Chapter 1. Introduction and Methods
National Healthcare Disparities Report, 2011
In 1999, Congress directed the Agency for Healthcare Research and Quality (AHRQ) to produce an annual report on "national trends in the quality of health care provided to the American people."i With support from the Department of Health and Human Services (HHS) and private-sector partners, AHRQ has designed and produced the National Healthcare Quality Report (NHQR) to respond to this legislative mandate. The NHQR provides a comprehensive overview of the quality of health care received by the general U.S. population and is designed to summarize data across a wide range of patient needs—staying healthy, getting better, living with chronic illness and disability, and coping with the end of life.
AHRQ was further tasked with producing an annual report that tracks "prevailing disparities in health care delivery as it relates to racial factors and socioeconomic factors in priority populations."ii Titled the National Healthcare Disparities Report (NHDR), this report examines disparities in health care received by designated priority populations. The referenced priority populations consist of groups with unique health care needs or issues that require special focus, such as racial and ethnic minorities, low-income populations, and people with special health care needs. AHRQ�s charge includes a directive to examine disparities in health care access, utilization, costs, outcomes, satisfaction, and perceptions of care.
The first NHQR and NHDR were significantly shaped by several Institute of Medicine (IOM) reports. Crossing the Quality Chasm (IOM, 2001) and To Err Is Human (Kohn, et al., 2000) raised awareness about gaps in the quality of health care and patient safety. The extensive literature review included in the IOM report Unequal Treatment (IOM, 2003) drew attention to disparities in the care rendered to racial and ethnic populations, low-income populations, and other vulnerable groups.
Before the publication of the first reports, AHRQ tasked the IOM with developing a vision for the two reports. With support from an HHS Interagency Work Group and AHRQ�s National Advisory Council, AHRQ has designed and produced the NHQR and NHDR since 2003.
Changes to the Reports
Over the years, AHRQ introduced several refinements to the NHQR and NHDR measure set and methodology. These include the following:
- 2004: Goal of the reports was expanded to include tracking of the Nation's quality improvement progress.
- 2005: Reports introduced a set of core measures and a variety of new composite measures.
- 2006: Data, measures, and methods were improved; databases and measures were added; and methods for quantifying and tracking changes in health care were refined.
- 2007: Chapter on health care efficiency was launched.
- 2008: Chapter on patient safety was expanded.
- 2009: New sections were included on lifestyle modification, healthcare-associated infections, and care coordination.
With rapid changes in health care, in 2008, AHRQ commissioned the IOM to review past reports and offer recommendations for enhancing future reports and associated products. Among the recommendations offered in Future Directions for the National Healthcare Quality and Disparities Reports (IOM, 2010), the IOM proposed that AHRQ report on progress in areas expected to yield the greatest gains in health care quality. These included patient and family engagement, population health, safety, care coordination, palliative care, overuse of services, access to care, and health system infrastructure.
As recommended, the 2010 reports aligned measures according to these priority areas. As also suggested by the IOM, the reports introduced measure-specific benchmarks that reflected the highest level of performance documented for a measure.
Pursuant to the provisions of the Patient Protection and Affordable Care Act of 2010,iii in 2011, the Secretary of HHS submitted a report to Congress titled National Strategy for Quality Improvement in Health Care (National Quality Strategy). This report set priorities to advance three quality improvement aims: better care, healthy people, and affordable care. Six priority areas were identified as a means to achieve the quality improvement aims:
- Making sure care is safer by reducing harm in the delivery of care.
- Ensuring that each person and his or her family members are engaged as partners in their care.
- Promoting effective communication and coordination of care.
- Promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
- Working with communities to promote wide use of best practices to enable healthy living.
- Making quality care more affordable for individuals, families, employers, and governments, by developing and spreading new health care delivery models.
The 2011 NHQR and NHDR align measures according to the National Quality Strategy in an effort to inform policymakers, the public, and other stakeholders of the Nation�s progress in achieving National Quality Strategy aims. The National Quality Strategy priorities considerably overlap with those proposed by the IOM. While the 2011 reports introduce several measures to address the National Quality Strategy priorities, the organization of the 2011 NHQR and NHDR is similar to that used in 2010. In addition to the change in framework, the 2011 NHQR and NHDR introduce several measures and major enhancements to the methods by which trends are estimated. These enhancements are discussed below in greater detail.
