Cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study
Main finding · ICERResult — go to the resultICER JPY 1,598,244/QALY (USD 11,375/QALY)Authors' conclusion
The introduction of AI-based DR screening for SHC and diabetes management was cost-effective compared to the current situation in Japan.
Study context
- Population
- Modelled population in Japan: nationwide health checkups (SHC) and diabetes complication management
- Comparison
- AI-based diabetic retinopathy (DR) screening in SHC and diabetes management vs no AI
- Outcome
- ICER (cost per QALY)
Methodological detailsmodelling study, individual-based state transition model, healthcare payer's perspective, Model parameters from literature data and expert opinion
- Modelling study
- Individual-based state transition model
- Healthcare payer's perspective
- Model parameters from literature data and expert opinion
Main finding
ICER
Incremental cost-effectiveness ratios (ICER)
JPY 1,598,244/QALY (USD 11,375/QALY)
As reported in the abstract
Further findings
ICER, scenario analysis: SHC-only
- ICER of AI-based DR screening in SHC-only condition
- JPY 1,895,226/QALY (USD 13,488/QALY)
ICER, scenario analysis: diabetes management-only
- ICER of AI-based DR screening in diabetes management-only condition
- JPY 3,960,839/QALY (USD 28,189/QALY)
Original publication
Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study. Diabetes Res Clin Pract. Published 30 January 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →