Assemble and run a budget impact model

Combines a bim_population(), bim_market_share(), and bim_costs() object into a complete budget impact model and computes the annual and cumulative budget impact across all scenarios.

The budget impact for year t is defined as:

$$BI_t = \sum_i N_t \cdot s_i^{new}(t) \cdot c_i(t) - \sum_i N_t \cdot s_i^{current}(t) \cdot c_i(t)$$

where \(N_t\) is the number of eligible patients, \(s_i(t)\) is the market share of treatment \(i\), and \(c_i(t)\) is the cost per patient for treatment \(i\).

Usage

bim_model(
  population,
  market_share,
  costs,
  payer = bim_payer_default(),
  discount_rate = 0,
  label = NULL
)

Arguments

population

A bim_population object from bim_population().

market_share

A bim_market_share object from bim_market_share().

costs

A bim_costs object from bim_costs().

payer

A bim_payer object from bim_payer() or one of the pre-built payer functions. Default is bim_payer_default().

discount_rate

numeric(1). Annual discount rate applied to Year 2+ costs. Per ISPOR guidelines, the base case should be undiscounted (0). Default 0.

label

character(1) or NULL. Optional model label for reporting.

Value

An object of class bim_model, a list containing:

population

The input bim_population object.

market_share

The input bim_market_share object.

costs

The input bim_costs object.

payer

The input bim_payer object.

results

A list with annual and cumulative data frames.

meta

A list with model metadata.

See also

bim_population(), bim_market_share(), bim_costs(), bim_payer(), plot.bim_model(), bim_table()

Examples

pop <- bim_population(
  indication    = "Disease X",
  country       = "GB",
  years         = 1:3,
  prevalence    = 0.003,
  n_total_pop   = 42e6,
  eligible_rate = 0.30
)

ms <- bim_market_share(
  population     = pop,
  treatments     = c("RASi", "Sparsentan", "Sibeprenlimab"),
  new_drug       = "Sibeprenlimab",
  shares_current = c(RASi = 0.75, Sparsentan = 0.25, Sibeprenlimab = 0.00),
  shares_new     = c(RASi = 0.60, Sparsentan = 0.20, Sibeprenlimab = 0.20)
)

costs <- bim_costs(
  treatments = c("RASi", "Sparsentan", "Sibeprenlimab"),
  drug_costs = c(RASi = 200, Sparsentan = 22000, Sibeprenlimab = 28500)
)

model <- bim_model(pop, ms, costs, label = "IgAN BIM")
summary(model)
#> 
#> == htaBIM Model Summary ==
#> =======================================================
#> Label      : IgAN BIM
#> Indication : Disease X
#> Country    : GB
#> Currency   : GBP (2026 prices)
#> New drug   : Sibeprenlimab
#> Payer      : Healthcare system (default)
#> Discount   : 0.0%
#> -------------------------------------------------------
#> Scenario: BASE
#> Year    Budget (curr)    Budget (new)     Impact         
#> 1       GBP 213,570,000  GBP 386,316,000  GBP 172,746,000
#> 2       GBP 213,570,000  GBP 386,316,000  GBP 172,746,000
#> 3       GBP 213,570,000  GBP 386,316,000  GBP 172,746,000
#> 
#> Cumulative impact (3 yrs): GBP 518,238,000
#>