a coma, who do not get or absorb the nutrients they need, or who cannot

move or change position on their own. Conversely, “low-risk” residents can be active, can change positions, and are

getting and absorbing the nutrients they need.

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Chapter 2

0

10

20

30

40

White

Black

API

1999

2000

2001

AI/AN

Percent

2002

2003

Hispanic

2004

Total

Short-stay all-risk residents

2005

2006

0

10

20

30

40

White

Black

API

1999

2000

2001

AI/AN

Percent

2002

2003

Hispanic

2004

Total

High-risk, long-stay residents

2005

2006

Nursing Home, Home Health, and Hospice Care
◆ In 2006, the percentage of high-risk, long-stay residents who developed pressure sores was

significantly higher for males than females (15.4% compared with 11.5%; data not shown).

Short-stay nursing home residents

◆ From 1999 to 2006, the percentage of short-stay residents who had pressure sores decreased

significantly for all groups (Figure 2.29).

◆ From 1999 to 2006, the gap between Blacks and Whites decreased. However, in 2006, Black shortstay residents were still more likely than Whites to have pressure sores (23.8% compared with

19.6%).

◆ From 1999 to 2006, the gap between APIs and Whites increased. In 2006, API short-stay residents

were still more likely than Whites to have pressure sores (22.3% compared with 19.6%).

◆ From 1999 to 2006, the gap between AI/ANs and Whites decreased. There were no statistically

significant differences between AI/ANs and Whites in 2006.

◆ From 1999 to 2006, the gap between Hispanics and Whites remained the same. In 2006, Hispanic

short-stay residents were still more likely than Whites to have pressure sores (24.1% compared with

19.6%).

◆ In 2006, the percentage of short-stay residents who had pressure sores was higher for males than for

females (22.4% compared with 19%; data not shown).

Management: Improvement by Home Health Care Patients in Walking or

Moving Around

How well a patient improves in ability level while getting home health care is a reflection of the provider’s

quality of service; patient factors, such as mobility and fear of falling; and the patient’s available support

system. Improved ambulation (i.e., getting better at walking or using a wheelchair) is a measure of

improved outcomes.xvii

xviiIn cases of patients with some neurologic conditions, such as progressive multiple sclerosis or Parkinson’s disease,

ambulation may not improve even when the home health service provides good care.

National Quality Report, 2000

Quality of Health Care Staying Healthy

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Chapter 2 Nursing Home, Home Health, and Hospice Care
Figure 2.30. Adult home health care patients whose ability to walk or move around improved, by

race (left) and ethnicity (right), 2002-2006

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

Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set, 2002-2006.

Denominator: Episodes for adult nonmaternity patients receiving at least some skilled home health care.

Note: An episode is a 60-day period during which a patient is under the direct care of a home health agency. It starts with the

beginning/resumption of care and finishes when the patient is discharged from home health care or is transferred to an inpatient

facility. Some patients have multiple episodes in a year. Data are reported only for those patients who were not already performing at

the highest level of ambulation.

◆ From 2002 to 2006, the percentage of home health care patients who got better at walking and

moving around improved for Whites (from 33.8% to 41.4%; Figure 2.30) and the total population

(from 33.9% to 41.2%). There were no statistically significant changes for other groups.

◆ In 2006, there were no statistically significant differences between minority groups and Whites

(Figure 2.30).

Management: Acute Care Hospitalization of Home Health Care Patients

Improvement in the acute care hospitalization outcome is demonstrated by a decrease in the percentage of

patients who had to be admitted to the hospital; lower percentages are the desirable outcome. Acute care

hospitalization may be avoided if home health staff adequately check the patient’s health condition at each

visit to detect problems early. However, patients may need to go into the hospital while they are getting

care. In some cases, this may not be avoidable even with good home health care.

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Chapter 2

25

30

35

40

45

50

Percent

2002

2003

0

Z

2004

Non-Hispanic White

Hispanic

2005

2006

25

30

35

40

45

50

White

Black

Asian

NHOPI >1 Race

AI/AN

Percent

2002

2003

0

Z

2004

2005

Total

2006

Nursing Home, Home Health, and Hospice Care
Figure 2.31. Adult home health care patients who were admitted to the hospital, by race (left)

and ethnicity (right), 2002-2006

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

Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set, 2002-2006.

Denominator: Episodes for adult nonmaternity patients receiving at least some skilled home health care.

Note: An episode is the time during which a patient is under the direct care of a home health agency. It starts with the

beginning/resumption of care and finishes when the patient is discharged from home health care or is transferred to an inpatient

facility. Some patients have multiple episodes in a year.

◆ From 2002 to 2006, the gap between Blacks and Whites in the percentage of home health care

patients who were admitted to the hospital remained the same. In 2006, the percentage was higher

for Blacks than for Whites (33.9% compared with 27.3%; Figure 2.31).

◆ The gap between AI/ANs and Whites in the percentage of home health care patients who were

admitted to the hospital increased. In 2006, the percentage was higher for AI/ANs than for Whites

(34.2% compared with 27.3%).

◆ The gap between Asians and Whites in the percentage of home health care patients who were

admitted to the hospital remained the same. In 2006, the percentage was lower for Asians than for

Whites (23.1% compared with 27.3%).

◆ During the same period, the gap between Hispanics and non-Hispanic Whites in the percentage of

home health care patients who were admitted to the hospital remained the same. In 2006, the

percentage was higher for Hispanics than for non-Hispanic Whites (31.0% compared with 27.3%).

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Chapter 2

0

10

20

30

40

50

Percent

2002

2003

2004

Non-Hispanic White

Hispanic

2005

2006

0

10

20

30

40

50 White

Black

Asian

NHOPI >1 Race

AI/AN

Percent

2002

2003

2004

2005

2006

Nursing Home, Home Health, and Hospice Care
Management: Hospice Care

Hospice care is generally delivered at the end of life to patients with a terminal illness or condition who

desire palliative medical care; it also includes psychosocial and spiritual support for the patient and

family. The goal of end-of-life care is to achieve a “good death,” defined by the Institute of Medicine

(IOM) as one that is “free from avoidable distress and suffering for patients, families, and caregivers; in

general accord with the patient’s and families’ wishes; and reasonably consistent with clinical, cultural,

and ethical standards.”71 The National Hospice and Palliative Care Organization’s Family Evaluation of

Hospice Care survey examines the quality of hospice care for patients and their family members.xviii

Family respondents report how well hospices respect patient wishes, communicate about illness, control

symptoms, support dying on one’s own terms, and provide family emotional support.72

Pain management

Addressing the comfort aspects of care, such as relief from pain, fatigue, and nausea, is an

important component of hospice care.xix

xviiiThis annual 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%. In addition, race and

ethnicity were not reported by large numbers of respondents. These limitations should be considered when interpreting

these findings.

xixThis measure is based on responses from a family member of the deceased. It should be noted that family members

may or may not be able to determine whether the right amount of medicine for pain was administered.

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Chapter 2 Nursing Home, Home Health, and Hospice Care
Figure 2.32. Hospice patients who did NOT receive the right amount of medicine for pain, by

race, ethnicity, and education, 2007

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, 2007.

Denominator: Adult hospice patients.

◆ The percentage of hospice patients whose families reported that they did not receive the right

amount of medicine for pain was 5.7% in 2007 (Figure 2.32).

◆ The percentage of hospice patients whose families reported that they did not receive the right

amount of medicine for pain was significantly higher for Blacks (7.6%) and APIs (11.3%) than for

Whites (5.7%).

◆ The percentage of hospice patients whose families reported that they did not receive the right

amount of medicine for pain was also higher for Hispanics than for non-Hispanic Whites (6.9%

compared with 5.7%).

End-of-life care

End-of-life care should respect a patient’s stated end-of-life wishes. This includes shared communication

and decisionmaking between providers, patients, and family members and respect for cultural beliefs.

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Chapter 2

White

Percent

Black

Non-Hispanic White

Hispanic

Total

<High School

High School Grad

Any College

0

5

10

15

20

25

AI/AN

API

Nursing Home, Home Health, and Hospice Care
Figure 2.33. Hospice patients age 18 and over who did NOT receive care consistent with their

stated end-of-life wishes, by race, ethnicity, and education, 2007

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,

2007.

Denominator: Adult hospice patients.

◆ The overall percentage of hospice patients whose families reported that they did not receive end-oflife care consistent with their wishes was 5.6% in 2007 (Figure 2.33).

◆ The percentage whose families reported that they did not receive care consistent with their wishes

was almost two times higher for Blacks (10.0%), almost three times higher for APIs (14.9%), and

more than two times higher for AI/ANs (11.4%) compared with Whites (5.2%).

◆ This percentage was more than two times higher for Hispanics than for non-Hispanic Whites (10.8%

compared with 5.1%).

◆ The percentage of patients whose families reported that they did not receive care consistent with

their wishes was higher for hospice patients with less than a high school education compared with

those who had any college education (10.1% compared with 4.6%).

Timeliness of hospice care

Research suggests that late referral to hospice results in unmet needs for some patients and

caregivers.73 Therefore, the perception of timeliness of referral is an indicator of adequacy of

access to hospice care.

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Chapter 2

White

Percent

Black

Non-Hispanic White

Hispanic

Total

<High School

High School Grad

Any College

0

5

10

15

20

25

AI/AN

API

Nursing Home, Home Health, and Hospice Care
Figure 2.34 Hospice patient caregivers who perceived patient was NOT referred to hospice at the

right time, by race, ethnicity, and education, 2007

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,

2007.

Denominator: Adult hospice patients.

Note: Caregivers were family members who

interacted with hospice providers.

◆ Overall in 2007, 11.3% of hospice patient caregivers perceived hospice care was not referred at the

right time (Figure 2.34).

◆ The percentage of caregivers who perceived hospice care was not referred at the right time was

lower for Blacks than for Whites (8.9% compared with 11.7%).

◆ The percentage of caregivers who perceived hospice care was not referred at the right time was

higher for AI/ANs than for Whites (12.7% compared with 11.7%).

◆ The percentage of caregivers who perceived hospice care was not referred at the right time was

lower for caregivers with less than a high school education (8.4%) and high school education (9.7%)

than for caregivers with any college education (13.1%).

◆ The percentage of caregivers who perceived hospice care was not referred at the right time was

higher for females than for males (12.7% compared with 8.8%; data not shown).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

91

Chapter 2

White

Percent

Black

Non-Hispanic White

Hispanic

Total

<High School

High School Grad

Any College

0

5

10

15

20

25

AI/AN

API

Nursing Home, Home Health, and Hospice Care
Patient Safety

Number of Americans who die each year from medical errors (1999 est.)..........................44,000-98,00074

Number of Americans who die in the hospital each year due to 18

types of medical injuries (2000 est.) .......................................................................................at least 32,00075

Rate of adverse drug reactions during hospital admissions .............................................2.0%-6.7%76,77,78,79

Rate of adverse drug events among Medicare beneficiaries in

ambulatory settings ..................................................................................................50 per 1,000 person-years

Percentage of serious, life-threatening, or fatal events deemed preventable ............................................40%

Cost (in lost income, disability, and health care costs) attributable to medical errors (1999 est.)$17 billion-

$29 billion74 .......................................................................................................................................................

Groups with higher rates of some adverse safety events.................................................racial minorities80,81

Note: Statistics may vary from previous years due to revised and updated source statistics or addition of data sources.

In 1999, the IOM published To Err Is Human, which called for a national effort to reduce medical errors

and increase patient safety.74 The IOM defines patient safety as freedom from accidental injury due to

medical care or medical errors.74 In response to the IOM’s report on patient safety, the President signed

the Patient Safety and Quality Improvement Act of 2005 (Patient Safety Act) to spur the development of

voluntary, provider-driven initiatives to improve the quality, safety, and outcomes of patient care. The act

addresses many of the current barriers to improving patient care.

Measuring patient safety is complicated by difficulties assessing and ensuring the systematic reporting of

medical errors and patient safety events. All too often, patient safety 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.

To Err Is Human does not mention race or ethnicity when discussing the problem of patient safety. A

2006 review of the literature found that only 9 of 323 articles on pediatric patient safety (2.8%) included

race or ethnicity in the analysis. Five of the nine studies from this review used data from the Agency for

Healthcare Research and Quality’s Healthcare Cost and Utilization Project.82

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92

Chapter 2 Patient Safety
This section highlights 10 measures of patient safety in three areas:

◆ Surgical complications.

◆ Other complications of hospital care.

◆ Complications of medications.

For findings related to all core measures of patient safety, see Table 2.2a.

Surgical Complications

Adverse health events can occur during episodes of care,

especially during and right after surgery. Although some

surgical complications may be related to a patient’s underlying

condition, many can be avoided if adequate care is provided.

Postoperative Complications

Patients are vulnerable to a variety of complications soon after they undergo surgery. Complications may

include, but are not limited to, pneumonia, urinary tract infection, and blood clots.

Figure 2.35. Composite measure: Medicare surgery patients with postoperative complications,

by race, 2004-2006

Source: Centers for Medicare & Medicaid Services, Medicare

Patient Safety Monitoring System, 2004-2006.

Denominator: Hospitalized Medicare patients having surgery, all

ages.

Note: Postoperative care complications included in this

composite are postoperative pneumonia and venous

thromboembolic event (blood clot). Note that this composite

measure changed from 2004 to 2005, with the alteration of the

complications of urinary tract infections being changed to

catheter-associated urinary tract infections. Catheter-associated

urinary tract infections was removed from this composite for 2006

data. Sensitivity analysis carried out on the composite shows that

this change does not significantly alter the composite estimate.

Data were unavailable for Asians, Native Hawaiians and Other

Pacific Islanders, and American Indians and Alaska Natives.

◆ There were no statistically significant differences between Blacks and Whites in the percentage of

hospital surgical patients with postoperative care complications (Figure 2.35).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

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Chapter 2

0

1

2

3

4

5 Total

Black

Percent

2004

2005

2006

White

Safety improving but

gains hard to measure:

AHRQ—Modern Healthcare

Daily Dose, March 3, 2008

Patient Safety
Postoperative Wound Infections

Infections acquired during hospital stays (nosocomial infections) are among the most serious safety

concerns. A common hospital-acquired infection is a wound infection following surgery. Hospitals can

reduce the risk of wound infection after surgery by making sure patients get the right antibiotics at the

right time on the day of their surgery. However, taking these antibiotics for more than 24 hours after

routine surgery is usually not necessary and can increase the risk of side effects, such as stomachaches,

serious types of diarrhea, and antibiotic resistance. Among adult hospital patients having surgery, the

NHDR tracks a composite of two measures: receipt of antibiotics within 1 hour prior to surgical incision

and discontinuation of antibiotics within 24 hours after end of surgery.

Figure 2.36. Composite measure: Adult surgery patients who received appropriate timing of

antibiotics, by race/ethnicity, 2006

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Medicare & Medicaid Services,

Medicare Quality Improvement Organization Program, 2006.

Denominator: Medicare patients age 18 and over having

surgery.

Note: Whites, Blacks, Asians, and AI/ANs are non-Hispanic

groups. Data were insufficient for this analysis for Native

Hawaiians and Other Pacific Islanders. Appropriate timing of

antibiotics received by adult surgical patients for all payers

included in this composite are: (1) antibiotics started within 1

hour of surgery, and (2) antibiotics stopped within 24 hours

after surgery.

◆ The percentage of appropriately timed antibiotics provided to surgery patients was significantly

lower for Asians (78.0%) and Hispanics (74.7%) than for Whites (80.7%; Figure 2.36). There were

no statistically significant differences for other groups.

Postoperative Wound Separation

Possible complications of abdominal and pelvic surgery include wound separation or rupture, involving

all layers of the abdominal wall and the need for surgical reclosure. This can occur within 30 days of the

procedure, typically between days 5 and 8. Separation is more likely to occur if wound infection is

present and can lead to prolonged hospitalization and death.

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Staying Healthy Quality of Health Care

National Healthcare Disparities Report, 2008

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Chapter 2

White

Percent

Black

Hispanic

Total

0

10

20

30

40

50

60

70

80

90

100

Asian

AI/AN

Patient Safety
Figure 2.37. Reclosure of postoperative abdominal wound separation per 1,000 abdominopelvicsurgery hospital discharges, adults age 18 and over, by race/ethnicity, 2001-2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2001-2005.

Denominator: Inpatient hospital abdominopelvic-surgery

discharges, excluding obstetric conditions.

Note: White, Black, and API are non-Hispanic. Data are adjusted

for age, gender, and diagnosis-related group clusters. The HCUP

SID disparities analysis file is designed to provide national

estimates using weighted records from a sample of hospitals from

23 States that have 63% of the U.S. resident population.

Figure 2.38. Reclosure of postoperative abdominal wound separation per 1,000 abdominopelvicsurgery hospital discharges, adults age 18 and over, by income, 2005

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project, State Inpatient Databases disparities

analysis file, 2001-2005.

Denominator: Inpatient hospital abdominopelvic-surgery

discharges, excluding obstetric conditions.

Note: Data are adjusted for age, gender, and diagnosis-related

group clusters. The HCUP SID disparities analysis file is designed

to provide national estimates using weighted records from a

sample of hospitals from 23 States that have 63% of the U.S.

resident population.

◆ From 2001 to 2005, the rate of postoperative abdominal wound separation during initial admissions

decreased overall (Figure 2.37).

National Quality Report, 2000

Quality of Health Care Staying Healthy

National Healthcare Disparities Report, 2008

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Chapter 2

0

1

2

3

4 White

Black

2003

2005

Rate

2001

Total Hispanic

API

2002

2004

0

1

2

3

4

5

Rate

<$25K

$25K-$34,999

$35K-$44,999

>$45K

Patient Safety
◆ There were no statistically significant differences between Whites and any racial or ethnic groups.

◆ There were also no statistically significant differences between high-income and other income

groups.

Accidental Puncture or Laceration

Adverse events are possible during any surgery or procedure, including the nicking or cutting of bodily

organs and blood vessels. This may be especially true in emergent situations, when, according to an

expert panel review, some of these occurrences are not preventable. Puncture or laceration can lead to

serious complications.

Figure 2.39. Accidental puncture or laceration during procedure per 1,000 discharges, adults age

18 and over, by race/ethnicity, 2001-2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2001-2005.

Denominator: Hospital medical and surgical discharges,

excluding obstetric admissions.

Note: White, Black, and API are non-Hispanic. Data are adjusted

for age, gender, and diagnosis-related group clusters. The HCUP

SID disparities analysis file is designed to provide national

estimates using weighted records from a sample of hospitals from

23 States that have 63% of the U.S. resident population.

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Staying Healthy Quality of Health Care

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Chapter 2

0

1

2

3

4

5

6

White

Black

2003

2005

Rate

2001

Total Hispanic

API

2002

2004

Patient Safety
Figure 2.40. Accidental puncture or laceration during procedure per 1,000 discharges, adults age

18 and over, by income, 2005

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2005.

Denominator: Hospital medical and surgical discharges,

excluding obstetric admissions.

Note: Data are adjusted for age, gender, and diagnosis-related

group clusters. The HCUP SID disparities analysis file is designed

to provide national estimates using weighted records from a

sample of hospitals from 23 States that have 63% of the U.S.

resident population.

◆ Overall, from 2001 to 2005, the rate of accidental puncture or laceration during a procedure

increased (Figure 2.39). The rate increased for all racial and ethnic groups except non-Hispanic

Whites.

◆ In 2005, the percentage of discharges of adults with accidental puncture or laceration during

procedure was higher for APIs (4.9 per 1,000) than for non-Hispanic Whites (4.4 per 1,000).

◆ There were no statistically significant differences by income in the rate of accidental puncture or

laceration (Figure 2.40).

Other Complications of Hospital Care

Types of care delivered in hospitals in addition to surgery can place patients at risk for injury or death.

Adverse Events Associated With Central Venous Catheters

Patients who require a central venous catheter to be inserted into the great vessels of their heart tend to be

severely ill. However, the procedure itself can result in a number of infectious and noninfectious

complications.

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Chapter 2

0

1

2

3

4

5

Rate

<$25K

$25K-$34,999

$35K-$44,999

>$45K

Patient Safety
Figure 2.41. Composite measure: Bloodstream infections (BSIs) or mechanical adverse events

per 1,000 central venous catheter (CVC) placements, Medicare hospital patients, by race,

2004-2006

Source: Centers for Medicare & Medicaid Services, Medicare

Patient Safety Monitoring System, 2004-2006.

Denominator: Hospitalized Medicare patients with central venous

catheter placement, all ages.

Note: Central venous catheter complications included in this

composite are bloodstream infections and mechanical adverse

events. Data were not available for Asians, Native Hawaiians and

Other Pacific Islanders, and American Indians and Alaska Natives.

◆ No statistically significant disparities were observed between Blacks and Whites in rates of central

venous catheter complications among hospital patients (Figure 2.41).

◆ From 2004 to 2006, the rate of central venous catheter complications increased significantly overall

(from 3.0% to 5.8%).

Iatrogenic Pneumothorax

Iatrogenic pneumothorax is a partial or complete collapse of a lung, due to an accumulation of air in the

pleural space (between the lungs and the chest wall) caused by medical care. This condition can be life

threatening. This indicator is intended to track cases of pneumothorax caused by medical care.

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Chapter 2

0

1

2

3

4

5

6

7

8

9

10 Total

Black

Percent

2004

2005

2006

White

Patient Safety

Gap between Blacks and Whites in the

rates of in-hospital death following

complications of care decreased.
Figure 2.42. Iatrogenic pneumothorax per 1,000 hospital discharges, adults age 18 and over, by

race/ethnicity, 2001-2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2001-2005.

Denominator: All nonmaternity medical and surgical hospital

discharges, excluding patients with trauma, thoracic surgery, lung

or pleural biopsy, or cardiac surgery.

Note: White, Black, and API are non-Hispanic. Data are adjusted

for age, gender, and diagnosis-related group clusters. The HCUP

SID disparities analysis file is designed to provide national

estimates using weighted records from a sample of hospitals from

23 States that have 63% of the U.S. resident population.

Figure 2.43. Iatrogenic pneumothorax per 1,000 hospital discharges, adults age 18 and over, by

income, 2005

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2005.

Denominator: All nonmaternity medical and surgical hospital

discharges, excluding patients with trauma, thoracic surgery, lung

or pleural biopsy, or cardiac surgery.

Note: Data are adjusted for age, gender, and diagnosis-related

group clusters. The HCUP SID disparities analysis file is designed

to provide national estimates using weighted records from a

sample of hospitals from 23 States that have 63% of the U.S.

resident population.

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Chapter 2

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

White

Black

2003

2005

Rate

2001

Total Hispanic

API

2002

2004

0.0

0.2

0.4

0.6

0.8

1.0

Rate

<$25K

$25K-$34,999

$35K-$44,999

>$45K

Patient Safety
◆ From 2001 to 2005, the overall rate of iatrogenic pneumothorax decreased (Figure 2.42). The rate

decreased for all groups except for Hispanics and Asians and Pacific Islanders. There were no

statistically significant changes for income groups (data not shown).

◆ From 2001 to 2005, the gap between Hispanics and non-Hispanic Whites remained the same. In

2005, the percentage of hospital discharges for adults with iatrogenic pneumothorax remained lower

for Hispanics than for non-Hispanic Whites (0.55 per 1,000 compared with 0.71 per 1,000).

◆ There were no other statistically significant differences by race or income (Figure 2.43).

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. This

indicator, also called “failure to rescue,” tracks deaths among patients whose hospitalizations are

complicated by pneumonia, thromboembolic event, sepsis, acute renal failure, shock, cardiac arrest,

gastrointestinal bleeding, or acute ulcer.

Figure 2.44. Deaths per 1,000 discharges with complications potentially resulting from care

(failure to rescue), adults ages 18-74, by race/ethnicity, 2001-2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2001-2005.

Denominator: Patients ages 18-74 from U.S. community

hospitals whose hospitalization is complicated by pneumonia,

thromboembolic event, sepsis, acute renal failure, shock, cardiac

arrest, gastrointestinal bleeding, or acute ulcer. The HCUP SID

disparities analysis file is designed to provide national estimates

using weighted records from a sample of hospitals from 23 States

that have 63% of the U.S. resident population.

Note: White, Black, and API are non-Hispanic. Data were not

available for American Indians and Alaska Natives. Data are

adjusted for age, gender, and diagnosis-related group clusters.

The HCUP SID disparities analysis file is designed to provide

national estimates using weighted records from a sample of

hospitals from 23 States that have 63% of the U.S. resident

population.

◆ From 2001 to 2005, there was significant improvement overall in the rates of in-hospital deaths

following complications of care (from 152.2 per 1,000 in 2001 to 125.8 per 1,000 in 2005; Figure

2.44).

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Chapter 2

100

125

150

175

200

Non-Hispanic White

Black

2002

Rate

2001

Total API

Hispanic

0

Z

2003

2004

2005

Patient Safety
◆ During this period, the gap between Blacks and non-Hispanic Whites in the rates of in-hospital

deaths following complications of care decreased. In 2005, there was no statistically significant

difference between Blacks and non-Hispanic Whites.

◆ The gap between Hispanics and non-Hispanic Whites stayed the same. In 2005, Hispanics had a

higher rate of in-hospital deaths following complications of care than non-Hispanic Whites (131.0

per 1,000 compared with 125.2 per 1,000).

◆ In 2005, there was no statistically significant difference between people living in communities with

median household incomes of less than $25,000 and people living in communities with median

household incomes of greater than $45,000 in the rate of deaths following complications of care

(data not shown).

Deaths in Low-Mortality Diagnosis-Related Groups

Health care errors are more likely responsible for in-hospital deaths of patients admitted for low-risk

illnesses or procedures than for deaths of high-risk patients.

Figure 2.45. Deaths per 1,000 admissions in low-mortality DRGs, adults age 18 and over, by

race/ethnicity, 2001-2005

Key: API = Asian or Pacific Islander; DRG = diagnosis-related

group.

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2001-2005.

Denominator: Hospital admissions in low-mortality diagnosisrelated groups (DRGs), excluding trauma, immunocompromised,

and cancer patients.

Note: White, Black, and API are non-Hispanic. Data are adjusted

for age, gender, and DRG clusters. The HCUP SID disparities

analysis file is designed to provide national estimates using

weighted records from a sample of hospitals from 23 States that

have 63% of the U.S. resident population.

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Chapter 2

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

White

Black

2003

2005

Rate

2001

Total Hispanic

API

2002

2004

1.0

Patient Safety
Figure 2.46. Deaths per 1,000 admissions in low-mortality DRGs, adults age 18 and over, by

income, 2005

Source: Agency for Healthcare Research and Quality, Healthcare

Cost and Utilization Project (HCUP), State Inpatient Databases

(SID) disparities analysis file, 2005.

Denominator: Hospital admissions in low-mortality diagnosisrelated groups (DRGs), excluding trauma, immunocompromised,

and cancer patients.

Note: Data are adjusted for age, gender, and DRG clusters. The

HCUP SID disparities analysis file is designed to provide national

estimates using weighted records from a sample of hospitals from

23 States that have 63% of the U.S. resident population.

◆ From 2001 to 2005, there were no statistically significant changes in the rate of deaths in lowmortality diagnosis-related groups (DRGs) (Figure 2.45).

◆ In 2005, the rate of deaths in low-mortality DRGs was lower for Hispanics than for non-Hispanic

Whites (0.29 per 1,000 compared with 0.63 per 1,000).

◆ While APIs have consistently had a lower rate of deaths in low-mortality DRGs, these were not

significantly different from Whites.

◆ There were no other statistically significant differences by race or income (Figure 2.46).

Complications of Medications

Complications of medications are common safety problems. Some adverse drug events may be related to

misuse of medication, but others are not. However, prescribing medications that are inappropriate for a

specific population may increase the risk of adverse drug events.

Adverse Drug Events in the Hospital

Some medications used in hospitals can cause serious complications. The Medicare Patient Safety

Monitoring System tracks a number of “high-risk” drugs and the adverse events associated with them.

Adverse drug events can include serious bleeding associated with intravenous heparin, subcutaneously

administered low-molecular-weight heparin, and oral warfarin, as well as hypoglycemia associated with

insulin or oral hypoglycemics.

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Chapter 2

0.0

0.2

0.4

0.6

0.8

Rate

<$25K

$25K-$34,999

$35K-$44,999

>$45K

1.0

Patient Safety
Figure 2.47. Medicare hospital patients with medication-related adverse drug events, by race,

2004-2006

Intravenous heparin Low-molecular-weight heparin

Warfarin Insulin

Source: Centers for Medicare & Medicaid Services, Medicare Patient Safety Monitoring System, 2004-2006.

Denominator: Random sample of Medicare medical records of patients receiving the drug, all ages.

Note: Data were not collected for Asians, Native Hawaiians and Other Pacific Islanders, American Indians and Alaska Natives, and

Hispanics.

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Chapter 2

0

5

10

15

20

25

White

Black

Percent

2004

2006

Total

2005

0

5

10

15

20

25

White

Black

Percent

2004

2006

Total

2005

0

5

10

15

20

25

White

Black

Percent

2004

2006

Total

2005

0

5

10

15

20

25

White

Black

Percent

2004

2006

Total

2005

Patient Safety
◆ In 2006, between 5.2% and 15.5% of hospitalized Medicare patients overall experienced an adverse

drug event in the hospital, depending on the type of drug (Figure 2.47).

◆ From 2004 to 2006, there was no change in the percentage of patients taking intravenous heparin

who experienced an adverse drug event. There was also no statistically significant difference

between Blacks and Whites.

◆ From 2004 to 2006, the percentage of patients taking low-molecular-weight heparin who

experienced an adverse drug event decreased for all groups. However, Blacks were still more likely

than Whites to have an adverse event (6.3% compared with 5.2%).

◆ From 2004 to 2006, the percentage of patients taking warfarin who experienced an adverse drug

event decreased overall except for Blacks. Blacks were more likely to experience an adverse drug

event than Whites (9.0% compared with 5.9%).

◆ From 2004 to 2006, the percentage of patients taking insulin or hypoglycemics who experienced an

adverse drug event increased. There was no statistically significant difference between Blacks and

Whites.

Potentially Inappropriate Medication Prescriptions for Older Patients

Some drugs that are appropriate for some patients are considered potentially harmful for older patients

but are still prescribed to them.83,xx Inappropriate medication use by older patients includes drugs that

should often be avoided for these patients.

xxEleven drugs that should always be avoided for older patients include barbiturates, flurazepam, meprobamate,

chlorpropamide, meperidine, pentazocine, trimethobenzamide, belladonna alkaloids, dicyclomine, hyoscyamine, and

propantheline. Twenty-two drugs that should often 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.

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Chapter 2 Patient Safety

Quarter of disabled seniors use risky

medications—HealthDay, May 7, 2008
Figure 2.48. Adults age 65 and over who received potentially inappropriate prescription medicines in

the calendar year, by race, ethnicity, income, education, insurance status, and gender, 2005

Source: Agency for Healthcare Research and

Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized

population age 65 and over.

Note: Data were insufficient for this analysis for

Native Hawaiians and Other Pacific Islanders and

for American Indians and Alaska Natives. This

measure includes 33 inappropriate prescription

medications. Prescription medications received

include all prescribed medications initially

purchased or otherwise obtained, as well as any

refills.

◆ In 2005, older Asians were more likely than older Whites to have inappropriate drug use (20.3%

compared with 17.3%; Figure 2.48).

◆ Older Hispanics were less likely than older non-Hispanic Whites to have inappropriate drug use

(13.5% compared with 17.6%).

◆ Older women were more likely than older men to have inappropriate drug use (20.2% compared

with 14.3%).

◆ There were no statistically significant differences by income or education.

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Chapter 2

White

Percent

Black

Poor

Non-Hispanic White

Total

<High School

High School Grad

Some College

Low Income

Middle Income

High Income

Hispanic

0

5

10

15

20

25

Asian

Medicare Only

Medicare+Private

Medicare+Other Public

Male

Female

Patient Safety
Timeliness

Timeliness is the health care system’s capacity to provide care quickly after a need is recognized. For

patients, lack of timeliness can result in emotional distress, physical harm, and financial

consequences.84,85 For example, stroke patients’ mortality and long-term disability are largely influenced

by the timeliness of therapy.86,87 Timely delivery of appropriate care can also help reduce mortality and

morbidity for chronic conditions such as chronic kidney disease,88 and timely antibiotic treatments are

associated with improved clinical outcomes.89 Timely delivery of childhood immunizations helps

maximize protection from vaccine-preventable diseases while minimizing risks to the child and reducing

the chance of disease outbreaks.90

Early care for comorbid conditions has been shown to reduce hospitalization rates and costs for Medicare

beneficiaries.91 Some research suggests that, over the course of 30 years, the costs of treating diabetic

complications can approach $50,000 per patient.92 Timely outpatient care can reduce admissions for

pediatric asthma, which account for $1.25 billion in total hospitalization charges annually.93 The

measures of timeliness highlighted in this section are getting care for illness or injury as soon as wanted

and emergency department visits in which patients left without being seen. (For findings related to all

core measures of timeliness, go to Tables 2.3a and 2.3b.)

Getting Care for Illness or Injury As Soon As Wanted

The ability of patients to receive illness and injury care in a timely fashion is a key element in a patientcentered health care system.

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Chapter 2 Timeliness

In 2005, Asians were twice as likely as

Whites to report problems getting care

as soon as wanted.
Figure 2.49. 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, by race (top left), ethnicity (top

right), and income (bottom left), 2002-2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population

age 18 and over.

Note: Data were insufficient for this analysis for American Indians

and Alaska Natives.

◆ From 2002 to 2005, the gap between Blacks and Whites in the percentage of adults who reported

sometimes or never getting care for illness or injury as soon as wanted remained the same (Figure

2.49). In 2005, Blacks fared worse than Whites on this measure of timeliness (20.9% compared

with 13.4%).

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Chapter 2

0

5

10

15

20

25

30

White

Black

Percent

2002

2003

Asian

2004

Total

2005

0

5

10

15

20

25

30

Percent

Non-Hispanic White Hispanic

2002

2003

2004

2005

0

5

10

15

20

25

30

Percent

2002

2003

Poor

Near Poor

Middle Income

High Income

2004

2005

Timeliness
◆ From 2002 to 2005, the gap between Asians and Whites also remained the same. In 2005, Asians

were twice as likely as Whites to report problems getting care as soon as wanted (27.4% compared

with 13.4%).

