Module 3: Information—Interpreting State Estimates of Diabetes Quality
Diabetes Care Quality Improvement: A Resource Guide for State Action
Key Ideas in Module 3:
Deriving Information From Data
Data do not necessarily convey information. Information comes from data that have been collected, analyzed and arranged to answer a question. Deriving information from data usually requires original data collection designed to answer the question. However, "secondary" use of data collected for another purpose can often lead to powerful information, obtained efficiently.
Both original and secondary data collection require strategies for summarizing and interpreting the results. For example, to determine how well the health care system has educated and motivated people with diagnosed diabetes to control their blood glucose levels requires original data collection of HbA1c laboratory values from clinical records. The resulting values of HbA1c levels must be summarized (e.g., using overall averages), explored by relevant subgroups (e.g., managed care versus private practice to determine how well providers in different settings educate and motivate their patients), and interpreted in terms of how well the assembled database answers the question and represents the total population (e.g., data collected from clinical records miss people without access to health care with undiagnosed diabetes).
Secondary data assembled from various sources for the NHQR address the overarching question of how well the U.S. health care system provides health care for U.S. residents. Although State-specific estimates are provided in the NHQR for many measures, they are not fully analyzed there from a State perspective.
Steering committees for State quality improvement programs need information to answer many questions on the State's health care quality performance. Among them are:
- What measures should the State use to assess health care quality?
- What metrics and comparisons for each measure should be used to compare with the State?
- What does the State's position among other States mean?
- What goals should be set for quality improvement?
While all the questions that a quality improvement committee might raise will not be answerable from data in the NHQR, it is a valuable source for identifying readily available and consensus-based measures for locating national averages, for deriving other benchmarks, and for selecting achievable targets for improvement. This module shows how to do these things from a State viewpoint. Module 2 presented a minimum set of measures from the NHQR that can be used for assessing diabetes quality within the State. Module 3 uses that measure set to describe two steps:
Step 1: Identifying appropriate metrics and comparisons
Step 2: Interpreting the State's position among other States
While the specific questions that State leaders ask about the quality of health care in the State will determine the comparisons to be made, below is a general guide to thinking about and using the data in the NHQR to create information for State quality improvement programs.
Step 1: Identifying Appropriate Metrics and Comparisons
Benchmark Metrics for States
The NHQR provides a national set of estimates and some State estimates that can be used as benchmarks for quality improvement. A benchmark is an external marker for assessing how one entity, for example a State, compares. The benchmark can represent the best performer or the average performer. How the State fares depends on what the benchmark is.
Several types of metrics or benchmarks can be used for assessing a State. From more to less stringent, they include:
- The theoretic limit of aiming for 100-percent achievement (or 0-percent occurrence for avoidable events), which is an ideal but often impractical goal.
- A best-in-class estimate of the top State or top tier of States (the top 10 percent of States is used in this Resource Guide), which shows what has been achieved.
- A national consensus-based goal, such as Healthy People 2010, set by a consensus of experts; such goals may be set more