Refinements to Report Format

The 2006 NHDR and its companion NHQR continue to be formatted as chartbooks. Although needed to assess health care in America comprehensively, the large number of measures tracked in the reports may sometimes be confusing and overwhelming for users. Hence, the 2006 reports continue to focus on a smaller subset of core measures. Other modifications have also been made to make the information in the reports easier to understand.

Core measures. For the 2005 reports, 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 relate to cancer prevention and childhood preventive services. Alternating measures are listed in Table 1.1.

Table 1.1. Alternating core measures

Reported in the 2006 NHDR and NHQR:	Reported in 2005 NHDR and NHQR*
Colorectal cancer screening. Late stage colorectal cancers. Colorectal cancer mortality. Children who received advice about diet. Children who had a vision check.	Breast cancer screening. Late stage breast cancers. Breast cancer mortality. Children who received advice about exercise. Children who had dental care.

* The measures listed in this column will be reported again in the 2007 reports.

The core measures of patient safety also underwent modifications. Several measures included in last year's report were not available this year. New composite measures were developed to summarize information across several individual patient safety measures (described below). Other new measures became available that cover important aspects of patient safety. The combination of these changes yielded this year's patient safety core measures:

• Timing of antibiotics to prevent postoperative wound infection composite measure adopted by the Hospital Quality Alliance (HQA) from the Centers for Medicare & Medicaid Services (CMS) Quality Improvement Organization (QIO) program.
• Postoperative complications composite measure from the Medicare Patient Safety Monitoring System (MPSMS).
• Complications of central venous catheter composite measure from the MPSMS.
• Deaths following complications of care from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases disparities analysis file.
• Inappropriate medication use among the elderly from the Medical Expenditure Panel Survey (MEPS).

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). Both types of measures are not reported for all conditions due to data limitations. For example, data on HIV care are suboptimal; hence, no HIV process measures are included as core measures. In addition, not all core measures are included in trending analysis because 2 or more years of data were not available.

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	Persons age 50 and over who ever had a flexible colonoscopy, sigmoidoscopy, or proctoscopy or fecal occult blood test in past 2 years	Colorectal cancers diagnosed as regional or distant staged cancers Cancer deaths per 100,000 persons per year for most common cancers-colorectal cancer
Effectiveness - Diabetes	Adults age 40 and over with diabetes had hemoglobin A1c test, eye and foot exam in past year	Hospital admissions for lower extremity amputation in patients with diabetes
Effectiveness - End Stage Renal Disease	Dialysis patients registered on waiting list for transplantation	Hemodialysis patients with adequate dialysis
Effectiveness - Heart Disease	Recommended hospital care received by Medicare patients with acute myocardial infarction Recommended hospital care received by Medicare patients with heart failure Smokers receiving advice to quit smoking Adults age 18 and over who were obese who were given advice about exercise	Acute myocardial infarction mortality
Effectiveness - HIV and AIDS		New AIDS cases per 100,000 population (age 13 and over)
Effectiveness - Maternal and Child Health	Pregnant women receiving prenatal care in first trimester Children 19-35 months who received all recommended vaccines Adolescents (age 13-15) reported to have received 3 or more doses of hepatitis B vaccine Children whose parents or guardians ever received advice from doctor or health professional about healthy eating Children ages 3-6 who ever received a vision check	Infant mortality per 1,000 live births,birthweight <1500 grams Hospital admissions for pediatric gastroenteritis per 100,000 population less than 18 years of age
Effectiveness - Mental Health and Substance Abuse	Adults age 18 and over with past year major depressive episode who received treatment for the depression in the past year Persons age 12 or older who needed treatment for any illicit drug use and who received such treatment at a specialty facility in the past year	Deaths due to suicide per 100,000 population Patients receiving substance abuse treatment who complete treatment
Effectiveness - Respiratory Diseases	Persons age 65 and over who ever received pneumococcal vaccination Recommended hospital care received by Medicare patients with pneumonia Visits where antibiotic was prescribed for diagnosis of a common cold, children	TB patients that complete a curative course of treatment within 12 months of initiation Hospital admissions for pediatric asthma per 100,000 population under age 18
Effectiveness - Nursing Home, Home Health, and Hospice Care	Nursing home residents who were physically restrained	High-risk nursing home residents who have pressure sores Short-stay nursing home residents with pressure sores Home health episodes showing ambulation/locomotion improvement Home health episodes with acute care hospitalization
Patient Safety	Appropriate timing of surgical infection prophylaxis Elderly who had at least one prescription that is potentially inappropriate	Postoperative pneumonia, urinary tract infection, and/or venous thromboembolic events Adverse events associated with central venous catheters Deaths following complications of care
Timeliness		Adults who report that they can get care for illness/injury as soon as they wanted Patients who left emergency department without being seen
Patient Centeredness	Adults whose health providers listened carefully, explained things clearly, respected what they had to say, and spent enough time with them Children whose parents or guardians report that their child's health providers listened carefully, explained things clearly, respected what they had to say, and spent enough time with them