◆ During this period, the gap between Hispanics and non-Hispanic Whites in the percentage of adults

who reported delayed care decreased. However, in 2005, Hispanics remained more likely than nonHispanic Whites to report problems getting care as soon as wanted (17.7% compared with 12.8%).

◆ During this period, the gap between poor and high-income people remained the same on this

measure. In 2005, poor adults were about 21⁄2 times as likely as high-income adults to report

problems getting care as soon as wanted (24.8% compared with 10.0%).

Racial and ethnic minorities are disproportionately of lower SES. To distinguish the effects of race,

ethnicity, income, and education on timeliness of primary care, this measure is stratified by income and

education level.

Figure 2.50. 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, by race (left) and ethnicity (right),

stratified by income, 2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

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Chapter 2

0

10

20

30

40

50

Percent

White

Black

Poor Near

Poor

Middle

Income

High

Income

0

10

20

30

40

50

Percent

Non-Hispanic White

Hispanic

Poor Middle

Income

Near

Poor

High

Income

Timeliness
Figure 2.51. 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, by race (left) and ethnicity (right),

stratified by education, 2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

◆ SES explains some but not all of the ethnic differences in timeliness of primary care (Figures 2.50

and 2.51).

◆ After stratification by income, high-income Hispanics were still more than twice as likely as highincome non-Hispanic Whites to report problems getting care as soon as wanted (18.1% compared

with 8.6%).

◆ After stratification by education, Blacks with a high school education and at least some college

education were still almost twice as likely as Whites of the same education level to report problems

getting care as soon as wanted (21.1% compared with 11.5% for high school graduates, and 19.3%

compared with 11.8% for people with at least some college education).

◆ After stratification by education, among people with some college, Hispanics were almost twice as

likely as non-Hispanic Whites to report problems getting care as soon as wanted (19.5% compared

with 11.2%).

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Chapter 2

0

10

20

30

40

50

Percent

White

Black

<High

School

High School

Grad

Some

College

0

10

20

30

40

50

Percent

Non-Hispanic White

Hispanic

<High

School

High School

Grad

Some

College

Timeliness
Figure 2.52. Children 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, by race (top left), ethnicity (top

right), and income (bottom left), 2002-2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population

under age 18.

◆ From 2002 to 2005, there were no statistically significant changes in the percentage of children

whose parents reported problems getting care as soon as wanted (Figure 2.52).

◆ There were no statistically significant differences observed between Blacks and Whites, between

Hispanics and non-Hispanic Whites, and between poor and high-income children.

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Chapter 2

0

3

6

9

12

15

White

Black

2002

Percent

2003

2005

Total

2004

0

3

6

9

12

15

Non-Hispanic White

Hispanic

2002

Percent

2003

2004

2005

0

3

6

9

12

15

2002

Percent

Near Poor High Income

Poor Middle Income

2003

2004

2005

Timeliness
Emergency Department Visits in Which Patients Left Without Being Seen

In 2004, patients who had an emergency department (ED) visit in the United States spent an average of

3.3 hours in the ED, with 47 minutes spent waiting to be seen by a physician.94 This may reflect the 18%

increase in ED visit volumes over the past 10 years, as the number of ED facilities has decreased by

12.4%.94 There are many reasons that a patient seeking care in an ED may leave without being seen, but

long waits tend to explain many departures.

Figure 2.53. Emergency department (ED) visits in which patients left without being seen, by race

(left) and payment source (right), 1997-1998, 1999-2000, 2001-2002, 2003-2004, and 2005-2006

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Ambulatory Medical Care

Survey, 1997-1998, 1999-2000, 2001-2002, 2003-2004, and 2005-2006.

Denominator: Visits by patients (of all ages) to the EDs of non-Federal, short-stay, and general hospitals, exclusive of military and

Department of Veterans Affairs hospitals.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

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Chapter 2

0.0

0.5

1.0

1.5

2.0

2.5

3.0

White

Black

Percent

1997-1998

1999-2000

2001-2002

Total

2003-2004

2005-2006

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Medicare

Medicaid

Percent

1997-1998

1999-2000

2001-2002

Private

2003-2004

2005-2006

Uninsured

Timeliness
◆ Between 1997-1998 and 2005-2006, the overall percentage of ED visits in which the patient left

without being seen almost doubled, from 1.2% to 2.0% (Figure 2.53).

◆ During this period, the gap between Blacks and Whites increased. In 2005-2006, Blacks were more

likely to leave without being seen than Whites (2.9% compared with 1.8%).

◆ During this period, the percentage of ED visits in which Medicaid patients left without being seen

remained the same and was higher than it was among patients with private insurance (in 2005-2006,

1.9% compared with 1.6%).

◆ During this period, the gap between uninsured patients and patients with private insurance remained

the same. Uninsured patients were about twice as likely to leave without being seen as patients with

private insurance (3.1% compared with 1.6%).

◆ Medicare patients were the least likely to leave the ED without being seen.

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Chapter 2 Timeliness

Uninsured patients were about twice as likely

to leave the emergency department without

being seen as patients with private insurance.
Patient Centeredness

The IOM identifies patient centeredness as a core component of quality health care.2 Patient

centeredness is defined as:

[H]ealth care that establishes a partnership among practitioners, patients, and their families

(when appropriate) to ensure that decisions respect patients’ wants, needs, and preferences

and that patients have the education and support they need to make decisions and participate

in their own care.95

Patient centeredness “encompasses qualities of compassion, empathy, and responsiveness to the needs,

values, and expressed preferences of the individual patient.”2

Patient-centered care is supported by good patient-provider communication so that patients’ needs and

wants are understood and addressed, and patients understand and participate in their own care.95,96,97,98

This style of care has been shown to improve patients’ health and health care.96,97,99,100,101 Unfortunately,

there are barriers to good communication.

About one-third of Americans are not “health literate,”102,103 which means they lack the “capacity to

obtain, process, and understand basic health information and services needed to make appropriate health

decisions.”104 They experience many difficulties, including:

◆ Less preventive care.105

◆ Poorer understanding of their conditions and care.102,106,107

◆ Higher use of emergency and inpatient services and higher rates of rehospitalization.108,109

◆ Lower adherence to medications.108

◆ Lower participation in medical decisionmaking.110

Low health literacy costs an estimated $29 billion to $69 billion per year.111 Providers also differ in

communication proficiency, including varied listening skills and views of symptoms and treatment

effectiveness compared with their patients’ views.112

When health care is patient centered, both underuse and overuse of medical services are reduced,113 as are

strains on system resources and costs through fewer diagnostic tests and referrals.99 Additional factors

influencing patient centeredness and patient-provider communication include:

◆ Language barriers.

◆ Racial and ethnic concordance between the patient and provider.

◆ Effects of disabilities on patients’ health care experiences

◆ Providers’ cultural competency.

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Chapter 2 Patient Centeredness
Efforts to remove these possible impediments to patient centeredness are underway. For example, the

Office of Minority Health, part of the Department of Health and Human Services, 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.114,xxi These modules are based on the National

Standards on Culturally and Linguistically Appropriate Services (CLAS). These standards are directed at

health care organizations and aim to improve the patient centeredness of care for people with limited

English proficiency (LEP). In addition, the HHS Office for Civil Rights has issued Guidance to Federal

Financial Assistance Recipients Regarding Title VI Prohibition Against National Origin Discrimination

Affecting Limited English Proficient Persons. This guidance explains that the failure of a recipient of

Federal financial assistance to take reasonable steps to provide LEP persons with a meaningful

opportunity to participate in HHS-funded programs may violate the prohibition under Title VI of the Civil

Rights Act of 1964, 42 U.S.C. 2000d, against national origin discrimination.115

The NHDR includes one core measure of patient centeredness—a composite measure on the patient

experience of care—and two new supplemental measures. Because having a diverse workforce of health

care providers may be an important component of patient-centered health care for many patients, this

year’s report includes a new supplemental measure of workforce diversity—race/ethnicity of the Nation’s

licensed practical nurse workforce. A supplemental measure focusing on health literacy of U.S. adults is

also presented in Chapter 4. (For findings related to all core measures of patient centeredness, go to

Tables 2.3a and 2.3b.)

Patients’ Experience of Care

Using methods developed for the CAHPS® (Consumer Assessment of Healthcare Providers and

Systems) survey,116 the NHDR uses a composite measure that combines four measures of patientprovider communication into a single core measure: providers who sometimes or never listen carefully,

explain things clearly, respect what patients say, and spend enough time with patients.

xxiThis online program (available at www.thinkculturalhealth.org) is accredited for 9 Continuing Medical Education

credits for physicians and 10.8 and 0.9 Continuing Education Units for nurses and pharmacists, respectively.

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Chapter 2 Timeliness
Figure 2.54. Composite measure: Ambulatory patients age 18 and over who reported poor

communication with health providers,* by race (top left), ethnicity (top right), and income

(bottom left), 2002-2005

* Average percentage of adults age 18 and over who had a

doctor’s office or clinic visit in the last 12 months and reported

poor communication with health providers (i.e., that their health

providers sometimes or never listened carefully, explained things

clearly, showed respect for what they had to say, and spent

enough time with them).

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Denominator: Civilian noninstitutionalized population age 18 and

over.

Note: Data were insufficient for this analysis for Native Hawaiians

and Other Pacific Islanders and American Indians and Alaska

Natives.

◆ From 2002 to 2005, the gap between Blacks and Whites and between Asians and Whites on this

measure increased. In 2005, Blacks and Asians were more likely than Whites to report poor

communication with their health providers (12.7% for Blacks and 13.0% for Asians compared with

9.1% for Whites; Figure 2.54).

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Chapter 2

0

5

10

15

20

White

Black

Asian >1 Race

Percent

2002

2003

2004

Total

2005

0

5

10

15

20

Percent

Non-Hispanic White Hispanic

2002

2003

2004

2005

0

5

10

15

20

Percent

2002

2003

Poor

Near Poor

Middle Income

High Income

2004

2005

Patient Centeredness
◆ The gap between Hispanics and non-Hispanic Whites in the percentage of adults who reported poor

communication with their health providers decreased from 2002 to 2005. However, in 2005, the

percentage was higher for Hispanics than for non-Hispanic Whites (11.7% compared with 8.8%).

◆ The gap between poor and high-income people increased. In 2005, the percentage of adults who

reported poor communication was higher for poor people than for high-income people (15.0%

compared with 7.4%).

Racial and ethnic minorities are disproportionately of lower SES. To distinguish the effects of race,

ethnicity, income, and education on patient-provider communication, this measure is stratified by

education level.

Figure 2.55. Composite measure: Adult ambulatory patients who reported poor communication

with health providers,* by race (left) and ethnicity (right), stratified by education, 2005

* Average percentage of adults age 18 and over who had a doctor’s office or clinic visit in the last 12 months and reported poor

communication with health providers (i.e., that their health providers sometimes or never listened carefully, explained things clearly,

showed respect for what they had to say, and spent enough time with them).

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

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 Asian high school

graduates.

◆ SES explains some but not all of the racial and ethnic differences in patient-provider communication

for patients age 18 and over (Figure 2.55).

◆ Among high school graduates, Blacks (13.0%) were more likely than Whites (8.7%) and Hispanics

(11.6%) were more like than non-Hispanic Whites (8.5%) to report poor communication with their

health providers.

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Chapter 2

0

5

10

15

20

25

Percent

White Black

<High

School

High School

Grad

Some

College

Asian

0

5

10

15

20

25

Percent

Non-Hispanic White

Hispanic

<High

School

High School

Grad

Some

College

Patient Centeredness
◆ Among people with less than a high school education, Blacks were more likely than Whites to report

poor communication with their health providers (18.6% compared with 12.5%).

Communication in children’s health care can pose a particular challenge, as children are often less able to

express their health care needs and preferences, and a third party (e.g., a parent or guardian) is involved in

communication and decisionmaking. 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 (CSHCN).

Figure 2.56. Composite measure: Children with ambulatory visits whose parents reported poor

communication* with health providers, by race (left), ethnicity (right), and family income (next

page top), 2002-2005

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Chapter 2

0

3

6

9

12

15

2002

Percent

2003

2004

2005

White

Black

Asian

>1 Race

0

3

6

9

12

15 Non-Hispanic White

Hispanic

2002

Percent

2003

2004

2005

Patient Centeredness

Blacks and Asians were more likely than

Whites to report poor communication with

their health providers.
* Children under 18 years of age whose parents or guardians

reported that their child’s health providers sometimes or never

listened carefully, explained things clearly, respected what they had

to say, and spent enough time with them.

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2004.

Denominator: Civilian noninstitutionalized population under age

18.

Note: Average percentage of children who had a doctor’s office or

clinic visit in the last 12 months and were reported to have had

poor communication with health providers (i.e., that their health

providers sometimes or never listened carefully, explained things

clearly, showed respect for what they had to say, and spent

enough time with them). Data for Asians (2005 only) and Native

Hawaiians and Other Pacific Islanders and American Indians and

Alaska Natives did not meet criteria for statistical reliability.

◆ Overall, the percentage of children whose parents or guardians reported poor communication with

their health providers decreased from 6.7% in 2002 to 5.5% in 2005 (data not shown).

◆ In 2005, there were no statistically significant differences between Blacks and Whites in the

percentage of children whose parents or guardians reported poor communication with their health

providers.

◆ From 2002 to 2005, the gap between Hispanics and non-Hispanic Whites in the percentage of

children whose parents or guardians reported poor communication with their health providers

decreased (Figure 2.56). However, in 2005, the percentage was still two times higher for Hispanics

than for non-Hispanic Whites (8.8% compared with 4.4%).

◆ The gap between poor people and high-income people in the percentage with poor communication

decreased. However, in 2005, the percentage was still significantly higher for poor (9.3%), nearpoor (7.3%), and middle-income (5.3%) people than for high-income people (2.5%).

Racial and ethnic minorities are disproportionately of lower SES. To distinguish the effects of race,

ethnicity, income, and education on patient-provider communication, this measure is stratified by income

level.

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Chapter 2

0

3

6

9

12

15

2002

Percent

Near Poor High Income

Poor Middle Income

2003

2004

2005

Patient Centeredness
Figure 2.57. Composite measure: Children with ambulatory visits whose parents reported poor

communication with health providers,* by race (left) and ethnicity (right), stratified by income,

2005

* Children under 18 years of age whose parents or guardians reported that their child’s health providers sometimes or never listened

carefully, explained things clearly, respected what they had to say, or spent enough time with them.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Denominator: Civilian noninstitutionalized population under age 18.

Note: Sample sizes were too small to provide estimates for poor and near-poor Asians. The seemingly large difference between

middle-income Asians and Whites is not statistically significant due to small sample sizes.

◆ SES explains some but not all of the racial and ethnic differences in patient-provider communication

for patients under age 18 (Figure 2.57).

◆ In 2005, among poor people, Blacks were more likely than Whites to report poor communication

with their health providers (20.0% compared with 13.5%).

◆ Among people with middle income, Hispanics were more likely than non-Hispanic Whites to report

poor communication with their health providers (13.8% compared with 9.7%).

Diversity of the Nurse Professionals Workforce

In 2000, more than 30% of Americans identified themselves as members of racial or ethnic minority

groups. It is estimated that by 2050, half of Americans will be members of minority groups.117 Minority

providers are more likely than their White colleagues to practice in underserved minority

communities.118,119 Health care workforce diversity 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.

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Chapter 2

0

5

10

15

20

25

Percent

White Black

Poor Near

Poor

Middle

Income

High

Income

Asian

0

5

10

15

20

25

Percent

Non-Hispanic White

Hispanic

Poor Middle

Income

Near

Poor

High

Income

Patient Centeredness
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.120 As such, diversity is an important element of a patientcentered health care encounter.

Previous reports have presented data on diversity in the physician and RN workforces. This year, the

NHDR presents data on diversity in the licensed practical nurse (LPN) workforce.

LPNs, known as licensed vocational nurses (LVNs) in California and Texas, provide patient care under the

supervision of physicians and registered nurses (RNs). Their scope of practice varies by State but may

include duties such as providing basic bedside care, assisting patients in daily living activities, performing

routine laboratory tests, monitoring patient response to medications or treatments, and gathering patient

information.

Compared with RNs, LPNs are less likely to work in hospitals and more likely to work in long-term and

personal care settings. Practical training programs are typically shorter than RN programs and are

therefore less costly to trainees seeking licensure. In May 2006, the median income of LPNs was

approximately $20,000 less than that of RNs. As the U.S. population ages and overall demand for health

care services increases, employment of LPNs is expected to grow faster than the average for all

occupations, particularly in long-term care facilities. Increases in hiring and in LPN-to-RN programs

may also help alleviate the national RN shortage.121,122

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Chapter 2 Patient Centeredness
Figure 2.58. U.S. nurse professionals compared with the U.S. population, by race/ethnicity, 2000

Key: AI/AN = American Indian or Alaska Native; NHOPI =

Native Hawaiian or Other Pacific Islander.

Source: U.S. Census 2000 and U.S. Census Bureau American

Community Survey, 2000.

Note: All racial groups are non-Hispanic.

◆ Of the RNs in the United States, 77.7% were White; 66.1% of LPNs/LVNs in the United States were

White (Figure 2.58).

◆ Relative to the U.S. population, Blacks were overrepresented in the LPN workforce, while Hispanic

individuals were underrepresented.

◆ In contrast, Whites and Asians were overrepresented in the RN workforce. The percentage of

Hispanics in the RN workforce (4.1%) was even smaller than the percentage in the LPN/LVN

workforce (6.1%).

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Chapter 2

Percent

RN

>1 Race

Asian

LPN/LVN

NHOPI

Black

AI/AN

Hispanic

White

U.S. population

0

20

40

60

80

100

Patient Centeredness
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Chapter 2

Table 2.1a. Racial and Ethnic Differences in Effectiveness of Care

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Cancer

Adults age 50 and over who received a

sigmoidoscopy, colonoscopy, or =

proctoscopy or fecal occult blood test in

the last 2 yearsiii

Colorectal cancer diagnosed

at advanced stageiv

Colorectal cancerv deaths per 100,000

population per year

Diabetes

Composite: Adults with diabetes who had

hemoglobin A1c measurement, dilated eye =

exam, and foot exam in the calender yearvi

Hospital admissions for lower extremity

amputations in patients per 1,000

population with diabetes age 18 and overvii

End Stage Renal Disease

Adult hemodialysis patients with adequate

dialysisviii =

Dialysis patients under age 70 who were

registered on a waiting list for

transplantationix = ==

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: National Health Interview Survey, 2005. iv Source: Surveillance, Epidemiology, and End Results Program, 2005. This source does not provide rate estimates for Asians and NHOPIs separately but

in aggregate as Asian and Pacific Islander. This source did not collect information for >1 race.

v Source: National Vital Statistics System-Mortality, 2005. This source did not collect information on Asians and NHOPIs separately but in aggregate as

Asian and Pacific Islander. This source did not collect information for >1 race.

vi Source: Medical Expenditure Panel Survey, 2005.

vii Source: National Hospital Discharge Survey, 2003-2006. This source did not collect information for >1 race. Missing rates preclude analysis by ethnicity. viii Source: CMS End Stage Renal Disease Clinical Performance Measures Project, 2006. ix U.S. Renal Data System, 2004. This source did not collect information on Asians and NHOPIs separately but in aggregate as Asian and Pacific Islander.

This source did not collect information for >1 race.

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

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Table 2.1a. Racial and Ethnic Differences in Effectiveness of Care (continued)

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Heart Disease

Adults with obesity who ever received

advice to exercise more = =

Adult current smokers who received

advice to quit smokingiii = =

Composite: Hospital patients with heart

attack who received recommended

hospital careiv = = =

Deaths per 1,000 adult hospital admissions

with acute myocardial infarctionv = =

Composite: Hospital patients with heart

failure who received recommended

hospital careiv = =

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: Medical Expenditure Panel Survey, 2005.

vii Source: CMS Quality Improvement Organization Program, 2006. This source categorizes race/ethnicity information as a single item: non-Hispanic

White, non-Hispanic Black, Hispanic, Asian and Pacific Islander, American Indian and Alaska Native. These contrasts compare each group with non-Hispanic

Whites.

v Source: HCUP State Inpatient Databases disparities analysis file, 2005. This source categorizes race/ethnicity information as a single item: non-Hispanic

White, non-Hispanic Black, Hispanic, Asian and Pacific Islander. These contrasts compare each group with non-Hispanic Whites.

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

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Chapter 2

Table 2.1a. Racial and Ethnic Differences in Effectiveness of Care (continued)

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

HIV and AIDS

New AIDS cases per 100,000

population 13 and overiii =

Maternal and Child Health

Pregnant women who first received

prenatal care in first trimesteriv =

Infant deaths per 1,000 live births,

<1,500 giv = =

Children ages 19-35 months who received

all recommended vaccinesv = = =

Children ages 2-17 with advice about

healthy eatingvi = = =

Children ages 3-6 who ever had their a

vision checkedvi

i

Compared with Whites.

iiCompared with non-Hispanic Whites.

iiiSource: Centers for Disease Control and Prevention, 2006. This source categorizes race/ethnicity information as a single item: non-Hispanic White, nonHispanic Black, Hispanic, Asian and Pacific Islander, American Indian and Alaska Native. These contrasts compare each group with non-Hispanic Whites.

ivSource: National Vital Statistics System-Natality, 2005. This source did not collect information for >1 race.

vSource: National Immunization Survey, 2006.

viSource: Medical Expenditure Panel Survey, 2005.

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

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Table 2.1a. Racial and Ethnic Differences in Effectiveness of Care (continued)

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Mental Health and Substance Abuse

Adults with a major depressive episode in

the last 12 months who received treatment

for depression in the last 12 monthsiii

Suicide deaths per 100,000 populationiv =

People age 12 and over who needed

treatment for illicit drug use who = =

received such treatmentiii

Respiratory Diseases

Adults age 65 and over who ever received

pneumococcal vaccinationv

Composite: Hospital patients with

pneumonia who received recommended

hospital carevi

Visits with antibiotics prescribed for a

diagnosis of common cold per

10,000 populationvii

Patients with tuberculosis who completed

a curative course of treatment within == =

1 year of treatment initiationviii

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2006.

iv Source: National Vital Statistics System-Mortality, 2005. This source did not collect information on Asians and NHOPIs separately but in aggregate as

Asian and Pacific Islander. This source did not collect information for >1 race.

v Source: National Health Interview Survey, 2006.

vi Source: CMS Quality Improvement Organization program, 2006. This source categorizes race/ethnicity information as a single item: non-Hispanic

White, non-Hispanic Black, Hispanic, Asian and Pacific Islander, American Indian and Alaska Native. These contrasts compare each group with nonHispanic Whites.

vii Source: National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey, 2005-2006. This source did not collect

information for >1 race. Missing rates preclude analysis by ethnicity.

viii Source: CDC National TB Surveillance System, 2004. This source did not collect information on Asians and NHOPIs separately but in aggregate as

Asian and Pacific Islander. This source did not collect information for >1 race.

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

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Chapter 2
Table 2.1a. Racial and Ethnic Differences in Effectiveness of Care (continued)

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Nursing Home, Home Health, and Hospice Care

Long-stay nursing home residents with

physical restraintsiii

High-risk, long-stay nursing home residents

with pressure soresiii =

Short-stay nursing home residents

with pressure soresiii =

Adult home health care patients whose

ability to walk or move around improvediv == = = = =

Adult home health care patients who were

admitted to the hospitaliv =

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: CMS Minimum Data Set, 2006. This source categorizes race/ethnicity information as a single item: non-Hispanic White, non-Hispanic Black,

Hispanic, Asian and Pacific Islander. Contrasts compare each group with non-Hispanic Whites.

iv Source: CMS Outcome and Assessment Information Set, 2006.

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

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Chapter 2

Table 2.1b. Socioeconomic Differences in Effectiveness of Care

Core Report Measure Income Educational Insurance

Differencei Differenceii Differenceiii

<100% 100-199% 200-399% <HS HS Grad Uninsured

Cancer

Adults age 50 and over who report

having ever received a sigmoidoscopy,

colonoscopy, or proctoscopy or who

report fecal occult blood test within

the last 2 yearsiv

Colorectal cancer deaths per 100,000

population per yearv

Diabetes

Composite: Adults with diabetes who

had hemoglobin A1c measurement, =

dilated eye exam, and foot exam in the

calender yearvi

Heart Disease

Adults with obesity who ever received

advice to exercise morevi

Adult current smokers who

received advice to quit smokingvi == ===

Maternal and Child Health

Pregnant women who first received

prenatal care in first trimestervii

Infant deaths per 1,000 live births,

birth weight <1,500 gvii

Children ages 19-35 months who

received all recommended vaccinesviii

Children ages 2-17 with advice about

healthy eatingvi

Children ages 3-6 who ever had their

vision checkedvi == =

i Compared with persons with family incomes 400% of Federal poverty thresholds or above.

ii Compared with persons with any college education.

iii Compared with persons under 65 with any private health insurance.

iv Source: National Health Interview Survey, 2006.

v Source: National Vital Statistics System-Mortality, 2005. This source did not collect information on Asians and NHOPIs separately but in aggregate as

Asian and Pacific Islander. This source did not collect information for >1 race.

vi Source: Medical Expenditure Panel Survey, 2005.

vii Source: National Vital Statistics System-Natality, 2005. This source did not collect information for >1 race.

viii Source: National Immunization Survey, 2006.

Key: HS=high school.

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Table 2.1b. Socioeconomic Differences in Effectiveness of Care (continued)

Core Report Measure Income Educational Insurance

Differencei Differenceii Differenceiii

<100% 100-199% 200-399% <HS HS Grad Uninsured

Mental Health and Substance Abuse

Adults with a major depressive episode

in the last 12 months who received = = = ==

treatment for the depression in the

last 12 monthsiv

Suicide deaths per 100,000 populationv

People age 12 and over who needed

treatment for illicit drug use who = = ==

received such treatmentiv

Respiratory Diseases

Adults age 65 and over who ever

received pneumococcal vaccinationvi = ==

i Compared with persons with family incomes 400% of Federal poverty thresholds or above.

ii Compared with persons with any college education.

iii Compared with persons under 65 with any private health insurance.

iv Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2006.

v Source: National Vital Statistics System-Mortality, 2005. This source did not collect information on Asians and NHOPIs separately but in aggregate as

Asian and Pacific Islander. This source did not collect information for >1 race.

vi Source: National Health Interview Survey, 2006.

Key: HS=high school.

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Chapter 2
Table 2.2a. Racial and Ethnic Differences in Patient Safety

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Postoperative Complications

Composite: Adult surgery patients with

postoperative complicationsiii

Other Complications of Hospital Care

Composite: Bloodstream infections

or mechanical complications per 1,000

central venous catheter placementsiii =

Deaths per 1,000 discharges following

complications of careiv =

Complications of Medications

Adults age 65 and over who received

potentially inappropriate

prescription medicationsv = =

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: Medicare Patient Safety Monitoring System, 2006.

iv Source: HCUP State Inpatient Databases disparities analysis file, 2005. This source categorizes race/ethnicity information as a single item: non-Hispanic

White, non-Hispanic Black, Hispanic, Asian and Pacific Islander. These contrasts compare each group with non-Hispanic Whites.

v Source: Medical Expenditure Panel Survey, 2005. This source did not collect information on Asians and NHOPIs separately but in aggregate as Asian and

Pacific Islander. This source did not collect information for >1 race.

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

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Chapter 2
Table 2.3a. Racial and Ethnic Differences in Timeliness and Patient Centeredness

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Timeliness

Adults who sometimes or never got

care for illness or injury as soon

as wantediii =

Emergency department visits in which

patients left without being seeniv =

Patient Centeredness

Composite: Adults who reported poor

provider-patient communicationiii =

Composite: Children whose parents

reported poor provider-patient

communicationiii = =

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: Medical Expenditure Panel Survey, 2005. This source did not collect information for >1 race.

iv Source: National Hospital Ambulatory Medical Care Survey – Emergency Department, 2005-2006. Missing rates preclude analysis by ethnicity.

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

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Chapter 2
Table 2.3b. Socioeconomic Differences in Timeliness and Patient Centeredness

Core Report Measure Income Educational Insurance

Differencei Differenceii Differenceiii

<100% 100-199% 200-399% <HS HS Grad Uninsured

Timeliness

Adults who sometimes or never

got care for illness or injury as soon

as wantediv =

Emergency department visits in which

patients left without being seenv

Patient Centeredness

Composite: Adults who reported poor

provider-patient communicationiv

Composite: Children whose parents

reported poor provider-patient

communicationiv =

i Compared with persons with family incomes 400% of Federal poverty thresholds or above.

ii Compared with persons with any college education.

iii Compared with persons under 65 with any private health insurance.

iv Source: Medical Expenditure Panel Survey, 2005. This source did not collect information for >1 race.

v Source: National Hospital Ambulatory Medical Care Survey – Emergency Department, 2005-2006. Missing rates preclude analysis by ethnicity.

Key: HS=high school.

Key to Symbols Used in Quality of Health Care Tables:

= Group and comparison group receive about same quality of health care or have similar outcomes.

Group receives better quality of health care than the comparison group or has better outcomes.

Group receives poorer quality of health care than the comparison group or has worse outcomes.

Blank cell: Reliable estimate for group could not be made.

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Chapter 2
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Chapter 2
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71. Field MJ, Cassell CK, eds. Institute of Medicine, Committee on Care at the End of Life. Approaching death: improving care at

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72. Connor SR, Teno J, Spence C, et al. Family Evaluation of Hospice Care: results from voluntary submission of data via website.

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74. Kohn LT, Corrigan JM, Donaldson MS, eds. Institute of Medicine, Committee on Quality of Health Care in America. To err is

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75. Zhan C, Miller MR. Excess length of stay, charges, and mortality attributable to medical injuries during hospitalization. JAMA

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76. Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of

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80. Romano PS, Geppert JJ, Davies S, et al. A national profile of patient safety in U.S. hospitals. Health Aff 2003

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81. Coffey RM, Andrews RM, Moy E. Racial, ethnic, and socioeconomic disparities in estimates of AHRQ Patient Safety

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82. Flores G, Ngui E. Racial/ethnic disparities and patient safety. Pediatr Clin N Am 2006;53:1197-1215.

83. Zhan C, Sangl J, Bierman AS, et al. Potentially inappropriate medication use in the community-dwelling elderly: findings from

the 1996 Medical Expenditure Panel Survey. JAMA 2001 Dec 12;286(22):2823-9.

84. Leddy KM, Kaldenberg DO, Becker BW. Timeliness in ambulatory care treatment. An examination of patient satisfaction and

wait times in medical practices and outpatient test and treatment facilities. J Ambul Care Manage 2003 AprJun; 26(2):138-49.

85. Boudreau RM, McNally C, Rensing EM, et al. Improving the timeliness of written patient notification of mammography

results by mammography centers. Breast J 2004 JanFeb;10(1):10-19.

86. Schellinger PD, Warach S. Therapeutic time window of thrombolytic therapy following stroke. Curr Atheroscler Rep 2004

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87. Kwan J, Hand P, Sandercock P. Improving the efficiency of delivery of thrombolysis for acute stroke: a systematic review.

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88. Kinchen KS, Sadler J, Fink N, et al. The timing of specialist evaluation in chronic kidney disease and mortality. Ann Intern

Med 2002 Sep 17;137(6):479-86.

89. Houck PM, Bratzler DW. Administration of first hospital antibiotics for community-acquired pneumonia: does timeliness

affect outcomes? Curr Opin Infect Dis 2005 Apr;18(2):151-6.

90. Luman ET, Barker LE, Shaw KM, et al. Timeliness of childhood vaccinations in the United States: days under vaccinated and

number of vaccines delayed. JAMA 2005 Mar 9;293(10):1204-11.

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91. Himelhoch S, Weller WE, Wu AW, et al. Chronic medical illness, depression, and use of acute medical services among

Medicare beneficiaries. Med Care 2004 Jun;42(6):512-21.

92. Caro JJ, Ward AJ, O’Brien JA. Lifetime costs of complications resulting from type 2 diabetes in the U.S. Diabetes Care 2002

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93. Calculated from: Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. 2003 Kids’ Inpatient

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94. McCaig LF, Nawar EN. National Hospital Ambulatory Medical Care Survey: 2004 emergency department summary. Advance

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95. Hurtado MP, Swift EK, Corrigan JM, eds. Institute of Medicine, Committee on the National Quality Report on Health Care

Delivery. Envisioning the National Health Care Quality Report. Washington, DC: National Academy Press, 2001.

96. Stewart M, Brown JB, Donner A, et al. The impact of patient centered care on outcomes. J Fam Pract 2000 Sep;49(9):796-804.

97. Anderson EB. Patient centeredness: a new approach. Nephrol News Issues 2002 Nov;16(12):8082.

98. Michie S, Miles J, Weinman J. Patient-centredness in chronic illness: what is it and does it matter? Patient Educ Couns 2003

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of general practice consultations. BMJ 2001 Oct 20;323(7318):908-11.

100. Beck R, Daughtridge R, Sloane PD. Physician-patient communication in the primary care office: a systematic review. J Am

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101. DiMatteo M. The role of the physician in the emerging health care environment. West J Med 1998 May;168(5):328-33.

102. Gazmararian J, Williams MV, Peel J, et al. Health literacy and knowledge of chronic disease. Patient Educ Couns 2003

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112. Rhoades DR, McFarland KF, Finch WH, et al. Speaking and interruptions during primary care office visits. Fam Med 2001

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Chapter 2
C h a p t e r 3 .

A c c e s s t o H e a l t h C a r e

Many Americans have good access to health care that enables them to benefit fully from the Nation’s

health care system. Others face barriers that make the acquisition of basic health care services difficult.

As demonstrated by extensive research and confirmed in previous National Healthcare Disparities

Reports (NHDRs), racial and ethnic minorities and people of low socioeconomic status (SES)i are

disproportionately represented among those with access problems. Poor access to health care comes at

both a personal and societal cost. For example, if people do not receive vaccinations, they may become

ill and spread disease to others, increasing the burden of disease for society overall in addition to the

burden borne individually.

Components of Health Care Access

Access to health care means having “the timely use of personal health services to achieve the best health

outcomes.”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. See measure specifications and data

source descriptions for more information on income groups by data source.

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139

Chapter 3
How This Chapter Is Organized

This chapter presents new information about disparities in access to health care in America since the last

NHDR. It is divided into two sections:

◆ Facilitators and barriers to health care, including measures of health insurance coverage, usual

source of care and primary care provider, and patient perceptions of need.

◆ Health care utilization, including measures of dental care, emergency care, potentially avoidable

admissions, mental health care, and substance abuse treatment.

Information about patient-provider communication is found in the section on patient centeredness in

Chapter 2, Quality of Health Care. As in previous NHDRs, this chapter focuses on disparities in access

to care related to race, ethnicity, and SES status in the general U.S. population. Disparities in access to

care and patient-provider communication within specific priority populations are discussed in Chapter 4,

Priority Populations. Analyses of changes over time and stratified analyses are also presented in this

chapter.

Facilitators and Barriers to Health Care

Facilitators and barriers to health care discussed in this section include health insurance, usual source of

care (including having a usual source of ongoing care and a usual primary care provider), and patient

perceptions of need. (Go to Tables 3.1a and 3.1b for a summary of findings related to all core measures

on facilitators and barriers to health care.)

Health Insurance

Health insurance facilitates entry into the health care system. Uninsured people are less likely to receive

medical care3 and are more likely to die early4 and have poor health status.5 The costs of early death and

poor health among uninsured people total $65 billion to $130 billion.4 The financial burden of

uninsurance is also great for uninsured individuals; almost 50% of personal bankruptcy filings are due to

medical expenses.6 Uninsured individuals report more problems getting care, are diagnosed at later

disease stages, and get less therapeutic care.6,7 They are sicker when hospitalized and more likely to die

during their stay.7

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140

Chapter 3

Racial and ethnic minorities and people of

low socioeconomic status are

disproportionately represented among

individuals with access problems, such as

uninsurance.
Figure 3.1. People under age 65 with health insurance, by race (top left), ethnicity (top right),

income (bottom left), and education (bottom right), 1999-2006

Access to Health Care

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141

Chapter 3

50

60

70

80

90

100

White

Black

Asian

1999

2000

2001

NHOPI >1 Race

AI/AN

Percent

2002

2003

0

Z

2004

2005

2006

Healthy People 2010

Target: 100%

50

60

70

80

90

100

1999

2000

2001

Percent

Non-Hispanic White Hispanic

2002

2003

0

Z

2004

2005

2006

Healthy People 2010

Target: 100%

50

60

70

80

90

100

1999

2000

2001

Percent

Near Poor High Income

Poor Middle Income

2002

2003

0

Z

2004

2005

2006

Healthy People 2010

Target: 100%

50

60

70

80

90

100

1999

2000

2001

Percent

2002

2003

0

Z

2004

2005

High School Grad

<High School At Least Some College

2006

Healthy People 2010

Target: 100%
Key: AI/AN = American Indian or Alaska Native; NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey (NHIS),

1999-2006.

Reference population: 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 (SCHIP), 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.

This measure reflects the percentage of survey respondents under age 65 who were covered by health insurance at the time of the

interview.

◆ From 1999 to 2006, the gap between Blacks and Whites in insurance coverage decreased (Figure

3.1). In 2006, the percentage of people with insurance was lower for Blacks than for Whites (81.9%

compared with 83.3%).

◆ From 1999 to 2006, the gap between Hispanics and non-Hispanic Whites in insurance coverage

remained the same. In 2006, the percentage of people with insurance was lower for Hispanics than

for non-Hispanic Whites (65.0% compared with 87.5%).

◆ The gap between poor people and high-income people decreased during this period. Still, in 2006,

the percentage of people with insurance was significantly lower for poor people than for highincome people (69.8% compared with 93.5%).

◆ The gap between people with less than a high school education and people with some college

increased. In 2006, the percentage of people with insurance was almost one-third lower for people

with less than a high school education than for people with some college (60.3% compared with

89.1%).

◆ From 1999 to 2006, the rates of insurance worsened for Whites, high-income people, and people at

every education level. There were no statistically significant changes in the rate of insurance for

Blacks, Asians, American Indians and Alaska Natives (AI/ANs), non-Hispanic Whites, and

Hispanics.

Racial and ethnic minorities are disproportionately of lower SES.8 To distinguish the effects of race,

ethnicity, income, and education on health insurance coverage, this measure is stratified by income and

education level.

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Figure 3.2. People under age 65 with health insurance, by race (left) and ethnicity (right),

stratified by income, 2006

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey (NHIS),

2006.

Reference population: Civilian noninstitutionalized population under age 65.

Note: NHIS respondents are asked about health insurance coverage at the time of interview; respondents are considered uninsured if

they lack private health insurance, public assistance, Medicare, Medicaid, State Children’s Health Insurance Program (SCHIP), 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. This measure reflects the percentage of survey respondents under age 65 who were covered by health

insurance at the time of the interview.

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0

20

40

60

80

100

Poor

Percent

White

Black

Near

Poor

High

Income

Asian

Middle

Income

AI/AN Healthy People 2010

Target: 100%

0

20

40

60

80

100

Poor

Percent

Non-Hispanic White

Hispanic

Near

Poor

High

Income

Middle

Income

Healthy People 2010

Target: 100%
Figure 3.3. People under age 65 with health insurance, by race (left) and ethnicity (right),

stratified by education, 2006

Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey (NHIS),

2006.

Reference population: 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, public assistance, Medicare, Medicaid, State Children’s Health Insurance Program (SCHIP), 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. This measure reflects the percentage of survey respondents under age 65 who were covered by health

insurance at the time of the interview.

◆ SES explains some but not all of the differences in the health insurance coverage of racial and ethnic

groups in people under age 65 (Figures 3.2 and 3.3).

◆ Hispanics of every income and education level were significantly less likely than their non-Hispanic

peers to have health insurance.

◆ Blacks who were poor and had less than a high school education (76.7% and 68.1%, respectively)

were significantly more likely than their White counterparts (67.1% and 58.4%, respectively) to have

health insurance.

◆ AI/ANs at every income level except poor and every education level except less than high school

were significantly less likely to have health insurance than Whites.

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0

20

40

60

80

100

<High School

Percent

High School

Grad

At Least

Some College

White

Black AI/AN

Asian

Healthy People 2010

Target: 100%

0

20

40

60

80

100

Percent

Non-Hispanic White

Hispanic

<High School High School

Grad

At Least

Some College

Healthy People 2010

Target: 100%
◆ Among people with a high school education, Blacks (74.5%), Asians (69.2%), and AI/ANs (54.5%)

were significantly less likely than Whites (79.4%) to have health insurance. Hispanics (65.7%) also

were significantly less likely than non-Hispanic Whites (81.6%) to have health insurance.

◆ No group has yet achieved the Healthy People 2010 target of 100% of Americans with health

insurance.

Prolonged periods of uninsurance can have a particularly serious impact on a person’s health and stability.

Uninsured people often postpone seeking care, have difficulty obtaining care when they ultimately seek

it, and may have to bear the full brunt of health care costs. Over time, the cumulative consequences of

being uninsured compound, resulting in a population at particular risk for suboptimal health care and

health status.

Figure 3.4. People under age 65 who were uninsured all year, by race (left), ethnicity (right),

income (next page top left), and education (next page top right), 2002-2005

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0

10

20

30

40

50 White

Black

Asian

NHOPI >1 Race

AI/AN

Percent

2002

2003

2004

2005

0

10

20

30

40

50

Percent

Non-Hispanic White

Hispanic

2002

2003

2004

2005
Key: AI/AN = American Indian or Alaska Native; NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2005.

Reference population: Analyses by race, ethnicity, and income performed for civilian noninstitutionalized population under age 65.

Analyses by education performed for civilian noninstitutionalized population ages 18-64.

Note: Beginning in 2002, survey respondents could report more than one race. Estimates for racial groups other than Whites and

Blacks are significantly affected by this change. Data for these groups are not directly comparable with earlier years and are not

shown here. Racial categories shown here exclude multiple-race individuals, who are shown as a separate group.

◆ From 2002 to 2005, the gap between Blacks and Whites in the percentage of uninsured people

remained the same (Figure 3.4). The percentage of people uninsured all year was still higher for

Blacks than for Whites in 2005 (15.6% compared with 13.8%).

◆ From 2002 to 2005, the gap between Hispanics and non-Hispanic Whites in the percentage of

uninsured people remained the same. The percentage of people uninsured all year was still almost

three times higher for Hispanics than for non-Hispanic Whites in 2005 (28.5% compared with 10.3%).

◆ From 2002 to 2005, the gap between poor people and high-income people in the percentage of

uninsured people remained the same. In 2005, the percentage of people uninsured all year was still

nearly four times higher for poor people than for high-income people (24.3% compared with 6.2%).

◆ From 2002 to 2005, the gap between people with less than a high school education and people with

some college in the percentage of uninsured people increased. The percentage of people uninsured

all year increased for people with less than a high school education (from 30.2% to 33.3%).

Each year, multivariate analyses are conducted in support of the NHDR to identify the independent

effects of race, ethnicity, and SES on access to health care. Past reports have listed some of these

findings. Figure 3.5 shows the results of a multivariate model for one additional access measure: people

without insurance all year. Adjusted odds ratios are shown to quantify the relative magnitude of

disparities after controlling for a number of confounding factors.

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Chapter 3

0

10

20

30

40

50

Percent

Near Poor High Income

Poor Middle Income

2002

2003

2004

2005

0

10

20

30

40

50

Percent

High School Grad

At Least

Some College

<High School

2002

2003

2004

2005
Figure 3.5. People ages 18-64 who were uninsured all year: Adjusted odds ratios, 2002-2005

Key: = reference group.

Source: Agency for Healthcare Research and Quality,

Medical Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized

population ages 18-64.

Note: Adjusted odds ratios are calculated from logistic

regression models controlling for race, ethnicity, income,

education, age, gender, insurance, and residence

location. White, non-Hispanic White, male, high income,

some college, and metropolitan are reference groups

with odds ratio = 1; odds ratios <1 indicate that a group

is less likely to receive service than the reference group.

For example, compared with non-Hispanic Whites,

Hispanics had 2.5 times the odds of having no

insurance after controlling for other factors. Data were

insufficient for this analysis for Native Hawaiians and

Other Pacific Islanders and for American Indians and

Alaska Natives.

From 2002 to 2005, in multivariate models controlling for race, ethnicity, gender, income, education,

insurance, and residence location:

◆ Blacks had 0.9 times the odds and Asians had 1.1 times the odds of being uninsured all year

compared with Whites (Figure 3.5).

◆ Hispanics had 2.5 times the odds of being uninsured all year compared with non-Hispanic Whites.

◆ Poor individuals had 5.8 times the odds of being uninsured all year compared with high-income

individuals.

◆ Females had 0.6 times the odds of being uninsured all year compared with males.

◆ Individuals within nonmetropolitan areas had 1.1 times the odds of being uninsured all year

compared with individuals within metropolitan areas.

Usual Source of Care

People with a usual source of care (a facility where one regularly receives care) experience improved

health outcomes and reduced disparities (smaller differences between groups)9 and costs,10 yet more than

40 million Americans do not have a specific source of ongoing care.11

Specific Source of Ongoing Care

Higher costs, poorer outcomes, and greater disparities (larger differences between groups) are observed

among individuals without a usual source of care.12

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Chapter 3

Non-Hispanic White

Odds Ratio

Non-Hispanic Black

Poor

Non-Hispanic White

Asian

<High School

High School Grad

Some College

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

Near Poor

Middle Income

High Income

Hispanic

Female

Male

Metropolitan

Nonmetropolitan

Poor
Figure 3.6. People with a specific source of ongoing care, by race (top left), ethnicity (top right),

income (bottom left), and education (bottom right), 1999-2006

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50

60

70

80

90

100

White

Black

Asian

>1 Race

AI/AN

Percent

2001

2002

0

Z

1999

2000

2003

2004

2005

2006

Healthy People 2010

Target: 96%

50

60

70

80

90

100

Percent

Hispanic Non-Hispanic White

0

Z

2000

2001

2002

2002

2003

2004

2005

2006

Healthy People 2010

Target: 96%

50

60

70

80

90

100 Percent

Near Poor High Income

Poor Middle Income

1999

0

Z

2000

2001

2002

2003

2004

2005

2006

Healthy People 2010

Target: 96%

50

60

70

80

90

100 Percent

High School Grad

At Least

Some College

<High School

1999

0

Z

2000

2001

2002

2003

2004

2005

2006

Healthy People 2010

Target: 96%
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 1999-

2006.

Reference population: 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. Data were insufficient for this analysis for Native Hawaiians and Other Pacific Islanders.

◆ From 1999 to 2006, the gap in usual source of care between Hispanics and non-Hispanic Whites

increased (Figure 3.6). In 2006, the percentage of people with a specific source of ongoing care was

significantly lower for Hispanics than for non-Hispanic Whites (74.3% compared with 88.8%).

◆ During this period, the gap between poor people and high-income people remained the same. In

2006, the percentage of people with a specific source of ongoing care was significantly lower for

poor people than for high-income people (77.8% compared with 91.7%).

◆ No group has yet achieved the Healthy People 2010 target of 96% of Americans with a specific

source of ongoing care.

Usual Primary Care Provider

Having a usual primary care provider (a doctor or nurse from whom one regularly receives care) is

associated with patients’ greater trust in their provider13 and with good patient-provider communication.

These factors increase the likelihood that patients will receive appropriate care.14 By learning about

patients’ diverse health care needs over time, a usual primary care provider can coordinate care (e.g.,

visits to specialists) to better meet patients’ needs.15 Indeed, having a usual primary care provider

correlates with receipt of higher quality care.16,17

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Chapter 3
Figure 3.7. People with a usual primary care provider, by race (top left), ethnicity (top right),

income (bottom left), and education (bottom right), 2002-2005

Key: AI/AN = American Indian or Alaska Native.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2005.

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Chapter 3

50

60

70

80

90

100

White

Total

Asian >1 Race

AI/AN

Percent

2002

0

Z

2003

2004

2005

Black

Healthy People 2010

Target: 85%

50

60

70

80

90

100

Percent

Non-Hispanic White

Hispanic

0

Z

2002

2003

2004

2005

Healthy People 2010

Target: 85%

50

60

70

80

90

100 Percent

Near Poor High Income

Poor Middle Income

0

Z

2002

2003

2004

2005

Healthy People 2010

Target: 85%

50

60

70

80

90

100 Percent

High School Grad

At least

Some College

<High School

0

Z

2002

2003

2004

2005

Healthy People 2010

Target: 85%
Reference population: 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. Data are age adjusted. Data were insufficient for this analysis for

Native Hawaiians and Other Pacific Islanders.

◆ From 2002 to 2005, the gap between Asians and Whites remained the same. In 2005, Asians were

less likely than Whites to have a usual primary care provider (70.2% compared with 77.5%; Figure

3.7).

◆ The gap between Hispanics and non-Hispanic Whites remained the same. In 2005, the percentage

of people with a usual primary care provider was significantly lower for Hispanics than for nonHispanic Whites (64.6% compared with 80.4%).

◆ The gap between poor people and high-income people remained the same. In 2005, the proportion

of people with a usual primary care provider was significantly lower for poor people than for highincome people (70.4% compared with 81.1%).

◆ The gap between people with less than a high school education and people with some college

remained the same. In 2005, the proportion of people with a usual primary care provider was

significantly lower for people with less than a high school education than for people with some

college (66.5% compared with 74.9%).

◆ No group has yet achieved the Healthy People 2010 target of 85% of Americans with a usual

primary care provider.

Each year, multivariate analyses are conducted in support of the NHDR to identify the independent

effects of race, ethnicity, and SES on access to health care. Past reports have listed some of these

findings. Figure 3.8 shows the results of a multivariate model for people who have a usual primary care

provider. Adjusted odds ratios are shown to quantify the relative magnitude of disparities after controlling

for a number of confounding factors.

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Chapter 3
Figure 3.8. People ages 18-64 with a usual primary care provider: Adjusted odds ratios,

2002-2005

Key: = reference group.

Source: Agency for Healthcare Research and

Quality, Medical Expenditure Panel Survey, 2002-

2005.

Reference population: Civilian noninstitutionalized

population ages 18-64.

Note: Adjusted odds ratios are calculated from

logistic regression models controlling for race,

ethnicity, income, education, age, gender, insurance,

and residence location. White, male, non-Hispanic

White, high income, some college, private insurance,

and metropolitan are reference groups with odds

ratio = 1; odds ratios <1 indicate that a group is less

likely to receive service than the reference group.

For example, compared with individuals with private

insurance, individuals with no insurance had 0.3

times the odds of reporting a usual primary care

provider after controlling for other factors. Data were

insufficient for this analysis for Native Hawaiians and

Other Pacific Islanders and for American Indians and

Alaska Natives.

From 2002 to 2005, in multivariate models controlling for race, gender, ethnicity, income, education,

insurance, and residence location:

◆ Blacks had 0.9 times the odds and Asians had 0.7 times the odds of having a usual primary care

provider compared with Whites (Figure 3.8).

◆ Females had 1.7 times the odds of having a usual primary care provider compared with males.

◆ Hispanics had 0.6 times the odds of having a usual primary care provider compared with nonHispanic Whites.

◆ Poor individuals had 0.7 times the odds of having a primary care provider compared with highincome individuals.

◆ Individuals with no health insurance had 0.3 times the odds of having a usual primary care provider

compared with individuals with private insurance.

◆ Individuals within nonmetropolitan areas had 1.2 times the odds of having a usual primary care

provider compared with individuals within metropolitan areas.

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Chapter 3

Odds Ratio

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

White

Black

Poor

Non-Hispanic White

Asian

<High School

High School Grad

Some College

Near Poor

Middle Income

High Income

Hispanic

Female

Male

Metropolitan

Nonmetropolitan

No Insurance

Public Only

Private Insurance
Patient Perceptions of Need

Patient perceptions of need include perceived difficulties or delays in obtaining care and problems getting

care as soon as it is wanted. Although patients may not always be able to assess their need for care,

problems getting care when patients perceive that they are ill or injured likely reflect significant barriers

to care.

Figure 3.9. People who were unable to get or delayed in getting needed medical care, dental

care, or prescription medicines in the last 12 months, by race, ethnicity, income, education, and

insurance status, 2005

Source: Agency for Healthcare Research and

Quality, Medical Expenditure Panel Survey, 2005.

Denominator: Analyses by race, ethnicity, income,

and insurance performed for civilian

noninstitutionalized population, all ages. Analyses by

education performed for civilian noninstitutionalized

population age 18 and over.

◆ The percentage of people who were unable to get or delayed in getting needed medical care, dental

care, or prescription medicines was higher for Blacks and people of multiple race than for Whites

(73.1% and 81.8% respectively, compared with 64.2%; Figure 3.9) and higher for Hispanics than for

non-Hispanic Whites (83.3% compared with 61.2%).

◆ The percentage of people who were unable to get or delayed in getting needed medical care, dental

care, or prescription medicines was significantly higher for poor (78.0%), near-poor (79.6%), and

middle-income (65.3%) people than for high-income people (44.2%).

◆ The percentage of people who were unable to get or delayed in getting needed medical care, dental

care, or prescription medicines was almost two times higher for people with no health insurance than

for people with private insurance (91.1% compared with 57.2%).

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Chapter 3

Percent

0

10

20

30

40

50

60

70

80

90

100

White

Black

Poor

Non-Hispanic White

Total

<High School

High School Grad

Some College

Near Poor

Middle Income

High Income

>1 Race

Hispanic

Any Private Insurance

Uninsured

Public Insurance Only
Health Care Utilization

Measures of health care utilization complement patient reports of barriers to care and permit a fuller

understanding of access to care. Barriers to care that are associated with differences in health care

utilization may have a more significant impact on health care quality than other factors. Landmark

reports on disparities have relied on measures of health care utilization,1,18 and these data demonstrate

some of the largest differences in care among diverse groups. More recent efforts to inform health care

delivery continue to include measures of health care utilization.19

Interpreting health care utilization data is more complex than analyzing data on patient perceptions of

access to care. Along with access to care, health care utilization is strongly affected by health care need

and patient preferences and values. In addition, greater use of services does not necessarily indicate

better care. In fact, high use of some inpatient services may reflect impaired access to outpatient services.

Tables 3.1a and 3.1b summarize facilitators and barriers to care for various racial, ethnic, and

socioeconomic groups. Tables 3.2a and 3.2b summarize findings on all core measures related to health

care utilization. Because of the many factors that affect health care utilization, the key to symbols used in

Tables 3.2a and 3.2b is different from that used for Tables 3.1a and 3.1b. Rather than indicating better or

worse access compared with the comparison group, symbols on the utilization tables simply identify the

amount of care received by racial or ethnic minority and socioeconomic groups relative to their

comparison groups.

In 2006, the Nation’s 14 million health services workers20 provided about 960 million office visits21 and

673 million hospital outpatient visits22 and treated 37 million hospitalized patients23 and 1.4 million

nursing home residents.23 About 70% of the civilian noninstitutionalized population visit a medical

provider’s office or outpatient department, about 60% receive a prescription medicine, and about 40%

visit a dental provider each year.24

National health expenditures totaled over $2 trillion in fiscal year 2006, nearly double those of a decade

earlier.25 Health expenditures among the civilian noninstitutionalized population in America are

extremely concentrated, with 5% of the population accounting for 55% of outlays.26 In addition, a study

using earlier data estimated that as much as $420 billion a year—almost one-third of all health care

expenditures—are the result of low-quality care, including overuse, misuse, and waste.27

Previous NHDRs reported that different racial, ethnic, and socioeconomic groups had different patterns of

health care utilization. Asians and Hispanics tended to have lower use of most health care services,

including routine care, emergency department visits, avoidable admissions, and mental health care.

Blacks tended to have lower use of routine care, outpatient mental health care, and outpatient HIV care.

Blacks had higher use of emergency departments and hospitals, including higher rates of avoidable

admissions, inpatient mental health care, and inpatient HIV care. Individuals with lower SES tended to

have lower use of routine care and outpatient mental health care and higher use of emergency

departments, hospitals, and home heath care. In this section, findings related to dental care, emergency

department visits, potentially avoidable admissions, and mental health care and substance abuse treatment

are highlighted.

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Chapter 3
Dental Visits

Regular dental visits promote prevention, early diagnosis, and optimal treatment of oral diseases and

conditions. Failure to visit the dentist can result in delayed diagnosis, overall compromised health, and,

occasionally, even death.28

Figure 3.10. People who had a dental visit in the calendar year, by race (top left), ethnicity (top

right), and income (bottom left), 2002-2005

Key: AI/AN = American Indian or Alaska Native; NHOPI = Native

Hawaiian or Other Pacific Islander.

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Analyses by race, ethnicity, and income

performed for civilian noninstitutionalized population, all ages.

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Chapter 3

0

10

20

30

40

50

60

70

80

90

100 White

Black

Asian

NHOPI >1 Race

AI/AN

Percent

2002

2003

2004

2005

Healty People 2010

Target: 56%

0

10

20

30

40

50

60

70

80

90

100

Percent

Non-Hispanic White

Hispanic

2002

2003

2004

2005

Healty People 2010

Target: 56%

0

10

20

30

40

50

60

70

80

90

100

Percent

Near Poor High Income

Poor Middle Income

2002

2003

2004

2005

Healty People 2010

Target: 56%
◆ There were no statistically significant changes in the percentage of people with a dental visit in the

calendar year from 2002 to 2005 across racial, ethnic, or income categories (Figure 3.10).

◆ From 2002 to 2005, the gap between Blacks and Whites in the percentage of people with a dental

visit in the calendar year remained the same. In 2005, the percentage was significantly lower for

Blacks than for Whites (30.5% compared with 45.7%).

◆ During the same period, the gap between Hispanics and non-Hispanic Whites remained the same. In

2005, the percentage was significantly lower for Hispanics than for non-Hispanic Whites (27.8%

compared with 49.5%).

◆ In 2005, the gap between poor people and high-income people remained the same. The percentage

was significantly lower for poor (27.1%), near-poor (29.7%), and middle-income people (41.5%)

than for high-income people (56.9%).

◆ Only high-income people met the Healthy People 2010 target of 56% of people with a dental visit in

the past year.

To distinguish the effects of race, ethnicity, and SES status on health care utilization and to identify

populations at greatest risk for barriers to health care utilization, this measure is stratified by income.

Figure 3.11. People who had a dental visit in the calendar year, by race (left) and ethnicity (right),

stratified by income, 2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population, all ages.

Note: Data were insufficient for this analysis for Native Hawaiians and Other Pacific Islanders and for American Indians and Alaska

Natives.

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Chapter 3

0

25

50

75

100

Percent

White

Black

Poor Near

Poor

Middle

Income

High

Income

Asian

0

25

50

75

100

Percent

Non-Hispanic White

Hispanic

Poor Middle

Income

Near

Poor

High

Income
◆ SES explains some, but not all, of the racial and ethnic differences in rates of dental visits

(Figure 3.11).

◆ In all income categories, Blacks were significantly less likely than Whites to have had a dental visit

in the calendar year (poor, 22.8% for Blacks versus 29.1% for Whites; near poor, 25.2% for Blacks

versus 30.7% for Whites; middle income, 32.3% for Blacks versus 43.0% for Whites; and high

income, 43.1% for Blacks versus 58.7% for Whites).

◆ Hispanics at every income level were significantly less likely than non-Hispanic Whites to have had

a dental visit (poor, 22.9% of Hispanics versus 32.3% of non-Hispanic Whites; near poor, 20.8% of

Hispanics versus 34.9% of non-Hispanic Whites; middle income, 29.5% of Hispanics versus 45.8%

of non-Hispanic Whites; high income, 43.1% of Hispanics versus 60.0% of non-Hispanic Whites).

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Chapter 3
Emergency Department Visits

Without good access to health care, people sometimes resort to using the emergency department (ED)

when care is needed. A high rate of ED visits may suggest that a population lacks access to preventive

and routine care and other avenues of treatment. Delaying care until care is urgent often results in poorer

health outcomes and increased health care costs.

Figure 3.12. Emergency department visits per 100 population in the calendar year, by race,

1997-1998, 1999-2000, 2001-2002, 2003-2004, and 2005-2006

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Hospital Ambulatory Medical

Care Survey, 1997-1998, 1999-2000, 2001-2002, 2003-2004, and

2005-2006.

Denominator: Civilian noninstitutionalized population, all ages.

Note: Data did not meet criteria for statistical reliability for Asians

(for data years 1997-1998, 1999-2000, and 2003-2004) and Native

Hawaiians and Other Pacific Islanders.

◆ From 1997-1998 to 2005-2006, the rate of ED visits remained the same except for Blacks (Figure

3.12).

◆ During this period, the gap between Blacks and Whites increased. In 2005-2006, the rate of ED

visits was more than twice as high for Blacks as for Whites (74.5 per 100 population compared with

36.5 per 100 population).

◆ In 2005-2006, the rate of ED visits was lower for Asians than for Whites (17.7 per 100 population

compared with 36.5 per 100 population).

◆ In 2005-2006, the rate of ED visits was higher for females than for males (42.5 per 100 population

compared with 37.5 per 100 population; data not shown).

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Chapter 3

0

25

50

75

White

1997-1998

1999-2000

ED visits per 100 persons

2001-2002

Total

2003-2004

Asian

Black

2005-2006
Potentially Avoidable Admissions

Potentially avoidable admissions are hospitalizations that might have been averted by good outpatient

care. They relate to conditions for which good outpatient care can prevent the need for hospitalization or

for which early intervention can prevent complications or more severe disease. Although all admissions

for these conditions cannot be avoided, rates in populations tend to vary with access to primary care.29

For example, better access to care should reduce the percentage of appendicitis admissions in which

rupture has already occurred.

Figure 3.13. Perforated appendixes per 1,000 admissions with appendicitis, by race/ethnicity

(left) and area income (median income of ZIP Code of residence) (right), 2001-2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases (SID)

disparities analysis file, 2001-2005.

Denominator: Patients hospitalized with appendicitis, age 18 and over.

Note: White, Black, and API are non-Hispanic groups. Numeric income categories are used instead of the NHDR’s usual descriptive

categories because that is how data are collected for this measure. Income categories are based on the median household income of

the ZIP Code of the patient’s residence. The HCUP SID disparities analysis file is designed to provide national estimates using

weighted records from a sample of hospitals from 23 States that have 64% of the U.S. resident population. Data for American Indians

and Alaska Natives from NPIRS can be found in Chapter 4 but is not collected by this data source.

◆ From 2001 to 2005, the gap between Blacks and Whites in the rate of hospital admissions for

perforated appendix decreased (Figure 3.13). In 2005, Blacks had a higher rate than Whites (317.3

per 1,000 compared with 282.7 per 1,000).

◆ In 2005, APIs and Whites were not significantly different in the rate of hospital admissions for

perforated appendix.

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Chapter 3

200

250

300

350

400

White

Black

2001

2003

Rate

2002

API

Hispanic

0

Z

2004

Total

2005

200

250

300

350

400 <$25,000

$25,000-$34,999

2001

2003

Rate

2002

0

Z

$35,000-$44,999

$45,000+

2004

2005
◆ The gap between Hispanics and non-Hispanic Whites was eliminated. In 2005, there was no

statistically significant difference between Hispanics and Whites (283.2 per 1,000 compared with

282.7 per 1,000).

◆ From 2001 to 2005, the gap between people living in poor communities and those living in highincome communities in the rate of hospital admissions for perforated appendix increased. In 2005,

people living in poor communities had a higher rate than those living in high-income communities

(308.8 per 1,000 compared with 265.8 per 1,000).

Mental Health Care and Substance Abuse Treatment

Mental Health Care

Although the prevalence of mental disorders for racial and ethnic minorities in the United States is similar

to that for Whites,30 minorities have less access to mental health care and are less likely to receive needed

services.31 These differences may reflect, in part, variation in preferences and cultural attitudes toward

mental health.32

Figure 3.14. Adults who received mental health treatment or counseling in the last 12 months,

by race (left), ethnicity (right), and education (next page top left), 2003-2006

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Chapter 3

0

5

10

15

20

25

White

Black

Asian >1 Race

AI/AN

Percent

2003

2004

2005

Total

2006

0

5

10

15

20

25

Percent

Non-Hispanic White

Hispanic

2003

2004

2005

2006
Key: AI/AN = American Indian or Alaska Native.

Source: Substance Abuse and Mental Health Services

Administration, National Survey on Drug Use and Health, 2003-

2006.

Reference population: U.S. population age 18 and over.

Note: Data were insufficient for this analysis for Native Hawaiians

and Other Pacific Islanders.

◆ From 2003 to 2006, the gap between Blacks and Whites remained the same (Figure 3.14). In 2006,

Blacks were significantly less likely than Whites to receive mental health treatment or counseling

(7.4% compared with 14.0%).

◆ In 2006, there was no statistically significant difference between AI/ANs and Whites.

◆ The gap between Asians and Whites in the percentage of people who received mental health

treatment or counseling remained the same. In 2006, the percentage of Asians was less than half

that of Whites (5.6% compared with 14.0%).

◆ The gap between Hispanics and non-Hispanic Whites remained the same. In 2006, the percentage

of Hispanics was less than half that of non-Hispanic Whites (7.0% compared with 15.2%).

◆ The gap in mental health service use between people with less than a high school education and

people with some college education remained the same. In 2006, the percentage was lower for

people with less than a high school education (10.9%) and for people with a high school education

(11.8%) than for people with some college education (14.2%).

◆ In 2006, there were no statistically significant differences between people of different income levels

in the receipt of mental health treatment or counseling (data not shown).

Substance Abuse Treatment

In 2006, about 17 million Americans age 12 and over acknowledged being heavy alcohol drinkers, and

about 57 million acknowledged having had a recent binge drinking episode.32 About 20.4 million people

age 12 and over were illicit drug users, and about 72.9 million reported recent use of a tobacco product.33

In 2001, an estimated $18 billion was devoted to treatment of substance use disorders. This amount

constituted 1.3% of all health care spending.33

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Chapter 3

Percent

High School Grad

<High School Some College

2003

2004

2005

0

5

10

15

20

25

2006
Racial, ethnic, and socioeconomic differences in substance abuse treatment32 may, in part, reflect

variation in preferences and cultural attitudes toward mental health and substance abuse.

Figure 3.15. People age 12 and over who received any treatment for illicit drug or alcohol abuse

in the last 12 months, by race (top left), ethnicity (top right), and education (bottom left),

2003-2006

Key: AI/AN = American Indian or Alaska Native; NHOPI = Native

Hawaiian or Other Pacific Islander.

Source: Substance Abuse and Mental Health Services

Administration, National Survey on Drug Use and Health, 2003-

2006.

Reference population: U.S. population age 12 and over.

Note: The figure reflects both prevalence and treatment; variations

in prevalence likely have an effect on racial and ethnic differences

in treatment.

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Chapter 3

0

1

2

3

4

5 White

Black

AI/AN

Percent

2003

2004

2005

Total Asian

NHOPI

2006

Percent

High School Grad

<High School Some College

2003

2004

2005

0

1

2

3

4

5

2006

0

1

2

3

4

5

Percent

Non-Hispanic White

Hispanic

2003

2004

2005

2006
◆ From 2003 to 2006, the gap between AI/ANs and Whites in the percentage of people age 12 and

over who received any treatment for illicit drug or alcohol abuse remained the same (Figure 3.15).

In 2005, the percentage was more than two times higher for AI/ANs than for Whites (3.8%

compared with 1.6%).

◆ During this period, the gap between Asians and Whites in the percentage of people age 12 and over

who received drug or alcohol abuse treatment remained the same. In 2006, the percentage of people

age 12 and over who received any treatment for illicit drug or alcohol abuse was lower for Asians

than for Whites (0.4% compared with 1.6%).

◆ During this period, there were no significant differences between Hispanics and non-Hispanic

Whites.

◆ The gap between people with less than a high school education and people with some college

education increased. In 2006, the percentage was more than two times higher for people with

less than a high school education than for people with some college education (3.2% compared

with 1.1%).

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Chapter 3
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Chapter 3

Table 3.1a. Racial and Ethnic Differences in Facilitators and Barriers to Health Care

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

Health Insurance Coverage

People under age 65 with health

insuranceiii = = = =

People under age 65 who were

uninsured all yeariv = = =

Usual Source of Care

People with a specific source of

ongoing careiii = = =

People with a usual primary care

provideriv = =

People without a usual source of care

who indicated a financial or insurance

reason for not having a source of careiv = =

Patient Perceptions of Need

People who were unable to get or

delayed in getting needed careiv

People unable to get or

delayed in getting needed care due to

financial or insurance reasonsiv = =

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iii Source: National Health Interview Survey, 2006.

iv Source: Medical Expenditure Panel Survey, 2005.

