Help for package tatooheene

Title:

Technology Appraisal Toolbox for Health Economic Evaluations in the Netherlands

Version:

0.19.0

Description:

Functions to support economic modelling in R based on the methods of the Dutch guideline for economic evaluations in healthcare https://www.zorginstituutnederland.nl/publicaties/publicatie/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg, CBS data https://www.cbs.nl/, and OECD data https://www.oecd.org/en.html.

License:

MIT + file LICENSE

Encoding:

UTF-8

RoxygenNote:

7.3.2

Depends:

R (≥ 3.5)

LazyData:

true

Imports:

dplyr (≥ 1.1.4), assertthat (≥ 0.2.1), tidyr (≥ 1.3.0), stats

Suggests:

cbsodataR, lubridate, here, testthat

NeedsCompilation:

Packaged:

2024-12-17 16:45:33 UTC; 85304spe

Author:

Frederick Thielen

[aut], Stijn Peeters

[aut, cre]

Maintainer:

Stijn Peeters <s.b.peeters@eshpm.eur.nl>

Repository:

CRAN

Date/Publication:

2024-12-18 15:50:06 UTC

A function to calculate the costs of medical equipment

Description

A function to calculate the costs of medical equipment based on Section 3.3 of the Dutch EE guideline; k = annual depreciation and interest expense jaarlijkse afschrijvings- en rentekosten

Usage

depreciation_interest(
  v_replace_val,
  r_salvage_val,
  n_amortisation_period = 10,
  i_interest_rt = 0.025,
  output = c("data frame", "annuity factor", "annual cost")
)

Arguments

v_replace_val

V: vervangingswaarde; replacement value

r_salvage_val

R: restwaarde; salvage value

n_amortisation_period

N: afschrijvingstermijn,; amortization period

i_interest_rt

i: renteperceof ntage; interest rate

output

Default of output is a data frame with both the annuity factor and yearly deprecation and interest costs, but the values can be selected independently

Value

A data frame with the annuity factor, yearly depreciation and interest costs, or the values independently.

Examples

# Example usage of the depreciation_interest function
# Calculate both annuity factor and yearly depreciation and interest costs as a data frame
depreciation_interest(v_replace_val = 50000, r_salvage_val = 5000)

# Get only the annuity factor
depreciation_interest(v_replace_val = 50000, r_salvage_val = 5000, output = "annuity factor")

# Get only the annual depreciation and interest cost
depreciation_interest(v_replace_val = 50000, r_salvage_val = 5000, output = "annual cost")

Consumer Price Index (CPI) data from CBS

Description

A subset data frame of Consumentenprijzen; prijsindex 2015=100 from CBS. Identifier: 83131NED

Usage

df_cpi_combined

Format

`df_cpi_combined`

A data frame with 11 rows and 8 columns:

Year from: Year from in case of two consecutive years
Year to: Year ending in case of two consecutive years
Percentage: Percentage change in case of two consecutive years
Factor: Factor for multiplication in case of two consecutive years
Year from': Year starting from, in the case of a range, the year up to the maximum year
Year to': Year ending in case of a range, the year up to the maximum year
Percentage': Percentage for multiplication in case of a range, the year up to the maximum year
Factor': Factor for multiplication in case of a range, the year up to the maximum year

Source

https://www.cbs.nl/nl-nl/cijfers

Job vacancy data from CBS

Description

A subset data frame of job vacancies; SBI 2008; by economic activity and company size from CBS. Identifier: 80472NED

Usage

df_fp

Format

`df_fp`

A data frame with 27 rows and 7 columns:

Year: Year
Filled vacancies: Vervulde vacatures
Open vacancies: Openstaande vacatures
Friction period in days: Calculation of the friction period in days
Friction period in weeks: Calculation of the friction period in weeks
Friction period days average over 5 years: Calculation of the 5 year average friction period in days
Friction period weeks average over 5 years: Calculation of the 5 year average friction period in weeks

Source

https://www.cbs.nl/nl-nl/cijfers

Purchasing Power Parity (PPP) data from OECD

Description

A subset data frame of the OECD data set containing the Purchasing Power Parity (PPP) data.

Usage

df_ppp

Format

`df_ppp`

A data frame with 64 rows and 2 columns:

Year: Year of PPP
PPP: Purchase Power Parity

Source

https://sdmx.oecd.org/public

Medical unit cost data from the Costing manual: Methods and Reference Prices for Economic Evaluations in Healthcare

Description

A subset data frame of medical unit cost data; chapter 4 of the Dutch Costing Manual

Usage

df_rp_medical

Format

`df_rp_medical`

A data frame with 116 rows and 4 columns:

Category: Category of the medical unit cost
Unit: Medical unit cost
2022: Year 2022 medical unit cost
2023: Year 2023 medical unit cost

Source

Patient & family unit cost data from the Costing manual: Methods and Reference Prices for Economic Evaluations in Healthcare

Description

A subset data frame of patient & family unit cost data; chapter 5 of the Dutch Costing Manual

