Targeting Diabetes Prevention to More Disadvantaged Groups Improves Cost-Effectiveness: Implications of Inequality in Type 2 Diabetes From Theoretical Interventions

Jul 1, 2023, 00:00 AM
10.1016/j.jval.2023.02.003
https://www.valueinhealthjournal.com/article/S1098-3015(23)00051-7/fulltext
Section Title : COMPARATIVE-EFFECTIVENESS RESEARCH/HTA
Section Order : 974
First Page : 974

Objectives

To determine the effect of socioeconomic status on efficacy and cost thresholds at which theoretical diabetes prevention policies become cost-effective.

Methods

We 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.

Results

From 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).

Conclusions

Policies 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.

https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(23)00051-7&doi=10.1016/j.jval.2023.02.003
HEOR Topics :
  • Cost-comparison, Effectiveness, Utility, Benefit Analysis
  • Decision Modeling & Simulation
  • Diabetes/Endocrine/Metabolic Disorders
  • Economic Evaluation
  • Health Disparities & Equity
  • Health Policy & Regulatory
  • Specific Diseases & Conditions
  • Study Approaches
Tags :
  • disease prevention
  • health economic analysis
  • socioeconomic status
  • type 2 diabetes
Regions :
  • Asia Pacific (including Oceania)