Organization of the NHQR and NHDR
The NHQR and NHDR are designed as chartbooks that contain data on more than 250 health care quality measures from more than 45 databases. Measures in these reports are selected with guidance from the AHRQ Interagency Work Group, an advisory body of representatives from across many HHS agencies. Measures represented in these reports are among the most important and scientifically supported measures. Together, these measures provide an annual snapshot of how our Nation�s health care system is performing and the extent to which health care quality and disparities have improved or worsened over time.
The NHQR and NHDR are complementary reports and, with few exceptions, are similarly organized. Where applicable, key findings from the NHDR are included in the NHQR, and NHQR findings are reported in the text of the NHDR. Readers should refer to the report from which results have been drawn to gather additional details on the data presented. Report chapters include:
Highlights, which immediately precede the current chapter, combine broad sets of measures to offer a high-level overview of the progress that has been made in advancing health care quality and reducing disparities in the United States. The Highlights chapter incorporates findings from both the NHQR and NHDR, and the same Highlights chapter is used in both reports.
Chapter 1: Introduction and Methods provides background on the NHQR and NHDR and modifications to the reports that have occurred over time. This chapter includes measures that have been added or retired from the measures list, along with an overview of the methods used to generate estimates, measure trends, and examine disparities.
Chapter 2: Effectiveness examines prevention, treatment, and outcomes for a range of conditions or population groups. The 2011 reports are organized around several clinical areas: cancer, cardiovascular disease, chronic kidney disease, diabetes, HIV and AIDS, maternal and child health, mental health and substance abuse, musculoskeletal disease, and respiratory disease. Three types of health care services that typically cut across clinical conditions are also examined: lifestyle modification, functional status preservation and rehabilitation, and supportive and palliative care. The section on musculoskeletal disease is new to the reports, as are measures related to adolescent health.
Chapter 3: Patient Safety tracks safety within the hospital setting. Among the areas examined are healthcare-associated infections, postoperative and other hospital complications, and preventable hospital deaths.
Chapter 4: Timeliness examines the delivery of time-sensitive clinical care and patient perceptions of how quickly they receive care. Among the measures reported in this chapter are the ability to get care when the patient needs it and emergency department wait times.
Chapter 5: Patient Centeredness examines individual experiences with care in an office or clinic setting, as well as during a hospital stay. Measures reported in this chapter focus on perceptions of communication with providers and satisfaction with the physician-patient relationship.
Chapter 6: Care Coordination presents data to assess the performance of the U.S. health care system in coordinating care across providers or services. Care coordination is measured, in part, using readmission measures as well as measures of success in transitioning across health care settings.
Chapter 7: Efficiency is often assessed by how well the health care system promotes quality, affordable care, and appropriate use of services. The emphasis in this chapter is on overuse of health services, as measures representing misuse or underuse overlap with other sections of the report and are included in various chapters.
Chapter 8: Health System Infrastructure explores the capacity of health care systems to support high-quality care. Most measures of health system infrastructure were assessed on the basis of region or provider characteristics. Infrastructure measures, which are primarily structural measures of quality, include adoption of computerized data systems and the supply of selected health care professionals. The 2011 reports include a new section that includes structural, process, and outcome measures to examine the quality of the health care safety net. Among the areas addressed in this new section are the magnitude of underserved populations in health professional shortage areas (HPSAs) and the performance of federally qualified health centers.
Chapter 9: Access measures cut across several priority areas and include measures that focus on barriers to care, such as the U.S. population that is uninsured, financial barriers to care experienced by the population with health insurance, and people with a usual source of care.
Chapter 10: Priority Populations continues to be unique to the NHDR. This chapter summarizes quality and disparities in care for populations identified as particularly significant to quality improvement, including racial and ethnic minorities, low-income populations, older adults, residents of rural areas and inner cities, and individuals with disabilities or special health care needs.
Appendixes are available online for both the NHQR and NHDR at . These include:
- Data Sources, which provides information about each database analyzed for the reports, including data type, sample design, and primary content.
- Measure Specifications, which provides information about how measures are generated and analyzed for the reports. Measures highlighted in the report are described, as well as other measures that were examined but not included in the text of the report.
- Detailed Methods, which provides detailed methodological and statistical information about selected databases analyzed for the reports.
