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htaBIM

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Overview

htaBIM provides a complete, reproducible framework for budget impact modelling (BIM) in health technology assessment (HTA), following the ISPOR Task Force guidelines.

It replaces error-prone Excel-based BIM workbooks with structured, auditable R workflows that produce submission-quality outputs for NICE, CADTH, and EU-HTA dossiers.

Key features

Epidemiology-driven population estimation – prevalent, incident, or combined approaches with an eligibility funnel
Flexible market share modelling – constant, linear ramp, logistic S-curve, or step uptake dynamics
Multi-category cost inputs – drug, administration, monitoring, adverse events, with rebate support
Multi-year projections – annual and cumulative budget impact across scenarios
Pre-built payer perspectives – NHS England, CADTH, US commercial, or custom
Deterministic sensitivity analysis (DSA) – one-way DSA with tornado diagrams
Probabilistic sensitivity analysis (PSA) – Monte Carlo with Beta/LogNormal distributions
Submission-ready outputs – formatted tables, plots, and text/HTML reports
Interactive Shiny dashboard – launch_shiny() for stakeholder communication

Installation

# From CRAN
install.packages("htaBIM")

# Development version from GitHub
# install.packages("pak")
pak::pkg_install("Heorlytics/htaBIM")

Quick start

library(htaBIM)

# Step 1: Define eligible population
pop <- bim_population(
  indication     = "Disease X",
  country        = "custom",
  years          = 1:5,
  prevalence     = 0.003,
  n_total_pop    = 42e6,
  diagnosed_rate = 0.60,
  treated_rate   = 0.45,
  eligible_rate  = 0.30
)

# Step 2: Define market shares
ms <- bim_market_share(
  population     = pop,
  treatments     = c("Drug C (SoC)", "Drug A (new)"),
  new_drug       = "Drug A (new)",
  shares_current = c("Drug C (SoC)" = 1.0, "Drug A (new)" = 0.0),
  shares_new     = c("Drug C (SoC)" = 0.8, "Drug A (new)" = 0.2),
  dynamics       = "linear",
  uptake_params  = list(ramp_years = 3)
)

# Step 3: Define costs
costs <- bim_costs(
  treatments = c("Drug C (SoC)", "Drug A (new)"),
  currency   = "GBP",
  drug_costs = c("Drug C (SoC)" = 1500, "Drug A (new)" = 28000)
)

# Step 4: Assemble and run
model <- bim_model(pop, ms, costs, payer = bim_payer_nhs())
summary(model)

# Step 5: Visualise and report
plot(model, type = "line")
plot(model, type = "bar")
bim_report(model)

Interactive Shiny dashboard

Launch the interactive dashboard for point-and-click model building and stakeholder presentations:

launch_shiny()

ISPOR alignment

htaBIM implements the methodology described in:

Sullivan SD, Mauskopf JA, Augustovski F et al. (2014). Budget impact analysis – principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value in Health, 17(1):5-14. doi:10.1016/j.jval.2013.08.2291

Mauskopf JA, Sullivan SD, Annemans L et al. (2007). Principles of good practice for budget impact analysis. Value in Health, 10(5):336-347. doi:10.1111/j.1524-4733.2007.00187.x

Citation

citation("htaBIM")

Pandey S (2025). htaBIM: Budget Impact Modelling for Health Technology
Assessment. R package version 0.1.0.
https://github.com/Heorlytics/htaBIM

Contributing

Contributions, bug reports, and feature requests are welcome via GitHub Issues.

Licence

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.