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Monetize health impacts

Source: R/monetize.R
monetize.Rd

This function monetizes health impacts

Usage

monetize(
  output_attribute = NULL,
  impact = NULL,
  valuation,
  discount_rate = NULL,
  discount_shape = "exponential",
  n_years = 0,
  inflation_rate = NULL,
  info = NULL
)

Arguments

output_attribute

List produced by healthiar::attribute() or healthiar::compare() as results.

impact

Numberic value referring to the health impacts to be monetized (without attribute function). If a Numberic vector is entered multiple assessments (by year) will be carried out. Be aware that the value for year 0 (current) must be entered, while n_years does not include the year 0. Thus, length of impact = n_years + 1.

valuation

Numberic value referring to unit value of a health impact.

discount_rate

Numeric value showing the discount rate for future years. If it is a nominal discount rate, no inflation is to be entered. If it is a real discount rate, the result can be adjusted by entering inflation in this function.

discount_shape

String referring to the assumed equation for the discount factor. By default: "exponential". Otherwise: "hyperbolic_harvey_1986" or "hyperbolic_mazur_1987".

n_years

Numeric value referring to number of years in the future to be considered in the discounting and/or inflation. Be aware that the year 0 (without discounting/inflation, i.e. the present) is not be counted here. If a vector is entered in the argument impact, n_years does not need to be entered (length of impact = n_years + 1).

inflation_rate

Numeric value between 0 and 1 referring to the annual inflation (increase of prices). Only to be entered if nominal (not real) discount rate is entered in the function. Default value = NULL (assuming no nominal discount rate).

info

String, data frame or tibble providing information about the assessment. Only attached if impact is entered by the users. If output_attribute is entered, use info in that function or add the column manually. Optional argument.

Value

This function returns a list containing:

1) monetization_main (tibble) containing the main monetized results;

  • monetized_impact (numeric column)

  • discount_factor (numeric column) calculated based on the entered discount_rate

  • And many more

2) monetization_detailed (list) containing detailed (and interim) results.

  • results_by_year (tibble)

  • health_raw (tibble) containing the monetized results for each for each combination of input uncertainty that were provided to the initial attribute_health() call

If the argument output_attribute was specified, then the two results elements are added to the existing output.

Details

Equation inflation factor (without discounting)

$$inflation\_factor = (1 + inflation\_rate)^{n\_years}$$

Equations discount factors (without inflation)

Exponential discounting (no inflation) $$discount\_factor = \frac{1}{(1 + discount\_rate) ^{n\_years}}$$

Hyperbolic discounting Harvey (no inflation) $$discount\_factor = \frac{1}{(1 + n\_years)^{discount\_rate}}$$ Hyperbolic discounting Mazure (no inflation) $$discount\_factor = \frac{1}{(1 + (discount\_rate \times n\_years)}$$

Equations discount factors with inflation

Exponential discounting (with inflation) $$discount\_and\_inflation\_factor = \frac{1}{((1 + discount\_rate) \times (1 + inflation\_rate)) ^{n\_years}}$$

Hyperbolic discounting Harvey (with inflation) $$discount\_and\_inflation\_factor = \frac{1}{(1 + n\_years)^{discount\_rate} \times (1 + inflation\_rate)^{n\_years}}$$ Hyperbolic discounting Mazure (with inflation) $$discount\_and\_inflation\_factor = \frac{1}{(1 + (discount\_rate \times n\_years) \times (1 + inflation\_rate)^{n\_years}}$$

Author

Alberto Castro & Axel Luyten

Examples

# Goal: monetize the attributable impacts of an existing healthiar
# assessment
output_attribute <- attribute_health(
erf_shape = "log_linear",
rr_central = exdat_pm$relative_risk,
rr_increment = 10,
exp_central = exdat_pm$mean_concentration,
cutoff_central = exdat_pm$cut_off_value,
bhd_central = exdat_pm$incidence
)

results <- monetize(
  output_attribute = output_attribute,
  discount_shape = "exponential",
  discount_rate = 0.03,
  n_years = 5,
  valuation = 50000 # E.g. EURO
)

# Attributable COPD cases its monetized impact
results$monetization_main |>
  dplyr::select(impact, monetized_impact)
#> # A tibble: 1 × 2
#>   impact monetized_impact
#>    <dbl>            <dbl>
#> 1  3502.       151041149.