Asthma Care Quality Improvement
Module 4: Measuring Quality of Care for Asthma (continued)
Factors That Affect Quality of Asthma Care
The State data presented above raise several questions for anyone involved in quality improvement.
- What does a State's position on the continuum of quality measures mean?
- What factors influence that position and the variability among the States?
- What factors can be influenced through State policy change and local efforts?
A number of factors influence quality and outcomes of health care for any disease, as Figure 4.6 (7 KB) shows. Some factors may be difficult to change, such as biologically inherited traits; income, education, and social status; and general population characteristics. Others may be changeable in the medium or long term, but not in the short term, such as the supply of health care professionals, the makeup and mission of health care organizations, and the disease prevalence of the population (which represents ingrained patterns of personal behaviors and health system effectiveness). All of these factors influence the process and outcome of health care.
Although State government and community leaders do not have control over all factors, State actions can influence some important factors to promote positive change. These include educating people with asthma about the risks of uncontrolled asthma, raising awareness among professionals about health care processes that can improve outcomes for people with asthma, raising awareness in schools and communities about mitigating risk factors that can trigger asthma attacks, and creating financial incentives to encourage providers to manage diseases with their patients. Some States, for example, target programs to affect patient self-management and other external causes toward minority populations that are disproportionately affected by asthma.
To better understand what influences a State's position and how it compares with other States, some of the factors presented in Figure 4.6 are discussed in more detail below.
Racial, Ethnic, and Socioeconomic Factors
The socioeconomic makeup of a State will likely play a role in how it compares to national norms on process and outcome measures. States with a higher proportion of individuals living in poverty, lower average education, and a more diverse racial and ethnic population, for instance, will likely find poorer outcomes for their population compared to the national population (IOM, 2003)
The NHDR (AHRQ, 2003; 2004a) summarized the racial, ethnic, and socioeconomic differences in asthma across the Nation (but not by State). Nationwide, minority or lower socioeconomic status is associated with higher asthma prevalence, higher asthma death rates, higher rates of serious asthma complications, and poorer asthma outcomes. (Blacks, for example, are much more likely than Whites to be hospitalized for asthma; go to Table 4.3).
The socioeconomic makeup of a State, therefore, should play a role in the strategies that the State uses to improve asthma care quality. For instance, States that target efforts to improve asthma care at population groups particularly at risk for asthma complications should also be able to improve their overall performance on asthma care quality.
Biological and Behavioral Factors
Understanding biological and behavioral influences on asthma should help in developing assessment tools and interventions for preventing or reducing the burden of asthma. Risk factors for asthma include (King, et al., 2004):
- Parental history of asthma.
- Early-life stressors and infections.
- Exposure to indoor allergens, tobacco smoke, and outdoor pollutants.
- Work-related exposures.
Socioeconomic factors may be related to underlying biological factors or behavioral factors. The accumulated stress of poverty, low levels of control in jobs and relationships, low job and life satisfaction, and societal discrimination against minority groups can influence health status (Williams, 1999).
The physical environment in which asthma patients live is an important contributor to their asthma severity. The presence of poor air quality, dust, pets, cockroaches, and other allergens can affect how well a patient is able to control his or her asthma. A recent study released by the National Institutes of Health shows the connection between decayed bacteria in bedrooms and other rooms of a house and asthma prevalence (Thorne, et al., 2005).
In addition to individual characteristics (some of which are amenable to change with personal motivation), each State has a different infrastructure and different environmental factors over which policymakers may or may not have control. These factors include the collective health status of the population, the distribution of health care services within locales, the distribution of wealth and tax resources among communities, and government programs and leadership.
State leaders will face different health care system challenges, including:
- Health system infrastructure—Availability of health professionals, emergency rooms, and hospitals beds.
- Uninsured populations—Presence of vulnerable and uninsured populations and the need for special State programs to cover the cost of health care for them.
- Safety net infrastructure—Availability of a safety net of health care providers as a last resort for those who cannot afford health insurance and private health care.
- Provider knowledge—Providers who have sufficient state-of-the-art knowledge to manage asthma effectively and to educate their patients in asthma self-management.
- Public education—Public education programs that raise patient awareness of the warning signs of the disease, its potential complications, the importance of diet and exercise, and the effectiveness of personal self-management, including knowing when to consult a doctor.
- Government resources—Funds, in a time of tight State budgets, to stimulate quality improvement activities related to asthma care.
- Leaders to champion quality improvement—Leaders who can draw attention to the problems associated with asthma and harness the commitment of health professionals to change practices and monitor results.
- Knowledge of what to do—Identification of effective quality improvement programs that are based on scientific evidence.
- Adequate data systems to assess progress—Availability of data systems that can provide comparable measures across providers, communities, and States.
The inter-relationship among all of the factors in Figure 4.6, then, affects how a State compares with other States on measures of asthma care quality.
It is difficult to measure all of these factors at the State level. An attempt was made to analyze the Behavioral Risk Factor Surveillance System (BRFSS) measures in Table 4.2 against individual State-level environmental factors—prevalence of asthma, emphysema and chronic bronchitis in the population, the percent of the population below poverty level, racial/ethnic makeup of the population, the HMO penetration rate, the supply of hospital beds, and air quality in the State. The findings were not consistent enough across measures and factors to be believable. Again, the small sample sizes and imprecision of the asthma estimates themselves may be the limiting factor. Moreover, survey averages (e.g., percent having planned care visits) related to State aggregates from other sources (e.g., percent of the population that is uninsured) do not provide a direct test of these relationships.
