Ping Zhang1, Karen M Atkinson2, George A Bray3, Haiying Chen4, Jeanne M Clark5, Mace Coday6, Gareth R Dutton7, Caitlin Egan8, Mark A Espeland4, Mary Evans9, John P Foreyt10, Frank L Greenway3, Edward W Gregg11, Helen P Hazuda12, James O Hill13, Edward S Horton14, Van S Hubbard9, Peter J Huckfeldt15, Sharon D Jackson14, John M Jakicic16, Robert W Jeffery17, Karen C Johnson6, Steven E Kahn2, Tina Killean18, William C Knowler18, Mary Korytkowski19, Cora E Lewis20, Nisa M Maruthur5, Sara Michaels21, Maria G Montez12, David M Nathan22, Jennifer Patricio23, Anne Peters24, Xavier Pi-Sunyer23, Henry Pownall25, Bruce Redmon17, Julia T Rushing4, Helmut Steinburg6, Thomas A Wadden26, Rena R Wing8, Holly Wyatt27, Susan Z Yanovski. 1. Centers for Disease Control and Prevention, Atlanta, GA paz2@cdc.gov. 2. VA Puget Sound Health Care System and University of Washington, Seattle, WA. 3. Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA. 4. Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC. 5. Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD. 6. Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN. 7. Division of Preventive Medicine, School of Medicine, The University of Alabama at Birmingham, Birmingham, AL. 8. Weight Control and Diabetes Research Center, The Miriam Hospital, Providence RI. 9. National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD. 10. Department of Medicine, Baylor College of Medicine, Houston, TX. 11. Department of Epidemiology and Biostatistics, Imperial College London, London, U.K. 12. Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX. 13. Department of Nutrition Sciences, The University of Alabama at Birmingham, Birmingham, AL. 14. Department of Medicine, Joslin Diabetes Center, Boston, MA. 15. Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN. 16. Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA. 17. Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN. 18. National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ. 19. Department of Medicine, University of Pittsburgh, Pittsburgh, PA. 20. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL. 21. Indian Health Service, Shiprock, NM. 22. Diabetes Research Center, Massachusetts General Hospital, Boston, MA. 23. Department of Medicine, St. Luke's-Roosevelt Hospital Center, Columbia University, New York, NY. 24. Houston Methodist Research Institute, Baylor College of Medicine, Houston, TX. 25. Division of Endocrinology and Diabetes, Keck School of Medicine of the University of Southern California, Los Angeles, CA. 26. Center for Weight and Eating Disorders, University of Pennsylvania, Philadelphia, PA. 27. Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO.
Abstract
OBJECTIVE: To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS: Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS: Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS: Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.
OBJECTIVE: To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS: Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS: Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS: Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.
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