Estimate the annual eligible patient population for a budget impact model

Builds a year-by-year estimate of the number of patients eligible for a new treatment, using an epidemiology-driven funnel approach aligned with ISPOR Task Force guidelines (Sullivan et al., 2014). Supports prevalent, incident, or combined population approaches.

Usage

bim_population(
  indication,
  country = "GB",
  years = 1:5,
  prevalence = NULL,
  incidence = NULL,
  n_total_pop = NULL,
  diagnosed_rate = 1,
  treated_rate = 1,
  eligible_rate = 1,
  growth_rate = 0,
  approach = c("prevalent", "incident", "both"),
  data_source = NULL
)

Arguments

indication: character(1). Name of the disease or indication. Used in outputs and reports.
country: character(1). ISO 3166-1 alpha-2 country code (e.g. "GB", "US", "CA", "DE"). Used to look up built-in population data if n_total_pop is NULL. Use "custom" to rely solely on n_total_pop.
years: integer. Vector of projection years (e.g. 1:5). Default is 1:5.
prevalence: numeric(1) or NULL. Point prevalence as a proportion (e.g. 0.002 for 0.2%). Required when approach is "prevalent" or "both".
incidence: numeric(1) or NULL. Annual incidence rate per 100,000. Required when approach is "incident" or "both".
n_total_pop: numeric(1) or NULL. Total reference population size. If NULL and country is recognised, uses built-in population data.
diagnosed_rate: numeric(1). Proportion of prevalent/incident cases that are diagnosed. Must be in [0, 1]. Default 1.0.
treated_rate: numeric(1). Proportion of diagnosed patients receiving any systemic treatment. Must be in [0, 1]. Default 1.0.
eligible_rate: numeric(1). Proportion of treated patients eligible for the new drug (e.g. meeting label criteria). Must be in [0, 1]. Default 1.0.
growth_rate: numeric(1). Annual growth rate applied to the total population (e.g. 0.005 for 0.5% per year). Default 0.0.
approach: character(1). Population approach: "prevalent" (stock population), "incident" (new cases per year), or "both" (sum of prevalent and incident). Default "prevalent".
data_source: character(1) or NULL. Citation for the epidemiology data, appended to outputs. Optional.

Value

An object of class bim_population, which is a list containing:

annual: A data.frame with columns year, n_total_pop, n_prevalent_or_incident, n_diagnosed, n_treated, n_eligible.
params: A list of all input parameters.
meta: A list with indication, country, approach, data_source.

References

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 Health, 17(1):5-14. doi:10.1016/j.jval.2013.08.2291

Examples

pop <- bim_population(
  indication     = "Disease X",
  country        = "GB",
  years          = 1:5,
  prevalence     = 0.003,
  n_total_pop    = 42e6,
  diagnosed_rate = 0.60,
  treated_rate   = 0.45,
  eligible_rate  = 0.30
)
print(pop)
#> 
#> -- htaBIM Population --
#> 
#> Indication : Disease X 
#> Country    : GB 
#> Approach   : prevalent 
#> Years      : 1 to 5 
#> 
#> Eligible patients:
#>   Year 1   : 10,206
#>    Year 2   : 10,206
#>    Year 3   : 10,206
#>    Year 4   : 10,206
#>    Year 5   : 10,206
summary(pop)
#> 
#> == Population Summary ==
#> Indication   : Disease X
#> Country      : GB
#> Approach     : prevalent
#> 
#> Epidemiological funnel (Year 1):
#>   Total pop          : 4.2e+07
#>   Prevalent/incident : 126,000
#>   Diagnosed          : 75,600
#>   Treated            : 34,020
#>   Eligible           : 10,206