- Data Tables, which contains detailed data tables for most measures analyzed for the reports, including measures highlighted in the report text and measures examined but not included in the text. A few measures cannot support detailed tables and are not included in the appendix.
Table 1.1 provides a crosswalk between the National Quality Strategy priorities and the report chapters. Chapter 10, Priority Populations, addresses all six priorities.
Table 1.1. Relationship of NHQR and NHDR to the National Quality Strategy
|National Quality Strategy Priorities||NHQR and NHDR Chapters Addressing Priority|
|Making sure care is safer by reducing harm in the delivery of care||Chapter 3: Patient Safety|
|Ensuring that each person and his or her family members are engaged as partners in their care||Chapter 5: Patient Centeredness|
|Promoting effective communication and coordination of care||Chapter 6: Care Coordination|
|Promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease||Chapter 2: Effectiveness, Cardiovascular Disease|
|Working with communities to promote wide use of best practices to enable healthy living||Chapter 2: Effectiveness, Lifestyle Modification|
|Making quality care more affordable for individuals, families, employers, and governments, by developing and spreading new health care delivery models||Chapter 7: Efficiency|
Chapter 9: Access
Measure Set for the 2011 NHQR and NHDR
The 2011 reports continue to focus on a consistent subset of measures, the "core" measures, which includes the most important and scientifically supported measures in the full measure set. "Supporting measures" are included in summary statistics and may be presented to complement core measures in key areas. Often, data are unavailable to track these measures on an annual basis. In other cases, supporting measures may not have been as rigorously evaluated as core measures, but they are still useful in characterizing the performance of the health care system.
In 2005, the Interagency Work Group selected core measures from the full measure set. Consistency in core measures enables AHRQ to monitor trends over time to identify areas for which health care is improving or getting worse. For most core measures, findings are presented each year.
A subset of the core measure group is presented on an alternating basis, typically rotating across odd or even years of the report. All alternating core measures are included in trend analyses. Examples of alternating measures include the set of measures focusing on breast cancer and colorectal cancer. While measures are tracked annually, breast cancer measures are presented in odd calendar years; these measures are contained in the 2011 reports. Colorectal cancer measures are also tracked annually, but results are presented in even calendar years, such as in the 2010 quality and disparities reports.
With the assistance of the Interagency Work Group, each year AHRQ reviews the NHQR and NHDR measures list to identify areas where additional information on the performance of the health care system is needed. Suitability of a measure for reporting may be based on the adequacy of data used to generate the measure, extent to which the measure has been scientifically tested, and acceptance of the measure by relevant stakeholders. The 2011 reports incorporate several new measures, many of which correspond to priorities identified in the recently released Healthy People 2020 report. These measures, which are listed in Table 1.2, were presented to and approved by the members of the Interagency Work Group for inclusion in the 2011 reports.
Table 1.2. New measures in NHQR/NHDR, 2011
|Effectiveness||Chronic kidney disease |
HIV and AIDS
Maternal and child health
Mental health and substance abuse
|Patient Safety||Surgical Care Improvement Project (SCIP) compositeiv |
|Health System Infrastructure||Electronic Medical Records in Home Health and Hospice Agencies |
Since the first NHQR and NHDR, significant improvements in a number of measures of quality of care have occurred, with U.S. health care providers achieving overall performance levels exceeding 95%. The success of these measures limits their utility for tracking improvement over time. Because these measures cannot improve to a significant degree, including them in the measure set creates a ceiling effect that may distort quantification of rate of change over time. Each year, measures for which performance has reached 95% are retired. Data on retired measures will continue to be collected and these measures will be added back to the reports if their performance falls below 95%.
Measures may also be retired if a more suitable measure is identified. Suitability is determined on the basis of scientific testing, measure acceptance, and availability of valid and reliable data to construct the measure.
Measures retired in 2011 include:
- Receipt of angiotensin-converting enyzme (ACE) inhibitor for heart attack.
- Adult hemodialysis patients with adequate dialysis (urea reduction ratio 65% or greater).
- Emergency department visits in which patients left without being seen.
- Cholesterol test among people with diabetes.
- Evaluation of left ventricular ejection fraction for heart failure.
