A Computer Simulation Model of Diabetes Progression, Quality of Life, and Cost

  1. Honghong Zhou, PHD1,
  2. Deanna J.M. Isaman, PHD1,
  3. Shari Messinger, PHD1,
  4. Morton B. Brown, PHD1,
  5. Ronald Klein, MD, MPH2,
  6. Michael Brandle, MD, MS34 and
  7. William H. Herman, MD, MPH34
  1. 1Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan
  2. 2Department of Ophthalmology, University of Wisconsin, Madison, Wisconsin
  3. 3Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
  4. 4Department of Epidemiology, University of Michigan, Ann Arbor, Michigan
  1. Address correspondence and reprint requests to William H. Herman, MD, MPH, University of Michigan Health System, 3920 Taubman Center, 1500 East Medical Center Dr., Ann Arbor, MI 48109-0354. E-mail: wherman{at}umich.edu


OBJECTIVE—To develop and validate a comprehensive computer simulation model to assess the impact of screening, prevention, and treatment strategies on type 2 diabetes and its complications, comorbidities, quality of life, and cost.

RESEARCH DESIGN AND METHODS—The incidence of type 2 diabetes and its complications and comorbidities were derived from population-based epidemiologic studies and randomized, controlled clinical trials. Health utility scores were derived for patients with type 2 diabetes using the Quality of Well Being–Self-Administered. Direct medical costs were derived for managed care patients with type 2 diabetes using paid insurance claims. Monte Carlo techniques were used to implement a semi-Markov model. Performance of the model was assessed using baseline and 4- and 10-year follow-up data from the older-onset diabetic population studied in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR).

RESULTS—Applying the model to the baseline WESDR population with type 2 diabetes, we predicted mortality to be 51% at 10 years. The prevalences of stroke and myocardial infarction were predicted to be 18 and 19% at 10 years. The prevalences of nonproliferative diabetic retinopathy, proliferative retinopathy, and macular edema were predicted to be 45, 16, and 18%, respectively; the prevalences of microalbuminuria, proteinuria, and end-stage renal disease were predicted to be 19, 39, and 3%, respectively; and the prevalences of clinical neuropathy and amputation were predicted to be 52 and 5%, respectively, at 10 years. Over 10 years, average undiscounted total direct medical costs were estimated to be $53,000 per person. Among survivors, the average utility score was estimated to be 0.56 at 10 years.

CONCLUSIONS—Our computer simulation model accurately predicted survival and the cardiovascular, microvascular, and neuropathic complications observed in the WESDR cohort with type 2 diabetes over 10 years. The model can be used to predict the progression of diabetes and its complications, comorbidities, quality of life, and cost and to assess the relative effectiveness, cost-effectiveness, and cost-utility of alternative strategies for the prevention and treatment of type 2 diabetes.


  • Additional information for this article can be found in an online appendix available at http://care.diabetesjournals.org.

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

    • Accepted September 11, 2005.
    • Received April 11, 2005.
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