Presentation. Each section in the 2006 report begins with a description of the importance of the section's topic in a standardized format. New this year is an assessment of the cost effectiveness of different clinical preventive services. These estimates come from a recent review by the National Commission on Prevention Priorities.¹ Cost effectiveness is measured as the average net cost of each quality adjusted life year (QALY)ⁱⁱⁱ that is saved by a particular health intervention. A lower cost per QALY saved indicates a greater degree of cost effectiveness while beneficial preventive services that fully cover their costs are labeled as cost saving.

After introductory text, chart figures and accompanying findings highlight a small number of measures relevant to this topic. When data are available, these charts typically show contrasts by:

• Race—Blacks, Asians,^iv Native Hawaiians or Other Pacific Islanders (NHOPIs), American Indians or Alaska Natives (AI/ANs), and people of more than one race compared with Whites.
• Ethnicity—Hispanics compared with non-Hispanic Whites.^v
• Income—Poor, near poor, and middle income people compared with high income people.^vi
• 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 often included. For some measures with supporting data, regression models were run and used to help interpret bivariate and stratified results. In addition, figures showing odds ratios adjusted for age, gender, race, ethnicity, income, education, insurance, and residence location are presented for two measures.^vii Figures include a note about the reference group for population-based measures and the denominator for measures based on services or events.

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ⁱⁱⁱ QALY is a measure of survival adjusted for its value: 1 year in perfect health is equal to 1.0 QALY, and a year in poor health would be something less than 1.0.

^iv "Asian" includes "Asian or Pacific Islander" (API) when information is not collected separately for each group.

^v Not all data sources used in the NHDR collect data by race and ethnicity separately (i.e., 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 (i.e., comparing non-Hispanic Blacks and Hispanics with non-Hispanic Whites).

^vi Throughout this report, "poor" is defined as having family incomes 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.

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

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As in last year's report, findings presented in the text meet report criteria for importance^viii; comparisons not discussed in 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. To facilitate linkage to other Federal reporting initiatives, this report indicates where NHDR measures are also tracked in Healthy People 2010.

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^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 is at least 10% different from the reference group when framed positively as a favorable outcome or negatively as an adverse outcome.

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Addition of New Data Sources

NHDR data sources include surveys of individuals and health care facilities and extract from surveillance, vital statistics, and health care organization data systems. Table 1.3 lists all data sources and includes five new data sources. Standardized suppression criteria were applied to all databases to support reliable estimates.^ix New data added this year come from:

• National Asthma Survey. This survey, sponsored by the Centers for Disease Control and Prevention (CDC) National Center for Environmental Health and conducted by the National Center for Health Statistics (NCHS) in 2003, is the most comprehensive national data set on asthma prevalence and asthma care. It examines the health, socioeconomic, behavioral, and environmental predictors that relate to control of asthma. Because it is not an ongoing survey, findings are presented in this year's report only.
• National Hospice and Palliative Care Organization's Family Evaluation of Hospice Care.This survey examines the quality of hospice care for patients and their family members.² 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. The survey is administered by about 800 hospices each year, and about 120,000 completed surveys are returned each year for an overall response rate of about 40%. Participation is voluntary; although participating hospices span the Nation, they are not nationally representative. Demographic information is often incomplete. Despite these limitations, this survey is the most comprehensive source of information about hospice care.
• CAHPS® Hospital Survey. This survey, developed by CMS and AHRQ, captures information about patients' experiences of care when hospitalized.³ In 2005, 254 hospitals across the United States volunteered to use this survey. In total, completed surveys were received from 84,779 respondents; the average response rate was 44%. Although it is not nationally representative, the sample of hospitals and respondents is comparable to the national distribution of hospitals registered with the American Hospital Association.
• U.S. Census. Data from the 2000 Census of Population are included this year to provide information about the physician workforce.
• Center for Studying Health System Change Community Tracking Study Physician Survey. Data from this periodic survey of physicians in direct patient care is used to assess trends in the physician workforce over time.