Policymakers and others have voiced support for composite measures of quality because they can be used to facilitate understanding of information from many different measures. A composite measure summarizes care represented by individual measures that are often related in some way, such as components of care for a particular disease or illness. Composite measures are composed of two or more measures that have been recommended or identified as a "best practice" in the treatment or prevention of complications associated with specific conditions.
Since measures used to construct composites represent various dimensions or processes of care, they provide a more complete understanding of the quality of the U.S. health care system. To ensure that actionable information is available, estimates of performance on the individual measures that make up a composite measure are available in an appendix to these reports.
Decisions concerning the appropriateness of pooling data to generate a composite measure were discussed with data sources. Several of the composite measures included in the reports were developed, tested, and estimated by the data source or other public or private organizations for use in quality assessment, monitoring, and improvement activities.
Composite measures in the NHQR and NHDR are created in several ways. The appropriateness model is sometimes referred to as the "all-or-none" approach because it is calculated based on the number of patients who received all of the services they needed. One example of this model is the diabetes composite, in which a patient who does not receive all four recommended services (two hemoglobin A1c (HbA1c) tests, a foot exam, an eye exam to detect diabetic retinopathy, and a flu shot) would not be counted as having received all recommended care.
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 components of appropriate care that are actually delivered.
The composite measure of recommended hospital care for pneumonia is an example of the use of the opportunities model. The total number of patients who receive treatments represented by individual components of the composite measure (e.g., blood culture collected before antibiotic treatment, initial antibiotic dose received within 6 hours of hospital arrival, influenza or pneumonia screening or vaccination) is divided by the sum of all of the opportunities to receive appropriate care.
The CAHPS® (Consumer Assessment of Healthcare Providers and Systems) surveys have their own method for computing composite measures that has been in use for many years. These composite measures average individual components of patient experiences of care and are presented as the proportion of respondents who indicate that providers and/or systems sometimes or never, usually, or always performed well.
Two composite measures pertaining to patient safety are postoperative complications and complications from central venous catheters. For these composites, an additive model is used that sums individual complication rates. Thus, 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 100 patients had a total of 30 complications among them (regardless of their distribution), the composite score would be 30%.
On occasion, changes to the specification of a composite measure are made to better reflect clinical guidelines or to replace one of the measures of the composite that has improved beyond the 95% threshold. For the 2011 reports, the following changes to the specification of selected composite measures were made:
- Heart failure treatment: Assessment of left ventricular ejection fraction replaced with use of ACE inhibitor.
- Diabetes: Annual receipt of flu shot added and receipt of HbA1c changed from once to twice a year.
Each year AHRQ staff, in conjunction with the Interagency Work Group, select a theme that will be explored in greater detail in the Highlights section, as well as in the body of the report. For 2011, the focus of the NHQR and NHDR is on understanding the quality of care rendered to America�s older population and the extent to which improvements in quality have occurred over time.
In the NHQR, measures are tracked for different groups, such as age, gender, and geographic location. In the NHDR, comparisons are made across groups defined by race, ethnicity, income, education, activity limitations, and geographic location. In general, either the largest subgroup or the best performing subgroup is used as the reference group. Unless specified, the reference group is individuals ages 18-44 for age comparisons, individuals with private health insurance for insurance comparisons, and non-Hispanic Whites for racial and ethnic comparisons.
Size of Disparities Across Groups
Two criteria are applied to determine whether the difference between two groups is meaningful:
- First, the difference between the two groups must be statistically significant with p <0.05 on a two-tailed test.
- Second, the relative difference between the comparison group and the reference group must have an absolute value of at least 10%.
Adjusted percentages, which quantify the magnitude of disparities after controlling for a number of confounding factors, were generated for several measures in the Priority Populations chapter of the NHDR. In examining the relationship between race and ethnicity, for example, multivariate regression analyses were performed to control for differences in the distributions of income, education, insurance, age, gender, and geographic location.
In prior reports, a log-linear regression analysis was conducted to estimate average annual rate of change.vHistorically, progress on individual measures was reported based solely on the magnitude of the annual rate of change. Progress on a measure was deemed to be improving if the annual rate of change was 1% or greater in the desirable direction. Progress on a measure was deemed to be getting worse when the annual rate of change was 1% or greater in the undesirable direction.
