Burden of Comorbid Medical Conditions and Quality of Diabetes Care

  1. Jewell H. Halanych, MD, MSC12,
  2. Monika M. Safford, MD12,
  3. Wendy C. Keys, MPH1,
  4. Sharina D. Person, PHD1,
  5. James M. Shikany, DRPH1,
  6. Young-Il Kim, PHD1,
  7. Robert M. Centor, MD23 and
  8. Jeroan J. Allison, MD, MSC23
  1. 1Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
  2. 2Deep South Center on Effectiveness at the Birmingham Veterans Affairs Medical Center, Birmingham, Alabama
  3. 3Division of General Internal Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
  1. Address correspondence and reprint requests to Jewell H. Halanych, MD, MT 639, 1530 3rd Ave. South, Birmingham, AL 35294-4410. E-mail: jhalanych{at}uab.edu


OBJECTIVE—With performance-based reimbursement pressures, it is concerning that most performance measurements treat each condition in isolation, ignoring the complexities of patients with multiple comorbidities. We sought to examine the relationship between comorbidity and commonly assessed services for diabetic patients in a managed care organization.

RESEARCH DESIGN AND METHODS—In 6,032 diabetic patients, we determined the association between the independent variable medical comorbidity, measured by the Charlson Comorbidity Index (CCI), and the dependent variables A1C testing, lipid testing, dilated eye exam, and urinary microalbumin testing. We calculated predicted probabilities of receiving tests for patients with increasing comorbid illnesses, adjusting for patient demographics.

RESULTS—A1C and lipid testing decreased slightly at higher CCI: predicted probabilities for CCI quartiles 1, 2, 3, and 4 were 0.83 (95% CI 0.70–0.91), 0.83 (0.69–0.92), 0.82 (0.68–0.91), and 0.78 (0.61–0.88) for A1C, respectively, and 0.82 (0.69–0.91), 0.81(0.67–0.90), 0.79 (0.64–0.89), and 0.77 (0.61–0.88) for lipids. Dilated eye exam and urinary microalbumin testing did not differ across CCI quartiles: for quartiles 1, 2, 3, and 4, predicted probabilities were 0.48 (0.33–0.63), 0.54 (0.38–0.69), 0.50 (0.34–0.65), and 0.50 (0.34–0.65) for eye exam, respectively, and 0.23 (0.12–0.40), 0.24 (0.12–0.42), 0.24 (0.12–0.41), and 23 (0.11–0.40) for urinary microalbumin.

CONCLUSIONS—Services received did not differ based on comorbid illness burden. Because it is not clear whether equally aggressive care confers equal benefits to patients with varying comorbid illness burden, more evidence confirming such benefits may be warranted before widespread implementation of pay-for-performance programs using currently available “one size fits all” performance measures.


  • Published ahead of print at http://care.diabetesjournals.org on 23 August 2007. DOI: 10.2337/dc06-1836.

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

    The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C Section 1734 solely to indicate this fact.

    • Accepted August 19, 2007.
    • Received August 31, 2006.
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  1. Diabetes Care vol. 30 no. 12 2999-3004
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