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^ix Estimates based on sample size fewer than 30 or with relative standard error greater than 30% are considered unreliable and suppressed. Databases with more conservative suppression criteria are allowed to retain them.

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Table 1.3. Databases used in the 2006 reports (new databases in italics)

Surveys collected from populations: AHRQ, Medical Expenditure Panel Survey (MEPS), 1999–2003. CAHPS® Hospital Survey, 2005. CDC, Behavioral Risk Factor Surveillance System (BRFSS), 2001-2004 CDC-NCHS, National Asthma Survey, 2003. CDC-NCHS, National Health and Nutrition Examination Survey (NHANES), 1999-2002. CDC-NCHS, National Health Interview Survey (NHIS), 1998-2004. CDC-NCHS/National Immunization Program, National Immunization Survey (NIS), 1998-2004. CMS, Medicare Current Beneficiary Survey (MCBS), 1998-2002. Health Resources and Services Administration, Healthy Schools Healthy Communities User Visit Survey, 2003. National Hospice and Palliative Care Organization, Family Evaluation of Hospice Care, 2005. Substance Abuse and Mental Health Services Administration (SAMHSA), National Survey on Drug Use and Health (NSDUH), 2002-2004. U.S. Census Bureau, U.S. Census of Population, 2000.

Data collected from samples of health care facilities and providers: Center for Studying Health System Change, Community Tracking Study Physician Survey, 1998-2005. CDC-NCHS, National Ambulatory Medical Care Survey (NAMCS), 1997-2003. CDC-NCHS, National Hospital Ambulatory Medical Care Survey-Outpatient Department (NHAMCS-OPD), 1997-2003. CDC-NCHS, National Hospital Ambulatory Medical Care Survey-Emergency Department (NHAMCS-ED), 1997-2003. CDC-NCHS, National Hospital Discharge Survey (NHDS), 1998-2004. CMS, End Stage Renal Disease Clinical Performance Measures Project (ESRD CPMP), 2001-2004.

Data extracted from data systems of health care organizations: AHRQ, Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases disparities analysis file,* 2001-2003. CMS, Hospital Compare, 2005. CMS, Medicare Patient Safety Monitoring System, 2002-2004. CMS, Home Health Outcomes and Assessment Information Set (OASIS), 2002-2004. CMS, Nursing Home Minimum Data Set, 2002-2004. CMS, Quality Improvement Organization (QIO) program, Hospital Quality Alliance (HQA) measures, 2000-2004. HIV Research Network data (HIVRN), 2001-2003. Indian Health Service, National Patient Information Reporting System (NPIRS), 2002-2004. National committee for Quality Assurance, Health Plan Employer Data and Information Set (HEDIS), 2001-2005. National Institutes of Health, United States Renal Data System (USRDS), 1998-2003. SAMHSA, Treatment Episode Data Set (TEDS), 2002-2003.

Data from surveillance and vital statistics systems: CDC, National Program of Cancer Registries (NPCR), 2002-2003. CDC-National Center for HIV, STD, and TB Prevention, HIV/AIDS Surveillance System, 2000-2004. CDC-National Center for HIV, STD, and TB Prevention, TB Surveillance System, 1999-2002. CDC-NCHS, National Vital Statistics System (NVSS), 1999-2003. NIH, Surveillance, Epidemiology, and End Results (SEER) program, 1992-2003.

* This 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 22 States: AZ, CA, CO, CT, FL, GA, HI, KS, MD, MA, MI, MO, NJ, NY, PA, RI, SC, TN, TX, VA, VT, and WI.

