Reports from the Field: How plans measure performance counts
Reports from the Field
How plans measure performance counts
Performance on standardized measures used by health plans to compute their scores through the Health Plan Employer Data and Information Set (HEDIS), developed by the National Committee for Quality Assurance (NCQA) in Washington, DC, is influenced by factors such as enrollee schooling, income, and ethnicity, according to a recent study. These findings are particularly important because large insurers and other health plan purchasers as well as individual consumers make health insurance contracting decisions based on how well a health plan performs on HEDIS measures.
Researchers analyzed data from 112,397 enrollees of 10 managed care plans in different regions of the United States. They examined how the characteristics of health plan enrollee neighborhoods were related to outcomes on the HEDIS quality measures. Researchers found that within each health plan, certain populations from areas with relatively high percentages of residents on welfare or who were black or Hispanic received generally poorer quality of care, while enrollees in urban areas and areas with higher educational levels or more Asian-American residents received consistently better care.
Although other studies have found that minority, low-income, and poorly educated patients under-use essential medical services, the important finding of this study is that it represents differences among commercially insured patients within the same health plans, notes lead author Alan M. Zaslavsky, PhD, associate professor in the department of health care policy at Harvard University Medical School in Cambridge, MA. He notes that the findings underscore the importance of determining the appropriate role for case-mix adjustment — a method used to make adjustments for the composition of a plan’s enrollees to permit a more accurate assessment of quality of care provided by the plan. Further, Zaslavsky says more detailed adjustments that go beyond geographic proxies for the characteristics of enrollees are necessary to determine the underlying causes of the variations in this study.
[See: Zaslavsky AM, Epstein AM, Cleary PD, et al. Impact of sociodemographic case mix on the HEDIS measures of health plan quality. Medical Care 2000; 38(10):981-992.]
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