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

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Installation

# From CRAN
install.packages("htaBIM")

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

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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)

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Interactive Shiny dashboard

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

launch_shiny()

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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

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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

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Contributing

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

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Licence

MIT (c) 2025 Heorlytics Ltd