Finding the right mapping algorithm for cost-effectiveness analysis just got easier.
Our study presents the creation of a freely accessible online database that classifies and rates published mapping algorithms, tools that convert clinical outcomes into EQ-5D utility values, a crucial step in health-economic modelling.
The aim was to develop a comprehensive, user-friendly resource that helps researchers, HTA bodies, and industry analysts quickly identify reliable mapping algorithms for their models. This initiative supports more transparent and standardised cost-effectiveness analyses.
We conducted a systematic literature review, identifying 556 mapping algorithms, of which 186 reported both R² and RMSE values.
To evaluate algorithm performance, we applied Monte Carlo simulations across multiple metrics, R², RMSE, and MAE, and developed a three-tier classification system:
🔴 Red: Poor
🟠 Amber: Useful / Use with caution
🟢 Green: Ready to use
We found that:
- 35% of algorithms were rated Poor,
- 38% classified as Use with caution,
- 27% deemed Ready to use.
The most frequently represented disease areas were Oncology (22%) and Musculoskeletal disorders (12%).
This project demonstrates that systematic classification of mapping algorithms is both feasible and valuable. The resulting online database provides a standardized, evidence-based resource for academics, HTA analysts, and pharmaceutical companies, enabling faster, more informed, and more reproducible health-economic evaluations.
📄 Explore the full poster:
Development of an Online Mapping Database of Published Usable Mapping Algorithms (PDF)