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

Key to Symbols Used in Access to Health Care Tables:

= Group and comparison group have about same access to health care.

Group has better access to health care than the comparison group.

Group has worse access to health care than the comparison group.

Blank cell: Reliable estimate for group could not be made.

➔

➔

➔

➔

➔➔

➔➔➔

➔➔

➔

➔➔

➔➔➔

➔➔
Table 3.1b. Socioeconomic Differences in Facilitators and Barriers to Health Care

Core Report Measure Income Educational Insurance

Differencei Differenceii Differenceiii

<100% 100-199% 200-399% <HS HS Grad Uninsured

Health Insurance Coverage

People under 65 with health insuranceiv

People under age 65 who were

uninsured all yearv

Usual Source of Care

People with a specific source of

ongoing careiv

People with a usual primary care

providerv =

People without a usual source of care

who indicated a financial or insurance

reason for not having a source of careiv =

Patient Perceptions of Need

People who were unable to get or

delayed in getting needed care v

People unable to get or

delayed in getting needed care due to =

financial or insurance reasonsv

i Compared with persons with family incomes 400% of Federal poverty thresholds or above.

ii Compared with persons with any college education.

iii Compared with persons under 65 with any private health insurance.

iv Source: National Health Interview Survey, 2006.

v Source: Medical Expenditure Panel Survey, 2005.

Key: HS=High school.

Key to Symbols Used in Access to Health Care Tables:

= Group and comparison group have about same access to health care.

Group has better access to health care than the comparison group.

Group has worse access to health care than the comparison group.

Blank cell: Reliable estimate for group could not be made.

➔➔➔

➔

➔

➔

➔

➔➔

➔

➔➔

➔➔

➔

➔➔➔

➔➔

➔

➔➔

➔➔

➔

➔➔➔

➔➔

➔

➔➔

➔➔

➔

➔➔

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Chapter 3
Table 3.2a. Racial and Ethnic Differences in Health Care Utilization

Core Report Measure Racial Differencei Ethnic

Differenceii

Black Asian NHOPI AI/AN >1 Race Hispanic

General Medical Care

People who had a dental visit in the

calendar yeariii =

Avoidable Admissions

Perforated appendixes per

1,000 admissions with appendicitisv = = =

Mental Health Care and Substance Abuse Treatment

Adults who received mental health

treatment or counseling in the last

12 monthsv = = = =

People age 12 and older who received

any treatment for illicit drug or alcohol == =

abuse in the last 12 monthsv

i Compared with Whites.

ii Compared with non-Hispanic Whites.

iiiSource: Medical Expenditure Panel Survey, 2005.

iv Source: HCUP SID disparities analysis file, 2005. This source categorizes race/ethnicity very differently from other sources. Race/ethnicity information

is categorized as a single item: Non-Hispanic White, Non-Hispanic Black, Hispanic, Asian or Pacific Islander. These contrasts compare each group with

non-Hispanic Whites.

v Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2006.

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

Key to Symbols Used in Health Care Utilization Tables:

= Group and comparison group receive about same amount of health care.

Group receives more health care than the comparison group.

Group receives less health care than the comparison group.

Blank cell: Reliable estimate for group could not be made.

➔

➔

➔

➔➔

➔

➔➔➔➔➔

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Chapter 3
Table 3.2b. Socioeconomic Differences in Health Care Utilization

Core Report Measure Income Educational Insurance

Differencei Differenceii Differenceiii

<100% 100-199% 200-399% <HS HS Grad Uninsured

General Medical Care

People who had a dental visit in the

calendar yeariv

Avoidable Admissions

Perforated appendixes per

1,000 admissions with appendicitis

Mental Health Care and Substance Abuse Treatment

Adults who received mental health

treatment or counseling in the last

12 monthsv == == =

Persons age 12 and older who received

any treatment for illicit drug or alcohol

abuse in the last 12 monthsv = =

i Compared with persons with family incomes 400% of Federal poverty threshold or above.

ii Compared with persons with any college education.

iii Compared with persons under 65 with any private health insurance.

iv Source: Medical Expenditure Panel Survey, 2005.

v Source: Substance Abuse and Mental Health Services Administration, National Survey on Drug Use and Health, 2006. Insurance disparities

were not analyzed.

Key: HS=high school.

Key to Symbols Used in Health Care Utilization Tables:

= Group and comparison group receive about same amount of health care.

Group receives more health care than the comparison group.

Group receives less health care than the comparison group.

Blank cell: Reliable estimate for group could not be made.

➔

➔

➔➔

➔

➔➔

➔

➔

➔➔

➔

➔➔➔

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Chapter 3
References

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6. Jacoby MB, Sullivan TA, Warren E. Medical problems and bankruptcy filings. Norton Bankruptcy Law Adviser 2000

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7. Hadley J. Sicker and poorer: the consequences of being uninsured. Paper prepared for the Kaiser Commission on Medicaid

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10. De Maeseneer JM, De Prins L, Gosset C, et al. Provider continuity in family medicine: does it make a difference for total

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11. U.S. Department of Health and Human Services. Healthy People 2010, 2nd ed. With Understanding and improving health and

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United States and the United Kingdom. Fam Med 2001 Jan;33(1):22-7.

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16. Parchman ML, Burge SK. Residency Research Network of South Texas investigators. Continuity and quality of care in type 2

diabetes: a Residency Research Network of South Texas study. J Fam Pract 2002 Jul;51(7):619-24.

17. Inkelas M, Schuster MA, Olson LM, et al. Continuity of primary care clinician in early childhood. Pediatrics 2004 June;113(6

Suppl):1917-25.

18. U.S. Department of Health and Human Services. Report of the Secretary’s Task Force on Black and Minority Health.

Washington, DC: DHHS; 1985.

19. Swift EK, ed. Institute of Medicine, Committee on Guidance for Designing a National Healthcare Disparities Report.

Guidance for the National Healthcare Disparities Report. Washington, DC: National Academies Press; 2002. p. 20.

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20. Table 105: Persons employed in health service sites, by sex: United States, selected years 2000-2006. In: National Center for

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for Disease Control and Prevention; 2007. Available at: http://www.cdc.gov/nchs/data/hus/hus07.pdf. Accessed September 18,

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21. Table 92: Visits to physician offices and hospital outpatient and emergency departments, by selected characteristics: United

States, selected years 1995-2005. In: National Center for Health Statistics. Health, United States, 2007. With chartbook on

trends in the health of Americans. Hyattsville, MD: Centers for Disease Control and Prevention; 2007. Available at:

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22. Table 103: Hospital admissions, average length of stay, outpatient visits, and outpatient surgery by type of ownership and size

of hospital: United States, selected years 1975-2005. In: National Center for Health Statistics. Health, United States, 2007.

With chartbook on trends in the health of Americans. Hyattsville, MD: Centers for Disease Control and Prevention; 2007.

Available at: http://www.cdc.gov/nchs/data/hus/hus07.pdf. Accessed September 18, 2008.

23. Table 104: Nursing homes, beds, occupancy, and residents, by geographic division and State: selected years 1995-2005. In:

National Center for Health Statistics. Health, United States, 2007. With chartbook on trends in the health of Americans.

Hyattsville, MD: Centers for Disease Control and Prevention; 2007. Available at: http://www.cdc.gov/nchs/data/hus/hus07.pdf.

Accessed September 18, 2008.

24. Krauss N, Machlin S, Kass BL. Use of health care services, 1996. Rockville, MD: Agency for Health Care Policy and

Research, 1999. MEPS Findings No. 7, AHCPR Publication No. 99-0018.

25. Office of the Actuary. National health expenditure data/historical. Baltimore: Centers for Medicare & Medicaid Services.

Available at: http://www.cms.hhs.gov/NationalHealthExpendData/downloads/tables.pdf. Accessed September 18, 2008.

26. Berk ML, Monheit AC. The concentration of health care expenditures, revisited. Health Aff 2001 Mar-Apr;20(2):9-18.

27. Reducing the costs of poor-quality health care through responsible purchasing leadership. Chicago: Midwest Business Group

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October 30, 2007.

28. Fryer GE, Dovey SM, Green LA. The importance of having a usual source of health care. One-Pager Number 2. Washington,

DC: The Robert Graham Center: Policy Studies in Family Practice and Primary Care; January 2000. Available at:

http://www.graham-center.org/online/graham/home/publications/onepagers/2000/op2-usual-source.html. Accessed October 30,

2007.

29. Oster A, Bindman AB. Emergency department visits for ambulatory care sensitive conditions: insights into preventable

hospitalizations. Med Care 2003 Feb;41(2):198-207.

30. Office of Applied Studies. The NSDUH report: co-occurring major depressive episode (MDE) and alcohol use disorder among

adults. Rockville, MD: Substance Abuse and Mental Health Services Administration; February 2007. Available at:

http://www.oas.samhsa.gov/2k7/alcDual/alcDual.cfm. Accessed May 30, 2007.

31. Center for Mental Health Services. Mental health: culture, race and ethnicity—a supplement to Mental Health: Report of the

Surgeon General. Executive Summary. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2001.

Available at: http://mentalhealth.samhsa.gov/cre/default.asp.

32. Office of Applied Studies. Results from the 2006 National Survey on Drug Use and Health: national findings. Rockville, MD:

Substance Abuse and Mental Health Services Administration; 2007. NSDUH Series H-32, DHHS Publication No. SMA 07-

4293. Available at: http://www.oas.samhsa.gov/NSDUH/2K6NSDUH/2K6results.cfm.

33. Mark T, Coffey RM, McKusick D, et al. National expenditures for mental health services and substance abuse treatment, 1991-

2001. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2005. DHHS Publication No. SMA 05-

3999. Available at: http://www.samhsa.gov/spendingestimates/SEPGenRpt013105v2BLX.pdf. Accessed on July 31, 2007.

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170
C h a p t e r 4 .

P r i o r i t y Po p u l a t i o n s

To examine the issue of disparities in health care, Congress directed the Agency for Healthcare Research

and Quality (AHRQ) to produce an annual report to track “prevailing disparities in health care delivery as

it relates to racial factors and socioeconomic factors in priority populations.” Although the emphasis is on

disparities related to race, ethnicity, and socioeconomic status, this directive includes a charge to examine

disparities in “priority populations,” which are groups with unique health care needs or issues that require

special attention.

This chapter addresses the congressional directive on priority populations.i Chapters 2 and 3 of this

report examine racial, ethnic, and socioeconomic differences in quality of health care and access to health

care in the general U.S. population. This chapter focuses on differences within and across priority

populations. For example, comparisons are made between Black and White women and between children

from low- and high-income families. This year, the National Healthcare Disparities Report’s (NHDR)

section on low-income groups focuses on examining differences in quality of care and access to care by

insurance status.

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. Appendix D 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 The congressional mandate for the National Healthcare Disparities Report also identifies populations living in innercity areas as a priority population. However, currently no data are available to support findings for this population.

National Quality Report, 2000

Priority Populations Staying Healthy

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Chapter 4
AHRQ’s Priority Populations

AHRQ’s priority populations, specified by Congress in the Healthcare Research and Quality Act of 1999

(Public Law 106-129), are:

◆ Racial and ethnic minority groups.ii

◆ Low-income groups.iii

◆ Women.

◆ Children (age 0-17).

◆ Older adults (age 65 and over).

◆ Residents of rural areas.iv

◆ Individuals with special health care needs,v including individuals with disabilities and individuals

who need chronic care or end-of-life care.

How This Chapter Is Organized

This chapter provides the most recent information available on racial, ethnic, and income differences in

quality and access for priority populations. It is presented in the following order:

◆ Racial and ethnic minorities.

◆ Low-income groups (focus on uninsured people).

◆ Women.

◆ Children.

◆ Older adults.

◆ Residents of rural areas.

◆ Individuals with disabilities or special health care needs.

ii Racial categories include White, Black, Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska

Native, and more than one race. Ethnic categories are Hispanic or Latino, non-Hispanic White, and non-Hispanic

Black.

iii In the NHDR, low income refers to poor people. 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 2005 the Federal poverty threshold for a family of two adults and two children was $19,806.

iv 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. Data for

metropolitan and micropolitan areas are used for comparisons with noncore areas.

v Individuals with special health care needs include children with special health care needs, defined as those 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 Quality Report, 2000

Staying Healthy Priority Populations

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Chapter 4
To avoid repetition of from previous chapters’ findings on race, ethnicity, and socioeconomic status, the

first two sections summarize quality of and access to health care for racial and ethnic minorities and lowincome groups. Subsequent sections focus on the remaining priority populations and examine disparities

in care within each population group and changes in disparities over time. To present this greater detail,

some sections highlight a small number of measures that supplement the core measures presented in

Chapters 2 and 3. While these measures may not necessarily be the core measures presented each year,

they add detail to the picture of disparities that each population may face. Interagency Work Group

members and AHRQ experts on particular populations assisted in selecting measures for these priority

populations.

For smaller priority populations, measure selection was often driven by available sample sizes. When

possible, measures were selected to encompass multiple components of health care need, such as

preventive services, treatment of acute illness, management of chronic disease, and access to health care.

Results for all measures are found in the detailed appendix tables.

The measures discussed in this chapter are the following:

Section Measure

Blacks or African Americans

Asians

Native Hawaiians and Other Pacific Cholesterol screening

Islanders Influenza and pneumococcal vaccinations for older adults

Health insurance

American Indians and Alaska Natives

Hispanics or Latinos

Recent Immigrants and Limited-English- Tuberculosis therapy

Proficient Populations Poor communication with health providers

Health insurance

Language assistance

Low-Income Groups Focus on Colorectal cancer screening

Uninsurance Counseling parents about physical activity in children

Dental care

Women Pregnant women receiving prenatal care in the first trimester

Adults with obesity given advice about physical activity

Acute myocardial infarction mortality

New AIDS cases

Usual source of care

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Priority Populations Staying Healthy

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Chapter 4
Section Measure

Children Early childhood vaccinations

Counseling to parents about physical activity

Vision screening

Accidental puncture or laceration during procedure

Hospital admissions with perforated appendix

Health insurance

Older Adults Influenza vaccination

Vision screening

Delayed care due to cost

Health literacy

Residents of Rural Areas Pregnant women receiving prenatal care in the first trimester

Recommended services for diabetes

Recommended care for colorectal cancer

Care for illness or injury as soon as wanted

Health insurance

Individuals With Disabilities or Special Adults with disabilities

Health Care Needs Pneumococcal vaccination for adults age 65 and over

Private health insurance for adults ages 18-64

Source of ongoing care

Hospital, emergency room, or clinic as source of ongoing care

Children with special health care needs

Effective care coordination

Family-centered care

Health insurance

Adequacy of health insurance

It should be noted that this chapter does not provide a comprehensive assessment of health care

differences in each priority population. Most of the measures tracked in the NHDR were selected to be

applicable across many population groups. Only a few, such as immunizations among children, were

specific to particular groups.

These general measures overlook some important health care problems specific to particular populations.

For example, people with disabilities may face barriers in getting access to care and experience

differences in quality of care that are not captured by data because of the limitations in the survey

instruments. In addition, national data may not address key health issues for specific population groups,

and it is not always possible to generate reliable estimates for many smaller groups such as Native

Hawaiians and Other Pacific Islanders (NHOPIs) and American Indians and Alaska Natives (AI/ANs).

Instead, this chapter should be seen as a starting point, identifying some problem areas and indicating

gaps in current data and understanding.

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Chapter 4
Racial and Ethnic Minorities

In 2000, about 33% of the U.S. population identified themselves as members of racial or ethnic minority

groups.1 By 2050, it is projected that these groups will account for almost half of the U.S. population.

For 2007, the U.S. Census Bureau estimated that the United States had almost 38.8 million Blacks or

African Americans2 (12.9% of the U.S. population)3; more than 45.5 million Hispanics or Latinos

(15.1%)2; almost 13.4 million Asians (4.4%); more than 0.5 million NHOPIs (0.2%); and more than 2.9

million AI/ANs (1.0%), of whom 38% reside on Federal trust lands.4 Racial and ethnic minorities are

more likely than non-Hispanic Whites to be poor or near poor.5 In addition, Hispanics, Blacks, and some

Asian subgroups are less likely than non-Hispanic Whites to have a high school education.6

Previous chapters of the NHDR described health care differences by racialvi and ethnicvii categories as

defined by the Office of Management and Budget and used by the U.S. Census Bureau.7 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.viii 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 in differences related to race and ethnicity over time. For each core

report measure, racial, ethnic, and socioeconomic groups are compared with a designated comparison

group at different points in time. 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.

Core report measures (see Table 1.2) for which the relative differences are changing less than 1% per year

are identified as staying the same. Core report measures for which the relative differences are becoming

vi Races include Black or African American, Asian, Native Hawaiian or Other Pacific Islander, American Indian or

Alaska Native, White, and people of multiple races.

vii Ethnicity differentiates Hispanics and non-Hispanics. Among non-Hispanics, this report identifies non-Hispanic

Whites and non-Hispanic Blacks.

viii Data are presented for each minority group except for people of multiple races due to unreliable estimates for this

group.

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Chapter 4
smaller at a rate of 1% or more per year are identified as improving. Core report measures for which the

relative differences are becoming larger at a rate of 1% or more per year are identified as worsening.

Changes of greater than 5% per year are also differentiated from changes of between 1% and 5% per year

in some figures.

Gaps in Information

As in previous NHDRs, this section includes information on programs and issues that may affect racial

and ethnic disparities. The assessment of disparities AI/ANs face includes information on the

approximately 1.5 million individuals who obtain care from Indian Health Service (IHS) facilities and

tribal facilities that receive IHS funding.

In interpreting findings for racial and ethnic minorities, readers should note that considerable gaps in

information for some racial and ethnic minorities exist, which limit the NHDR’s ability to identify the

current state of disparities for some groups. Gaps can relate to insufficient data to produce reliable

estimates or, when estimates are possible, to inadequate power to detect large differences. For example,

of core report measures of quality, it is rarely possible to provide estimates for NHOPIs and people of

more than one race. For Asians, only about two-thirds of core report measures of quality support

analyses. For AI/ANs, only about half of these same measures support analyses. In addition, many data

sources changed racial classifications for Asians and NHOPIs in 2003 to adhere to new Federal standards.

This change has further constrained the ability to perform trend analyses for these groups. Chapter 1,

Introduction and Methods, and the summary section at the end of this report present more detailed

descriptions of current data limitations and ways in which data are gradually improving.

Below is a summary of the measures that identify opportunities for improvement. For all groups,

opportunities to improve health care quality and access exist.

Table 4.1. Percentage of core quality and access measures that are not improving for various

racial and ethnic groups

Group Reference group Percentage of core measures not improving (n = number of

measures that could be tracked)

Quality of care Access to care

Black White 77 (n = 35) 50 (n = 4)

Asian White 82 (n = 22) 60 (n = 5)

AI/AN White 67 (n = 15) 33 (n = 3)

Hispanic Non-Hispanic White 65 (n = 31) 50 (n = 4)

Key: AI/AN = American Indian or Alaska Native.

Note: “Not improving” is defined for quality measures as population received about the same or worse quality of care as Whites or

non-Hispanic Whites; and for access measures, as population had about the same or worse access to care as Whites or nonHispanic Whites. Percentages are based on a subset of core measures that have data for these groups. Some measures include

data for all ages and some are age-group specific. Refer to Measure Specifications and Data Tables appendixes for more information.

Baseline year and most recent year are not the same for all measures, depending on the data source.

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Chapter 4
For each racial or ethnic group, Table 4.2 highlights the core measures with gaps that are increasing (i.e.,

getting worse) for the group compared with its reference group.

Table 4.2. Core measures that are getting worse for group compared with reference group

Group Preventive Acute Chronic Patient Timeliness Patient

services illness disease safety centeredness Access

treatment management

Black Adults age Patients with Colorectal Adults age Adults Adults with People

vs. 50 and over tuberculosis cancer 65 and over who can poor with a

White who who diagnosed at who received sometimes or provider- usual

received completed advanced potentially never get care patient primary

colorectal treatment stage inappropriate for illness or communication care

cancer within 1 year prescription injury as soon provider

screening of initiation medicines as wanted

of treatment

Children Adults age 40

ages 2-17 and over with

for whom a diagnosed

health diabetes who

provider received all

ever gave three

advice recommended

about services

physical

activity

Adults age Hospital

65 and over admissions

who ever for lower

received extremity

pneumo- amputations

coccal per 1,000

vaccination population

age 18 and

over with

diabetes

Adult Adults with a

current major

smokers depressive

who episode who

received received

advice to treatment

quit for depression

smoking

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Chapter 4
Table 4.2. Core measures that are getting worse for group compared with reference group

Group Preventive Acute Chronic Patient Timeliness Patient

services illness disease safety centeredness Access

treatment management

Adult home

health care

patients

whose ability

to walk or

move around

improved

Asian Adults age Colorectal Adult surgery Adults who Adults with People

vs. 50 and over cancer patients can poor provider- with a

White who received diagnosed at who sometimes patient specific

colorectal advanced received or never communication source of

cancer stage appropriate get care for ongoing

screening timing of illness or injury care

antibiotics as soon as

wanted

Adults age Adult

65 and over hemodialysis

who ever patients

received with

pneumococcal adequate

vaccination dialysis

(urea reduction

ratio 65% or

higher)

Dialysis

patients who

were

registered on

a waiting list

for

transplantation

Short-stay

nursing home

residents with

pressure

sores

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Chapter 4
Table 4.2. Core measures that are getting worse for group compared with reference group

Group Preventive Acute Chronic Patient Timeliness Patient

services illness disease safety centeredness Access

treatment management

American Adults age Adult People

Indian 50 and over hemodialysis under age

or who patients with 65 who

Alaska received adequate were

Native colorectal dialysis (urea uninsured

vs. cancer reduction all year

White screening ratio 65%

or higher)

Long-stay

nursing home

residents with

physical

restraints

Adult home

health care

patients who

were admitted

to the hospital

Hispanic Adults age Patients with Adult Adults age

vs. non- 50 and over tuberculosis hemodialysis 65 and over

Hispanic who who complete patients who received

White received treatment with potentially

colorectal within 12 adequate inappropriate

cancer months of dialysis prescription

screening initiation of (urea medicines

treatment reduction ratio

65% or higher)

Adults age Adults with Adult surgery

65 and over obesity who patients who

who ever received received

received advice to appropriate

pneumococ- exercise timing of

cal more antibiotics

vaccination

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Chapter 4
Table 4.2. Core measures that are getting worse for group compared with reference group

Group Preventive Acute Chronic Patient Timeliness Patient

services illness disease safety centeredness Access

treatment management

Adults age 18

and over with

a major

depressive

episode who

received

treatment for

depression

Poor- Adults age Adults age 40 Adults who Adults with

high 50 and over and over with can poor

income who received diagnosed sometimes or providercolorectal diabetes who never get care patient

cancer received all for illness or communication

screening three recom- injury as soon

mended as wanted

services

Children People age 12 Children with People

ages 19-35 and over who poor provider- without

months who needed patient a usual

received all treatment communication source of

recommen- for illicit drug care who

ded vaccines use and who indicated a

received such financial or

treatment at a insurance

specialty reason

facility in the

last 12

months

Note: “Asian” includes “Asian or Pacific Islander” when information is not collected separately for each group. The time period for

this table is the most recent and oldest years of data used in the NHDR. Measures with the highest annual percentage change in the

direction of “getting worse” are shown here. Measures with no change are not included here. A blank cell indicates that no disparity

in quality of care was getting worse for the group, which could reflect lack of data or small sample sizes for some populations.

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Chapter 4
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 (see Table 1.2) of quality

and access to health care are shown below.

Figure 4.1. Blacks compared with Whites on core measures of quality and access

Better = Blacks receive better quality of care or have better

access to care than Whites.

Same = Blacks and Whites receive about the same quality of care

or access to care.

Worse = Blacks receive poorer quality of care or have worse

access to care than Whites.

Key: CRM = core report measures (see Table 1.2).

Note: Data presented are the most recent available.

Table 4.3. Blacks compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Colorectal cancer diagnosed

at advanced stage

Adults age 50 and over who

report they ever received a

Cancer colonoscopy, sigmoidoscopy,

proctoscopy, or fecal occult

blood test

Colorectal cancer deaths per

100,000 population per year

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(38 CRM)

Better

Same

Worse

2

19

4

3

Access

(6 CRM)

15 2

1

Blacks or African Americans
Table 4.3. Blacks compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Hospital admissions for Adults age 40 and over

Diabetes lower extremity amputations with diagnosed diabetes

per 1,000 population age 18 who received all three

and over with diabetes recommended services

Adult hemodialysis patients

with adequate dialysis (urea

End stage renal reduction ratio 65% or greater)

disease Dialysis patients who were

registered on a waiting list

for transplantation

Deaths per 1,000 adult Adult current smokers

hospital admissions with who received advice

acute myocardial infarction to quit smoking

(AMI)

Heart disease Recommended hospital Recommended hospital

care for heart failure care for heart attack

Adults with obesity who

ever received advice to

exercise more

New AIDS cases per

HIV and AIDS 100,000 population age

13 and over

Pregnant women who first Children ages 2-17 for

received prenatal care in whom a health provider

Maternal and the first trimester ever gave advice about

child health physical activity

Children ages 19-35 months Children ages 3-6 who

who received all ever had their vision

recommended vaccines checked

Suicide deaths per 100,000 Adults with a major People age 12 and over

population depressive episode who who needed treatment

received treatment for for illicit drug use and

depression who received such

Mental health and treatment at a specialty

substance abuse facility in the last 12

months

People age 12 and over

treated for substance abuse

who completed treatment

course

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Chapter 4 Blacks or African Americans
Table 4.3. Blacks compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Respiratory Adults age 65 and over who Patients with tuberculosis

diseases ever received pneumococcal who completed a

vaccination curative course of

treatment within 12

months of initiation

of treatment

Recommended hospital

care for pneumonia

Long-stay nursing home High-risk, long-stay nursing Adult home health care

residents with physical home residents with pressure patients whose ability to

restraints sores walk or move around

Nursing home, improved

home health, Short-stay nursing home

and hospice care residents with pressure sores

Adult home health care

patients who were admitted

to the hospital

Adult surgery patients

who received appropriate

timing of antibiotics

Adult surgery patients

with postoperative

complications

Patient safety Failure to rescue

Central venous catheterassociated adverse

events

Adults age 65 and over

who received potentially

inappropriate prescription

medicines

Emergency department

visits in which patients left

Timeliness without being seen

Adults who can sometimes

or never get care for illness

or injury as soon as wanted

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Chapter 4 Blacks or African Americans
Table 4.3. Blacks compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Patient Adults with poor provider- Children with poor

centeredness patient communication provider-patient

communication

People without a usual People under age 65 who People under age 65

source of care who indicated were uninsured all year with health insurance

a financial or insurance

reason

Access People with a usual primary People with a specific

care provider source of ongoing care

People unable to get or

delayed in getting needed

medical care, dental care,

or prescription medicines

◆ For 19 of the 38 core report measures of quality, Blacks had significantly poorer quality of care than

Whites (Figure 4.1). For 4 of the core report measures, Blacks had better quality of care. For

example, Black nursing home residents were less likely to be physically restrained, and Blacks were

more likely to receive recommended care for heart failure than Whites.

◆ For 3 of the 6 core report measures of access, Blacks had significantly worse access to care than

Whites. For example, Blacks were more likely than Whites to delay or not get medical care. For

one measure (people without a usual source of care due to financial or insurance reasons), Blacks

had better access to care than Whites.

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Chapter 4 Blacks or African Americans
Figure 4.2. Change in Black-White disparities over time

Improving >5% = Black-White difference becoming smaller at an

average annual rate greater than 5%.

Improving 1-5% = Black-White difference becoming smaller at an

average annual rate between 1% and 5%.

Same = Black-White difference not changing.

Worsening 1-5% = Black-White difference becoming larger at an

average annual ate between 1% and 5% per year.

Worsening >5% = Black-White difference becoming larger at an

average annual rate greater than 5%.

Key: CRM = core report measures (see Table 1.2).

Note: The time period for this figure is the most recent and oldest

years of data used in the NHDR. Only 38 core report measures

could be tracked over time for Blacks.

Table 4.4. Change in Black-White disparities over time: Specific measures

Topic Improving Worsening Same

Colorectal cancer diagnosed

at advanced stage

Adults age 50 and over who

report they ever received a

Cancer colonoscopy, sigmoidoscopy,

proctoscopy, or fecal

occult blood test

Colorectal cancer deaths per

100,000 population per year

Adults age 40 and over with

diagnosed diabetes who

received all three

Diabetes recommended services

Hospital admissions for lower

extremity amputations per

1,000 population age 18 and

over with diabetes

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(34 CRM)

Improving >5%

Worsening 1-5%

13

9

Access

(4 CRM)

Same

Worsening >5%

Improving 1-5%

3

5

4

1

2

2

1

Blacks or African Americans
Table 4.4. Change in Black-White disparities over time: Specific measures

Topic Improving Worsening Same

Adult hemodialysis

patients with adequate

dialysis (urea reduction

End stage ratio 65% or greater)

renal disease Dialysis patients who

were registered on a

waiting list for

transplantation

Deaths per 1,000 admissions Adults with obesity who

Heart disease with acute myocardial ever received advice to

infarction (AMI) exercise more

Adult current smokers who

received advice to quit

smoking

HIV and AIDS New AIDS cases per 100,000

population age 13 and over

Pregnant women who first Childrens ages 2-17 for Children ages 19-35

received prenatal care in the whom a health provider months who received

Maternal and first trimester ever gave advice about all recommended

child health physical activity vaccines

Children ages 3-6 who ever

had their vision checked

People age 12 and over Adults age 18 and over People age 12 and over

discharged for substance abuse with a major depressive who needed treatment

treatment who completed episode who received for illicit drug use and

Mental health and treatment treatment for depression who received such

substance abuse treatment at a specialty

facility in the last

12 months

Suicide deaths per

100,000 population

Adults age 65 and over

who ever received

pneumococcal vaccination

Respiratory Patients with tuberculosis

diseases who completed a curative

course of treatment within

12 months of initiation of

treatment

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Chapter 4 Blacks or African Americans
Table 4.4. Change in Black-White disparities over time: Specific measures

Topic Improving Worsening Same

Short-stay nursing home Long-stay nursing home

residents with pressure residents with physical

sores restraints

Nursing home, High-risk, long-stay

home health, nursing home residents

and hospice with pressure sores

care Adult home health care

patients who were

admitted to the hospital

Adult home health care

patients whose ability to

walk or move around

improved

Failure to rescue Adults age 65 and over Adult surgery patients

who received potentially who received appropriate

inappropriate prescription timing of antibiotics

Patient safety medicines

Central venous catheterassociated adverse events

Emergency department Adults who can sometimes

Timeliness visits in which patients left or never get care for illness

without being seen or injury as soon as wanted

Patient Adults with poor provider- Children with poor

centeredness patient communication provider-patient

communication

People under age 65 with People with a usual primary People with a specific

health insurance care provider source of ongoing care

Access People under age 65 who

were uninsured all year

◆ Of core report measures of quality that could be tracked over time for Blacks and Whites, BlackWhite differences became smaller for 8 measures and larger for 13 measures (Figure 4.2). For

example, Black-White differences in central venous catheter-associated adverse events and new

AIDS cases have decreased, but the difference in lower extremity amputations for patients with

diabetes has increased. For 13 measures, Black-White differences did not change over time.

◆ Of core report measures of access that could be tracked over time for Blacks and Whites, BlackWhite differences became smaller for 2 measures and larger for 1 measure. For 1 measure, BlackWhite differences did not change over time.

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Chapter 4 Blacks or African Americans
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 the reports track. 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.

Figure 4.3. Asians compared with Whites on measures of quality and access

Better = Asians receive better quality of care or have better

access to care than Whites.

Same = Asians and Whites receive about the same quality of care

or access to care.

Worse = Asians receive poorer quality of care or have worse

access to care than Whites.

Key: CRM = core report measures (see Table 1.2).

Note: Data presented are the most recent available.

Table 4.5. Asians compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Colorectal cancer diagnosed at Adults age 50 and over

advanced stage who report they ever

Cancer received a colonoscopy,

sigmoidoscopy,

proctoscopy, or fecal

occult blood test

Colorectal cancer deaths per

100,000 population per year

Adult hemodialysis patients with

adequate dialysis (urea

End stage reduction ratio 65% or greater)

renal disease Dialysis patients who were

registered on a waiting list

for transplantation

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(27 CRM)

Same

Worse

11

4

9

1

7

Better

Access

(5 CRM)

Asians
Table 4.5. Asians compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Deaths per 1,000

adult hospital

admissions with

acute myocardial

infarction (AMI)

Heart disease Recommended

hospital care for heart

attack

Recommended

hospital care for heart

failure

HIV and AIDS New AIDS cases per 100,000

population age 13 and over

Children ages 2-17 for Pregnant women who

whom a health provider first received prenatal

ever gave advice about care in the first

Maternal and physical activity trimester

child health Children ages 19-35

months who received

all recommended

vaccines

Mental health and Suicide deaths per 100,000

substance abuse population

Adults age 65 and over Patients with

who ever received tuberculosis who

pneumococcal completed a curative

Respiratory diseases vaccination course of treatment

within 12 months of

initiation of treatment

Recommended hospital

care for pneumonia

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Chapter 4 Asians
Table 4.5. Asians compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Adult home health care patients Long-stay nursing home High-risk, long-stay

who were admitted to the hospital residents with nursing home residents

physical restraints with pressure sores

Nursing home, Adult home health

home health, care patients whose

and hospice care ability to walk or

move around

improved

Short-stay nursing

home residents with

pressure sores

Adult surgery patients Adults age 65 and

who received appropriate over who received

timing of antibiotics potentially

Patient safety inappropriate

prescription

medicines

Failure to rescue

Adults who can Emergency

Timeliness sometimes or never get department visits in

care for illness or injury which patients left

as soon as wanted without being seen

Patient centeredness Adults with poor providerpatient communication

People with a usual People under age 65

primary care provider with health insurance

People under age 65

who were uninsured

all year

Access to care People with a specific

source of ongoing

care

People without a

usual source of care

who indicated a

financial or insurance

reason

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Chapter 4 Asians
◆ For 9 of the 27 core report measures of quality, Asians had significantly poorer quality of care than

Whites. For example, Asians were less likely than Whites to get recommended care for pneumonia

and to ever receive a pneumococcal vaccine. For 7 measures, Asians had significantly better quality

of care than Whites (Figure 4.3). For example, Asian dialysis patients were more likely than Whites

to have adequate dialysis and to be on a waiting list for transplantation.