This approach is limited by the fact that, depending on the type of measure and the size of the standard error, a 1% difference may not be particularly meaningful. For instance, measures generated from administrative records (such as discharge data), which tend to have thousands or even millions of records, usually have smaller variances than other types of measures, such as those from surveys. The traditional approach for determining whether progress on a measure has been made does not consider the magnitude of error around an estimate, and no mechanism to ascertain whether such a change could have occurred by chance is used in making determinations about progress. It is therefore possible that, while a measure may meet the 1% threshold, annual rates of change may not be significant.
Data used for trending are aggregate or average estimates for a measure, with data collected for a minimum of four data points (years), covering periods between 2000 and 2010. As such, trend analyses are generally conducted with a small number of observations. The level of precision across these points may be nonconstant, or heteroskedastic. Ideally, values with lower variances, indicative of greater precision, would be weighted more heavily than estimates with higher variances, or lower precision.
With guidance from the Interagency Work Group methods subgroup, we identified and tested options for strengthening trend analyses by addressing heteroskedasticity or the amount of uncertainty around an estimate. A weighted log-linear model, where data points with lower variances are weighted more heavily than those with greater variances, as indicated below, was found to improve model fit.
- Model: ln(M) = β0 + β1Y, where ln(M) is the natural logarithm of the value of the measure and β1 is the coefficient corresponding to year Y.
- Weight: w = (M2/v), where M2 is the square of the measure value and v is the variance.
Progress on individual measures was determined as follows:
- Progress on a measure is deemed to be improving if the average annual rate of change is 1% or greater in the desirable direction, and p <0.10.vi
- Progress on a measure is deemed to be getting worse when the average annual rate of change is 1% or greater in the undesirable direction, and p <0.10.
- Progress is determined to have remained the same if the average annual rate of change is ≤1% in either the desirable or undesirable direction or p >0.10.
Trends in Disparities in Population Subgroups
Across subpopulation groups, the absolute annual rate of change was estimated to ascertain the extent to which disparities in quality and access measures were increasing, decreasing, or remaining the same over time. As shown below, calculation of change in subgroup disparities was conducted in a manner similar to that described above, except that a linear regression model was used in the analyses.
- Model: M = β0 + β1Y, where M is the value of the measure and β1 is the coefficient corresponding to year Y.
- Weight: w = (1/v), where v is the variance.
The difference in annual rate of change for the comparison group relative to the reference group was estimated. Determinations of whether subgroup differences have grown, narrowed, or remained the same were based on estimated differences in annual rate of changes as specified below:
- Subgroup differences are deemed to be narrowing if the change in disparities is less than -1 and p <0.10.
- Subgroup differences are deemed to be growing if the change in disparities is greater than 1 and p <0.10.
- Subgroup differences are deemed to have remained the same if the change in disparities is between -1 and 1, or p >0.10.
Only those measures with 4 or more years of data were included in this trending analysis. Due to methodological changes in trending analysis, it is not appropriate to compare the annual change or rates of change for measure groups discussed in this year�s report with those from prior years.
Measure-specific benchmarks, which were first incorporated into the NHQR and NHDR in 2010, are also included in the 2011 reports. Benchmarks reflect the highest level of performance documented for individual measures, with performance assessed at the State level. Benchmarks enable readers to assess national performance on a measure relative to that of the highest performing States. They also aid in establishing reasonable performance improvement goals.
From an equity perspective, standards of performance should not differ across population groups. As such, benchmarks corresponding to measures included in both the NHQR and NHDR were identical. Benchmarks were estimated for the subset of measures for which State data were available. Values of benchmarks estimated in 2010 have been carried over to the 2011 reports.
For measures for which State-level data were available, benchmarks were estimated as the average value for the 10% of States that had the best performance on the measure of interest. For benchmarking purposes, the District of Columbia is treated as a State. Benchmarks were estimated only if data were available for a minimum of 30 States. Identical benchmarks were used to characterize performance in both the NHDR and NHQR.
State-level estimates used in constructing benchmarks were primarily calculated from the same data source as the measure. In some cases, such as when the number of individuals sampled from a specific State was too small, data did not support estimation at a subnational level and benchmarks were not identified. We made exceptions for three measures derived from the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS).
