Targeting Diabetes Prevention to More Disadvantaged Groups Improves Cost-Effectiveness: Implications of Inequality in Type 2 Diabetes From Theoretical Interventions |
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| Institution: | 1. Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia;2. Baker Heart and Diabetes Institute, Melbourne, VIC, Australia;3. School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia;1. Austrian Institute for Health Technology Assessment GmbH, Vienna, Austria;2. Village Research Group, Medical University Innsbruck, Innsbruck, Austria;3. London School of Economics, Care Policy and Evaluation Centre (CPEC), London, England, UK;4. Monash University Australia, School of Rural Health, Melbourne, VIC, Australia;5. Philipps-University Marburg, Fachbereich Psychologie, Marburg, Germany;1. RTI Health Solutions, Research Triangle Park, NC, USA;2. Department of Pharmaceutical Systems and Policy, West Virginia University School of Pharmacy, Morgantown, WV, USA;1. Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA;2. Center for Global Public Health, Tufts University School of Medicine, Boston, MA, USA;3. Division of Geographic Medicine and Infectious Disease, Tufts Medical Center, Boston, MA, USA;4. Center for Global Health, Massachusetts General Hospital, Boston, MA, USA;5. Department of Medicine, Harvard Medical School, Boston, MA, USA;6. TB Centre, London School of Hygiene & Tropical Medicine, London, England, UK;1. Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, USA;2. Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, Medical School, University of Michigan, Ann Arbor, MI, USA;1. Health Services Management Department, Guizhou Medical University, Gui’an, China;2. College of Pharmacy, Jinan University, Guangzhou, China;3. School of Public Health, Fudan University, Shanghai, China;4. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China;5. Department of Pharmacy Administration, School of Pharmacy, Health Science Center, Xi’an Jiaotong University, Xi’an, China;6. School of Pharmacy, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China;7. The Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, Nanjing, China;8. Saw Swee Hock School of Public Health, National University of Singapore, Singapore |
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| Abstract: | ObjectivesTo determine the effect of socioeconomic status on efficacy and cost thresholds at which theoretical diabetes prevention policies become cost-effective.MethodsWe designed a life table model using real-world data that captured diabetes incidence and all-cause mortality in people with and without diabetes by socioeconomic disadvantage. The model used data from the Australian diabetes registry for people with diabetes and the Australian Institute of Health and Welfare for the general population. We simulated theoretical diabetes prevention policies and estimated the threshold at which they would be cost-effective and cost saving, overall, and by socioeconomic disadvantage, from the public healthcare perspective.ResultsFrom 2020 to 2029, 653 980 people were projected to develop type 2 diabetes, 101 583 in the least disadvantaged quintile and 166 744 in the most. Theoretical diabetes prevention policies that reduce diabetes incidence by 10% and 25% would be cost-effective in the total population at a maximum per person cost of Australian dollar (AU$) 74 (95% uncertainty interval: 53-99) and AU$187 (133-249) and cost saving at AU$26 (20-33) and AU$65 (50-84). Theoretical diabetes prevention policies remained cost-effective at a higher cost in the most versus least disadvantaged quintile (eg, a policy that reduces type 2 diabetes incidence by 25% would be cost-effective at AU$238 169-319] per person in the most disadvantaged quintile vs AU$144 103-192] in the least).ConclusionsPolicies targeted at more disadvantaged populations will likely be cost-effective at higher costs and lower efficacy compared to untargeted policies. Future health economic models should incorporate measures of socioeconomic disadvantage to improve targeting of interventions. |
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| Keywords: | disease prevention health economic analysis socioeconomic status type 2 diabetes |
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