◆ For 1 of the 5 core report measures of access, Asians had significantly worse access to care than

Whites; Asians were less likely than Whites to have a usual primary care provider. Asians had the

same access to care as Whites for 4 of the 5 measures. For example, there was no statistically

significant difference between Asians and Whites in having a usual source of care.

Figure 4.4. Change in Asian-White disparities over time

Improving >5% = Asian-White difference becoming smaller at an

average annual rate greater than 5%.

Improving 1-5% = Asian-White difference becoming smaller at an

average annual rate between 1% and 5%.

Same = Asian-White difference not changing.

Worsening 1-5% = Asian-White difference becoming larger at an

average annual rate between 1% and 5%.

Worsening >5% = Asian-White difference becoming larger at an

average annual rate greater than 5%.

Key: CRM = core report measures (see Table 1.2).

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 Asians and Whites.

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(22 CRM)

Improving >5%

Worsening 1-5%

9

Access

(5 CRM)

Same

Worsening >5%

Improving 1-5%

9

2

2

4

7

2

1

Asians
Table 4.6. Change in Asian-White disparities over time: Specific measures

Topic Improving Worsening Same

Colorectal cancer deaths Colorectal cancer

per 100,000 population diagnosed at advanced

per year stage

Cancer Adults age 50 and over

who report they ever

received a colonoscopy,

sigmoidoscopy,

proctoscopy, or fecal

occult blood test

Adult hemodialysis

patients with adequate

End stage renal dialysis (urea reduction

disease ratio 65% or greater)

Dialysis patients who were

registered on a waiting

list for transplantation

Deaths per 1,000 adult

Heart disease hospital admissions with

acute myocardial

infarction (AMI)

New AIDS cases per

HIV and AIDS 100,000 population age

13 and over

Children ages 19-35 Pregnant women who first

months who received received prenatal care in

all recommended the first trimester

Maternal and vaccines

child health Children ages 2-17 for

whom a health provider

ever gave advice about

physical activity

Mental health and Suicide deaths per

substance abuse 100,000 population

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Chapter 4 Asians
Table 4.6. Change in Asian-White disparities over time: Specific measures

Topic Improving Worsening Same

Adults age 65 and over Patients with tuberculosis

who ever received who completed a curative

Respiratory diseases pneumococcal vaccination course of treatment within

12 months of initiation of

treatment

Short-stay nursing home Long-stay nursing home

residents with pressure residents with physical

sores restraints

High-risk, long-stay

nursing home residents

Nursing home, with pressure sores

home health, Adult home health care

and hospice care patients whose ability to

walk or move around

improved

Adult home health care

patients who were

admitted to the hospital

Adult surgery patients who Failure to rescue

Patient safety received appropriate

timing of antibiotics

Adults who can sometimes

Timeliness or never get care for illness

or injury as soon as wanted

Patient centeredness Adults with poor providerpatient communication

People under age 65 People with a specific People under age 65 with

who were uninsured source of ongoing care health insurance

Access to care all year

People with a usual People without a usual

primary care provider source of care who

indicated a financial or

insurance reason

◆ Of core report measures of quality that could be tracked over time for Asians and Whites, AsianWhite differences became smaller for 4 measures but larger for 9 measures (Figure 4.4). For 9

measures, Asian-White differences did not change over time.

◆ Of core report measures of access that could be tracked over time for Asians and Whites, AsianWhite differences became smaller for 2 measures but larger for 1 measure. For 2 measures, the

Asian-White differences did not change over time.

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Chapter 4 Asians
Native Hawaiians and Other Pacific Islanders

The ability to assess disparities among NHOPIs for the NHDR has been hampered 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.7 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.

Consequently, in previous NHDRs, estimates for the NHOPI population could be generated for only a

handful of NHDR 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 the quality of care for people who

identified themselves as NHOPI (including people of mixed race who identified primarily as NHOPI).

These measures include cholesterol screening, influenza and pneumococcal vaccinations, and health

insurance.

Data from BRFSS does not replace the need for continued efforts to improve data collection and statistical

methods to provide more information on health and health care of the NHOPI population. While BRFSS

may have larger samples of NHOPIs due to State efforts to improve sample sizes, the survey is not

necessarily a comprehensive survey of health and health care. Other surveys and data collection efforts,

such as vital statistics and hospital administrative data, include more topics but do not identify NHOPIs or

have large enough sample sizes to provide data for these populations. Also, for all national data sources,

the relatively small population sizes of many Pacific Islander groups can cause these populations to be

overlooked when categorized as NHOPIs. In addition, identifying individuals with chronic conditions or

other health conditions within such small populations further reduces the sample sizes that exist. However,

as data become available, this information will be included in future reports.

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Chapter 4 Native Hawaiians and Other Pacific Islanders

The percentage of adults who did not

receive a cholesterol check in the past 5

years was significantly higher for Native

Hawaiians and Other Pacific Islanders.
Preventive Care: Cholesterol Screening

In the State of Hawaii, where 54% of Native Hawaiians reside, cardiovascular disease is the leading cause

of death.8 Screening for risk factors for cardiovascular disease such as high blood pressure and high

cholesterol are important in preventing disease. Cholesterol screening is shown below to highlight one

aspect of cardiovascular disease prevention for Native Hawaiians.

Figure 4.5. Adults who did NOT receive a cholesterol check in the last 5 years, 2005

Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral

Risk Factor Surveillance System, 2005.

Note: These data are self-reported from a survey of adults in a

household.

◆ The percentage of adults who did not receive a cholesterol check in the last 5 years was significantly

higher for NHOPIs than for Whites (34.8% compared with 24.6%; Figure 4.5).

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Chapter 4

Percent

0

5

10

15

20

25

30

35

40

Total White NHOPI

Native Hawaiians and Other Pacific Islanders
Preventive Care: Influenza and Pneumococcal Vaccinations for Older

Adults

Older adults are at increased risk for complications from influenza and pneumococcal infections, and

vaccination is an effective strategy to reduce illness and deaths due to influenza and pneumonia. The U.S.

Preventive Services Task Force and the Centers for Disease Control and Prevention recommend annual

influenza vaccinations and at least one pneumococcal vaccination for all older individuals.

Figure 4.6. Adults age 65 and over who did NOT receive an influenza vaccination in the last 12

months, 2006

Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral

Risk Factor Surveillance System, 2006.

Note: These data are self-reported from a survey of adults in a

household.

◆ The percentage of older adults who did not receive flu shots in the last 12 months was lower for

NHOPIs than for Whites (15.9% compared with 30.6%; Figure 4.6).

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196

Chapter 4

Percent

0

5

10

15

20

25

30

35

40

Total White NHOPI

Native Hawaiians and Other Pacific Islanders
Figure 4.7. Adults age 65 and over who have never received pneumococcal vaccination, 2006

Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral

Risk Factor Surveillance System, 2006.

Note: These data are self-reported from a survey of adults in a

household.

◆ The percentage of older adults who have never received a pneumococcal vaccination was lower for

NHOPIs than for Whites (20.0% compared with 32.6%; Figure 4.7).

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197

Chapter 4

Percent

0

5

10

15

20

25

30

35

40

Total White NHOPI

Native Hawaiians and Other Pacific Islanders
Access to Care: Health Insurance

Having health insurance is an important facilitator to getting health care. Individuals without health care

coverage are less likely to have a usual source of care and access to preventive care and are more likely to

delay needed care.

Figure 4.8. Adults who were uninsured all year, 2006

Key: NHOPI = Native Hawaiian or Other Pacific Islander.

Source: Centers for Disease Control and Prevention, Behavioral

Risk Factor Surveillance System, 2006.

Note: These data are self-reported from a survey of adults in a

household.

◆ The percentage of adults who did not have any health insurance in the past year was higher for

NHOPIs than for Whites (19.7% compared with 12.7%; Figure 4.8).

◆ The percentage of adults ages 18-64 who did not have any health insurance was not significantly

different between NHOPIs and Whites (15.3% for Whites, 20.9% for NHOPIs; data not shown).

National Quality Report, 2000

Staying Healthy Priority Populations

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Chapter 4

Percent

0

5

10

15

20

25

30

35

40

Total White NHOPI

Native Hawaiians and Other Pacific Islanders
American Indians and Alaska Natives

Previous NHDRs showed that AI/ANs had poorer quality of care and worse access to care than Whites

for many measures tracked in the reports. Findings based on core report measures of quality and access

that support estimates for AI/ANs are shown below.

Figure 4.9. AI/ANs compared with Whites on measures of quality and access

Better = AI/ANs receive better quality of care or have better

access to care than Whites.

Same = AI/ANs and Whites receive about the same quality of care

or access to care.

Worse = AI/ANs receive poorer quality of care or have worse

access to care than Whites.

Key: AI/AN = American Indian or Alaska Native; CRM = core

report measures (see Table 1.2).

Note: Data presented are the most recent available.

Table 4.7. AI/ANs compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Colorectal cancer Adults age 50 and over

diagnosed at advanced who report they ever

stage received a colonoscopy,

sigmoidoscopy,

Cancer proctoscopy, or fecal

occult blood test

Colorectal cancer

deaths per 100,000

population per year

Dialysis patients Adult hemodialysis

End stage renal disease registered on a waiting patients with adequate

list for transplantation dialysis (urea reduction

ratio 65% or greater)

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(19 CRM)

Better

Same

Worse

2

8

2

2

Access

(3 CRM)

9

1

American Indians and Alaska Natives
Table 4.7. AI/ANs compared with Whites on measures of quality and access: Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Recommended hospital

Heart disease care for heart attack

Recommended hospital

care for heart failure

New AIDS cases per

HIV and AIDS 100,000 population age

13 and over

Pregnant women who Children ages 19-35

Maternal and child health first received prenatal months who received all

care in the first trimester recommended vaccines

Mental health and Suicide deaths per

substance abuse 100,000 population

Recommended hospital Patients with tuberculosis

care for pneumonia who completed a curative

Respiratory diseases course of treatment

within 12 months of

initiation of treatment

Long-stay nursing home Short-stay nursing home

residents with physical residents with pressure

restraints sores

High-risk, long-stay Adult home health care

Nursing home, nursing home residents patients whose ability to

home health, with pressure sores walk or move around

and hospice care improved

Adult home health care

patients who were

admitted to the hospital

Adult surgery patients

Patient safety who received appropriate

timing of antibiotics

People under age 65 People with a usual

with health insurance primary care provider

Access to care People under age 65

who were uninsured

all year

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Staying Healthy Priority Populations

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Chapter 4 American Indians and Alaska Natives
◆ Only about half of the core report measures of quality supported estimates for AI/ANs.

◆ For 8 of the 19 core report measures of quality, AI/ANs had significantly poorer quality of care than

Whites (Figure 4.9). For example, AI/ANs were less likely than Whites to receive colorectal cancer

screening and recommended care for heart failure. For 2 measures, AI/ANs had better outcomes

than Whites (colorectal cancer diagnosed at advanced stage and colorectal cancer mortality).

◆ For 2 of the 3 core report measures of access, AI/ANs had significantly worse access to care than

Whites. AI/ANs under age 65 were less likely than Whites to have health insurance and were more

likely to be uninsured all year.

Figure 4.10. Change in AI/AN-White disparities over time

Improving >5% = AI/AN-White difference becoming smaller at an

average annual rate greater than 5%.

Improving 1-5% = AI/AN-White difference becoming smaller at an

average annual rate between 1% and 5%.

Same = AI/AN-White difference not changing.

Worsening 1-5% = AI/AN-White difference becoming larger at an

average annual rate between 1% and 5%.

Worsening >5% = AI/AN-White difference becoming larger at an

average annual rate greater than 5%.

Key: AI/AN = American Indian or Alaska Native; CRM = core

report measures (see Table 1.2).

Note: The time period for this figure is the most recent and oldest

years of data used in the NHDR. Only 18 core report measures

could be tracked over time for AI/ANs and Whites.

Table 4.8. Change in AI/AN-White disparities over time: Specific measures

Topic Improving Worsening Same

Adults age 50 and over who Colorectal cancer

report they ever received a diagnosed at advanced

colonoscopy, stage

sigmoidoscopy,

Cancer proctoscopy, or fecal

occult blood test

Colorectal cancer deaths

per 100,000 population

per year

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(15 CRM)

Improving >5%

Worsening 1-5%

6

3

Access

(3 CRM)

Same

Worsening >5%

Improving 1-5%

2

3

1

1

2

2

American Indians and Alaska Natives
Table 4.8. Change in AI/AN-White disparities over time: Specific measures

Topic Improving Worsening Same

Adult hemodialysis patients Dialysis patients

End stage renal with adequate dialysis registered on a waiting

disease (urea reduction ratio 65% list for transplantation

or greater)

New AIDS cases per

HIV and AIDS 100,000 population age

13 and over

Maternal and child Children ages 19-35

health months who received all

recommended vaccines

Mental health and Suicide deaths per

substance abuse 100,000 population

Patients with tuberculosis

who completed a curative

Respiratory diseases course of treatment within

12 months of initiation of

treatment

Nursing home, Short-stay nursing home Long-stay nursing home High-risk, long-stay

home health, residents with pressure residents with nursing home residents

and hospice care sores physical restraints with pressure sores

Adult home health care Adult home health care

patients who were patients whose ability to

admitted to the hospital walk or move around

improved

Adult surgery patients

Patient safety who received appropriate

timing of antibiotics

People under age 65 with People under age 65 who

Access to care health insurance were uninsured all year

People with a usual

primary care provider

◆ Fewer than half of the core report measures could be tracked over time for AI/ANs.

◆ Of core report measures of quality that could be tracked over time for AI/ANs and Whites, AI/ANWhite differences became smaller for 5 measures. For example, AI/AN-White differences in

recommended vaccinations for children and the rate of new AIDS cases have decreased over time.

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Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

202

Chapter 4 American Indians and Alaska Natives
◆ AI/AN-White differences became larger for 4 measures (Figure 4.10). For example, the difference

in colorectal cancer screening has worsened over time. For 6 measures, AI/AN-White differences

did not change over time. These include nursing home residents with pressure sores and home

health care patients with improved mobility.

◆ Of core report measures of access that could be tracked over time for AI/ANs and Whites, AI/ANWhite differences became smaller for 2 measures (people under age 65 with health insurance and

people with a usual primary care provider) but larger for 1 measure (people under age 65 who were

uninsured all year).

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Priority Populations Staying Healthy

National Healthcare Disparities Report, 2008

203

Chapter 4 American Indians and Alaska Natives
Focus on Indian Health Service Facilities

Nationwide, many AI/ANs who are members of a federally recognized tribe rely on the Indian Health

Service (IHS) to provide access to health care in the counties on or near reservations.9,10,ix Due to low

numbers and lack of data, information about AI/AN hospitalizations is difficult to obtain in most Federal

and State hospital utilization data sources. The NHDR addresses this gap by examining utilization data

from IHS, Tribal, and contract hospitals.

Diabetes is one of the leading causes of morbidity and mortality among AI/AN populations. Its

prevention and control are a major focus of the IHS Director’s Chronic Disease Initiative and the IHS

Health Promotion/Disease Prevention Initiative. Addressing barriers to health care is a large part of the

overall IHS goal of ensuring that comprehensive, culturally acceptable personal and public health services

are available and accessible to AI/ANs.

Figure 4.11. Hospital admissions for uncontrolled diabetes per 100,000 population age 18 and

over in IHS, Tribal, and contract hospitals, and community hospitals, by race (left) and ethnicity

(right), 2003-2005

Key: AI/AN = American Indian or Alaska Native, API = Asian or Pacific Islander; HCUP SID = Healthcare Cost and Utilization Project

State Inpatient Databases; NPIRS = National Patient Information Reporting System.

Source: IHS, Tribal, and contract hospitals: IHS NPIRS, 2003-2005; community hospitals: Agency for Healthcare Research and

Quality, HCUP SID disparities analysis file, 2003-2005.

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 23 States that have 63% of the

U.S. resident population. Years of IHS data prior to 2003 use a denominator based on the 1990 census. This source is not

comparable with estimates following those years, which are based on 2000 Bridged Census Data. Therefore, for comparing IHS with

national estimates, only 2003, 2004, and 2005 data from both data sources are presented.

ixOf potentially eligible AI/ANs, 74% sought health care in 2004 at an IHS or tribally contracted facility, according to

the most recent published IHS estimates developed by the Office of Public Health Support, Division of Program

Statistics.

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Staying Healthy Priority Populations

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204

Chapter 4

0

20

40

60

80

100

2005

Rate

2003

2004

AI/AN

IHS, Tribal, and contract hospitals (NPIRS)

0

20

40

60

80

100

White

Black

2005

Rate

2003

2004

Total

Hispanic

API

Community hospitals (HCUP SID)

American Indians and Alaska Natives
◆ From 2003 to 2005, the age-adjusted rate of hospitalizations for uncontrolled diabetes decreased for

AI/ANs in IHS, Tribal, and contract hospitals (from 37.8 per 100,000 to 29.3 per 100,000; Figure

4.11).

◆ There were no statistically significant changes for other racial and ethnic groups in community

hospitals during this period.

For the more than 538,000 AI/ANs living on reservations or other trust lands where the climate is

inhospitable, roads are often impassable, and transportation is scarce, health care facilities are far from

accessible.11 These conditions contribute to high rates of perforated appendix and hospitalizations for

urinary tract infections, two problems that are receiving particular attention by IHS. Perforated appendix

and urinary tract infection hospitalization rates, which decreased from 2003 to 2004, are illustrative of the

efforts underway, as well as the work that needs to continue to achieve high-quality, comprehensive care

that is accessible to AI/ANs.12

Figure 4.12. Perforated appendixes per 1,000 admissions with appendicitis, age 18 years and

over with appendicitis in IHS, Tribal, and contract hospitals, and community hospitals, by race

(left) and ethnicity (right), 2003-2005

Key: AI/AN = American Indian or Alaska Native, API = Asian or Pacific Islander; HCUP SID = Healthcare Cost and Utilization Project

State Inpatient Databases; NPIRS = National Patient Information Reporting System.

Source: IHS, Tribal, and contract hospitals: IHS NPIRS, 2003-2005; community hospitals: Agency for Healthcare Research and

Quality, HCUP SID disparities analysis file, 2003-2005.

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 23 States that have 63% of the

U.S. resident population. Years of IHS data prior to 2003 use a denominator based on the 1990 Census. This source is not

comparable with estimates following those years, which are based on 2000 Bridged Census Data. Therefore, for comparing IHS with

national estimates, only 2003, 2004, and 2005 data from both data sources are presented.

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Chapter 4

0

100

200

300

400

2005

Rate

2003

2004

AI/AN

IHS, Tribal, and contract hospitals (NPIRS)

0

100

200

300

400

White

Black

2005

Rate

2003

2004

Total

Hispanic

API

Community hospitals (HCUP SID)

American Indians and Alaska Natives
◆ From 2003 to 2005, the age-adjusted rate of appendicitis hospitalizations with perforated appendix

decreased for AI/ANs in IHS, Tribal, and contract hospitals (from 384.4 per 1,000 to 355.8 per

1,000; Figure 4.12).

◆ The rate in community hospitals during this period also decreased overall (from 299.7 per 1,000 to

287.2 per 1,000), for Whites (from 294.6 per 1,000 to 282.7 per 1,000), and for Blacks (from 334.3

per 1,000 to 317.3 per 1,000).

Figure 4.13. Hospitalizations for urinary tract infection per 100,000 population age 18 years and

over in IHS, Tribal, and contract hospitals, and community hospitals, by race (left) and ethnicity

(right), 2003-2005

Key: AI/AN = American Indian or Alaska Native, API = Asian or Pacific Islander; HCUP SID = Healthcare Cost and Utilization Project

State Inpatient Databases; NPIRS = National Patient Information Reporting System.

Source: IHS, Tribal, and contract hospitals: IHS NPIRS, 2003-2005; community hospitals: Agency for Healthcare Research and

Quality, HCUP SID disparities analysis file, 2003-2005.

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 23 States that have 63% of the

U.S. resident population. Years of IHS data prior to 2003 use a denominator based on the 1990 Census. This source is not

comparable with estimates following that year, which are based on 2000 Bridged Census Data. Therefore, for comparing IHS with

national estimates, only 2003, 2004, and 2005 data from both data sources are presented.

◆ From 2003 to 2005, the rate of hospitalizations for urinary tract infection for AI/AN adults in IHS,

Tribal, and contract hospitals decreased from 212.1 per 100,000 to 186.3 per 100,000 (Figure 4.13).

◆ In comparison, from 2003 to 2005, hospitalizations for urinary tract infection in community

hospitals increased overall (from 164.6 per 100,000 to 178.5 per 100,000) and for Whites (from

149.8 per 100,000 to 165.3 per 100,000).

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Chapter 4

0

100

200

300

2005

Rate

2003

2004

AI/AN

IHS, Tribal, and contract hospitals (NPIRS)

0

100

200

300

2005

Rate

2003

2004

White

Total Black

Hispanic

API

Community hospitals (HCUP SID)

American Indians and Alaska Natives
Hispanics or Latinos

Previous NHDRs showed that Hispanics had poorer quality of care and worse access to care than nonHispanic Whites for many measures the reports track. Findings based on core report measures of quality

and access to health care that support estimates for Hispanics are shown below.

Figure 4.14. Hispanics compared with non-Hispanic Whites on measures of quality and access

Better = Hispanics receive better quality of care or have better

access to care than non-Hispanic Whites.

Same = Hispanics and non-Hispanic Whites receive about the

same quality of care or access to care.

Worse = Hispanics receive poorer quality of care or have worse

access to care than non-Hispanic Whites.

Key: CRM = core report measures (Table 1.2).

Note: Data presented are the most recent available.

Table 4.9. Hispanics compared with non-Hispanic Whites on measures of quality and access:

Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Colorectal cancer Adults age 50 and over

diagnosed at advanced who report they ever

stage received a colonoscopy,

sigmoidoscopy,

Cancer proctoscopy, or fecal

occult blood test

Colorectal cancer deaths

per 100,000 population

per year

Adults age 40 and over

Diabetes with diagnosed diabetes

who received all three

recommended services

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207

Chapter 4

0

20

40

60

80

100

Percent

Quality

(34 CRM)

Same

Worse

10

19

6

5

Better

Access

(6 CRM)

Hispanics or Latinos
Table 4.9. Hispanics compared with non-Hispanic Whites on measures of quality and access:

Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Adult hemodialysis patients Dialysis patients

End stage renal disease with adequate dialysis registered on a waiting

(urea reduction ratio 65% list for transplantation

or greater)

Recommended hospital Adult current smokers

care for heart attack who received advice to

quit smoking

Adults with obesity who Recommended

Heart disease ever received advice to hospital care for heart

exercise more failure

Deaths per 1,000 adult

hospital admissions

with acute myocardial

infarction (AMI)

New AIDS cases per

HIV and AIDS 100,000 population age

13 and over

Pregnant women who first Children ages 3-6 who

Maternal and child health received prenatal care in ever had their vision

the first trimester checked

Children for whom a

health provider ever

gave advice about

physical activity

Children ages 19-35

months who received

all recommended

vaccines

Suicide deaths per Adults with a major People age 12 and

100,000 population depressive episode who over who needed

received treatment for treatment for illicit drug

depression use and who received

Mental health and such treatment at a

substance abuse specialty facility in the

last 12 months

People age 12 and over

discharged for substance

abuse treatment who

completed treatment

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208

Chapter 4 Hispanics or Latinos
Table 4.9. Hispanics compared with non-Hispanic Whites on measures of quality and access:

Specific measures

Topic Better than Whites Worse than Whites Same as Whites

Adults age 65 and over

who ever received

pneumococcal vaccination

Recommended hospital

Respiratory diseases care for pneumonia

Patients with tuberculosis

who completed a curative

course of treatment within

12 months of initiation

of treatment

Long-stay nursing home Adult home health care

residents with physical patients whose ability

restraints to walk or move around

improved

High-risk, long-stay

Nursing home, home nursing home residents

health, and hospice care with pressure sores

Short-stay nursing home

residents with pressure

sores

Adult home health care

patients who were

admitted to the hospital

Adults age 65 and over Adult surgery patients Failure to rescue

Patient safety who received potentially who received appropriate

inappropriate prescription timing of antibiotics

medicines

Adults who can sometimes

Timeliness or never get care for

illness or injury as soon

as wanted

Adults with poor providerpatient communication

Patient centeredness Children with poor

providerpatient communication

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209

Chapter 4 Hispanics or Latinos
Table 4.9. Hispanics compared with non-Hispanic Whites on measures of quality and access:

Specific measures

Topic Better than Whites Worse than Whites Same as Whites

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

Access to care primary care provider

People unable to get

or delayed in getting

needed medical care,

dental care, or prescription

medicines

People without a usual

source of care who

indicated a financial or

insurance reason

◆ For 19 of the 34 core report measures of quality, Hispanics had poorer quality of care than nonHispanic Whites (Figure 4.14). For example, Hispanics were less likely to receive recommended

care for heart attack and obese Hispanics were less likely to receive advice about exercise than

Whites. For 5 measures, Hispanics had better quality care than Whites. These include older adults

not receiving inappropriate medications and hemodialysis patients with adequate dialysis. For 10

measures of quality of care, Hispanics were not significantly different from Whites. For example,

Hispanic children were as likely as White children to receive vaccinations and vision screening.

◆ For 6 of the 6 core report measures of access, Hispanics had worse access to care than non-Hispanic

Whites. These include people under age 65 with health insurance, people with a usual primary care

provider, and people who were unable to get care or who delayed care.

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210

Chapter 4 Hispanics or Latinos
Figure 4.15. Change in Hispanic-non-Hispanic White disparities over time

Improving >5% = Hispanic-non-Hispanic White difference

becoming smaller at an average annual rate greater than 5%.

Improving 1-5% = Hispanic-non-Hispanic White difference

becoming smaller at an average annual rate between 1% and 5%.

Same = Hispanic-non-Hispanic White difference not changing.

Worsening 1-5% = Hispanic-non-Hispanic White difference

becoming larger at an average annual rate between 1% and 5%.

Worsening >5% = Hispanic-non-Hispanic White difference

becoming larger at an average annual rate greater than 5%.

Key: CRM = core report measures (see Table 1.2).

Note: The time period for this figure is the most recent and oldest

years of data used in the NHDR. Only 34 core report measures

could be tracked over time for Hispanics and non-Hispanic

Whites.

Table 4.10. Change in Hispanic-non-Hispanic White disparities over time: Specific measures

Topic Improving Worsening Same

Adults age 50 and over Colorectal cancer

who report they ever diagnosed at advanced

received a colonoscopy, stage

sigmoidoscopy,

Cancer proctoscopy, or fecal

occult blood test

Colorectal cancer deaths

per 100,000 population

per year

Adults age 40 and over with

Diabetes diagnosed diabetes who

received all three

recommended services

Adult hemodialysis Dialysis patients who were

End stage renal patients with registered on a waiting list

disease adequate dialysis (urea for transplantation

reduction ratio 65%

or greater)

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Chapter 4

0

20

40

60

80

100

Percent

Quality

(30 CRM)

Improving >5%

Worsening 1-5%

12

6

Access

(4 CRM)

Same

Worsening >5%

4 Improving 1-5%

6

2

1

1

2

1

Hispanics or Latinos
Table 4.10. Change in Hispanic-non-Hispanic White disparities over time: Specific measures

Topic Improving Worsening Same

Adult current smokers who Adults with obesity who Deaths per 1,000 adult

Heart disease received advice to quit were ever given advice hospital admissions with

smoking to exercise more acute myocardial infarction

(AMI)

HIV and AIDS New AIDS cases per 100,000

population age 13 and over

Children ages 19-35 months Children ages 2-17 for

who received all whom a health provider

Maternal and recommended vaccines ever gave advice about

child health physical activity

Children ages 3-6 who ever

had their vision checked

Adults with a major Suicide deaths per 100,000

depressive episode who population

received treatment for

depression

People age 12 and over

Mental health and who needed treatment for

substance abuse illicit drug use and who

received such treatment

at a specialty facility in the

last 12 months

People age 12 and over

discharged for substance

abuse treatment who

completed treatment

Adults age 65 and over

who ever received

pneumococcal

vaccination

Respiratory diseases Patients with

tuberculosis who

completed a curative

course of treatment

within 12 months of

initiation of treatment

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Chapter 4 Hispanics or Latinos
Table 4.10. Change in Hispanic-non-Hispanic White disparities over time: Specific measures

Topic Improving Worsening Same

Long-stay nursing home

residents with physical

restraints

Nursing home, Adult home health care High-risk, long-stay

home health, patients whose ability to walk nursing home residents

and hospice care or move around improved with pressure sores

Short-stay nursing home

residents with pressure sores

Adult home health care

patients who were admitted

to the hospital

Adult surgery patients Failure to rescue

who received appropriate

timing of antibiotics

Patient safety Adults age 65 and over

who received potentially

inappropriate

prescription medicines

Adults who can sometimes

Timeliness or never get care for illness

or injury as soon as wanted

Adults with poor providerPatient patient communication

centeredness Children with poor providerpatient communication

People under age 65 who People under age 65 with

Access to care were uninsured all year health insurance

People with a usual primary People with a specific

care provider source of ongoing care

◆ Of core report measures of quality that could be tracked over time for Hispanics and non-Hispanic Whites,

Hispanic-non-Hispanic White differences became smaller for 10 measures (Figure 4.15). For example,

Hispanic-non-Hispanic White differences in timeliness of care and appropriate timing of antibiotics improved

over time. Hispanic-non-Hispanic White differences became larger for 8 measures. These include differences

in colorectal cancer screening and pneumococcal vaccination for older adults, which worsened over time. For

12 measures, Hispanic-non-Hispanic White differences did not change over time. For example, the

differences in the percentage of patients who received substance abuse treatment remained the same.

◆ Of core report measures of access that could be tracked over time for Hispanics and non-Hispanic Whites,

Hispanic-non-Hispanic White differences became smaller for 2 measures (people under age 65 who were

uninsured all year and people who had a usual primary care provider). For 2 measures, Hispanic-nonHispanic White differences did not change over time (people under age 65 who had health insurance

and people who had a specific source of ongoing care).

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Chapter 4 Hispanics or Latinos
Recent Immigrants and Limited-English-Proficient

Populations

Recent Immigrants and Language Barriers

Immigrants often encounter barriers to high-quality health care. In 2003, about 33.5 million people living

in the United States were born outside the United States,13 up from 20 million in 1990.14 Asians and

Hispanics are much more likely to be foreign born. About 70% of Asians and 40% of Hispanics in the

United States are foreign born, compared with about 4% of Whites and 6% of Blacks.14

Certain diseases are concentrated among Americans born in other countries. For example, in 2006,

56.6% of tuberculosis cases in the Nation were among foreign-born individuals.15 In addition, the case

rate among foreign-born individuals is more than 10 times higher than among individuals born in the

United States.15 However, the case rates for tuberculosis among U.S.-born and foreign-born individuals

are both decreasing.15

Quality health care requires that patients and providers communicate effectively. People who speak a

language other than English at home may have less access to resources, such as health insurance, that

facilitate getting needed health care. Providers and patients’ ability to communicate clearly with one

another 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 and do

not have an interpreter’s assistance. Communication problems between the patient and provider can lead

to lower patient adherence to medications and decreased participation in medical decisionmaking, as well

as exacerbate cultural differences that impair the delivery of quality health care. Moreover, Title VI of the

Civil Rights Act of 1964, 42 U.S.C. 2000d, prohibits discrimination against patients based on their

national origin by providers receiving Federal financial assistance.16 Such providers are required to take

reasonable steps to provide people with limited English proficiency with a meaningful opportunity to

participate in programs the U.S. Department of Health and Human Services funds.

Limited English proficiency is a barrier to quality health care for many Americans. About 52 million

Americans, or 19.4% of the population, spoke a language other than English at home in 2000, up from 32

million in 1990. Of the 52 million, 32 million (about 12% of the population) spoke Spanish, 10 million

(about 4% of the population) spoke another Indo-European language, 7.8 million (about 3% of the

population) spoke an Asian or Pacific Islander language, and 2 million spoke other languages at home.

Almost half of the people who spoke a foreign language at home reported not speaking English very

well.17 A study of health plan members and use of interpreters showed that the use of interpreters

reduced disparities for Hispanic and Asian and Pacific Islander members (28% and 21%, respectively).18

As in previous NHDRs, findings are presented below for several quality and access measures based on

data from the National Tuberculosis Surveillance System and the Medical Expenditure Panel Survey

(MEPS). These sources also are supplemented with data from the California Health Interview Survey.

National Quality Report, 2000

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Chapter 4 Recent Immigrants and Limited-English-Proficient Populations
Information on disparities in health care quality and access for Americans born outside the United States

and for Americans with limited English-speaking skills are presented for tuberculosis therapy, poor

communication with health care providers, and uninsurance.

Figure 4.16. Completion of therapy for tuberculosis within 12 months of being diagnosed among

people born outside the United States, by race (left) and ethnicity (right), 1999-2004

Key: API = Asian or Pacific Islander.

Source: Centers for Disease Control and Prevention, National Tuberculosis Surveillance System, 1999-2004.

Reference population: Foreign-born U.S. resident population with verified tuberculosis, all ages.

◆ From 1999 to 2004, the percentage of people who completed therapy for tuberculosis within 12

months of being diagnosed improved for foreign-born APIs (from 79.0% to 82.4%) and foreign-born

Hispanics (from 78.5% to 79.1%; Figure 4.16).

◆ In 2004, the percentage of people who completed therapy for tuberculosis within 12 months of being

diagnosed was significantly higher for foreign-born Blacks (83.6%) and APIs (82.4%) than for

foreign-born Whites (79.5%), but lower for Hispanics compared with non-Hispanic Whites (79.1%

compared with 82.7%).

