ce_unit

ce_unit is a small R class library providing Cost‑Effective (CE) specific types for HTA (health technology assessment) workflows. It exposes lightweight, user-defined types that make it easy to represent, manipulate, and serialize cost and outcome data such as QALYs.

This package is currently a prototype. Contributions and integration with wider HTA standards are welcome.

Installation

Install from GitHub (example):

# install.packages("remotes") # if needed
remotes::install_github("validate-hta/ce_unit")

Or clone and install locally:

git clone https://github.com/validate-hta/ce_unit.git
R CMD INSTALL ce_unit

How to use the Cost type

The package provides an R6-style Cost object (or equivalent constructor) to capture monetary values with metadata (value, year, currency, base currency) and helper methods to:

• inspect value and currency (get_value(), get_currency())
• convert currency for a given year (convert_currency(to_currency))
• inflate values between years (inflate_value(to_year) / inflate_next_year())
• convert to/from a base currency (currency_to_base_country() / change_year())

Below are usage examples showing the public API (no internal class source).

Example: create, inspect, convert, and inflate

library(ce_unit)
library(jsonlite)

# Construct a Cost object
# (replace Cost$new(...) with the actual constructor if the package uses a different name)
mycost <- Cost$new(value = 10000, year = 2005, currency = "GBP", base_currency = "GBP")

# Inspect
mycost$get_value()    # numeric value in current currency/year
mycost$get_currency() # e.g. "GBP"

# Convert to another currency for the same year
mycost$convert_currency("USD")
mycost$get_value()    # value updated (converted)
mycost$get_currency() # "USD"

# Inflate to a target year (keeps currency unless you convert)
mycost$inflate_value(2020)
current_value <- mycost$get_value()  # value in USD in year 2020 (after inflation)

Design notes & best practices

• Store cost as a structured object: { value: numeric, currency: "USD" | "GBP", year: integer } so downstream code can safely convert/inflate.
• Represent QALYs as numeric outcomes with unit label "QALY".
• The package leaves conversion/inflation data sources to the environment — supply reliable conversion_df and inflation_df or use the package helper/data you prefer.