of these process measures partially because adults over age 64 are excluded from this measure (while they are included in the other three measures). Moreover, Healthy People 2010 did not set a goal for influenza immunization of this population.
Understanding State Variation
Although comparing the State's rate to a benchmark shows how far or close the State's rate is from the benchmark, it gives few clues as to the State's position among all other States. If a State's rate is below the national average, is it the lowest of the low States? Or, is it doing better than all the other States that are below the national norm? Knowing this ranking can help a State understand how much effort might be needed to catch up with health care quality in other States.
Average benchmark values do not reveal the degree of variation that exists on any one measure across the Nation. Variation among States can be seen on a scatter diagram, where each State represents one point on the graph. Other indicators can be added to and identified on that scatter diagram with different symbols. Figure 3.2 shows (as gray diamonds) the distribution of State rates for important tests that should be performed each year for people with diabetes. It superimposes the national average as a black square and the best-in-class average as a black triangle.
Figure 3.2 reveals that immunization for influenza for people with diabetes has the most State variation among the four measures and it has the lowest rates — providers in one State vaccinated only 17 percent of adults aged 18 to 64 with diabetes. The spread among the States is nearly fourfold, from 17 to 64 percent. Also, the other tests are performed with wide variation — spread from about 50 percent to 80 or 90 percent of adults with diabetes, across the States. Such variation indicates considerable room for improvement for many of the States.
Figure 3.2 was modified to track an individual State (State A) across all the measures of diabetes care quality. For example, in Figure 3.3, State A is represented as a black diamond when it is statistically different from the national average or as a black-bordered white diamond when it is not statistically different from the national average.
The solid black diamond in Figure 3.3 shows that State A's rate compared to the national average is considered a statistically significant difference and probably is not attributable to just random variation that appears among the States and within each State. It may well represent some practice difference in State A that is not common nationally. What that difference is caused by cannot be deciphered from these data. Local insights and exploration are needed to understand underlying factors that might influence State A's rate of HbA1c testing.
The black-bordered white diamond in Figure 3.3 indicates that State A's rate compared to the national average is not considered a statistically significant difference and could as easily occur because of random variation as because of any specific practice by health care providers in State A. (Statistical significance and how it is determined is explained in Appendix E.)
In general (although not shown for all States, here), when individual States are tracked across diabetes measures, it becomes apparent that there is uneven performance across measures. No single State consistently ranks highest or lowest across all measures. Thus, all States have some room for improvement compared to national benchmarks and clinical guidelines for the treatment of people with diabetes.
Four States Compared to Benchmarks
To show how States may want to examine their own estimates, four States are compared to national, regional, and best-in-class State-average benchmarks, below. The national average and best-in-class average, when used together, summarize key information across the States and enable graphical comparisons to be simplified as bar charts (go to Figures 3.4.A, 3.4.B, 3.4.C, and 3.4.D).
In the bar charts, statistical significance from the national average is represented by a bold value at the top 