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Chapter 4

75

80

85

90

95

100 White

Black

API

2000

2002

Percent

1999

Z

2001

2003

2004

75

80

85

90

95

100 Non-Hispanic White

Hispanic

Percent

Z

1999

2000

2001

2002

2003

2004

Recent Immigrants and Limited-English-Proficient Populations
Figure 4.17. Composite measure: Adult ambulatory patients who reported poor communication

with health providers, by race and ethnicity, stratified by language spoken at home, 2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2005.

Denominator: Civilian noninstitutionalized population age 18 and

over.

Note: Average percentage of adults age 18 and over who had a

doctor’s office or clinic visit in the last 12 months and were

reported to have had poor communication with health care

providers (i.e., their health care providers sometimes or never

listened carefully, explained things clearly, showed respect for

what they had to say, and spent enough time with them). Data

were insufficient for this analysis for Black non-English speakers.

◆ The overall percentage of adults who had a doctor’s office or clinic visit in the last 12 months who

reported poor communication with their health care provider was significantly higher for individuals

who speak a foreign language at home than for individuals who speak English at home (Figure

4.17).

◆ The percentage of adults who reported poor communication with their health care provider was

significantly higher for Whites who speak some other language at home (10.9%) than for Whites

who speak English at home (8.9%). There were no statistically significant differences for other

racial or ethnic groups due to small sample sizes.

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216

Chapter 4

0

5

10

15

20

25

White

Percent

English

Other language

Hispanic

Total

Asian

Non-Hispanic

White

Recent Immigrants and Limited-English-Proficient Populations

Problems With English Help Block Many

Hispanics From Medical Care—

Medical News Today.
Figure 4.18. Adults under age 65 who were uninsured all year, by race and ethnicity, stratified by

language spoken at home, 2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population

ages 18-64.

◆ The overall percentage of adults under age 65 uninsured all year was significantly higher for

individuals who speak a foreign language at home than for individuals who speak English at home

(Figure 4.18).

◆ The percentage of people uninsured all year was significantly higher for Whites, Blacks, and Asians

who speak some other language at home than for their counterparts who speak English at home

(35.8% compared with 10.4% for Whites, 38.5% compared with 14.7% for Blacks, and 18.8%

compared with 9.9% for Asians).

◆ The percentage of people uninsured all year was more than twice as high for Hispanics who speak

some other language at home than for Hispanics who speak English at home (36.9% compared with

16.6%).

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217

Chapter 4

0

10

20

30

40

50

White

Percent

English

Other language

Hispanic

Total

Asian

Non-Hispanic

White

Black

Recent Immigrants and Limited-English-Proficient Populations
Language Assistance

Clear communication is an important component of effective health care delivery. It is vital for providers

to understand patients’ health care needs and for patients to understand providers’ diagnoses and treatment

recommendations. Communication barriers can relate to language, culture, and health literacy.

For people with limited English proficiency, having language assistance is of particular importance.

People with limited English proficiency may choose a usual source of care in part based on language

concordance. Not having a language-concordant provider may limit or discourage some patients from

establishing a usual source of care.

The NHDR includes a noncore measure of access: provision of language assistance by the usual source

of care. Language assistance includes bilingual clinicians, trained medical interpreters, and bilingual

receptionists and other informal interpreters.

Figure 4.19. Adults with limited English proficiency, by whether they had a usual source of care

with or without language assistance, 2003-2005

Key: USC = usual source of care.

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2003-2005.

Reference population: Civilian noninstitutionalized population

age 18 and over.

Note: Language assistance includes bilingual clinicians, trained

medical interpreters, and informal interpreters (e.g., bilingual

receptionists).

◆ Approximately half (52%) of individuals with limited English proficiency did not have a usual

source of care in 2005 (Figure 4.19).

◆ In 2005, less than half (44%) of individuals with limited English proficiency had a usual source of

care who offered language assistance.

◆ Only 4% of individuals with limited English proficiency had a usual source of care who did not

offer language assistance.

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218

Chapter 4

0

20

40

60

80

100

Percent

2003

2

51

7 7

47

2004

42 46

No USC

USC with language assistance

USC without language assistance

2

52

44

4

2005

Recent Immigrants and Limited-English-Proficient Populations
Low-Income Groups

In this report, poor populations are defined as people living in families whose household income falls

below specific poverty thresholds. These thresholds vary by family size and composition and are updated

annually by the U.S. Bureau of the Census.19,x After falling for nearly a decade (1990-2000), the number

of poor people in America rose from 31.6 million in 2000 to 36.5 million in 2006, and the rate of poverty

increased from 11.3% to 12.3% during the same period.20

Poverty varies by race and ethnicity. In 2006, 24% of Blacks, 21% of Hispanics, 10% of Asians, and 8%

of Whites were poor.20 People with low incomes often experience worse health and are more likely to

die prematurely.21 In general, poor populations have reduced access to high-quality care. While people

with low incomes are more likely to be uninsured, income-related differences in quality of care that are

independent of health insurance coverage have also been demonstrated.22

Previous chapters of this report described health care differences by income. This section summarizes

disparities in quality of and access to health care for poorxi individuals compared with high-incomexii

individuals. For each core report measure, poorer people can have health care that is worse than, about

the same as, or better than health care received by high-income people. Only relative differences of at

least 10% that are statistically significant with alpha = 0.05 are discussed in this report. Access measures

focus on facilitators and barriers to health care and exclude health care utilization measures.

In addition, changes in differences related to income are examined over time. For each core report

measure, racial, ethnic, and socioeconomic groups are compared with a designated comparison group at

different points in time. 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.

Core report measures (see Table 1.2) for which the relative differences are changing less than 1% per year

are identified as staying the same. Core report measures for which the relative differences are becoming

smaller at a rate of more than 1% per year are identified as improving. Core report measures for which

the relative differences are becoming larger at a rate of more than 1% per year are identified as

worsening. Changes of greater than 5% per year are also differentiated from changes of between 1% and

5% per year in some figures.

x For example, in 2006, the Federal poverty threshold for a family of two adults and two children was $20,444.

xi Household income less than Federal poverty thresholds.

xii Household income 400% of Federal poverty thresholds and higher.

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Chapter 4 Low-Income Groups
Figure 4.20. Poor compared with high-income individuals on measures of quality and access

Better = Poor people receive better quality of care or have better

access to care than high-income individuals.

Same = Poor and high-income individuals receive about the same

quality of care or access to care.

Worse = Poor people receive poorer quality of care or have worse

access to care than high-income individuals.

Key: CRM = core report measures (see Table 1.2).

Note: Data presented are for the most recent data year available.

Table 4.11. Poor compared with high income on measures of quality and access: Specific

measures

Topic Better than high income Worse than high income Same as high income

Adults age 50 and over

who report they ever

Cancer received a colonoscopy,

sigmoidoscopy,

proctoscopy, or fecal

occult blood test

Adults age 40 and over

Diabetes with diagnosed diabetes

who received all three

recommended services

Adult current smokers

who received advice

to quit smoking

Deaths per 1,000 adult

Heart disease hospital admissions with

acute myocardial infarction

(AMI)

Adults with obesity who

ever received advice to

exercise more

National Quality Report, 2000

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220

Chapter 4

0

20

40

60

80

100

Percent

Quality

(17 CRM)

Same

Worse

5

6

11

Better

Access

(6 CRM)

1

Low-Income Groups
Table 4.11. Poor compared with high income on measures of quality and access: Specific

measures

Topic Better than high income Worse than high income Same as high income

Children ages 2-17 for Children ages 3-6 who

whom a health provider ever had their vision

Maternal and ever gave advice about checked

child health physical activity

Children ages 19-35

months who received all

recommended vaccines

People age 12 and over Adults with a major

who needed treatment for depressive episode who

Mental health and illicit drug use and who received treatment for

substance abuse received such treatment depression

at a specialty facility in

the last 12 months

Adults age 65 and over

Respiratory diseases who ever received

pneumococcal vaccination

Failure to rescue

Adults age 65 and over

Patient safety who received potentially

inappropriate

prescription medicines

Emergency department

visits in which patients left

Timeliness without being seen

Adults who can sometimes

or never get care for illness

or injury as soon as wanted

Adults with poor providerPatient centeredness patient communication

Children with poor providerpatient communication

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Chapter 4 Low-Income Groups
Table 4.11. Poor compared with high income on measures of quality and access: Specific

measures

Topic Better than high income Worse than high income Same as high income

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

Access to care People unable to get or

delayed in getting needed

medical care, dental care,

or prescription medicines

People without a usual

source of care who

indicated a financial or

insurance reason for not

having usual source of care

◆ Fewer than half of the core report measures of quality supported estimates for poor populations.

◆ For 11 of the 17 core report measures of quality with income data, poor individuals had significantly

poorer quality of care than high-income individuals (Figure 4.20). Only one measure (receipt of

drug or alcohol treatment) was better for poor individuals than for high-income individuals.

◆ For all 6 core report measures of access, poor individuals had significantly worse access to care than

high-income individuals.

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Chapter 4 Low-Income Groups
Figure 4.21. Change in poor-high-income disparities over time

Improving >5% = Poor-high-income difference becoming smaller

at an average annual rate greater than 5%.

Improving 1-5% = Poor-high-income difference becoming smaller

at an average annual rate between 1% and 5%.

Same = Poor-high-income difference not changing.

Worsening 1-5% = Poor-high-income difference becoming larger

at an average annual rate between 1% and 5%.

Worsening >5% = Poor-high-income difference becoming larger

at an average annual rate greater than 5%.

Key: CRM = core report measures (see Table 1.2).

Note: The time period for this figure is the most recent and oldest

years of data used in the NHDR. Only 20 core report measures of

quality and access could be tracked over time for poor and highincome individuals.

Table 4.12. Change in poor-high-income disparities over time: Specific measures

Topic Improving Worsening Same

Adults age 50 and over

who report they ever

Cancer received a colonoscopy,

sigmoidoscopy,

proctoscopy, or fecal

occult blood test

Adults age 40 and over

Diabetes with diagnosed diabetes

who received all three

recommended services

Adult current smokers who Deaths per 1,000 adult

received advice to quit hospital admissions with

smoking acute myocardial

Heart disease infarction (AMI)

Adults with obesity who

ever received advice to

exercise more

Children ages 3-6 who ever Children ages 19-35 Children ages 2-17 for

Maternal and child had their vision checked months who received all whom a health provider

health recommended vaccines ever gave advice about

physical activity

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223

Chapter 4

1

0

20

40

60

80

100

Percent

Quality

(15 CRM)

Improving >5%

Worsening 1-5%

5

3

Access

(5 CRM)

Same

Worsening >5%

Improving 1-5%

2

4 1

1

2

1

Low-Income Groups
Table 4.12. Change in poor-high-income disparities over time: Specific measures

Topic Improving Worsening Same

People age 12 and over

who needed treatment for

Mental health and illicit drug use and who

substance abuse received such treatment

at a specialty facility in the

last 12 months

Adults age 65 and over

Respiratory diseases who ever received

pneumococcal

vaccination

Adults age 65 and over Failure to rescue

Patient safety who received potentially

inappropriate prescription

medicines

Adults who can

Timeliness sometimes or never get

care for illness or injury as

soon as wanted

Adults with poor providerpatient communication

Patient centeredness Children with poor

provider-patient

communication

People under age 65 with People without a usual People with a specific

health insurance source of care who source of ongoing care

indicated a financial or

insurance reason for not

having a usual source of

care

Access to care People under age 65 who

were uninsured all year

People with a usual

primary care provider

◆ Only about half of the core report measures of quality allow comparisons between poor and highincome individuals over time.

National Quality Report, 2000

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224

Chapter 4 Low-Income Groups
◆ Of core report measures of quality that could be tracked over time for poor and high-income

individuals, poor-high-income differences became smaller for 3 measures (Figure 4.21). For

example, the gap between poor people and high-income people in current smokers receiving advice

to quite smoking and children with a vision exam became smaller. For 7 measures, the gap

increased, including children who received all recommended vaccines and timeliness of care for

illness or injury. For 5 measures, the poor-high-income difference did not change. For example, the

gap between poor people and high-income people in pneumococcal vaccination and advice about

exercise remained the same.

◆ Of core report measures of access that could be tracked over time for poor and high-income

individuals, poor-high-income differences became smaller for 3 measures (people under age 65 with

health insurance, people under age 65 who were uninsured all year, and people who have a usual

primary care provider), became larger for 1 measure (people without a usual source of care due to

financial or insurance reason), and remained the same for 1 measure (people with a specific source

of ongoing care).

Focus on Uninsurance

Because low-paying jobs are less likely to offer health insurance as a benefit and the cost of health

insurance leaves poorer individuals less likely to be able to afford it, this year’s NHDR again focuses on

uninsurance. Compared with insured people, uninsured people report more problems getting care and are

diagnosed at later disease stages.23,24 They report poorer health status,25 are sicker when hospitalized, and

are more likely to die during their hospital stay.24 Uninsured people often avoid nonurgent care, such as

preventive screenings; have difficulty obtaining care for illness or injury; and must bear the full cost of

health care. In addition, prolonged periods of uninsurance can have a particularly serious effect on health

and stability.

Findings presented here highlight two quality measures related to prevention (screening for colorectal

cancer and counseling parents about physical activity in children) and one access measure (dental care) of

special relevance to uninsured people. Two of these measures include bivariate analyses to show data by

income and insurance status.

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225

Chapter 4 Low-Income Groups
Quality of Health Care

Prevention: Screening for Colorectal Cancer

Screening for colorectal cancer is an effective way to reduce new cases of late-stage disease and mortality

caused by this cancer.

Figure 4.22. Composite measure: Adults age 50 and over who received colorectal cancer

screening (colonoscopy, sigmoidoscopy, proctoscopy, or fecal occult blood test), by income,

stratified by insurance status, 2005

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health Interview Survey,

2005.

Reference population: Civilian noninstitutionalized men and

women age 50 and over who reported they received a

colonoscopy, sigmoidoscopy, proctoscopy, or fecal occult blood

test in the last 2 years.

◆ Overall, adults age 50 and over without insurance were less than half as likely as adults with private

insurance to report they had colorectal cancer screening in the last 2 years (24.1% compared with

53.4%; Figure 4.22). Publicly insured adults were also less likely than adults with private insurance

to report they had colorectal cancer screening in the last 2 years (48.8% compared with 53.4%).

◆ Among poor adults, there was no statistically significant difference by insurance status.

◆ Among near-poor adults, the percentage was significantly lower for uninsured adults (25.2%) than

for privately insured adults (44.9%).

◆ Among middle-income adults, the percentage was significantly lower for uninsured adults than for

privately insured adults (19.0% compared with 50.5%).

◆ Among high-income adults, the percentage was significantly lower for uninsured adults than for

privately insured adults (34.5% compared with 56.5%).

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Chapter 4

0

25

50

75

100

Percent

Any private

Public only

Uninsured

Poor Near

Poor

Middle

Income

High

Income

Total

Low-Income Groups
Prevention: Counseling Parents About Physical Activity in Children

Counseling about physical activity can play an important role in helping children to lose excess weight

and establish healthy lifestyle behaviors.

Figure 4.23. Children ages 2-17 with ambulatory visits for whom a health provider ever gave

advice about the amount and kind of exercise, sports, or physically active hobbies they should

have, by insurance status, 2002-2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population

ages 2-17.

Note: Estimates were for children whose parents or guardians

reported ever receiving advice from a health care provider about

their children’s physical activity. More data by race and ethnicity

can be found in the Children section.

◆ From 2002 to 2005, the gap between uninsured children and privately insured children whose

parents or guardians reported receiving advice about physical activity remained the same. In 2005,

the percentage was significantly less for uninsured children than for privately insured children

(28.5% compared with 36.1%; Figure 4.23).

◆ During this period, there was no significant difference between publicly insured and privately

insured children whose parents or guardians reported receiving advice about physical activity.

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227

Chapter 4

0

10

20

30

40

50

Any private

Public only

2003

Percent

2002

Total

Uninsured

2004

2005

Low-Income Groups
Access to Health Care

Dental Care

Regular dental visits promote prevention, early diagnosis, and optimal treatment of oral diseases and

conditions.

Figure 4.24. People who had a dental visit in the calendar year, by income, stratified by

insurance status, 2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population, all

ages.

◆ Overall, the percentage of people with a dental visit in the past year was significantly lower for

publicly insured and uninsured people than for privately insured people (30.7% and 17.3%,

respectively, compared with 50.9%; Figure 4.24).

◆ Among poor people, the percentage did not differ significantly between publicly insured and

privately insured people (29.6% compared with 34.1%) but was significantly lower for uninsured

people than for privately insured people (12.9% compared with 34.1%).

◆ Among near-poor, middle-income, and high-income people, uninsured people were less than half as

likely as privately insured people to have had a dental visit in the past year.

◆ Only high-income people with private health insurance met the Healthy People 2010 target of 56%

of people with a dental visit in the past year (58.6%).

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228

Chapter 4

0

25

50

75

Percent

Any private

Public only

Uninsured

Poor Near

Poor

Middle

Income

High

Income

Total

Healthy People 2010

Target: 56%

Low-Income Groups
Women

The U.S. Census Bureau estimated 152 million females in the United States in 2006, 51% of the U.S.

population,26 of whom 47 million are members of racial or ethnic minority groups.27 By 2050, it is

projected that just under half of females in the United States will be members of racial or ethnic minority

groups.27 The ratio of males to females is highest at birth, when male infants outnumber female infants,

and gradually declines with age due to higher male mortality rates. Among Americans 85 and older,

women outnumber men by more than 2 to 1.28 Poverty disproportionately affects women; in 2006, 14.1%

of women lived in households with incomes below the Federal poverty level compared with 11.1% of

men.29

Women in the United States have a life expectancy 5.2 years longer than men30 and lower age-adjusted

death rates than men for 12 of the 15 leading causes of death.31 However, women are more likely than

men to report having arthritis, asthma,32 and serious mental illness.33 There is significant variation in

health status and health-related behaviors for women of different races and ethnicities.34 In general,

gender differences in quality of care are small.

Many measures of relevance to women are tracked in the NHDR. Findings presented here highlight four

quality measures and one access measure of particular importance to women:

Component of health care need Measure

Prevention Prenatal care and maternal health, obese adults

advised about exercise

Treatment Mortality rate for acute myocardial infarction

Management New AIDS cases

Access to care Usual source of care

Quality of Health Care

Prevention: Prenatal Care and Maternal Health

Childbirth and reproductive care are the most common reasons for women of childbearing age to use

health care services. With more than 11,000 births each day in the United States, childbirth is the most

common reason for hospital admission.35 Given that birth outcomes may have lifetime effects, good

prenatal care has the potential to affect the Nation’s future health and health care needs.36 Prenatal care is

expected to maintain and improve the health of both mother and newborn during pregnancy. It is

recommended that women begin receiving prenatal care in the first trimester of pregnancy.

National Quality Report, 2000

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229

Chapter 4 Women
Figure 4.25. Women who completed a pregnancy in the last 12 months who first received

prenatal care in the first trimester for selected States, by race, ethnicity, and education, 2005

Key: AI/AN = American Indian or Alaska Native; API = Asian or

Pacific Islander.

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Vital Statistics SystemNatality, 2005.

Reference population: Women with live births.

Note: Data for 2005 include the 39 reporting areas (37 States,

DC, and New York City) that used the 1989 revision of the US

Standard Certificate of Live Birth in 2005. Reporting areas that

have adopted the 2003 revision are excluded because prenatal

data based on the 2003 revision are not comparable with data

based on 1989 and earlier revisions of the US Standard

Certificate of Live Birth. More information on the measure

specification can be found in the Measure Specifications

Appendix. Further discussion of this measure can be found in

the Residents of Rural Areas section.

◆ In 2005, the percentage was significantly lower for Blacks (76.3%) and AI/ANs (69.6%) compared

with Whites (85.5%).

◆ In 2005, the percentage was significantly lower for Hispanics than for non-Hispanic Whites (77.6%

compared with 88.7%).

◆ The percentage was significantly lower for women with less than a high school education (72.8%)

and high school graduates (82.0%) than for women with any college education (91.2%).

◆ Only women with some college education achieved the Healthy People 2010 target of 90% of

women receiving prenatal care in the first trimester.

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Chapter 4

50

60

70

80

90

100

White

Percent

Hispanic

API

<High School

High School Grad

Some College

Total

Black

Non-Hispanic White

AI/AN

Z

0

Healthy People 2010

Target: 90%

Women

Only college-educated women achieved the

Healthy People 2010 target of 90% of women

receiving prenatal care in the first trimester.
Racial and ethnic minorities are disproportionately of lower socioeconomic status than Whites.20 Since

information about income is not typically collected on birth certificates, the source of some health data,

education is commonly used as a proxy for socioeconomic status. To distinguish the effects of race,

ethnicity, and education on quality of health care, this measure is stratified by level of education.

Figure 4.26. Women who completed a pregnancy in the last 12 months who first received

prenatal care in the first trimester for selected States, by race (left) and ethnicity (right),

stratified by education, 2005

Key: AI/AN = American Indian or Alaska Native; API = Asian or Pacific Islander.

Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System-Natality,

2005.

Reference population: Women with live births.

Note: Data for 2005 include the 39 reporting areas (37 States, DC, and New York City) that used 1989 revision of the US Standard

Certificate of Live Birth in 2005. Reporting areas that have adopted the 2003 revision are excluded because prenatal data based on

the 2003 revision are not comparable with data based on 1989 and earlier revisions of the US Standard Certificate of Live Birth.

◆ Education explains some but not all of the differences in prenatal care among women by race and

ethnicity. Racial and ethnic differences in early prenatal care tended to persist among women with

similar education (Figure 4.26).

◆ Only college-educated APIs (90.0%) and non-Hispanic Whites (93.2%) achieved the Healthy People

2010 target of 90% of women receiving prenatal care in the first trimester.

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Chapter 4

Percent

White

Black

<High

School

High

School Grad

Some

College

API

0

Z

50

55

60

65

70

75

80

85

90

95

100

AI/AN

50

55

60

65

70

75

80

85

90

95

100

Percent

Non-Hispanic White

Hispanic

<High

School

High

School Grad

Some

College

0

Z

Women
Prevention: Obese Adults Advised About Exercise

In 2005-2006, more than 35% of adult women age 20 and over in the United States were obese,

compared with 33% of men,37,xiii putting them at increased risk for many chronic, deadly conditions, such

as hypertension, cancer, diabetes, and coronary heart disease.38 Reducing obesity is a major objective in

preventing heart disease and stroke.39 Research shows large racial and ethnic differences among women.

The prevalence of obesity is higher for Black and Mexican-American women compared with White

women.40 The health care system has a central role to play in helping people become aware of the risks

of obesity when they are overweight and suggesting strategies for reducing these risks.

Figure 4.27. Adults with obesity who ever received advice from a health provider to exercise

more, by race (left) and ethnicity (right), stratified by gender, 2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Data were insufficient for this analysis for Asians, Native Hawaiians and Other Pacific Islanders, and American Indians and

Alaska Natives.

◆ Obese women were more likely than men to receive advice about exercise (62.6% compared with

53.5%; Figure 4.27). Among obese women, Hispanics were less likely than non-Hispanic Whites to

receive advice about exercise (52.5% compared with 65.4%). There were no significant differences

between Black women and White women.

xiii Obesity is defined as having a body mass index (BMI) of 30 or higher. It is noteworthy that BMI incorporates both

a person’s weight and height in determining if he or she is overweight or obese.

National Quality Report, 2000

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232

Chapter 4

0

10

20

30

40

50

60

70

80

90

100

Percent

Total White Black

Male

Female

0

10

20

30

40

50

60

70

80

90

100

Percent

Non-Hispanic

White

Hispanic

Male

Female

Women
Treatment: Mortality Rate for Acute Myocardial Infarction

Cardiovascular disease is the number one killer among women.41 While significant progress has been

made in reducing mortality from heart disease over the past three decades, one woman in four still dies

from this group of conditions. Women are generally older than men when diagnosed with heart disease

(e.g., 73 versus 65 years on average, according to one study42). Therefore, treatment and outcomes may

be compromised by the fact that women are more likely to have other chronic conditions when initially

diagnosed. Acute myocardial infarction (AMI) is one type of cardiovascular disease discussed in this

report. Measuring processes of AMI care can provide information about whether a patient received

specific needed services, but these processes make up a very small proportion of all the care that an AMI

patient needs. Measuring outcomes of AMI care, such as mortality, can provide a more global assessment

of all the care a patient receives and usually is the aspect of quality that matters most to patients.

Figure 4.28. Deaths per 1,000 adult hospital admissions with acute myocardial infarction (AMI),

by gender and race, 2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality,

Healthcare Cost and Utilization Project (HCUP), State Inpatient

Databases (SID) disparities analysis file, 2005.

Note: Rates are adjusted by age, gender, age-gender

interactions, and All Patient Refined-Diagnosis-Related Group

risk of mortality score. The HCUP SID disparities analysis file

is designed to provide national estimates using weighted

records from a sample of hospitals from 23 States that have

63% of the U.S. resident population.

◆ The mortality rate for hospital admissions with AMI was higher for females compared with males

(94.8 per 1,000 compared with 67.9 per 1,000; Figure 4.28). Among females, rates were lower both

for Black (66.5 per 1,000) and Hispanic (83.7 per 1,000) females than for White females (100.6 per

1,000).

National Quality Report, 2000

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Chapter 4

Rate

0

20

40

60

80

100

120

White Female

Black Female

Total

Male

Female

API Female

Hispanic Female

Women
Management: New AIDS Cases

Although differences in the progression of HIV to AIDS do not necessarily result from differences in

quality of care, early and appropriate treatment of HIV infection can delay progression to AIDS.

Improved management of HIV infections has likely contributed to reduced transmission and therefore

decline in new AIDS cases.

Figure 4.29. New AIDS cases per 100,000 population age 13 and over, by race/ethnicity, stratified

by gender, 2006

Key: AI/AN = American Indian or Alaska Native; API = Asian or

Pacific Islander.

Source: Centers for Disease Control and Prevention, HIV/AIDS

Surveillance System, 2006.

Reference population: U.S. population age 13 and over.

Note: The source categorizes race/ethnicity as a single item.

White = non-Hispanic White; Black = non-Hispanic Black.

◆ For the overall U.S. population, the rate of new AIDS cases for males was nearly triple that for

females (22.4 compared with 7.8 per 100,000 population; Figure 4.29).

◆ The rate was significantly higher for males than for females in all groups: Blacks (82.9 per 100,000

for males and 40.4 per 100,000 for females), APIs (7.5 per 100,000 for males and 1.6 per 100,000

for females), AI/ANs (12.2 per 100,000 for males and 3.6 per 100,000 for females), Hispanics (31.3

per 100,000 for males and 9.5 per 100,000 for females), and Whites (11.2 per 100,000 for males and

1.9 per 100,000 for females).

◆ Among females, Blacks and Hispanics had significantly higher rates of new AIDS cases than Whites

(40.4 and 9.5 per 100,000, respectively, compared with 1.9 per 100,000). API women had lower

rates than White women (1.6 per 100,000 compared with 1.9 per 100,000).

◆ No group has yet achieved the Healthy People 2010 target of 1.0 new AIDS case per 100,000

population.

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234

Chapter 4

0

10

20

30

40

50

60

70

80

90

100

White

Rate

Male

Female

API

Hispanic

Total

Black

AI/AN

Healthy

People 2010

Target: 1.0

Women
Access to Care

Usual Source of Care

Higher costs, poorer outcomes, and greater disparities are observed among individuals without a usual

source of care.43

Figure 4.30. People with a specific source of ongoing care, by race, ethnicity, and income,

stratified by gender, 2006

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health

Interview Survey, 2006.

Reference population: Civilian noninstitutionalized

population, all ages.

Note: Measure is age adjusted to the 2000 standard

population.

◆ Overall, the percentage of people with a specific source of ongoing care was significantly higher for

females than for males (88.2% compared with 81.2%; Figure 4.30).

◆ This percentage was also significantly higher for females than males for all racial and ethnic groups:

Whites (88.2% for females compared with 80.8% for males), Asians (97.3% for females compared

with 82.2% for males), non-Hispanic Whites (90.9% for females compared with 83.6% for males),

and Hispanics (78.5% for females compared with 72.8% for males).

◆ Among women, this percentage was significantly lower for poor (84.9%), near-poor (86.6%), and

middle-income (90.2%) individuals than for high-income individuals (97.0%).

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Chapter 4

50

60

70

80

90

100

Asian

Percent

Female

Male

Non-Hispanic White

Hispanic

Poor

Middle Income

Near Poor

High Income

Total

White

Black

0

Z

Women
Figure 4.31. People without a usual source of care who indicate a financial or insurance reason

for not having a source of care, by race (left) and ethnicity (right), stratified by gender, 2005

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Note: Data for Native Hawaiians and Other Pacific Islanders women, American Indians and Alaska Natives, and Asian males did not

meet the criteria for statistical reliability, data quality, or confidentiality.

◆ Women were more likely than men to not have a usual source of care due to financial or insurance

reasons (19.0% compared with 14.0%; Figure 4.31). This was also true among Blacks, nonHispanic Whites, and Hispanics.

◆ There were no statistically significant racial or ethnic differences among women.

National Quality Report, 2000

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236

Chapter 4

0

5

10

15

20

25

30

Percent

Total White Black

Male

Female

Asian

0

5

10

15

20

25

30

Percent

Non-Hispanic

White

Hispanic

Male

Female

Women
Children

Children (individuals less than 18 years old) made up 24.6% of the U.S. population, or 73.5 million

people, in 2006.26 Almost 40% of all children were members of racial and ethnic minority groups,1 and

17.6% of children lived in families with incomes below the Federal poverty level.19

In 2003, Black children and AI/AN children had death rates about one and one-half to two times higher

than White children. In 2005, Black infants were more than twice as likely as White infants to die during

their first year.30 Life expectancy at birth was 78.3 years for White children30 and 73.2 years for Black

children, a difference of about 5 years.30

Many measures relevant to children are tracked in the NHDR. Findings presented here highlight four

quality measures and two access measures of particular importance to children (for ages 2 months to 19

years, depending on the measure):

Component of health care need Measure

Prevention Early childhood vaccinations, counseling about

physical activity, vision screening

Patient safety Accidental puncture or laceration

Timeliness Admissions with perforated appendix

Access to care Health insurance

In addition, the final section of this chapter, which discusses individuals with special health care needs,

includes findings related to children with special health care needs.

Quality of Health Care

Prevention: Early Childhood Vaccinations

Childhood vaccinations protect recipients from illness and disability and protect others in the community.

Vaccinations are important for reducing mortality and morbidity in populations.

National Quality Report, 2000

Priority Populations Staying Healthy

National Healthcare Disparities Report, 2008

237

Chapter 4 Children

Untreated Cavities More Common Among LowIncome Children—Austin American-Statesman
Figure 4.32. Composite measure: Children ages 19-35 months who received all recommended

vaccines, by race (top), ethnicity (bottom), and income (next page top), 2000-2006

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

238

Chapter 4

50

60

70

80

90

100 White

Black

Asian

AI/AN

2001

2005

>1 Race

2002

Percent

2003

Z

0

2000

2004

2006

Healthy

People 2010

Target: 80%

50

60

70

80

90

100 Non-Hispanic White

Hispanic

2001

2002

2005

Percent

2003

2004

0

Z

2000

2006

Healthy

People 2010

Target: 80%

Children
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Immunization

Survey, 2000-2006.

Reference population: Civilian noninstitutionalized

population ages 19-35 months.

Note: Recommended vaccines for children ages 19-35

months are based on the Healthy People 2010 objective

and do not include varicella vaccine or vaccines added to

the recommended schedule after 1998 for children up to

35 months of age. Racial categories changed in 2000 and

may not be comparable with those used for previous years.

More information can be found in the Measure

Specifications appendix.

◆ From 2000 to 2006, the gap between Blacks and Whites and between Asians and Whites who

received all recommended vaccines decreased (Figure 4.32). However, in 2006, Black children were

less likely than White children to receive all recommended vaccines (77.0% compared with 81.6%).

◆ The gap between Hispanics and non-Hispanic Whites in the percentage of children who received all

recommended vaccines decreased during this time period. In 2006, there were no statistically

significant differences between Hispanics and non-Hispanic Whites.

◆ The gap between children from poor families and children from high-income families decreased.

However, in 2006, the percentage of children who received all recommended vaccines was lower for

children from poor (76.5%), near-poor (79.5%), and middle-income families (80.6%) than for

children from high-income families (86.3%).

◆ Nationally, vaccination coverage levels among White (81.6%), AI/AN (81.4%), non-Hispanic White

(82.2%), Hispanic (80.1%), middle-income (80.6%), and high-income (86.3%) children achieved the

Healthy People 2010 objective of 80% of children receiving all recommended vaccines.

Prevention: Counseling About Physical Activity

Lack of physical activity contributes to overweight in children. Routine promotion of physical activity

among children is widely recommended and may help them develop habits that will last into adulthood,

thereby influencing better long-term health.

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Chapter 4

50

60

70

80

90

100

2001

2002

2005

Percent

Near Poor High Income

Poor Middle Income

2003

0

Z

2000

2004

2006

Healthy

People 2010

Target: 80%

Children
Figure 4.33. Children ages 2-17 for whom a health provider ever gave advice about the amount

and kind of exercise, sports, or physically activity hobbies they should have, by race (top left),

ethnicity (top right), and income (bottom left), 2002-2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2002-2005.

Reference population: Civilian noninstitutionalized population

ages 2-17.

Note: More data by insurance status can be found in the LowIncome Groups section.

National Quality Report, 2000

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Chapter 4

0

10

20

30

40

50 Total

2003

2004

Percent

2002

2005

White

Black

Asian >1 Race

0

10

20

30

40

50 Non-Hispanic White

Hispanic

2002

2003

Percent

2004

2005

0

10

20

30

40

50

2002

2003

Percent

Low Income High Income

Poor Middle Income

2004

2005

Children
◆ From 2002 to 2005, the overall percentage of children whose parents or guardians reported ever

receiving advice from a health provider about physical activity improved (from 31.9% to 34.8%;

Figure 4.33). However, there were no significant changes for racial or ethnic groups.

◆ In 2005, Asian children (26.3%) and children of multiple race (28.0%) were less likely than Whites

(35.9%) to have received advice about physical activity.