Changes to the Measure Set

New measures. The measure sets used in the 2006 NHDR and NHQR have been improved in several ways. First, a handful of measures were modified to reflect more current standards of care. Second, age adjustment^x for a number of measures was updated. For example, to enhance the comparability of measures of diabetes care from MEPS, the Behavioral Risk Factor Surveillance System (BRFSS), and the National Health and Nutrition Examination Survey (NHANES), these measures now apply the same age adjustment methodology among persons age 40 and over with diabetes.^xi Finally, a number of new measures were added to fill identified gaps, including:

• Four measures of care for obesity from MEPS and NHANES:
  • Obese adults age 20 and over who were told by their provider that they were overweight (NHANES).
  • Overweight children and teens ages 2-19 who were told by their provider that they were overweight (NHANES).
  • Obese adults who were given counseling from their provider about exercise (MEPS).^xii
  • Obese adults who were given counseling from their provider about diet (MEPS).
• Two measures of hospice care from the National Hospice and Palliative Care Organization's Family Evaluation of Hospice Care survey:
  • Hospice patients who did not receive the right amount of medicine for pain.
  • Hospice patients who received care inconsistent with their stated end-of-life wishes.
• Two measures of patient safety, one from the Medicare Patient Safety Monitoring System and one adopted by the Hospital Quality Alliance (HQA) from the CMS Quality Improvement Organization program:
  • Medication-related adverse drug events (MPSMS).
  • Timing of antibiotics to prevent postoperative wound infection (HQA).^xii
• Four measures of patient centeredness of hospital care from the CAHPS® Hospital Survey:
  • Communication with doctors in the hospital.
  • Communication with nurses in the hospital.
  • Communication about medications in the hospital.
  • Discharge information from the hospital.
• Two measure of workforce diversity from the U.S. Census 2000 and the Center for Studying Health System Change Community Tracking Study Physician Survey:
  • U.S. physicians and surgeons by race and ethnicity (U.S. Census 2000).
  • U.S. physicians in direct patient care by race and ethnicity (Community Tracking Study Physician Survey).
• One measure of language assistance from MEPS:
  • Adults with limited English proficiency with and without a usual source of care who offers language assistance (MEPS).
• As noted earlier, the 2006 reports also include measures of asthma care from the National Asthma Survey.^xiii The four measures include persons with current asthma who were:
  • Taught to recognize early signs of an asthma attack.
  • Told how to change their environment.
  • Given an asthma controller medication.
  • Given an asthma management plan.

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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^x Age-adjusted measures are labeled as such. All other measures are not age adjusted.

^xi Prior to 2006, these measures tracked persons age 18 and over.

^xii This is a new core measure.

^xiii Because this is not a periodic survey, the four measures from this survey will not be permanently added to the measure set.

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Composite measures. Composite measures provide readers with a summarized picture of some aspect of health care by combining information from multiple component measures. Policymakers and others have voiced their support for composite measures because they can be used to facilitate understanding of information from many individual measures. The effort to develop new composites is ongoing; and this year, a number of new composite measures were added. Composite measures now make up about 20% of the core measures. New composite measures included in the 2006 reports and the individual component measures they aggregate are shown in Table 1.4. Future reports will include more composite measures.

Table 1.4. Composite measures in the 2006 NHQR and NHDR (new measures in italics)