With large databases, it is possible to assess asthma care quality at not only the State but also local levels for some measures. For example, HCUP data and the statewide discharge data systems that are the source of HCUP data (with its hundreds of thousands of discharge records per State per year) support analyses at the county or other market areas. County-level data related to health care resources are generally available, although county data on health risk behaviors of the population generally are not. State analysts could use their county-level databases to compare asthma outcome measures based on HCUP data—e.g., asthma hospitalizations—or on data from their statewide data organization with other county characteristics. AHRQ's Prevention Quality Indicator software can be applied to a State's discharge data to produce county-level statistics.
Local leaders and health care professionals must see their own data in comparison with other provider data and with State, regional, and national benchmarks in order to appreciate the importance of their work. Assessing State quality of care for asthma begins with identifying quality measures. These fall into two main groups: process measures, which reflect the quality of care delivered, and outcome measures, which reflect patient health status. The former are needed to guide health care providers on how to change, the latter are needed to know whether the changed processes have had the intended effect. Data (whether State, county, municipal, or individual health care provider data) are essential for quality improvement programs to have an impact locally. Ideally, improvements in particular processes yield improvements in the associated outcomes.
The National Healthcare Quality Report (NHQR) provides a starting point for accessing consensus-based measures. The NHQR provides estimates for asthma hospitalizations by State. In addition, BRFSS estimates are used to assess asthma care quality by State. Although consensus on a few key measures of asthma care quality has not yet evolved, this Resource Guide provides an inventory of some measures.
Data are essential to improve quality. States need performance data on asthma care to gauge their own performance against national benchmarks and to focus quality improvement efforts by identifying potential problem areas. This Resource Guide provides a list of national, State, and local sources for estimates for asthma, asthma care, and other related information.
This module also shows how data can be analyzed and interpreted to answer the global question: How does my State compare with other States and national benchmarks on health care quality for asthma? State-level baseline estimates across all conditions studied in the NHQR afford State leaders a broad view of health care quality in their State. More refined questions about areas within the State will require local data and analysis.
Resources for Further Reading
Data and Data Tools on the Internet
Many data resources are available on the Internet, including many sources used in the NHQR and NHDR. Some Web sites allow users to manipulate the data to produce tables and other useful outputs. Such resources include:
HCUPnet allows users to select national statistics, or detailed statistics for certain States, for various conditions and procedures. The interactive program also allows users to compare types of patients and types of hospitals. These statistics are based on data received from Statewide hospital discharge data programs for inclusion in HCUP.
- HCUP User Support (HCUP-US)
This Web site is designed to answer HCUP-related questions; provide detailed information on HCUP databases, tools, and products; and offer assistance to HCUP users.
- AHRQ Quality Indicators
The AHRQ Quality Indicators are measures of health care quality that make use of readily available hospital inpatient administrative data. Asthma measures can be found in the Prevention Quality Indicators module.
This Web site offers users statistics and trends about health care expenditures, utilization, and health insurance, including national and regional health insurance estimates.
- BRFSS—Annual Survey
This Web site has detailed technical information about the survey in addition to downloadable data sets in ASCII and SAS formats.
- Behavioral Risk Factor Surveillance System (BRFSS)
This Web site provides useful background information about the BRFSS implementation, technical information, and documentation.
- Centers for Disease Control and Prevention (CDC) Faststats—Asthma
The Centers for Disease Control and Prevention's (CDC) Faststats Web site provides easy access to statistics on topics of public health importance. The asthma page has a general overview of asthma statistics and links to specific data sources for more information on national data for asthma.
Some additional Web sites offer links to useful tools and information to facilitate data collection at the local level. Two Web sites that offer instruction for implementing asthma registries to track the treatments given to people with asthma are:
This Web site, associated with the HRSA Health Disparities Collaboratives, offers a number of useful tools, including helpful information for creating and assessing computer registries.
This Web site offers a comparison of asthma registries.
Other Useful Web Sites
Agency for Healthcare Research and Quality—http://www.ahrq.gov/
National Asthma Control Program—http://www.cdc.gov/asthma/NACP.htm
National Committee for Quality Assurance—http://www.ncqa.org/index.asp
National Quality Forum—http://www.qualityforum.org/
National Guideline Clearinghouse—http://www.guidelines.gov/
National Asthma Education and Prevention Program— http://www.nhlbi.nih.gov/about/naepp/
Associated Appendixes for Use With This Module
Appendix E: 2003 BRFSS Measures, Data, and Benchmarks
Appendix E provides the results of significance tests for BRFSS State estimates compared to the national average of each measure and compared to the best-in-class estimates for each measure. P-values less than 0.05 are considered statistically significant. State estimates that have p-value less than 0.05 are statistically different from the comparison estimate (national average or best-in-class). State estimates that have p-value greater than 0.05 are not statistically different from the comparison estimate.
Appendix F: Other Data Sources
Appendix F summarizes data sources used in this Resource Guide other than BRFSS data. This appendix includes descriptions and tables, where available, of national data sources (HCUP, HEDIS®, MEPS, and NHDS) and local data sources available from some States.
Appendix G: Benchmarks from the NHQR
Appendix G provides additional detail on benchmarks that can be derived from the NHQR and explains how they were developed and defined for this Resource Guide. This appendix discusses the best benchmarks for stimulating quality improvement, emphasizing that methods used to generate the benchmarks must be understood to ensure they are compatible with a State's estimates.
Appendix H: Information on Statistical Significance
Appendix H shows how to compare State estimates to benchmarks using statistical significance and p-values that take into account the expected random variation in estimates. This appendix also shows how to calculate p-values when estimates and standard errors are provided.