Availability of Data to Measure Disparities in Leading Health Indicators at the State and Local Levels
Healthy People 2010 identifies the elimination of health disparities as a critical national goal. The article analyzes the availability of state and local data to support this work.
We assessed data availability for the 10 leading health indicators (LHIs), comprising a set of 26 measures. Our analysis is based on a mid-2007 review of federal and state Web sites.
Federal data sources allow aggregate state estimates for 24 LHI measures, although some either are not available for all states or vary from the federal definition. National sources capture some but not all of the subgroup characteristics, defined as national disparities priorities. Limited sample size is a barrier to generating state estimates for specific subgroups, and data by geographic subdivision within a state are often lacking. States also vary in how aggressively they use disparities data or make them available externally.
Federal leadership has been critical to state capacity to assess LHI disparities. Although some relevant state-level disparities data exist, major gaps remain, local estimates are limited, and some states make better use of the data than others. Continued federal leadership and support is critical to states' abilities to address Healthy People 2010's disparities goal.
Available from: ncbi.nlm.nih.gov
- "Small sample sizes restrict the ability of researchers to measure disparities, even for some of the major racial, ethnic, and socioeconomic subgroups at the national level (Bilheimer and Sisk 2008). The difficulties are compounded at the state and community levels, where actions to address disparities are most likely to occur (Gold, Dodd, and Neuman 2008). Only a few states have their own household health surveys in addition to the Behavioral Risk Factor Surveillance System (BRFSS), which can identify a limited number of racial, ethnic, and socioeconomic groups, but often cannot provide substate estimates for subgroups of the population. "
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ABSTRACT: To describe measurement challenges and strategies in identifying and analyzing health disparities and inequities.
We discuss the limitations of existing data sources for measuring health disparities and inequities, describe current strategies to address those limitations, and explore the potential of emerging strategies.
Larger national sample sizes are necessary to identify disparities for major population subgroups. Collecting self-reported race and granular ethnicity data may reduce some measurement errors, but it raises other methodological questions. The assessment of health inequities presents particular challenges, requiring analysis of the interactive effects of multiple determinants of health. Indirect estimation and modeling methods are likely to be important tools for estimating health disparities and inequities for the foreseeable future.
Interdisciplinary training and collaborative research models will be essential for future disparities research. Evaluation of evolving methodologies for assessing health disparities should be a priority for health services researchers in the next decade.
Health Services Research 10/2010; 45(5 Pt 2):1489-507. DOI:10.1111/j.1475-6773.2010.01143.x · 2.78 Impact Factor
Available from: Joseph G L Lee
Nicotine & Tobacco Research 06/2009; 11(7):908-9. DOI:10.1093/ntr/ntp069 · 3.30 Impact Factor
Available from: Jamie F Chriqui
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ABSTRACT: Public health policy has a profound impact on health status. Missing from the literature is a clear articulation of the definition of evidence-based policy and approaches to move the field forward. Policy-relevant evidence includes both quantitative (e.g., epidemiological) and qualitative information (e.g., narrative accounts). We describe 3 key domains of evidence-based policy: (1) process, to understand approaches to enhance the likelihood of policy adoption; (2) content, to identify specific policy elements that are likely to be effective; and (3) outcomes, to document the potential impact of policy. Actions to further evidence-based policy include preparing and communicating data more effectively, using existing analytic tools more effectively, conducting policy surveillance, and tracking outcomes with different types of evidence.
American Journal of Public Health 08/2009; 99(9):1576-83. DOI:10.2105/AJPH.2008.156224 · 4.55 Impact Factor
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