Usage

df_rp_patient

Format

`df_rp_patient`

A data frame with 6 rows and 4 columns:

Category: Category of the patient & family unit cost
Unit: Patient & family unit cost
2022: Year 2022 patient & family unit cost
2023: Year 2023 patient & family unit cost

Source

Productivity & other unit cost data from the Costing manual: Methods and Reference Prices for Economic Evaluations in Healthcare

Description

A subset data frame of productivity & other unit cost data; chapter 6 of the Dutch Costing Manual

Usage

df_rp_prod

Format

`df_rp_prod`

A data frame with 38 rows and 4 columns:

Category: Category of the productivity & other unit cost
Unit: Productivity & other unit cost
2022: Year 2022 productivity & other unit cost
2023: Year 2023 productivity & other unit cost

Source

A function to calculate the discounted value of future costs or effects

Description

A function to calculate the discounted value of a future costs or effects based on the in paragraph 2.6.1.2 of the Dutch EE guideline mentioned discount rate and time period

Usage

discount_value(
  current_value,
  discount_rate = 0.03,
  time,
  time_unit = c("years", "months", "weeks", "days"),
  discount_year_one = FALSE
)

Arguments

current_value

The current value.

discount_rate

The discount rate to use for the calculation. Default is 0.03. The guideline stipulates 0.03 for costs and 0.015 for effects.

time

The time at which the future value occurs.

time_unit

The unit of time to use for the calculation. Default is "years", but "months", "weeks", and "days" are also valid options.

discount_year_one

Logical value indicating whether to discount the first year as well. Default is FALSE.

Value

A numeric value of the discounted future value.

Examples

# Example usage of the discount_value function
# Calculate the discounted value of 100 after 5 years, the first year is not discounted
discount_value(current_value = 100, discount_rate = 0.03, time = 5, time_unit = "years")

# Calculate the discounted value of 100 after 60 months, the first year is not discounted
discount_value(current_value = 100, discount_rate = 0.03, time = 60, time_unit = "months")

# Calculate the discounted value of 100 after 365 days, the first year is discounted
discount_value(current_value = 100, time = 365, time_unit = "days", discount_year_one = TRUE)

A function to create a discount vector for a given time period

Description

A function to calculate a discount vector for a given time period based on the in paragraph 2.6.1.2 of the Dutch EE guideline mentioned discount rate and time period

Usage

discount_vector(
  discount_rate = 0.03,
  start_time = 0,
  end_time,
  time_unit = c("years", "months", "weeks", "days"),
  discount_year_one = FALSE
)

Arguments

discount_rate

The discount rate to use for the calculation. Default is 0.03. The guideline stipulates 0.03 for costs and 0.015 for effects.

start_time

The start time for the discount vector. Default is 0.

end_time

The end time for the discount vector.

time_unit

The unit of time to use for the calculation. Default is "years", but "months", "weeks", and "days" are also valid options.

discount_year_one

Logical value indicating whether to discount the first year as well. Default is FALSE.

Value

A numeric vector of discounted values for each time period.

Examples

# Example usage of the discount_vector function
# Calculate the discount vector for 5 years, a discount rate of 0.015, first year is not discounted
discount_vector(discount_rate = 0.015, end_time = 5, time_unit = "years")

# Calculate the discount vector for 60 months, a start time of 2, the first year is not discounted
discount_vector(discount_rate = 0.03, start_time = 2, end_time = 60, time_unit = "months")

# Calculate the discount vector for 365 days, a discount rate of 0.06, the first year is discounted
discount_vector(discount_rate = 0.06, end_time = 365, time_unit = "days", discount_year_one = TRUE)

A function to download the friction period over one or multiple years

Description

Usage

friction_period(year = "all", period = "all", type = "5_year_avg")

Arguments

year

The year of which the friction period should be downloaded, multiple years are possible. The default is the whole data frame

period

The friction period that should be included (days/weeks), default is including the whole dataframe

type

If period is chosen, a decision can be made between the 5 year average and 1 year friction period in days/weeks. The default is the 5 year average

Value

A data frame with friction periods for all years or a selection of years and variables.

Examples

# Example usage of the depreciation_interest function
friction_period(year = 2019, period = "weeks", type = "5_year_avg")

A function to download the Medical Reference prices of the Dutch Costing Manual for one or multiple years

Description

A function downloads the Medical Reference prices of the Dutch Costing Manual for one or multiple years. The prices are available in Euro (EUR) or International Dollar (INT$).

Usage

nl_med_prices(
  year = "all",
  category = "all",
  unit = "all",
  currency = c("EUR", "INT$")
)

Arguments

year

The year of which the reference price should be downloaded, multiple years are possible, default is the whole dataset

category

The category of prices that should be included (one or more categories), default is including all categories

unit

The reference price that should be included (one or multiple reference prices), default is including the whole dataframe

currency

The currency of the output of the prices. A decision can be made between EUR and INT$, the default is EUR.

