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Generate a budget impact model report

Source: R/bim_report.R
bim_report.Rd

Produces a structured text summary report of a budget impact model, written to a file or returned as a character vector. For Word (.docx) or HTML output, install the suggested packages officer and rmarkdown.

Usage

bim_report(
  model,
  output_file = NULL,
  format = c("text", "html", "docx"),
  title = NULL,
  author = NULL,
  date = Sys.Date(),
  scenario = "base"
)

Arguments

model

A bim_model object.

output_file

character(1) or NULL. File path for the output report. If NULL, returns the report as a character vector (default).

format

character(1). Output format: "text" (default), "html", or "docx". For "html" and "docx", the rmarkdown and officer packages must be installed.

title

character(1) or NULL. Report title. Defaults to the model label.

author

character(1) or NULL. Author name for the report header.

date

Date or character(1). Report date. Default Sys.Date().

scenario

character(1). Scenario to report. Default "base".

Value

If output_file is NULL, a character vector of report lines. Otherwise, the path to the written file, invisibly.

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", "NewDrug"),
  new_drug       = "NewDrug",
  shares_current = c(RASi = 1.0, NewDrug = 0.0),
  shares_new     = c(RASi = 0.8, NewDrug = 0.2)
)
costs <- bim_costs(
  treatments = c("RASi", "NewDrug"),
  drug_costs = c(RASi = 500, NewDrug = 25000)
)
model <- bim_model(pop, ms, costs)

# Return as character vector
rpt <- bim_report(model)
cat(rpt, sep = "\n")
#> ============================================================
#>   Disease X BIM
#>   Budget Impact Analysis Report
#> ============================================================
#> 
#> Author  : htaBIM
#> Date    : 19 March 2026
#> Model   : htaBIM v0.1.0
#> 
#> ------------------------------------------------------------
#> 1. MODEL OVERVIEW
#> ------------------------------------------------------------
#> Indication  : Disease X
#> Country     : GB
#> New drug    : NewDrug
#> Currency    : GBP (2026 prices)
#> Payer       : Healthcare system (default)
#> Discount    : 0.0%
#> Scenario    : base
#> 
#> ------------------------------------------------------------
#> 2. POPULATION
#> ------------------------------------------------------------
#> Approach    : prevalent
#> 
#>   Year 1 : 37,800 eligible patients (of 42,000,000 total)
#>   Year 2 : 37,800 eligible patients (of 42,000,000 total)
#>   Year 3 : 37,800 eligible patients (of 42,000,000 total)
#> 
#> ------------------------------------------------------------
#> 3. MARKET SHARE (with new drug, base case)
#> ------------------------------------------------------------
#> 
#>   RASi                      : 80.0%
#>   NewDrug                   : 20.0%
#> 
#> ------------------------------------------------------------
#> 4. BUDGET IMPACT RESULTS
#> ------------------------------------------------------------
#> 
#>   Year    GBP Current         GBP New             Budget impact    Impact %
#>   1       18,900,000          204,120,000         185,220,000      980.0%  
#>   2       18,900,000          204,120,000         185,220,000      980.0%  
#>   3       18,900,000          204,120,000         185,220,000      980.0%  
#> 
#>   3-year cumulative budget impact: GBP 555,660,000
#> 
#> ------------------------------------------------------------
#> 5. COST INPUTS (annual per patient, Year 1)
#> ------------------------------------------------------------
#> 
#>   NewDrug                   : GBP 25,000
#>   RASi                      : GBP 500
#> 
#> ------------------------------------------------------------
#> 6. REFERENCES
#> ------------------------------------------------------------
#> 
#>   Sullivan SD 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
#> 
#>   Mauskopf JA et al. (2007). Principles of good practice for budget impact
#>   analysis. Value Health, 10(5):336-347.
#>   doi:10.1111/j.1524-4733.2007.00187.x
#> 
#> ============================================================
#>   Generated by htaBIM | 2026-03-19 21:10
#> ============================================================