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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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.