◆ From 2002 to 2005, the gap between poor and high-income families in the percentage of children

whose parents or guardians reported advice from a health care provider about physical activity

remained the same. In 2005, poor children (30.9%) and middle-income children (33.7%) were less

likely than high-income children (38.7%) to have received advice about physical activity.

◆ In 2005, uninsured children were less likely than privately insured children to have received advice

about physical activity (28.5% compared with 36.1%; data not shown in this figure. See Figure 4.23).

Prevention: Vision Screening

Vision checks for children can help to detect eye problems early and, in some cases, improve the chances

that corrective treatments will be prescribed and successful.

National Quality Report, 2000

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241

Chapter 4 Children

Uninsured children were less likely

than privately insured children to

receive vision screening.
Figure 4.34. Children ages 3-6 who ever had their vision checked by a health provider, by race

(top left), ethnicity (top right), and income (bottom left), 2001-2005

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2001-2005.

Reference population: Civilian noninstitutionalized population

ages 3-6.

◆ There were no statistically significant racial or ethnic differences in the percentage of children who

received vision screening (Figure 4.34).

◆ Uninsured children were less likely than privately insured children to receive vision screening

(41.6% compared with 61.4%; data not shown).

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

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Chapter 4

50

55

60

65

70

75

2003

2004

Percent

2002

2005

White

Black

2001

0

Z

50

55

60

65

70

75 Non-Hispanic White

Hispanic

2002

2003

Percent

2001

2004

2005

0

Z

50

55

60

65

70

75

2002

2003

Percent

Near Poor High Income

Poor Middle Income

2001

2004

2005

Children
Patient Safety: Accidental Puncture or Laceration

Adverse events occurring during surgical procedures include unintended cuts, punctures, perforations, and

lacerations. Such events may be more likely in children, whose smaller anatomy may make avoiding such

events more technically challenging. Prior analyses of Healthcare Cost and Utilization Project (HCUP)

data from 2000 using earlier versions of the present indicator identified a cumulative incidence of 1

accidental puncture or laceration per 1,000 pediatric discharges, with significant associated increases in

length of stay, billed charges, and inpatient mortality.44 To the degree that such adverse events can be

avoided by proper surgical technique, variations in their occurrence may be a marker of differences in the

quality of pediatric surgical care. However, such rates are best interpreted in light of the risks associated

with medical or surgical discharges of varying complexity.

Figure 4.35. Accidental puncture or laceration during procedure per 1,000 discharges, children

under age 18, by race/ethnicity (left) and income (right), 2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization

Project (HCUP), State Inpatient Databases (SID) disparities analysis file, 2005.

Note: White, Black, and API are non-Hispanic. The HCUP SID disparities analysis file is designed to provide national estimates on

disparities using weighted records from a sample of hospitals from 23 States that have 63% of the U.S. resident population. Income

categories are based on the median income of the ZIP Code of the patient’s residence. These data are not risk adjusted. Rates

include medical or surgical discharges only.

◆ Black children (0.79 per 1,000 discharges) and Hispanic children (0.77 per 1,000 discharges) had

lower rates of accidental puncture or laceration than White children (0.96 per 1,000 discharges)

(Figure 4.35).

◆ Children living in low-income communities had a higher rate of accidental puncture or laceration

than children living in high-income communities (0.96 per 1,000 discharges compared with 0.84 per

1,000 discharges).

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Chapter 4

White

Rate per 1,000 discharges

Black

Hispanic

API

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Rate per 1,000 discharges

Poor

Low Income

Middle Income

High Income

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Children
Timeliness: Admissions With Perforated Appendix

Appendiceal perforation or rupture may increase risks of internal organ damage, female infertility, and

even death.45 Research suggests that there is little lag in the United States between correct diagnosis of

appendicitis and surgical intervention.46 Therefore, perforated appendicitis in children may better reflect

delayed symptom recognition by parents or providers, combined with logistical, financial, racial,

sociocultural, and other barriers to timely access to acute care for what is a time-dependent acute illness.47

Prior studies based on data from the HCUP and other sources have identified minority status, lower

income, lack of private insurance, and admission from a non-emergency department source as risk factors

for discharge with appendiceal rupture.48

Figure 4.36. Perforated appendixes per 1,000 admissions with appendicitis, ages 1-17, by

race/ethnicity (left) and income (right), 2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization

Project (HCUP), State Inpatient Databases (SID) disparities analysis file, 2005.

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

designed to provide national estimates on disparities using weighted records from a sample of hospitals from 23 States that have

63% of the U.S. resident population. Income categories are based on the median income of the ZIP Code of the patient’s residence.

◆ Among children with appendicitis, discharges with perforations were higher for Blacks (367.0 per

1,000 admissions) and Hispanics (328.0 per 1,000 admissions) than Whites (272.9 per 1,000

admissions) (Figure 4.36).

◆ Among children with appendicitis, discharges with perforations were higher for people living in poor

communities (324.1 per 1,000 admissions), low-income communities (298.6 per 1,000 admissions),

and middle-income communities (296.7 per 1,000 admissions) than for people living in high-income

communities (271.3 per 1,000 admissions).

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Chapter 4

White

Rate per 1,000 admissions

Black

Hispanic

API

0

50

100

150

200

250

300

350

400

Rate per 1,000 admissions

Poor

Low Income

Middle Income

High Income

0

50

100

150

200

250

300

350

400

Children
To distinguish between the effects of race and ethnicity and those of income on pediatric discharges with

perforated appendix, this measure is stratified by income level.

Figure 4.37. Perforated appendixes per 1,000 admissions with appendicitis, ages 1-17, by

race/ethnicity, stratified by income, 2005

Key: API = Asian or Pacific Islander.

Source: Agency for Healthcare Research and Quality, Center for

Delivery, Organization, and Markets, Healthcare Cost and

Utilization Project (HCUP), State Inpatient Databases (SID)

disparities analysis file, 2005.

Note: White, Black, and API are non-Hispanic. The HCUP SID

disparities analysis file is designed to provide national estimates

on disparities using weighted records from a sample of hospitals

from 23 States that have 63% of the U.S. resident population.

Income categories are based on the median income of the ZIP

Code of the patient’s residence.

◆ Hispanic children living in communities of every income level except high-income communities had

higher rates of hospital discharges with perforated appendix than Whites (Figure 4.37).

◆ Black children living in communities of every income level except middle-income communities had

higher rates of hospital discharges with perforated appendix than Whites.

◆ There were no statistically significant differences between APIs and Whites at any income level.

National Quality Report, 2000

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245

Chapter 4

Rate per 1,000 admissions

Black Hispanic

White

Poor

Low Income

Middle Income

High Income

API

0

100

200

300

400

500

Children
Access to Health Care

Health Insurance

Insurance coverage is among the most important factors in access to health care. Special efforts have

been made to provide insurance coverage to children.49

Figure 4.38. Children with health insurance, by race (left), ethnicity (right), and family income

(next page top), 1999-2006

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Chapter 4

50

60

70

80

90

100

White

Black AI/AN >1 Race

2002

Percent

Z

0

1999

2000

2004

Asian

2001

2003

2005

2006

50

60

70

80

90

100 Non-Hispanic White Hispanic

2001

2002

2005

Percent

2003

2004

0

Z

1999

2000

2006

Children
Key: AI/AN = American Indian or Alaska Native.

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Health Interview Survey,

1999-2006.

Reference population: Civilian noninstitutionalized population

under age 18.

Note: Insurance status is determined at the time of interview.

Children are considered uninsured if they lack private health

insurance, public assistance (including the State Children’s Health

Insurance Program), Medicare, Medicaid, a State-sponsored

health plan, other government-sponsored program, or a military

health plan, or if their only coverage is through the Indian Health

Service. This measure reflects the percentage of children who

were covered by health insurance at the time of interview.

◆ From 1999 to 2006, the gap between AI/ANs and Whites and between Hispanics and non-Hispanic

Whites in the percentage of children with health insurance decreased (Figure 4.38).

◆ In 2006, the percentage of children with health insurance was significantly lower for AI/AN children

than for White children (76.0% compared with 90.5%).

◆ In 2006, the percentage of children with health insurance was significantly lower for Hispanic

children than for non-Hispanic White children (80.7% compared with 93.8%).

◆ In 2006, the percentage of children with health insurance was significantly lower for poor (86.1%)

and near-poor children (84.0%) than for high-income children (96.9%).

National Quality Report, 2000

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Chapter 4

50

60

70

80

90

100

2001

2002

2005

Percent

Near Poor High Income

Poor Middle Income

2003

0

Z

1999

2000

2004

2006

Children
Older Adults

In 2006, 37.3 million people age 65 and over lived in the United States.50 Further, the percentage of the

population over age 65 is swiftly increasing. People age 65 and over represented 12.4% of the population

in 2006 but are expected to grow to about 20% of the population by 2030.51 The past century has seen

significant increases in life expectancy; in 2007, 65-year-olds could expect to live an additional 18.7

years.50 Nonetheless, older adults face greater health care concerns than younger populations. In 2006,

38.9% of noninstitutionalized older adults assessed their health as excellent or very good, compared with

65.1% of people ages 18-64,52 and most older adults have at least one chronic condition.

Older women outnumber older men by more than one-third.50 In addition, members of minority groups

are projected to represent more than 25% of the older population in 2030, up from about 16% in 2000.53

About 3.4 million older people lived below the poverty level in 2006, corresponding to a poverty rate of

9.4%.50 Another 2.2 million, or 6.2% of older people, were classified as near poor, with incomes

between 100% and 125% of the Federal poverty level.50

The Medicare program provides core health insurance to nearly all older Americans and reduces many

financial barriers to acute and post-acute care. The Medicare Prescription Drug Improvement and

Modernization Act of 2003 has added prescription drug and preventive benefits to Medicare and provides

extra financial help to people with low incomes. Therefore, differences in access to and quality of health

care tend to be smaller among Medicare beneficiaries than among younger populations.

Surveys of the general population often do not include enough older people to examine racial, ethnic, or

socioeconomic differences in health care. The NHDR relies on data from the Medicare Current

Beneficiary Survey to examine disparities in access to and quality of care. Findings presented here

highlight three quality measures and one access measure of particular importance to the older population:

Component of health care need Measure

Prevention Influenza vaccination, vision screening

Access to care Delayed care due to cost

Patient centeredness Health literacy

Quality of Health Care

Prevention: Influenza Vaccination

Influenza is responsible for significant morbidity and decreased productivity during outbreaks. Older

adults are at increased risk for complications from influenza infections. Vaccination is an effective

strategy to reduce illness and deaths due to influenza. The U.S. Preventive Services Task Force and the

Centers for Disease Control and Prevention recommend annual influenza vaccination of all older

individuals.

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Chapter 4 Older Adults
Figure 4.39. Medicare beneficiaries age 65 and over who had an influenza vaccination in the last

winter, by race (top left), ethnicity (top right), and income (bottom left), 1998, 2000, 2002, and 2004

Key: AI/AN = American Indian or Alaska Native; API = Asian or

Pacific Islander.

Source: Centers for Medicare & Medicaid Services, Medicare

Current Beneficiary Survey, 1998, 2000, 2002, and 2004.

Reference population: Medicare beneficiaries age 65 and over

living in the community.

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Chapter 4

50

60

70

80

90

100

White

Black

API AI/AN

2002

Percent

Z

0

1998

2000

2004

Total

Healthy People 2010

Target: 90%

50

60

70

80

90

100 Non-Hispanic White Hispanic

2002

Percent

2004

0

Z

1998

2000

Healthy People 2010

Target: 90%

50

60

70

80

90

100

2002

Percent

Near Poor High Income

Poor Middle Income

0

Z

1998

2000

2004

Healthy People 2010

Target: 90%

Older Adults
◆ From 1998 to 2004, the percentage of Medicare beneficiaries age 65 and over with an influenza

vaccination in the last winter increased overall from 68.7% to 71.7% (Figure 4.39).

◆ From 1998 to 2004, the gap between Blacks and Whites decreased. However, in 2004, the

percentage was still significantly lower for Blacks than for Whites (55.9% compared with 73.7%).

◆ During this period, the gap between Hispanics and non-Hispanic Whites increased. In 2004, the

percentage was also significantly lower for Hispanics than for non-Hispanic Whites (58.6%

compared with 74.6%).

◆ In 2004, the percentage was significantly lower for poor (61.3%), near-poor (68.6%), and middleincome (74.4%) beneficiaries than for high-income beneficiaries (77.6%).

◆ In 2004, the Healthy People 2010 target of 90% of older Americans with influenza vaccination was

not achieved by any population group.

Prevention: Vision Screening

Visual impairment is a common and potentially serious problem among older people. Personal safety

may be compromised as risks of falls and car accidents increase. Because eye problems are often not

recognized by older people, the U.S. Preventive Services Task Force recommends routine vision

screening.54

National Quality Report, 2000

Staying Healthy Priority Populations

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250

Chapter 4 Older Adults
Figure 4.40. Medicare beneficiaries age 65 and over who had an eye examination in the last 12

months, by race (top left), ethnicity (top right), and income (bottom left), 1998, 2000, 2002, and

2004

Key: AI/AN = American Indian or Alaska Native; API = Asian or

Pacific Islander.

Source: Centers for Medicare & Medicaid Services, Medicare

Current Beneficiary Survey, 1998, 2000, 2002, and 2004.

Reference population: Medicare beneficiaries age 65 and over

living in the community.

National Quality Report, 2000

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251

Chapter 4

25

35

45

55

65

75 White

Black

API

AI/AN

2002

Percent

Z

0

1998

2000

2004

25

35

45

55

65

75 Non-Hispanic White Hispanic

2002

Percent

2004

0

Z

1998

2000

25

35

45

55

65

75

2002

Percent

Near Poor High Income

Poor Middle Income

0

Z

1998

2000

2004

Older Adults
◆ From 1998 to 2004, the gap between Blacks and Whites in the percentage of Medicare beneficiaries

age 65 and over with an eye exam in the past year decreased. In 2004, there was no statistically

significant difference between Blacks and Whites (Figure 4.40).

◆ During this period, there were no statistically significant changes or differences between Hispanics

and non-Hispanic Whites.

◆ During this period, the gap between poor individuals and high-income individuals remained the

same. In 2004, poor (52.8%) and near-poor (58.0%) individuals were less likely than high-income

individuals (67.2%) to have had an eye exam in the past year.

Access to Care

Delayed Care Due to Cost

Timely delivery of appropriate care has been shown to improve health care outcomes and reduce health

care costs. Timely receipt of care is especially important for the older population due to their often

increased medical needs. Delayed health care can lead to diagnosis at a more advanced disease stage and

reduce opportunities for optimal treatment.xiv

Figure 4.41. Medicare beneficiaries age 65 and over with delayed care due to cost, by race (left),

ethnicity (right), and income (next page top), 1998, 2000, 2002, 2003, and 2005

xiv In this measure, delayed care due to cost is self-reported by patients.

National Quality Report, 2000

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252

Chapter 4

0

2

4

6

8

10 White

Black

2000

2002

Percent

1998

2003

2005

0

2

4

6

8

10 Non-Hispanic White

Hispanic

2000

2002

Percent

1998

2003

2005

Older Adults
Source: Centers for Medicare & Medicaid Services, Medicare

Current Beneficiary Survey, 1998, 2000, 2002, 2003, and 2005.

Reference population: Medicare beneficiaries age 65 and over

living in the community.

◆ The percentage of Medicare beneficiaries age 65 and over who delayed care due to cost was higher

for Hispanics compared with non-Hispanic Whites (7.8% compared with 4.4%; Figure 4.41).

◆ From 1998 to 2005, there were no significant changes in the gap between poor and high-income

people in the percentage of Medicare beneficiaries age 65 and over who delayed care due to cost. In

2005, the percentage delaying care was significantly higher for poor (9.5%), near-poor (6.9%), and

middle-income (3.6%) beneficiaries than for high-income beneficiaries (2.0%).

National Quality Report, 2000

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Chapter 4

0

2

4

6

8

10

2000

2002

Percent

Near Poor High Income

Poor Middle Income

1998

2003

2005

Older Adults
Focus on Health Literacy

Healthy People 2010’s Objective 11-2 is to improve Americans’ health literacy, defined as the capacity to

obtain, process, and understand basic health information and services needed to make appropriate health

care decisions.55 In 2003, the first-ever national assessment of health literacy was conducted—the Health

Literacy Component (HLC) of the National Assessment of Adult Literacy (NAAL). The HLC assesses

responses to health-related tasks presented in written form. These tasks fall into three categories:

clinical, prevention, and health system navigation.

The HLC tasks require familiarity with health-related words; experience with written materials, such as

drug labels and health insurance forms; or knowledge of how the health care system works. The HLC did

not measure the ability to obtain or understand information from nonprint sources.

There are racial and ethnic differences in health literacy, with minority adults having lower health literacy

than White adults, with the exception of Asians and Pacific Islanders.56 There is evidence that inadequate

health literacy is linked to all-cause mortality and cardiovascular mortality among older adults.57

The HLC measures the English health literacy of adults in the United States. Four million adults had

language barriers or cognitive or mental disabilities that prevented them from taking the NAAL;

therefore, they are not included in the results presented below. The NAAL captures no information on

these adults’ literacy in another language.

The NAAL groups adults without language barriers into four performance levels:

◆ Below basic: This performance level indicates that a person can understand no more than the most

simple and concrete skills (e.g., circle the date of a medical appointment on a hospital appointment

slip). Thirty million adults were found to have below basic health literacy; 7 million of these were

unable to answer the simplest of questions and were determined to be nonliterate in English.

◆ Basic: This performance level indicates that a person can perform the skills needed for simple and

everyday activities (e.g., give two reasons a person with no symptoms of a specific disease should be

tested for the disease, based on information in a clearly written pamphlet). Forty-seven million

adults were found to have basic health literacy.

◆ Intermediate: This performance level indicates that a person can perform the skills needed for

moderately challenging activities (e.g., identify three substances that may interact with an over-thecounter drug to cause a side effect, using the information on the over-the-counter drug label). One

hundred and fourteen million adults were found to have intermediate health literacy.

◆ Proficient: This performance level indicates that a person can perform the skills needed for more

complex and challenging activities (e.g., find the information required to define a medical term by

searching through a complex document) needed to manage health and prevent disease. Twenty-six

million adults were found to have proficient health literacy.

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

254

Chapter 4 Focus on Health Literacy
Racial and ethnic disparities in health literacy were discussed in the 2007 NHDR.58 Findings on health

literacy continue to be a topic of interest in the area of health disparities. This year, differences by age are

discussed here.

Figure 4.42. Adults at each health literacy level, by age, 2003

Source: National Assessment of Adult Literacy, Health

Literacy Component, 2003.

Note: Adults are defined as people age 16 years and

over living in households or prisons. Adults who could

not be interviewed because of language spoken or

cognitive or mental disabilities (3% in 2003) are

excluded from this figure.

◆ Adults age 65 and over were more likely to have below basic or basic health literacy skills than

those under age 65 (Figure 4.42).

◆ The health literacy of adults over age 75 was significantly worse than adults ages 65 to 75. More

than two-thirds of adults over age 75 had below basic or basic health literacy.

◆ Age had relatively little relationship to health literacy among adults who were under age 65.

National Quality Report, 2000

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255

Chapter 4

0

20

40

60

80

100

Percent

16-49

Proficient

Basic

50-64

Intermediate

Below Basic

65-75 Over 75

Focus on Health Literacy
Residents of Rural Areas

About one in five Americans lives in a nonmetropolitan area.59 Compared with their urban counterparts,

rural residents are more likely to be older, poor,60 and in fair or poor health and to have chronic

conditions.59 Rural residents are less likely to receive recommended preventive services and report, on

average, fewer visits to health care providers.61

Although 20% of Americans live in rural areas,xv only 9% of physicians in America practice in those

settings.62 Nurse practitioners, nurse midwives, and physician assistants also deliver care. Multiple

programs and services 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.

Many rural residents depend on small rural hospitals for their care. There are approximately 2,000 rural

hospitals throughout the country,63 1,500 of which have 50 or fewer beds. Most of these hospitals are

critical access hospitals that have 25 or fewer beds. Rural hospitals largely provide primary care and

chronic disease management. They face unique challenges due to their size and case mix. During the

1980s, many were forced to close because of financia1 losses64; however, finances of small rural

hospitals have improved and few closures have occurred since 2003.

Transportation needs are pronounced among rural residents, who must travel longer distances to reach

health care delivery sites. Of the nearly 1,000 “frontier counties”xvi in the Nation, most have limited

health care services and many do not have any.65

Many measures of relevance to residents of rural areas are tracked in the NHDR. Findings presented here

highlight four quality measures and one access measure of particular importance to residents of rural

areas, with additional geographic data from metropolitan areas:

Component of health care need Measure

Prevention Prenatal care and maternal health

Management Recommended services for diabetes

Treatment Recommended care for colorectal cancer

Timeliness Care for illness or injury as soon as wanted

Access to care Health insurance

xv 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.

xvi “Frontier counties” have a population density of less than 7 people per square mile; thus, residents travel long

distances for care.

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

256

Chapter 4 Residents of Rural Areas
In previous NHDRs, detailed geographic typologies were applied to two AHRQ databases—MEPS and

HCUP—to define variations in health care quality and access for a range of rural and urban locations.

This year, in addition to presenting data from MEPS and HCUP, the NHDR presents a measure from the

National Vital Statistics System-Natality. Federal definitions of micropolitan and noncore statistical areas

(not metropolitan or micropolitan areas) published in June 2003 are used.66 In addition, urban influence

codes are used to subdivide metropolitan areas into large and small metropolitan areas. Thus, categories

used in this section of the NHDR may be defined as follows:

◆ Metropolitan (total): all metropolitan areas.

◆ Large central metropolitan statistical area: central counties in metropolitan area of 1 million or more

inhabitants.

◆ Large fringe metropolitan statistical area: outlying (suburban) counties in metropolitan areas of 1

million or more inhabitants.

◆ Medium metropolitan statistical area: counties in metropolitan areas of 250,000-999,999 inhabitants.

◆ Small metropolitan statistical area: metropolitan area of 50,000-249,999 inhabitants.

◆ Nonmetropolitan (total): all nonmetropolitan areas.

◆ Micropolitan statistical area: counties with an urban cluster of at least 10,000 but fewer than 50,000

inhabitants.

◆ Noncore statistical area (rural): not metropolitan or micropolitan.

Urban-rural contrasts for measures from MEPS and HCUP compare residents of rural statistical areas

(including both micropolitan and noncore statistical areas) with residents of urban statistical areas

(including both large central, large fringe, medium, and small metropolitan statistical areas). Sample

sizes are often too small to provide reliable estimates for noncore statistical areas, limiting the ability to

assess disparities among residents of these areas.

Quality of Health Care

Prevention: Prenatal Care and Maternal Health

Childbirth and reproductive care are the most common reasons for women of childbearing age to use

health care services, and childbirth is the most common reason for hospital admission.67 It is

recommended that women begin receiving prenatal care in the first trimester of pregnancy.

National Quality Report, 2000

Priority Populations Staying Healthy

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257

Chapter 4 Residents of Rural Areas
Figure 4.43. Women who completed a pregnancy in the last 12 months who first received

prenatal care in the first trimester, selected States, by geographic location, stratified by race (top

left), ethnicity (top right), and education (bottom left), 2005

Large Central Metropolitan = central counties in metropolitan

areas ≥1 million inhabitants.

Large Fringe Metropolitan = outlying (suburban) counties in

metropolitan areas ≥1 million inhabitants.

Medium Metropolitan = counties in metropolitan areas of

250,000-999,999 inhabitants.

Small Metropolitan = counties in metropolitan areas of 50,000-

249,999 inhabitants.

Micropolitan = counties in an area with an urban cluster of

10,000-49,999 inhabitants.

Noncore = <10,000 inhabitants.

Key: AI/AN = American Indian or Alaska Native; API = Asian

Pacific Islander.

Source: Centers for Disease Control and Prevention, National

Center for Health Statistics, National Vital Statistics SystemNatality, 2005.

Reference population: Women with live births.

Note: Data for 2005 include the 39 reporting areas (37 States,

DC, and New York City) that used 1989 revision of the U.S.

Standard Certificate of Live Birth in 2005. Reporting areas that

have adopted the 2003 revision are excluded because prenatal

data based on the 2003 revision are not comparable with data

based on 1989 and earlier revisions of the U.S. Standard

Certificate of Live Birth.

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

258

Chapter 4

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

White

Black

API

AI/AN

Total

Noncore

0

Z

60

65

70

75

80

85

90

95

100

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Healthy People 2010

Target: 90%

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Hispanic

Non-Hispanic White

Noncore

0

Z

60

65

70

75

80

85

90

95

100

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Healthy People 2010

Target: 90%

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Noncore

0

Z

60

65

70

75

80

85

90

95

100

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Healthy People 2010

Target: 90%

<High School

High School Grad

Some College

Residents of Rural Areas
◆ In 2005, there were no significant differences observed between geographic locations in the

percentage of women who initiated prenatal care in the first trimester (Figure 4.43).

◆ In micropolitan and noncore (rural) areas, there were significant racial and educational disparities.

In these areas, Black women were less likely than White women to receive prenatal care

(micropolitan, 73.9% compared with 83.2%; noncore, 74.1% compared with 83.4%). In

micropolitan areas, APIs were also less likely than Whites to receive prenatal care (73.7% compared

with 83.2%). In both areas, women with less than a high school education were less likely than

women with at least some college education to receive prenatal care (micropolitan, 67.4% compared

with 89.8%; noncore, 66.6% compared with 89.5%).

◆ In large central metropolitan areas, there were significant racial and education disparities. In these

areas, Black women were less likely than White women to receive prenatal care (75.9% compared

with 86.0%). Individuals with less than a high school education (76.7%) and high school graduates

(81.9%) were less likely to receive prenatal care than individuals with at least some college

education (91.2%).

◆ In medium and small metropolitan areas, there were significant ethnic and educational disparities.

Hispanic women were less likely than non-Hispanic White women to receive prenatal care (medium,

75.6% compared with 88.5%; small, 68.2% compared with 87.2%). Women with less than a high

school education were less likely than women with at least some college education to receive

prenatal care (medium, 71.3% compared with 91.2%; small, 68.8% compared with 90.3%).

◆ In 2005, only women with at least some college education who lived in metropolitan areas and nonHispanic White women in large central and large fringe metropolitan areas achieved the Healthy

People 2010 target of 90% of women receiving prenatal care in the first trimester.

National Quality Report, 2000

Priority Populations Staying Healthy

National Healthcare Disparities Report, 2008

259

Chapter 4 Residents of Rural Areas
Management: Recommended Services for Diabetes

The NHDR presents a composite measure that tracks receipt of three recommended services for effective

management of diabetes: hemoglobin A1c testing, dilated eye examination, and foot examination in the

past year.

Figure 4.44. Composite measure: 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), by geographic location, 2005

Large Central Metropolitan = central counties in metropolitan

areas ≥1 million inhabitants.

Large Fringe Metropolitan = outlying (suburban) counties in

metropolitan areas ≥1 million inhabitants.

Medium Metropolitan = counties in metropolitan areas of

250,000-999,999 inhabitants.

Small Metropolitan = counties in metropolitan areas of 50,000-

249,999 inhabitants.

Micropolitan = counties in an area with an urban cluster of

10,000-49,999 inhabitants

Noncore = <10,000 inhabitants.

Source: Agency for Healthcare Research and Quality, Medical

Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population

age 40 and over.

Note: Recommended services for diabetes are (1) hemoglobin

A1c testing, (2) dilated eye examination, and (3) foot

examination. Sample sizes were too small to provide estimates

by race, ethnicity, income, or education in all areas except

metropolitan (total).

◆ In 2005, the percentage of diabetes patients who received all three recommended services for

diabetes was lower for patients in noncore areas overall than in metropolitan areas (31.9% compared

with 41.9%; Figure 4.44).

◆ In metropolitan areas (total), there were significant ethnic, income, and educational disparities (data

not shown). Hispanics were less likely than non-Hispanic Whites to receive recommended care for

diabetes (33.6% compared with 45.4%). Poor (32.4%), near-poor (31.1%), and middle-income

(38.6%) individuals were less likely than high-income individuals (54.6%) to receive recommended

care for diabetes. Individuals with less than a high school education were less likely than individuals

with at least some college education to receive recommended care for diabetes (33.2% compared

with 48.4%).

National Quality Report, 2000

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260

Chapter 4

Percent

Medium Metropolitan

Small Metropolitan

Nonmetropolitan (Total)

Noncore

0

10

20

30

40

50

60

70

80

90

100

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Micropolitan

Residents of Rural Areas
Treatment: Recommended Care for Colorectal Cancer

Figure 4.45. Patients with colon cancer who received surgical resection of colon cancer that

included at least 12 lymph nodes pathologically examined, by geographic location, stratified by

race (top left), ethnicity (top right), and income (bottom left), 2005

Metropolitan = Large and small metropolitan areas.

Large Metropolitan = metropolitan areas of ≥1 million residents.

Small Metropolitan = metropolitan areas of <1 million residents.

Micropolitan = adjacent to large and small metropolitan areas.

Noncore = adjacent to micropolitan areas or does not contain a

town of at least 2,500 residents.

Source: Commission on Cancer, American College of Surgeons

and American Cancer Society, National Cancer Data Base, 2005.

Note: Definitions of metropolitan, large metropolitan, small

metropolitan, and noncore are based on U.S. Department of

Agriculture Economic Research Service 2003 urban influence

codes. Data did not meet the criteria for statistical reliability for

Asians in micropolitan and noncore areas; Hispanics in

micropolitan and noncore areas; high-income individuals in small

metropolitan, micropolitan, and noncore areas; middle-income

individuals in micropolitan and noncore areas; poor individuals in

small metropolitan and micropolitan areas; and near-poor

individuals in noncore areas.

National Quality Report, 2000

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National Healthcare Disparities Report, 2008

261

Chapter 4

Percent

Small Metropolitan

Noncore

0

10

20

30

40

50

60

70

80

90

100

Metropolitan (Total)

Large Metropolitan

Micropolitan

White

Black

Asian

Total

Percent

Small Metropolitan

Noncore

0

10

20

30

40

50

60

70

80

90

100

Metropolitan (Total)

Large Metropolitan

Micropolitan

Hispanic

Non-Hispanic White

Percent

Small Metropolitan

Noncore

0

10

20

30

40

50

60

70

80

90

100

Metropolitan (Total)

Large Metropolitan

Micropolitan

Poor

Near Poor

Middle Income

High Income

Residents of Rural Areas
◆ There are statistically significant differences among geographic locations in the percentage of colon

cancer patients who received recommended treatment. Patients in micropolitan areas (51.6%) were

less likely to receive recommended treatment than patients in metropolitan areas (61.0%; Figure

4.45).

◆ In small metropolitan areas, Asian patients with colon cancer were more likely than White patients

with colon cancer to receive recommended treatment (70.7% compared with 59.5%).

◆ In metropolitan areas, the overall percentages of poor patients with colon cancer (58.0%) and nearpoor (59.5%) patients who received recommended treatment were lower than the percentage of

high-income patients (66.8%).

◆ Findings for other geographic locations and other comparisons were not statistically significant.

National Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

262

Chapter 4 Residents of Rural Areas
Timeliness: Care for Illness or Injury as Soon as Wanted

Timely delivery of appropriate care has been shown to improve health care outcomes and reduce health

care costs. In addition, when patients need or want care, having access to that care improves their health

care experience, which may further promote health.

Figure 4.46. Adults who needed care right away for an illness, injury, or condition last 12 months

who sometimes or never got care as soon as wanted, by geographic location, stratified by

income (left) and education (right), 2005

Large Central Metropolitan = central counties in metropolitan areas ≥1 million inhabitants.

Large Fringe Metropolitan = outlying (suburban) counties in metropolitan areas ≥1 million inhabitants.

Medium Metropolitan = counties in metropolitan areas of 250,000-999,999 inhabitants.

Small Metropolitan = counties in metropolitan areas of 50,000-249,999 inhabitants.

Micropolitan = counties in an area with an urban cluster of 10,000-49,999 inhabitants.

Noncore = <10,000 inhabitants.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Data are not available for all income or education groups in noncore areas. Data are not available for poor and high-income

groups in small metropolitan areas or for high-income groups in micropolitan areas.

National Quality Report, 2000

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263

Chapter 4

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Total

Noncore

0

10

20

30

40

50

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Poor

Near Poor

Middle Income

High Income

Nonmetropolitan (Total)

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Noncore

0

10

20

30

40

50

Large Fringe Metropolitan

Large Central Metropolitan

Metropolitan (Total)

<High School

High School Grad

Some College

Nonmetropolitan (Total)

Residents of Rural Areas
◆ There were no significant differences observed between different geographic locations in the overall

rate of adults who sometimes or never get care for illness or injury as soon as wanted (Figure 4.46).

◆ There were significant differences by income in nonmetropolitan areas. Poor (19.0%), and nearpoor (18.0%) individuals were more likely than high-income individuals (9.4%) to sometimes or

never get care for illness or injury as soon as wanted in these areas.

◆ Differences by education were also observed in nonmetropolitan areas. In micropolitan areas,

individuals with less than a high school education (21.2%) were more likely than individuals with at

least some college education (12.1%) to sometimes or never get care for illness or injury as soon as

wanted.

◆ There were significant differences by income in metropolitan locations. Poor, near-poor, and

middle-income individuals were more likely than high-income individuals to sometimes or never get

care for illness or injury as soon as wanted in large central metropolitan and large fringe

metropolitan areas.

◆ There were also some differences by education in metropolitan locations. Individuals with less than

a high school education were more likely than individuals with at least some college education to

sometimes or never get care for illness or injury as soon as wanted in small and medium

metropolitan areas.

Access to Health Care

Health Insurance

Access to health care services is a prerequisite to receipt of care, yet many Americans still face barriers to

care. Data for prolonged periods of uninsurance (no insurance coverage for a full year) are presented.

National Quality Report, 2000

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National Healthcare Disparities Report, 2008

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Chapter 4 Residents of Rural Areas

In rural areas, Hispanics were more than twice

as likely as non-Hispanic Whites to be

uninsured all year.
Figure 4.47. Adults under age 65 who were uninsured all year, by geographic location, stratified

by race (left), ethnicity (right), income (next page left), and education (next page right), 2005

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Chapter 4

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Total

Noncore

0

10

20

30

40

50

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

White

Black

Asian

Non-Metropolitan (Total)

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Non-Hispanic White

Noncore

0

10

20

30

40

50

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Hispanic

Non-Metropolitan (Total)

Residents of Rural Areas
Large Central Metropolitan = central counties in metropolitan areas ≥1 million inhabitants.

