Per-patient cost breakdown by component and treatment
Source:R/bim_cost_breakdown.R
bim_cost_breakdown.RdExtracts and formats the per-patient annual cost decomposed by cost category (drug, admin, monitoring, adverse events, other) for each treatment in the model. This supports transparency and helps reviewers understand the drivers of differential costs between treatments.
The table is suitable for direct inclusion in HTA dossier appendices.
Arguments
- model
A
bim_modelobject.- year
integer(1). Price year to extract costs for. Defaults tomodel$costs$meta$price_year(base price year, before inflation).- currency_millions
logical(1). Express values in millions. DefaultFALSE(per-patient costs are typically in whole currency units).- digits
integer(1). Decimal places. Default0L.
Value
A data.frame with rows = cost categories and columns =
treatments, plus a Total row. Values are formatted character strings.
Carries a "caption" attribute.
Examples
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
)
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)
)
costs <- bim_costs(
treatments = c("Drug C (SoC)", "Drug A (new)"),
drug_costs = c("Drug C (SoC)" = 500, "Drug A (new)" = 25000),
monitoring_costs = c("Drug C (SoC)" = 200, "Drug A (new)" = 1500),
ae_costs = c("Drug C (SoC)" = 50, "Drug A (new)" = 300)
)
model <- bim_model(pop, ms, costs)
bim_cost_breakdown(model)
#> Cost component Drug C (SoC) Drug A (new)
#> 1 Drug cost 500 25,000
#> 2 Administration cost 0 0
#> 3 Monitoring cost 200 1,500
#> 4 Adverse event cost 50 300
#> 5 Other cost 0 0
#> 6 Total per patient 750 26,800