Value

A dataframe or value with the Medical Reference price(s) of the Dutch Costing Manual for the specified years

Examples

# Example usage of the nl_med_prices function
# Calculate for year 2023 with the category Nursing
nl_med_prices(year = "2023", category = "Nursing")

# Calculate for year 2022 and 2023 the category Nursing
nl_med_prices(year = "all", category = "Nursing")

# Calculate for year 2022 with the category Nursing in INT$
nl_med_prices(year = "2022", category = "Nursing" , currency = "INT$")

A function to download the Patient & Family Reference prices of the Dutch Costing Manual for one or multiple years

Description

This function downloads the Patient & Family Reference prices of the Dutch Costing Manual for one or multiple years. The prices are available in Euro (EUR) or International Dollar (INT$).

Usage

nl_pat_fam_prices(
  year = "all",
  category = "all",
  unit = "all",
  currency = c("EUR", "INT$")
)

Arguments

year

The year of which the reference price should be downloaded, multiple years are possible, default is the whole dataset (year = "all")

category

The category of prices that should be included (one or more categories), default is including all categories

unit

The reference price that should be included (one or multiple reference prices), default is including the whole data frame

currency

The currency of the output of the prices. A decision can be made between EUR and INT$, the default is EUR.

Value

A dataframe or value with the Patient & Family Reference price(s) of the Dutch Costing Manual for the specified years

Examples

# Example usage of the nl_pat_fam_prices function
# Calculate for 2023 with the category Transportation and the unit Car, cost per kilometer in EURO
nl_pat_fam_prices(year = "2022", category = "Transportation", unit = "Car, cost per kilometer")

# Calculate for year 2022 and 2023 the unit Car, cost per kilometer in EURO
nl_pat_fam_prices(year = "all", unit = "Car, cost per kilometer")

# Calculate for the year 2022 with the category Transportation in INT$
nl_pat_fam_prices(year = "2022", category = "Transportation", currency = "INT$")

A function to obtain the Dutch PPP factor values in International Dollar (INT$)

Description

This function downloads the Purchasing Power Parity (PPP) factor values for the Netherlands from the OECD website per year in International Dollar (Int$).

Usage

nl_ppp(year = "all")

Arguments

year

The year of which the PPP factor should be downloaded, multiple years are possible, default is the whole dataset.

Value

A dataframe or value with the PPP factor values for the specified years.

Examples

# Example usage of the nl_ppp function
nl_ppp(year = 2019)

A function to calculate the Consumer Price Index (CPI) for a given year range.

Description

This function provides the Consumer Price Index (CPI) for a given year range both in a factor or dataframe based on CBS data and further described in 2.6.1.1 of the Dutche EE guideline

Usage

nl_price_index(
  start_year = 2013,
  end_year = 2023,
  output = c("table", "factor")
)

Arguments

start_year

start year for CPI output table or factor

end_year

End year for CPI output table or factor

output

Which output we would like to see. "factor": is the factor from start to end year, "table" is the table of all CPIs from start to end year

Value

Dataframe or factor with CPI data from start year to end year

Examples

# Example usage of the nl_price_index function
# Get the CPI factor from 2013 to 2023
nl_price_index(start_year = 2013, end_year = 2023, output = "factor")

# Get the CPI table from 2013 to 2023
nl_price_index(start_year = 2013, end_year = 2023, output = "table")

A function to download the Productivity and other societal Reference prices of the Dutch Costing Manual for one or multiple years

Description

This function downloads the Productivity and other societal Reference prices of the Dutch Costing Manual for one or multiple years. The prices are available in Euro (EUR) or International Dollar (INT$).

Usage

nl_prod_oth_prices(
  year = "all",
  category = "all",
  unit = "all",
  currency = c("EUR", "INT$")
)

Arguments

year

The year of which the reference price should be downloaded, multiple years are possible, default is the whole dataset

category

The category of prices that should be included (one or more categories), default is including all categories

unit

The reference price that should be included (one or multiple reference prices), default is including the whole dataframe

currency

The currency in which the reference price should be included (EUR or INT$), default is EUR

Value

A dataframe or value with the Productivity and/other societal Reference price(s) of the Dutch Costing Manual

Examples

# Example usage of the nl_prod_oth_prices function:
# Calculate for 2023 with the category Productivity loss - Paid work in EUR
nl_prod_oth_prices(year = "2023", category = "Productivity loss - Paid work")

# Calculate for 2022 and 2023 with the category Productivity loss - Paid work in EUR
nl_prod_oth_prices(year = "all", category = "Productivity loss - Paid work")

# Calculate for 2022 with the category Productivity loss - Paid work in INT$
nl_prod_oth_prices(year = "2022", category = "Productivity loss - Paid work", currency = "INT$")

A function to write pretty prices in `bookdown` reports

Description

This function writes pretty prices in bookdown reports. The function uses the formatC() function to format the number and adds the currency to the end of the number.

Usage

pretty_price(x, digi = 2, currency = "EUR", ...)

Arguments

x

A number to be printed

digi

Number of digits

currency

The name of the currency

...

Extra arguments for formatC()

Value

A pretty price with the currency

Examples

# Example usage of the pretty_price function
pretty_price(1000, currency = "EUR")