Distributional Cost-Effectiveness Analysis for Health Technology Assessment.

dceasimR

The first comprehensive R package for Distributional Cost-Effectiveness Analysis (DCEA) — implementing methods endorsed by NICE (2025) and described in Cookson et al. (2020).

Overview

Standard cost-effectiveness analysis treats a QALY gained by the most deprived patient as equivalent to a QALY gained by the least deprived. DCEA breaks this assumption by distributing health gains across socioeconomic groups, measuring inequality impact, and applying social welfare function weights.

dceasimR provides:

• Aggregate DCEA (Love-Koh et al. 2019) — the NICE-endorsed default method
• Full-form DCEA — for subgroup-specific evidence
• Inequality indices — SII, RII, concentration index, Atkinson, Gini
• Social welfare functions — EDE health, equity weights, welfare decomposition
• Visualisation — equity-efficiency impact plane, Lorenz curves, EDE profiles
• Preloaded data — England (IMD quintile), Canada (income quintile), WHO regions
• NICE-formatted export — tables, Excel workbooks, HTML reports

NICE 2025 compliance

dceasimR implements the DCEA methods described in NICE's modular update to PMG36 (Technology Evaluation Methods: Health Inequalities, 2025). The aggregate DCEA approach follows Love-Koh et al. (2019) Value in Health.

Installation

# CRAN (once available)
install.packages("dceasimR")

# Development version from GitHub
# install.packages("remotes")
remotes::install_github("heorlytics/dceasimR")

Quick start

library(dceasimR)

# Run aggregate DCEA for a hypothetical NSCLC treatment (NICE TA style)
result <- run_aggregate_dcea(
  icer            = 28000,
  inc_qaly        = 0.45,
  inc_cost        = 12600,
  population_size = 12000,
  disease_icd     = "C34",   # Lung cancer -> uses internal HES utilisation data
  wtp             = 20000,
  opportunity_cost_threshold = 13000
)

# View summary
summary(result)

# Plot equity-efficiency impact plane
plot_equity_impact_plane(result)

# Sensitivity over inequality aversion
plot_ede_profile(result, eta_range = seq(0, 10, 0.1))

# Export NICE-formatted table
generate_nice_table(result, format = "flextable")

Documentation

Full documentation and tutorials are available at https://heorlytics.github.io/dceasimR/

Citation

If you use dceasimR in published research, please cite:

citation("dceasimR")

Pandey S (2026). dceasimR: Distributional Cost-Effectiveness Analysis
for Health Technology Assessment. R package version 0.1.0.
https://heorlytics.github.io/dceasimR/

Key references

Cookson R, Griffin S, Norheim OF, Culyer AJ (2020). Distributional Cost-Effectiveness Analysis: Quantifying Health Equity Impacts and Trade-Offs. Oxford University Press (ISBN:9780198838197).

Love-Koh J, Asaria M, Cookson R, Griffin S (2019). The Social Distribution of Health: Estimating Quality-Adjusted Life Expectancy in England. Value in Health 22(5): 518-526. https://doi.org/10.1016/j.jval.2018.10.007

Asaria M, Griffin S, Cookson R (2016). Distributional Cost-Effectiveness Analysis: A Tutorial. Medical Decision Making 36(1): 8-19. https://doi.org/10.1177/0272989X15583266

NICE (2025). Technology Evaluation Methods: Health Inequalities (PMG36). National Institute for Health and Care Excellence, London.

Robson M, Asaria M, Cookson R, Tsuchiya A, Ali S (2017). Eliciting the Level of Health Inequality Aversion in England. Health Economics 26(10): 1328-1334. https://doi.org/10.1002/hec.3386

Contributing

Contributions are welcome! Please see CONTRIBUTING.md and file issues at https://github.com/heorlytics/dceasimR/issues.