A named list containing example inputs for a hypothetical budget impact model for a new treatment (Drug A) in a chronic condition (Disease X), for use in vignettes, examples, and testing. All values are illustrative only and do not represent any real drug, price, or epidemiological estimate.
Format
A named list with three elements:
population_paramsA
listof arguments forbim_population().market_share_paramsA
listof arguments forbim_market_share()(excludingpopulation).cost_paramsA
listof arguments forbim_costs().
Examples
data(bim_example)
str(bim_example)
#> List of 3
#> $ population_params :List of 11
#> ..$ indication : chr "Disease X"
#> ..$ country : chr "GB"
#> ..$ years : int [1:5] 1 2 3 4 5
#> ..$ prevalence : num 0.003
#> ..$ n_total_pop : num 4.2e+07
#> ..$ diagnosed_rate: num 0.6
#> ..$ treated_rate : num 0.45
#> ..$ eligible_rate : num 0.3
#> ..$ growth_rate : num 0.005
#> ..$ approach : chr "prevalent"
#> ..$ data_source : chr "Illustrative — not from a real submission"
#> $ market_share_params:List of 7
#> ..$ treatments : chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ new_drug : chr "Drug A (new)"
#> ..$ shares_current: Named num [1:4] 0.68 0.22 0 0.1
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ shares_new : Named num [1:4] 0.54 0.18 0.18 0.1
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ dynamics : chr "linear"
#> ..$ uptake_params :List of 1
#> .. ..$ ramp_years: num 3
#> ..$ scenarios :List of 2
#> .. ..$ conservative: Named num [1:4] 0.62 0.18 0.1 0.1
#> .. .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> .. ..$ optimistic : Named num [1:4] 0.44 0.16 0.3 0.1
#> .. .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> $ cost_params :List of 7
#> ..$ treatments : chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ currency : chr "GBP"
#> ..$ price_year : int 2025
#> ..$ drug_costs : Named num [1:4] 220 22400 28800 31200
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ admin_costs : Named num [1:4] 0 0 480 0
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ monitoring_costs: Named num [1:4] 650 1550 1950 1750
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
#> ..$ ae_costs : Named num [1:4] 80 210 240 290
#> .. ..- attr(*, "names")= chr [1:4] "Drug C (SoC)" "Drug B" "Drug A (new)" "Drug D"
# Reconstruct the full model
pop <- do.call(bim_population, bim_example$population_params)
ms <- do.call(bim_market_share,
c(list(population = pop), bim_example$market_share_params))
costs <- do.call(bim_costs, bim_example$cost_params)
model <- bim_model(pop, ms, costs)
summary(model)
#>
#> == htaBIM Model Summary ==
#> =======================================================
#> Label : Disease X BIM
#> Indication : Disease X
#> Country : GB
#> Currency : GBP (2025 prices)
#> New drug : Drug A (new)
#> Payer : Healthcare system (default)
#> Discount : 0.0%
#> -------------------------------------------------------
#> Scenario: BASE
#> Year Budget (curr) Budget (new) Impact
#> 1 GBP 94,770,240 GBP 110,291,920 GBP 15,521,680
#> 2 GBP 95,259,610 GBP 126,469,240 GBP 31,209,630
#> 3 GBP 95,723,870 GBP 142,751,790 GBP 47,027,920
#> 4 GBP 96,190,030 GBP 143,500,890 GBP 47,310,860
#> 5 GBP 96,679,400 GBP 144,194,360 GBP 47,514,960
#>
#> Cumulative impact (5 yrs): GBP 188,585,050
#>
#> -------------------------------------------------------
#> Scenario: CONSERVATIVE
#> Year Budget (curr) Budget (new) Impact
#> 1 GBP 94,770,240 GBP 101,990,480 GBP 7,220,240
#> 2 GBP 95,259,610 GBP 109,774,800 GBP 14,515,190
#> 3 GBP 95,723,870 GBP 117,604,260 GBP 21,880,390
#> 4 GBP 96,190,030 GBP 118,199,810 GBP 22,009,780
#> 5 GBP 96,679,400 GBP 118,771,200 GBP 22,091,800
#>
#> Cumulative impact (5 yrs): GBP 87,717,400
#>
#> -------------------------------------------------------
#> Scenario: OPTIMISTIC
#> Year Budget (curr) Budget (new) Impact
#> 1 GBP 94,770,240 GBP 121,197,270 GBP 26,427,030
#> 2 GBP 95,259,610 GBP 148,315,870 GBP 53,056,260
#> 3 GBP 95,723,870 GBP 175,724,720 GBP 80,000,850
#> 4 GBP 96,190,030 GBP 176,632,780 GBP 80,442,750
#> 5 GBP 96,679,400 GBP 177,517,630 GBP 80,838,230
#>
#> Cumulative impact (5 yrs): GBP 320,765,120
#>