Large Fringe Metropolitan = outlying (suburban) counties in metropolitan areas ≥1 million inhabitants.

Medium Metropolitan = counties in metropolitan areas of 250,000-999,999 inhabitants.

Small Metropolitan = counties in metropolitan areas of 50,000-249,999 inhabitants.

Micropolitan = counties in an area with an urban cluster of 10,000-49,999 inhabitants.

Noncore = <10,000 inhabitants.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2005.

Reference population: Civilian noninstitutionalized population age 18 and over.

Note: Estimates for Asians in small metropolitan, nonmetropolitan, micropolitan, and noncore areas did not meet criteria for statistical

reliability and are not reported here.

◆ There were statistically significant differences within metropolitan areas in the percentage of adults

under age 65 who were uninsured all year (lowest percentage of uninsured overall was in large

fringe metropolitan areas, 11.1%; Figure 4.47), as well as between metropolitan and nonmetropolitan

areas. In metropolitan areas, small metropolitan areas had a higher percentage of adults who were

uninsured than large fringe metropolitan areas (12.7% compared with 11.1%). In nonmetropolitan

areas, micropolitan areas had a higher percentage of adults who were uninsured than large fringe

metropolitan areas (13.1% compared with 11.1%).

◆ In noncore areas, there were significant ethnic, income, and education disparities. Hispanics were

more than twice as likely as non-Hispanic Whites to be uninsured all year (39.0% compared with

16.0%). Poor individuals and near-poor individuals (23.2% and 26.6%, respectively) were more

likely than high-income individuals (7.7%) to be uninsured all year. Individuals with less than a

high school education (38.5%) and high school graduates (21.4%) were more likely than individuals

with at least some college education (12.8%) to be uninsured all year.

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Chapter 4 Residents of Rural Areas

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Noncore

0

10

20

30

40

50

Large Central Metropolitan

Large Fringe Metropolitan

Metropolitan (Total)

Non-Metropolitan (Total)

Poor

Near Poor

Middle Income

High Income

Percent

Medium Metropolitan

Small Metropolitan

Micropolitan

Noncore

0

10

20

30

40

50

Large Fringe Metropolitan

Large Central Metropolitan

Metropolitan (Total)

<High School

High School Grad

Some College

Non-Metropolitan (Total)
◆ In micropolitan areas, there were significant racial, ethnic, income, and education disparities. Blacks

were more likely than Whites to be uninsured all year (21.2% compared with 12.3%). Hispanics

were almost twice as likely as non-Hispanic Whites to be uninsured all year (22.5% compared with

11.4%). Poor individuals (22.9%), near-poor individuals (21.6%), and middle-income individuals

(10.9%) were also more likely than high-income individuals (6.1%) to be uninsured all year.

Individuals with less than a high school education (30.0%) and high school graduates (15.4%) were

less likely than individuals with at least some college education (9.5%) to be uninsured all year.

◆ Large central metropolitan areas had significant ethnic and income disparities. In these areas,

Hispanics were almost three times as likely as non-Hispanic Whites to be uninsured all year (30.4%

compared with 10.6%). Poor individuals (25.2%), near-poor individuals (27.5%), and middleincome individuals (18.1%) were also more likely than high-income individuals (8.7%) to be

uninsured all year.

◆ Large fringe metropolitan areas had significant ethnic, income, and education disparities. In these

areas, Hispanics were more than three times as likely to be uninsured all year (27.8% compared with

8.2%). Poor individuals (23.0%), near-poor individuals (23.6%), and middle-income individuals

(13.1%) were also more likely than high-income individuals (4.9%) to be uninsured all year.

Individuals with less than a high school education (30.2%) and high school graduates (16.4%) were

less likely than individuals with at least some college education (7.5%) to be uninsured all year.

◆ Medium metropolitan areas had significant ethnic, income, and education disparities. In these areas,

Hispanics were almost three times as likely to be uninsured all year (26.1% compared with 9.6%).

Poor individuals (26.8%), near-poor individuals (21.1%), and middle-income individuals (10.8%)

were also more likely than high-income individuals (4.2%) to be uninsured all year. Individuals

with less than a high school education (30.6%) and high school graduates (16.7%) were less likely

than individuals with at least some college education (8.6%) to be uninsured all year.

◆ Small metropolitan areas had significant ethnic, income, and education disparities. In these areas,

Hispanics were almost twice as likely to be uninsured all year (20.3% compared with 11.7%). Poor

individuals (18.7%), near-poor individuals (21%), and middle-income individuals (13.1%) were also

more likely than high-income individuals (6.6%) to be uninsured all year. Individuals with less than

a high school education (28.7%) and high school graduates (18.3%) were less likely than individuals

with at least some college education (9.9%) to be uninsured all year.

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Chapter 4 Residents of Rural Areas
Individuals With Disabilities or Special Health Care Needs

Individuals with disabilities or special health care needs include individuals with disabilities, individuals

who use nursing home and home health care or end-of-life health care, and children with special heath

care needs (CSHCN). Many measures of relevance to individuals with special health care needs are

tracked in the NHDR.

In this year’s report, data on quality and access are presented for adults with disabilities and CSCHN.

This is the second year in which the Adults With Disabilities section has been expanded to include more

analyses and additional data sources using a comparable measure of disability. In this year’s report, the

Adults With Disabilities section uses data from the National Health Interview Survey (NHIS) for the first

time. In the 2007 report, this section used MEPS data.

The appendix tables in this year’s report include activity limitations as a stub variable for all NHIS and

MEPS appendix tables. The goal for future reports is to include more information about individuals with

disabilities using NHIS, MEPS, and additional data sources. As in previous reports, data on quality and

access are presented for CSHCN.

Adults With Disabilities

Component of health care need Measure

Prevention Pneumococcal vaccination for adults age 65 and over

Access to care Private health insurance for adults ages 18-64; specific

source of ongoing care; and use of hospital, emergency

department, or clinic as a source of ongoing care

Children With Special Health Care Needs

Component of health care need Measure

Management Care coordination

Patient centeredness Family-centered care

Access to care Health insurance status; adequacy of health insurance

Additionally, findings for people who use nursing home care are presented in the section on nursing

home, home health, and hospice care in Chapter 2, Quality of Health Care.

Adults With Disabilities

In reaching its goal to include more information about individuals with disabilities, AHRQ convened a

disabilities subgroup of the NHQR/NHDR Interagency Work Group with the assistance of the

Interagency Subcommittee on Disability Statistics of the Interagency Committee on Disability Research.

The charge to this group was to advise AHRQ on measures of disabilities from existing data that could

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268

Chapter 4 Individuals With Disabilities or Special Health Care Needs
track disparities for disabled individuals in quality of and access to care for the NHDR and that would be

comparable across national surveys. For this initial effort, the subgroup focused on measures for adults, a

population for which the most survey data are available.

Several ways of defining and measuring disability exist. Among the more common approaches are to

identify individuals who have problems in performing everyday functions such as vision, hearing,

communication, self-care, mobility, learning, and behavior; have difficulty with complex activities such as

working; or meet the eligibility criteria for important income maintenance or training programs (e.g.,

Social Security Disability Income or vocational rehabilitation). However, a particular challenge in

reporting on racial, ethnic, and socioeconomic differences related to disability is that many data

collections do not capture disability. When data are collected, the collection methods are different.

The International Classification of Functioning, Disability and Health (ICF)68 was adopted by the

disabilities subgroup as a model to guide the deliberations. The subgroup carefully reviewed questions

and response categories for three national surveys (NHIS, MEPS, and Medicare Current Beneficiary

Survey) for consistencies and discrepancies in measurement of the major domains of disabilities in

the ICF.

For the 2008 NHDR, as for the 2007 NHDR, AHRQ is using a broad, inclusive measure of disability that

is intended to be consistent with statutory definitions of disability, such as the first criterion of the

Americans With Disabilities Act of 1990, 42 U.S.C. §12181 et seq. (i.e., having a physical or mental

impairment that substantially limits one or more major life activities69,70) and Federal program definitions

based on the Americans With Disabilities Act. For the purpose of the NHDR, people with disabilities are

those with physical, sensory, and/or mental health conditions that can be associated with a decrease in

functioning in such day-to-day activities as bathing, walking, doing everyday chores, and/or engaging in

work or social activities. 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 limitations encountered when the person, in interaction

with his or her environment, attempts to participate in community 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 disability3,71 and is consistent with the

ICF separation of activities and participation domains.1 These two categories are not mutually exclusive;

people may have limitations in both basic activities and complex activities.

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Chapter 4 Individuals With Disabilities or Special Health Care Needs
Prevention: Pneumococcal Vaccination for Adults Age 65 and Over

Vaccination is an effective strategy for reducing illness, death, and disparities associated with

pneumococcal disease and influenza.72,73 Receiving a pneumococcal vaccination is particularly important

for high-risk individuals, including older adults, adults with specified chronic conditions, and residents of

long-term care facilities.74,75 Such groups are overrepresented by individuals with disabilities. In 2006,

the overall percentage of adults age 65 and over who had ever received a pneumococcal vaccination was

57.3% (data not shown). The Healthy People 2010 target is to have 90% of adults age 65 and over

receive a pneumococcal vaccination.

Figure 4.48. Adults age 65 and over who ever received pneumococcal vaccination by race,

ethnicity, and family income, stratified by activity limitation, 2006

Basic = basic activity limitation (i.e., limitation in mobility or

other basic person-level functioning).

Complex = complex activity limitation (i.e., limitation in

ability to participate in community life).

Neither = neither basic nor complex activity limitations.

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health

Interview Survey, 2006.

Reference population: Civilian noninstitutionalized

population age 65 and over.

Note: Estimates are age adjusted to the 2000 U.S.

standard population. Data for Asians and Hispanics with

complex limitations did not meet criteria for statistical

reliability.

◆ For all adults age 65 and over, those with basic activity limitations were significantly more likely

than those with neither limitation to have had a pneumococcal vaccination (63.1% compared with

54.4%; Figure 4.48).

◆ For White, non-Hispanic White, poor, low-income, and middle-income adults age 65 and over, those

with basic activity limitations were significantly more likely than those with neither limitation to

have had a pneumococcal vaccination.

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Chapter 4

Asian

Percent

Basic Complex

Non-Hispanic White

Hispanic

Poor

Middle Income

Low Income

High Income

Total

White

Black

0

25

50

75

100

Non-Hispanic Black

Neither

Healthy People 2010

Target: 90%

Individuals With Disabilities or Special Health Care Needs
◆ For middle-income adults age 65 and over, those with complex activity limitations were significantly

more likely than those with neither limitation to have had a pneumococcal vaccination (70.7%

compared with 55.3%). Differences between those with complex activity limitations and those with

neither limitation were not significant for any other income, race, or ethnic group among adults age

65 and over.

◆ For adults age 65 and over, Blacks were significantly less likely than Whites and non-Hispanic

Blacks were significantly less likely than non-Hispanic Whites to have had a pneumococcal

vaccination overall and within each of the three activity limitation groups (basic, complex, and

neither). For adults age 65 and over, Asians were significantly less likely than Whites and Hispanics

were significantly less likely than non-Hispanic Whites to have had a pneumococcal vaccination for

those with basic activity limitations and those with neither limitation.

◆ Poor adults age 65 and over were significantly less likely than high-income individuals to have had a

pneumococcal vaccination among those with basic activity limitations and those with neither

limitation. Poor adults age 65 and over were significantly less likely than those with high income to

have had a pneumococcal vaccination among those with neither limitation (37.1% vs. 60.3%).

Access to Care: Private Health Insurance for Adults Ages 18-64

Health insurance facilitates entry into the health care system and private health insurance may be

associated with the amount and quality of health care received.76 Private health insurance is mainly

associated with individuals’ employment and may be less available to people with disabilities because

individuals with disabilities are less likely to be employed.77

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Chapter 4 Individuals With Disabilities or Special Health Care Needs

Among adults, those with basic activity

limitations were more likely than those with no

limitations to use hospitals, emergency rooms,

or clinics as their source of ongoing care.
Figure 4.49. Adults ages 18-64 with any private health insurance, by race, ethnicity, and family

income, stratified by activity limitation, 2006

Basic = basic activity limitation (i.e., limitation in mobility or

other basic person-level functioning).

Complex = complex activity limitation (i.e., limitation in

ability to participate in community life).

Neither = neither basic nor complex activity limitations.

Key: NH = non-Hispanic.

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health

Interview Survey, 2006.

Reference population: Civilian noninstitutionalized

population ages 18-64.

Note: Estimates are not age adjusted to the 2000 U.S.

standard population.

◆ For all adults ages 18-64, those with complex activity limitations were significantly less likely than

those with basic activity limitations to have any private health insurance (39.1% compared with

43.2%; Figure 4.49). Those with basic activity limitations were significantly less likely than those

with neither limitation to have any private health insurance (43.2% compared with 72.0%). This

same pattern (those with complex activity limitations being less likely than those with basic activity

limitations to have private insurance and those with basic activity limitations being less likely than

those with neither to have private insurance) holds for Blacks and non-Hispanic Blacks.

◆ For White, Asian, non-Hispanic White, Hispanic, poor, low-income, middle-income, and highincome adults ages 18-64, those with basic or complex activity limitations were significantly less

likely than those with neither limitation to have any private health insurance.

◆ For adults ages 18-64, Blacks were significantly less likely than Whites, and non-Hispanic Blacks

and Hispanics were significantly less likely than non-Hispanic Whites, to have any private health

insurance within each of the three activity limitation groups (basic, complex, and neither).

◆ Poor, low-income, and middle-income adults ages 18-64 were significantly less likely than highincome individuals to have any private health insurance within each of the three activity limitation

groups (basic, complex, and neither). Adults ages 18-64 with basic activity limitations and high

income were more than eight times as likely as those who were poor to have any private health

insurance (80.7% vs. 9.3%).

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Chapter 4

Asian

Percent

Complex

Basic

Non-Hispanic White

Hispanic

Poor

Middle Income

Low Income

High Income

Total

White

Black

0

25

50

75

100

Non-Hispanic Black

Neither

Individuals With Disabilities or Special Health Care Needs
Access to Care: Specific Source of Ongoing Care

People with a usual source of care (a facility where one regularly receives ongoing care) experience

improved health outcomes and reduced disparities (smaller differences between groups)78 and costs.79

In 2006, the overall percentage of adults who had a specified source of ongoing care was 86.1 (data not

shown). The Healthy People 2010 target is to have 96% of adults with a source of ongoing care.

Figure 4.50. Adults with a specific source of ongoing care, by race, ethnicity, and family income,

stratified by activity limitation, 2006

Basic = basic activity limitation (i.e., limitation in mobility or

other basic person-level functioning).

Complex = complex activity limitation (i.e., limitation in

ability to participate in community life).

Neither = neither basic nor complex activity limitations.

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health

Interview Survey, 2006.

Reference population: Civilian noninstitutionalized

population age 18 and over.

Note: Estimates are age adjusted to the 2000 U.S.

standard population.

◆ For Hispanic, poor, or low-income adults age 18 and over, those with basic or complex activity

limitations were significantly more likely than those with neither limitation to have a specific source

of ongoing care (Figure 4.50). For Black or non-Hispanic Black adults age 18 and over, those with

basic activity limitations were significantly more likely than those with neither limitation to have a

specific source of ongoing care. Asian adults age 18 and over with complex activity limitations

were significantly more likely than those with neither limitation to have a specific source of ongoing

care (93.2% compared with 84.8%).

◆ For adults age 18 and over with neither limitation, Hispanics were significantly less likely than nonHispanic Whites to have a specific source of ongoing care. Poor and low-income adults with neither

limitation were significantly less likely than high-income adults to have a specific source of ongoing

care. None of the other racial, ethnic, or income differences were statistically significant within any

of the three activity limitation groups.

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Chapter 4

Asian

Percent

Complex

Basic

Non-Hispanic White

Hispanic

Poor

Middle Income

Low Income

High Income

Total

White

Black

0

25

50

75

100

Non-Hispanic Black

Neither

Healthy People 2010

Target: 96%

Individuals With Disabilities or Special Health Care Needs
Access to Care: Use of Hospital, Emergency Room, or Clinic as a

Source of Ongoing Care

In many cases, individuals have a source of ongoing care, but it is not a primary care physician or other

health professional who can be seen regularly. Some people use hospitals, emergency rooms, or clinics as

a source of ongoing care. Although these may meet certain patients’ needs, they may not always provide

the continuity of care associated with a regular primary care provider.

Figure 4.51. Adults who identified a hospital, emergency room, or clinic as a source of ongoing

care, by race, ethnicity, and family income, stratified by activity limitation, 2006

Basic = basic activity limitation (i.e., limitation in mobility

or other basic person-level functioning).

Complex = complex activity limitation (i.e., limitation in

ability to participate in community life).

Neither = neither basic nor complex activity limitations.

Source: Centers for Disease Control and Prevention,

National Center for Health Statistics, National Health

Interview Survey, 2006.

Reference population: Civilian noninstitutionalized

population age 18 and over.

Note: Estimates are age adjusted to the 2000 U.S.

standard population. Data for Asians with complex

limitations did not meet criteria for statistical reliability.

◆ Among adults age 18 and over, those with basic activity limitations were more likely than those with

neither limitation to use hospitals, emergency rooms, or clinics as their source of ongoing care

(22.4% compared with 15.0%; Figure 4.51). This finding was also true for those with complex

activity limitations (23.4% compared with 15.0%).

◆ Among White, Hispanic, and low-income adults age 18 and over, those with basic or complex

activity limitations were significantly more likely than those with neither limitation to use hospitals,

emergency rooms, or clinics as a source of ongoing care. Among Black, non-Hispanic White, nonHispanic Black, and poor adults age 18 and over, those with complex activity limitations were

significantly more likely than those with neither limitation to use hospitals, emergency rooms, or

clinics as a source of ongoing care. Asian adults age 18 and over with basic activity limitations were

significantly more likely than those with neither limitation to use hospitals, emergency rooms, or

clinics as a source of ongoing care (36.2% compared with 14.5%).

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Chapter 4

Asian

Percent

Complex

Basic

Non-Hispanic White

Hispanic

Poor

Middle Income

Low Income

High Income

Total

White

Black

0

25

50

75

100

Non-Hispanic Black

Neither

Individuals With Disabilities or Special Health Care Needs
Children With Special Health Care Needs

Addressing questions on access to and quality of care for children with chronic conditions is difficult due

to the relatively low prevalence of most conditions in children.80,81,82 A standard definition of CSHCN

was developed in 1995.80,83 This definition was subsequently used to develop the CSHCN Screener

Questionnaire80 and was included in the 2001 and 2005-2006 National Survey of Children With Special

Healthcare Needs (NSCSHCN),84,85,86 among other surveys.

According to MEPS, in 2004, approximately 13.8 million children, or 20% of the child population ages

0-17, were identified as having a special health care need (i.e., a specific chronic condition with a

functional limitation or other consequence). Among the most highly prevalent chronic conditions of

childhood in 2005 were asthma (13% of children under age 18), upper respiratory allergies (12% of

children under age 18), learning disabilities (7% of children ages 3-17), and attention-deficit/hyperactivity

disorder (7% of children ages 3-17).87 Other conditions that may affect CSHCN include depression,

spina bifida, hemophilia, HIV infection, cystic fibrosis, and metabolic disorders.88

Having higher health care needs makes CSHCN susceptible to cost, quality, and access weaknesses in the

health care system.89 Because they need more medical care, CSHCN have higher medical expenses, on

average, than other children.80,84,90 For more than one in five CSHCN, costs of care caused financial

problems for their families.85

In addition to financial burdens, families of CSHCN spend considerable time caring for them. An

estimated 9.7% of CSHCN had families who spent 11 or more hours per week providing or coordinating

care in 2005-2006.85 Studies have documented that children with chronic conditions in poor families

and racial and ethnic minority groups may experience lower quality care.91,92 Children with chronic

conditions are reported by their parents to be less likely than other children to receive the full range of

needed health services.93 Among CSHCN, minorities are more likely than White children to be without

health insurance coverage or a usual source of care.94

Two quality measures (care coordination and family-centered care) and two access measures (health

insurance status and adequacy of health insurance) of relevance to CSHCN are tracked in this section of

the NHDR.

Focus on Care Coordination

CSHCN often need access to multiple health professionals. The children’s families may need assistance

coordinating care across providers and settings. For families who use more than one health or related

service and wanted or needed help with care coordination, effective care coordination requires receiving

“as much help as a family wants with arranging or coordinating care.”

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Chapter 4 Individuals With Disabilities or Special Health Care Needs
Figure 4.52. Children with special health care needs who received wanted or needed care

coordination, by race (top left), ethnicity (top right), and family income (bottom left), 2005-2006

Key: AI/AN = American Indian or Alaska Native; NHOPI = Native

Hawaiian or Other Pacific Islander.

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 With Special Health Care Needs (CSHCN), 2005-2006.

Reference population: CSHCN who were reported to use more

than one service during the survey period.

◆ Overall, 59.2% of CSHCN were reported to have received needed or wanted care coordination

(Figure 4.52).

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Chapter 4

0

10

20

30

40

50

60

70

White

Percent

NHOPI

Total

Black

Asian

AI/AN

>1 Race

0

10

20

30

40

50

60

70

Hispanic

Percent

Non-Hispanic

White

0

10

20

30

40

50

60

70

Near Poor

Percent

Poor

Middle Income

High Income

Individuals With Disabilities or Special Health Care Needs
◆ AI/AN and Asian CSHCN were reported to have the lowest levels of care coordination among racial

groups (53.9% and 52.5%, respectively, compared with White CSHCN, 61.1%).

◆ Hispanic CSHCN received less care coordination than non-Hispanic White CSHCN (49.9%

compared with 62.0%).

◆ CSHCN in high- and middle-income families had higher rates of care coordination (63.5% and

61.9%, respectively) than CSHCN in poor and near-poor families (53.3% and 55.1%, respectively).

Focus on Family-Centered Care

Family-centered care requires providers who:

◆ Spend adequate time with the child.

◆ Listen carefully to the parent.

◆ Show sensitivity to family values and customs.

◆ Communicate specific needed health information.

◆ Help the family feel like a partner in the child’s care.

◆ Help the family with language interpretation when needed.

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Chapter 4 Individuals With Disabilities or Special Health Care Needs
Figure 4.53. Children with special health care needs without family-centered care, by race (top)

and ethnicity (bottom), stratified by income, 2005-2006

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

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 With Special Health Care Needs, 2005-2006.

Reference population: Civilian noninstitutionalized population ages 0-17 with special health care needs.

Note: Data for low-income and high-income Native Hawaiians and Pacific Islanders did not meet criteria for statistical reliability.

◆ Overall, 34.5% of CSHCN were without family-centered care in 2005-2006 (data not shown).

◆ The contribution of income to differences in family-centered care by race and ethnicity was

significant. For example, 43.9% of poor White CHSCN lacked family-centered care, compared with

29.4% of White CSHCN overall (Figure 4.53). More than half of poor Black CSHCN (56.4%)

lacked family-centered care, compared with 47.8% of Black CSHCN overall. More than 60% of

poor Hispanic CSHCN (62.4%) lacked family-centered care, compared with 35.4% of high-income

Hispanic CSHCN.

◆ Significant differences between racial and ethnic groups remained overall. More than half (52.6%)

of Hispanic CSHCN lacked family-centered care, compared with 28.0% of non-Hispanic White

CSHCN, not accounting for variations in income.

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Chapter 4

Percent

Non-Hispanic White

Total

Poor

Low Income

Middle Income High Income

0

10

20

30

40

50

60

70

80

Hispanic Asian

Percent

White

Black

AI/AN

>1 Race

Total

Poor

Low Income

Middle Income High Income

0

10

20

30

40

50

60

70

80

NHOPI

Individuals With Disabilities or Special Health Care Needs
Access to Care

Access to care for CSHCN is especially critical since they may require more frequent and costly visits

than other children. Having health insurance is an important facilitator to accessing needed medical care.

Figure 4.54. Children with special health care needs who were without health insurance at some

point in the last 12 months, by race, ethnicity, income, and parental education, 2005-2006

Key: AI/AN = American Indian or Alaska Native.

Source: Health Services and Research Administration; Maternal

and Child Health Bureau; Centers for Disease Control and

Prevention, National Center for Health Statistics, National Survey

of Children With Special Health Care Needs, 2005-2006.

Reference population: Civilian noninstitutionalized population

ages 0-17 with special health care needs.

Note: Data for Asians and Native Hawaiian and Pacific Islanders

did not meet criteria for statistical reliability.

◆ Overall, 8.8% of CSHCN were without health insurance at some point during 2005-2006.

◆ White CSHCN were less likely to be without health insurance (7.6%). Black (11.1%), AI/AN

(15.3%), and multiple-race (9.1%) CSHCN were more likely to be without insurance at some point

during 2005-2006. Among Hispanic CSHCN, 15.1% were without insurance at some point during

2005-2006, compared with 7.1% of non-Hispanic White CSHCN.

◆ Poor and low-income CSHCN were more likely to be without health insurance (14.2% and 14.1%,

respectively) than middle- and high-income CSHNC (7.1% and 2.9%, respectively).

◆ Compared with data from 2001, in 2005-2006, the percentage of CSHCN without health insurance

at some point during the past year declined for White CSHCN (10.4% in 2001 and 7.6% in 2005-

2006) and CSHCN of more than one race (14.3% in 2001 and 9.1% in 2005-2006) but did not

change between 2001 and 2005-2006 for Black CSHCN (11.1% at both time points) (data not

shown). The 2001 data are insufficient to make comparisons for other racial groups.

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0

2

4

6

8

10

12

14

16

18

AI/AN

Percent

Non-Hispanic White

Hispanic

Poor

Middle Income

Low Income

High Income

Total

White

Black

>1 Race

Individuals With Disabilities or Special Health Care Needs
◆ The percentage of Hispanic CSHCN without health insurance declined between 2001 and 2005-

2006 (19.4% and 15.1%, respectively; data not shown, available at

http://www.ahrq.gov/qual/nhdr04/fullreport/Appd.htm).

◆ Similarly, the percentage of poor and low-income CSHCN without health insurance declined

between 2001 and 2005-2006 (21.8% and 20.3%, respectively, in 2001, and 14.2% and 14.1% in

2005-2006), as did the percentages for middle- and high-income CSHCN (2001 data not shown).

Figure 4.55. Currently insured children with special health care needs whose insurance is not

adequate, by race (left), ethnicity (right), and income (next page top), 2005-2006

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Chapter 4

0

10

20

30

40

50

White

Percent

NHOPI

Total

Black

Asian

AI/AN

>1 Race

0

10

20

30

40

50

Hispanic

Percent

Non-Hispanic

White

Individuals With Disabilities or Special Health Care Needs
Key: AI/AN = American Indian or Alaska Native; NHOPI = Native

Hawaiian or Other Pacific Islander.

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 With Special Health Care Needs (CSHCN), 2005-2006.

Reference population: Civilian noninstitutionalized population

ages 0-17 with special health care needs who have health

insurance.

Note: Among CSHCN with insurance, adequacy of health

insurance assesses the degree to which benefits cover the child’s

needs, uncovered costs are reasonable, and the child is able to

see the providers he or she needs.

◆ Overall, the percentage of CSHCN with less than adequate insurance was 33.1% in 2005-2006

(Figure 4.55).

◆ In 2005-2006, the percentage of CSHCN with less than adequate insurance was higher for AI/ANs

and NHOPIs (40.7% and 40.8%, respectively) than for Whites (32.5%).

◆ Hispanic CSHCN were more likely to have less than adequate insurance than non-Hispanic White

CSHCN (37.3% compared with 32.3%). Poor, low-income, and middle-income CSHCN were more

likely to have less than adequate insurance (35.8%, 34.0%, and 34.6%, respectively) than highincome CSHCN (29.0%).

◆ From 2001 to 2005-2006, the overall percentage of CSHCN with less than adequate insurance

remained the same (33.5% in 2001, 33.1% in 2005-2006).xvii However, the percentage for Hispanic

CSHCN decreased (from 45.9% to 37.3%; data not shown). The percentage for poor CSHCN also

decreased (from 43.0% to 35.8%; data not shown).

xviiThe 2001 data not shown are available at http://www.ahrq.gov/qual/nhdr04/fullreport/Appd.htm.

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0

10

20

30

40

50

Low Income

Percent

Poor

Middle Income

High Income

Individuals With Disabilities or Special Health Care Needs
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List of Core Measures

Core Measures, Data Sources, and Availability for Select Groups

Measure Data source Black Hispanic Asian or API AI/AN Poor

Quality

Adults age 50 and over who received

a colonoscopy, sigmoidoscopy, proctoscopy, NHIS ✔ ✔ ✔ ✔

or fecal occult blood test

Colorectal cancer diagnosed at advanced

stage per 100,000 population age 50 and over SEER ✔ ✔ ✔✔

Colorectal cancer deaths per 100,000

population per year NVSS-M ✔ ✔ ✔✔

Adults age 40 and over with diabetes

who received all three exams in the calender

year: hemoglobin A1c measurement, MEPS ✔ ✔ ✔

dialated eye examination, and foot

examination

Hospital admissions for lower extremity

amputations per 1,000 population age 18 NHDS ✔ ✔ ✔

and over with diabetes

Dialysis patients registered on a

waiting list for transplantation USRDS ✔ ✔ ✔✔

Hemodialysis patients with ESRD

adequate dialysis CPMP ✔ ✔ ✔✔

Adult smokers who received advice to quit

smoking MEPS ✔ ✔ ✔

Adults with obesity who received

advice to exercise more MEPS ✔ ✔ ✔

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 ✔ ✔ ✔✔

Pregnant women who received prenatal

care in first trimester NVSS-N ✔ ✔ ✔✔

Infant deaths per 1,000 live births,

birth weight <1,500 g NVSS-I ✔ ✔ ✔✔

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.
Core Measures, Data Sources, and Availability for Select Groups (continued)

Measure Data source Black Hispanic Asian or API AI/AN Poor

Children ages 2-17 for whom a health

provider gave advice about physical activity MEPS ✔ ✔✔ ✔

Children ages 3-6 who had their vision

checked by a health provider MEPS ✔ ✔ ✔

Suicide deaths per 100,000 population NVSS-M ✔ ✔ ✔✔

Adults with a major depressive episode

who received treatment for depression NSDUH ✔ ✔ ✔

People age 12 and over who needed

treatment for illicit drug use and NSDUH ✔ ✔ ✔

who received such treatment at a

specialty facility

People treated for substance abuse

who completed treatment course TEDS ✔ ✔

Adults age 65 and over who ever received

pneumococcal vaccination NHIS ✔ ✔✔ ✔

Hospital care for pneumonia patients QIO ✔ ✔ ✔✔

Visits with antibiotics prescribed for

a diagnosis of common cold per NAMCS10,000 population NHAMCS

Patients with tuberculosis who

completed a curative course of treatment CDC TB ✔ ✔ ✔✔

within 1 year of initiation of treatment Surveillance

Long-stay nursing home residents with

physical restraints MDS ✔ ✔ ✔✔

High-risk, long-stay nursing home

residents with pressure sores MDS ✔ ✔ ✔✔

Short-stay nursing home residents

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 Quality Report, 2000

Staying Healthy Priority Populations

National Healthcare Disparities Report, 2008

288

Chapter 4
Core Measures, Data Sources, and Availability for Select Groups (continued)

Measure Data source Black Hispanic Asian or API AI/AN Poor

Bloodstream infections or mechanical

adverse events per 1,000 central venous MPSMS ✔

catheter placements

Deaths per 1,000 discharges potentially

resulting from complications of care HCUP ✔ ✔✔ ✔

Adults age 65 and over who received

potentially inappropriate prescription MEPS ✔ ✔✔ ✔

medicines

Adults who can sometimes or never get

care for illness or injury as soon as wanted MEPS ✔ ✔✔ ✔

Emergency department visits in which

patients left without being seen NHAMCS ✔ ✔

Adults whose health providers sometimes

or never listened carefully, explained things MEPS ✔ ✔✔ ✔

clearly, respected what they had to say,

and spent enough time with them

Children whose health providers

sometimes or never listened carefully, MEPS ✔ ✔ ✔

explained things, clearly respected what

they or their parents had to say, and spent

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 due

to a financial or insurance reason for not MEPS ✔ ✔✔ ✔

having a source of care

People unable to get or delayed in receiving

needed medical care, dental care, or MEPS ✔ ✔ ✔

prescription medication due to

financial or insurance reasons

✔ 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 Quality Report, 2000

Priority Populations Staying Healthy

National Healthcare Disparities Report, 2008

289

Chapter 4
Key to Data Sources:

CDC = Centers for Disease Control and Prevention

ESRD CPMP = End Stage Renal Disease Clinical Performance Measures Project

HCUP = Healthcare Cost and Utilization Project

MDS = Medicare Minimum Data Set

MEPS = Medical Expenditure Panel Survey

MPSMS = Medicare Patient Safety Monitoring System

NAMCS = National Ambulatory Medical Care Survey

NHAMCS = National Hospital Ambulatory Medical Care Survey

NHDS = National Hospital Discharge Survey

NHIS = National Health Interview Survey

NIS = National Immunization Survey

NSDUH = National Survey on Drug Use and Health

NVSS-I = National Vital Statistics System, Linked Birth-Infant Death

NVSS-M = National Vital Statistics System, Mortality

NVSS-N = National Vital Statistics System, Natality

OASIS = Centers for Medicare and Medicaid Services Outcome and Assessment Information Set

QIO = Quality Improvement Organization Program

SEER = Surveillance, Epidemiology, and End Results Program

TEDS = Treatment Episode Data Set

USRDS = United States Renal Data System

National Quality Report, 2000

Staying Healthy

National Healthcare Disparities Report, 2008

290

Chapter 4
National Quality Report, 2000

Staying Healthy
National Quality Report, 2000

Staying Healthy
National Quality Report, 2000

Staying Healthy
AHRQ Publication No. 09-0002

March 2009

U.S. Department of

Health and Human Services

Agency for Healthcare Research and Quality

540 Gaither Road

Rockville, MD 20850