Variation in Diabetes Care Among States

Do patient characteristics matter?

  1. David R. Arday, MD, MPH1,
  2. Barbara B. Fleming, MD, PHD2,
  3. Dana K. Keller, PHD3,
  4. Peter W. Pendergrass, MD, MPH4,
  5. Robert J. Vaughn, MPH4,
  6. James M. Turpin, BS4 and
  7. David A. Nicewander, MS2
  1. 1Army Medical Surveillance Activity, Washington, DC
  2. 2Centers for Medicare and Medicaid Services, Baltimore, Maryland
  3. 3Delmarva Foundation for Medical Care, Inc., Easton, Maryland
  4. 4Texas Medical Foundation, Austin, Texas


    OBJECTIVE—To examine state variability in diabetes care for Medicare beneficiaries and the impact of certain beneficiary characteristics on those variations.

    RESEARCH DESIGN AND METHODS—Medicare beneficiaries with diabetes, aged 18–75 years, were identified from 1997 to 1999 claims data. Claims data were used to construct rates for three quality of care measures (HbA1c tests, eye examinations, and lipid profiles). Person-level variables (e.g., age, sex, race, and socioeconomic status) were used to adjust state rates using logistic regression.

    RESULTS—A third of 2 million beneficiaries with diabetes aged 18–75 years did not have annual HbA1c tests, biennial eye examinations, or biennial lipid profiles. There was wide variability in the measures among states (e.g., receipt of HbA1c tests ranged from 52 to 83%). Adjustment using person-level variables reduced the variance in HbA1c tests, eye examinations, and lipid profiles by 30, 23, and 27%, respectively, but considerable variability remained. The impact of the adjustment variables was also inconsistent across measures.

    CONCLUSIONS—Opportunities remain for improvement in diabetes care. Large variations in care among states were reduced significantly by adjustment for characteristics of state residents. However, much variability remained unexplained. Variability of measures within states and variable impact of the adjustment variables argues against systems effects operating with uniformity on the three measures. These findings suggest that a single approach to quality improvement is unlikely to be effective. Further understanding variability will be important to improving quality.


    • Address correspondence and reprint requests to James M. Turpin, Texas Medical Foundation, 901 Mopac Expressway South, Barton Oaks Plaza II, Suite 200, Austin, TX 78746. E-mail: txpro.jturpin{at}

      Received for publication 30 January 2002 and accepted in revised form 11 September 2002.

      Additional information for this article can be found in an online appendix at

      The content of this manuscript does not necessarily reflect the view of policies of the Department of Health and Human Services or the Centers for Medicare and Medicaid Services. The opinions expressed are those of the authors, who assume full responsibility for the accuracy and completeness of the ideas presented.

      A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

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