For these measures of colorectal cancer screening, diabetes care, and pneumococcal vaccination, almost identical data were available from Behavioral Risk Factor Surveillance System (BRFSS) State data. However, BRFSS sampling and mode of administration differ from MEPS and NHIS. Hence, to calculate a benchmark for these measures, we first calculated the ratio of the top 10% achievable benchmark to the overall national estimate from BRFSS. We then applied this ratio to the overall national estimate from MEPS or NHIS. For example, if the BRFSS benchmark to national estimate ratio for a measure was 1.5, we would multiply the national estimate for that measure from MEPS by 1.5 to obtain a corresponding benchmark.
Time To Achieve Benchmark
Projections of the time expected for population subgroups to achieve the designated benchmark based on past performance are again included in the 2011 reports. Using standard linear regression of the actual values over time and extrapolating to future years, we calculated the time required for the population, or population subgroup, to perform at the level of the top-performing States. Since projections of future performance were based on past performance data, we needed to ensure reliability by limiting estimates to those cases in which at least four data points were available.
An important caveat to consider in using information on time to achieve benchmarks is that the linear estimation approach used to derive these estimates assumes that characteristics of the population, technology, and health care infrastructure remain constant. Changes in the characteristics of the population or health care system may be expected to alter achievement of benchmarks. Advancements in medical science, changes in the organization of health services, or reductions in the uninsured population following implementation of the Patient Protection and Affordable Care Act (P.L. 11-148) would be expected to alter the performance trajectory. In some cases, the time to achieve the benchmark will drop, while in other cases it may increase.
Time to achieve a benchmark is not presented for measures that met one or more of the following conditions:
- Average annual rate of change is less than 1%.
- Time to benchmark is estimated at 25 or more years.
- Trends over time show movement away from the benchmark (these occurrences are mentioned in the reports).
- Direction of trend changes over time; operationally, these were identified as cases in which there were at least 4 years of data showing "upward" movement and at least 4 years of data showing "downward" movement.
Methods Used in Highlights
Data presented in the Highlights differ from those in other chapters of the report in that core and supporting measures are characterized or grouped along several dimensions that offer insight into the performance of specific elements of the health care system. One category is type of care, where measures are classified as follows:
- Prevention measures focus on educating people about healthy behaviors and lifestyle modification in order to postpone or avoid illness and disease.
- Acute care measures pertain to the delivery of care for an acute condition and receipt of optimal treatment to help reduce the effects of illness and promote the best recovery possible.
- Chronic disease management measures pertain to diseases, such as diabetes and chronic kidney disease, that are chronic and must be managed across a lifetime. Effective management of chronic disease can mean the difference between healthy living and frequent medical problems.
- Outcome measures are indicative of the result or impact of medical care. Many factors other than the care received affect health outcomes, such as lifestyle, social and physical environment, and genetic predisposition to disease. Outcome measures are typically adjusted for risk or patient characteristics.
Other groupings used in the Highlights chapter to summarize results include type of measure (quality, safety, access) and care setting.
Not all measures may be readily classified into the above groupings. For instance, many measures of patient perceptions of care do not fit within "type of care" groupings (e.g., "adults who had a doctor's office or clinic visit in the last 12 months whose health providers listened carefully to them"). Because these measures contain no information to suggest the type of care rendered, they are excluded from analyses that aggregate measures by type of care.
The Highlights also summarize disparities by race and ethnicity. For each racial or ethnic subgroup, the percentages of measures for which that group received worse care, similar care, or better care than the reference group (White or non-Hispanic White) were estimated. Group rates were divided by reference group rate to calculate the relative rate for core measures, with each core measure framed negatively (e.g., for immunization, the likelihood of not receiving the vaccine).
The process involved in compiling data for the Highlights is complicated by the fact that data on all measures are not collected or reported each year. In the summary trend analyses, we obtain all available data points between the year 2000 and the current data year for each measure. For most measures, trends include data points from 2001-2002 to 2007-2008.
To avoid duplication of estimates within categories, composite measures are not included in other categories where estimates from their component measures are used. For example, the diabetes composite measure (which includes HbA1c measurement, eye exam, flu vaccination, and foot exam) contributes to the overall rate for the core measures group but not to the diabetes group rate, which uses the estimates from the four supporting component measures.