Composite measure	Individual measures forming composite	Model
Receipt of three recommended diabetic services*	Adults aged 40 and older with diagnosed diabetes who received at least one HbA1c test Adults aged 40 and older with diagnosed diabetes who received at least one retinal eye exam Adults aged 40 and older with diagnosed diabetes who received at least one foot exam	Appropriateness
Childhood immunization	Children age 19-35 months who received at least 4 doses of diphtheria-tetanus-acellular pertussis (DTa P) Children age 19-35 months who received at least 3 doses of polio Children age 19-35 months who received at least 1 dose of measles-mumps-rubella (MMR) Children age 19-35 months who received at least 3 doses of Haemophilus influenza B (Hib) Children age 19-35 months who received at least 3 doses of hepatitis B antigens	Appropriateness
Recommended hospital care for heart attack	Receipt of aspirin within 24 hours of hospitalization Receipt of aspirin upon discharge Receipt of beta-blocker within 24 hours of hospitalization Receipt of beta-blocker upon discharge Receipt of ACE inhibitor for left ventricular systolic dysfunction Receipt of counseling about smoking cessation among smokers	Opportunities
Recommended hospital care for heart failure	Receipt of evaluation of left ventricular ejection fraction Receipt of ACE inhibitor for left ventricular systolic dysfunction	Opportunities
Recommended hospital care for pneumonia	Receipt of initial antibiotics within 4 hours Receipt of appropriate antibiotics Receipt of culture before antibiotics Receipt of influenza screening or vaccination Receipt of pneumococcal screening or vaccination	Opportunities
Timing of antibiotics to prevent postoperative wound infection	Antibiotics started within 1 hour of surgery Antibiotics stopped 24 hours after surgery	Opportunities
Patient - provider communication problems	Provider sometimes or never listened carefully to you Provider sometimes or never explained things clearly to you Provider sometimes or never showed respect for what you had to say Provider sometimes or never spent enough time with you	CAHPS®
Communication with doctors in the hospital	Doctors sometimes or never treated you with courtesy and respect Doctors sometimes or never listened carefully to you Doctors sometimes or never explained things in a way you could understand	CAHPS®
Communication with nurses in the hospital	Nurses sometimes or never treated you with courtesy and respect Nurses sometimes or never listened carefully to you Nurses sometimes or never explained things in a way you could understand	CAHPS®
Communication about medications in the hospital	Hospital staff sometimes or never told you what a new medicine was for Hospital staff sometimes or never described possible side effects of a new medicine in a way you could understand	CAHPS®
Discharge information from the hospital	Hospital staff talked with you about whether you would have the help you needed when you left the hospital Hospital staff provided information in writing about what symptoms or health problems to look out for after you left the hospital	CAHPS®
Postoperative complications	Postoperative pneumonia Postoperative bladder infection Postoperative blood clot	Additive
Complications of central venous catheters	Bloodstream infection due to central venous catheter Mechanical problem due to central venous catheter	Additive

* This composite measure was modified between the 2004 and 2005 reports. Starting with the 2005 composite, two tests, flu vaccination and lipid profile, were omitted due to differences in the manner in which they were collected. The current composite measure on diabetes care focuses on the receipt of three processes for which the best data are available: HbA1c testing, retinal eye examination, and foot examination in the past year. Starting in 2006, the target age group for this measure changed from age 18 and older to age 40 and older.

When possible, an appropriateness model is used to create composite measures. In this model, the denominator is the number of patients who should receive the services included in the composite, and the numerator is the number of patients who receive all of these services. The composite measure is presented as the percentage of patients who receive all services recommended to them. Because no partial credit is given for incomplete care, this model is sometimes referred to as an "all-or-none" approach. The appropriateness model is attractive to patients, who naturally desire to receive every appropriate service.⁴ 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.

Sometimes, insufficient data are available to apply an appropriateness model. In these instances, an opportunities model developed by Qualidigm⁵ and used in the CMS Premier Hospital Quality Incentive Demonstration⁶ and for public reporting by the Rhode Island Department of Health⁷ is used. The model assumes that each patient needs and has the opportunity to receive one or more processes of care but that not all patients need the same care. The denominator for an opportunities model composite is the sum of these opportunities to receive appropriate care across a panel of process measures. The numerator is the sum of the appropriate care that is actually delivered. The composite measure is typically presented as the proportion of appropriate care that is delivered.

For example, recommended hospital care for heart failure includes evaluation of left ventricular ejection fraction and ACE inhibitor for patients with left ventricular systolic dysfunction. This represents two opportunities for providing appropriate care. The number of patients who should have an evaluation of left ventricular ejection fraction is added to the number of patients who should receive an ACE inhibitor to calculate the total number of opportunities for providing appropriate care. The number of patients who actually receive an evaluation of left ventricular ejection fraction is added to the number of patients who actually receive an ACE inhibitor to calculate the number of opportunities for providing care for which appropriate care was actually delivered. The composite is created by dividing the number of opportunities for care for which appropriate care was actually delivered by the total number of opportunities for care.