Using the analytic approach previously described, we calculated the sum of measures that were identified as better, worse, or the same (when considering subgroup differences) or that were improving, worsening, or remaining the same over time (when considering trend data). The distribution of measures by subpopulation, type of service, and type of measure (i.e., quality or access) is presented as a way to summarize the status of health care quality and disparities in the United States.
Whereas the NHQR charts show contrast by age, gender, insurance status, and geographic location, the NHDR shows contrasts by:
- Race: White, Black, Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, and more than one race.vii
- Ethnicity: Hispanic and non-Hispanic.viii
- Income: Poor, low income, middle income, and high income.ix
- Education: People with less than a high school education,x high school graduates, and people with any college.
- Disabilities: Basic activity limitations (problems with mobility, self-care, domestic life, and activities that depend on sensory functioning) and complex activity limitations (limitations experienced in work and in community, social, and civic life).xi
Rates relative to standard reference groups are used to quantify the magnitude of disparities and to identify the largest disparities specific groups face. For each group, the group rate was divided by the reference group rate to calculate the relative rates for each measure, with each measure framed in the negative (e.g., the likelihood of not receiving an immunization).
In addition to the measures related to racial and ethnic groups, low-income groups, rural residents, and people with special health care needs presented in the Priority Populations chapter of the NHDR, measures pertaining to women, children, and older adults are presented in other chapters of the NHDR and include comparisons.
In presentation of data and results, the NHQR and NHDR adhere to the following conventions, which are presented below to facilitate understanding of report findings.
- Unless otherwise stated, results discussed in the reports are statistically significant at the 5% level for subgroup differences and at the 10% level for trend analyses.
- For most measures presented in the reports, a higher score indicates better performance. However, in some cases, lower scores are better. Measures for which lower scores represent better performance are identified in the text.
- Trend analyses were performed only for measures for which a minimum of 4 years of data were available.
- Information on the construction of each measure is not always contained in the text, and readers should refer to the Measure Specifications appendix for measure details.
- When racial subgroups used by data sources for routine reporting are inconsistent with NHQR and NHDR standards, the source classification is used in the reports.
Institute on Medicine, Committee on Future Directions for the National Healthcare Quality and Disparities Reports. Future directions for the National Healthcare Quality and Disparities Reports. Washington, DC: National Academies Press; 2010.
Institute of Medicine, Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care. Unequal treatment: confronting racial and ethnic disparities in health care. Washington, DC: National Academy Press; 2003.
i. 42 U.S.C. 299b-2(b)(2).
ii. 42 U.S.C. 299a-1(a)(6).
iii. Public Law 111-148.
iv. Measures included in this composite are: (1) surgery patients who were given an antibiotic at the right time, (2) surgery patients who were given the right kind of antibiotic to help prevent infection, (3) surgery patients whose preventive antibiotics were stopped at the right time, (4) heart surgery patients whose blood sugar is kept under good control in the days right after surgery, (5) surgery patients needing hair removed from the surgical area before surgery who had hair removed using a safer method, (6) surgery patients whose doctors ordered treatments to prevent bloods clots after certain types of surgeries, (7) patients who got treatment at the right time to help prevent blood clots after certain types of surgery, and (8) surgery patients on beta blocker therapy prior to admission who received a beta blocker during the preoperative period.
v. Regression models were specified as follows: ln(M) = β0 + β1(Y), where ln(M) = natural logarithm of the measure value (M); β0 = intercept or constant; β1(Y) = coefficient corresponding to year (Y). The average annual rate of change was calculated as 100 � (exp(β1) - 1).
vi. A probability of 0.10 was selected as the significance level because the magnitude of the standard errors varied considerably by type of data.
vii. Asian includes the former category of Asian or Pacific Islander prior to Office of Management and Budget guidelines, when information was not collected separately by group.
viii. Not all data sources collect information by race and ethnicity separately. In such cases, comparisons are made by combining racial/ethnic group categories (e.g., comparing non-Hispanic Blacks and Hispanics with non-Hispanic Whites.)
ix. Unless otherwise indicated, throughout this report, poor is defined as having family income less than 100% of the Federal poverty level (FPL); near poor or low income refers to income between 100% and 200% of the FPL; middle income refers to income between 200% and 400% of the FPL; and high income refers to income above 400% of the FPL. These are based on U.S. census poverty thresholds for each data year, which are used for statistical purposes.
x. Less than a high school education refers to people who did not complete high school.
xi. 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.