Measures from the CAHPS® (Consumer Assessment of Healthcare Providers and Systems⁸) surveys have their own method for computing composite measures that has been in use for many years. These composite measures average individual components of patient experiences of care. These composite measures are typically presented as the proportion of respondents who reported that providers sometimes or never, usually, or always performed well.

Two new composite measures relate to rates of complications of hospital care—postoperative complications and complications of central venous catheters. For these complication rate composites, an additive model is used, which sums together individual complication rates. Thus, for these composites, the numerator is the sum of individual complications and the denominator is the number of patients at risk for these complications. The composite rates are presented as the overall rate of complications. The postoperative complications composite is a good example of this type of composite measure; if 50 patients had a total of 15 complications between them (regardless of their distribution), the composite score would be 30%.

Expanded Analyses

Trends in health care quality and access. As in previous NHDRs, the 2006 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, the geometric rate of change, which assumes the same rate each year between the two time periods, has been calculated for the 2006 NHDR and NHQR.^xiv

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 with alpha=0.05.
• Second, the magnitude of average annual rate of change must be at least 1% per year, 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 2006 reports.

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^xiv The 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] X 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.

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One additional constraint relates to trends among specific racial and ethnic groups. Some Federal databases completed transition by 2003 (as required) to the new Federal standards for racial and ethnic data during years covered by the NHDR. 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, which significantly affected estimates for the "American Indian or Alaska Native" category. In contrast, effects on estimates for Whites, Blacks, and Hispanics were proportionately much smaller. Consequently, the 2006 NHDR shows shorter trends (i.e., fewer years of data) for groups directly or significantly affected by the new standards such as Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, and multiple race individuals.

Hispanic subpopulations. As with all U.S. populations, racial and ethnic minority groups that are the focus of the NHDR can be highly heterogeneous. Data are typically not available to examine different racial and ethnic groups in greater detail. One exception relates to Hispanic subpopulations for which increasing amounts of data are available. The 2006 NHDR shows information from MEPS related to health care differentiating Hispanics of Mexican, Central or South American, Puerto Rican, and Cuban descent. These analyses are presented in the section on racial and ethnic minorities in Chapter 4, Priority Populations.

Uninsurance. Lack of health insurance is widely recognized as a risk factor for poorer quality of health care and worse access to health care. Previous reports have included analyses of uninsured compared with privately insured individuals but did not bring these findings together into a specific section of the reports. This year, a focus on disparities related to insurance status is introduced. These analyses are presented in the section on low income groups in Chapter 4, Priority Populations.

Summary of Disparities

In the 2006 NHDR, efforts to summarize disparities have been further refined.

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 the poor. 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. Health care utilization measures are difficult to interpret and were excluded when summarizing disparities in access to care.^xv In Chapter 4, Priority Populations, which presents information on each population separately, all core measures are used when summarizing 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 are used to facilitate comparisons across the groups. An exception is made for income comparisons of quality measures because much less information is available for these groups.

As in 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. The median relative rate across core measures is presented in Chapter 4 as another way of summarizing the magnitude of disparities in quality and access; the relative rates are also presented to identify potential areas for improvement.

Trends in disparities. The method for summarizing trends in disparities introduced in the 2005 NHDR is improved in the 2006 NHDR. For each core measure, racial, ethnic, and socioeconomic groups are compared with a designated reference group at different points in time. Consistent with Healthy People 2010, disparities are measures in relative terms as the percent difference between each group and a reference group; changes in disparity are measured by subtracting the percent difference from the reference group at the baseline year from the percent difference from the reference 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. Thus, in determining change:

• Core measures for which the relative differences are changing less than 1% per year are identified as staying the same.
• Core measures for which the relative differences are becoming smaller at a rate of more than 1% per year are identified as improving disparities.
• Core measures for which the relative differences are becoming larger at a rate of more than 1% per year are identified as worsening disparities.
• Changes of greater than 5% per year are also differentiated from changes of between 1% and 5% per year in some figures.

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^xv 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. For these reasons, measures of health care utilization are excluded from summaries of access to health care.

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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 the groups. As noted above, an exception is made for income comparisons of quality measures because much less information is available for these groups.