Plot the results of summariseDrugUtilisation

Plot the results of summariseDrugUtilisation

Usage

plotDrugUtilisation(
  result,
  variable = "number exposures",
  plotType = "barplot",
  facet = strataColumns(result),
  colour = "cohort_name",
  style = NULL
)

Arguments

result

A summarised_result object.

variable

Variable to plot. See unique(result$variable_name) for options.

plotType

Must be a choice between: 'scatterplot', 'barplot', 'densityplot', and 'boxplot'.

facet

Columns to facet by. See options with availablePlotColumns(result). Formula is also allowed to specify rows and columns.

colour

Columns to color by. See options with availablePlotColumns(result).

style

Visual theme to apply. Character, or NULL. If a character, this may be either the name of a built-in style (see plotStyle()), or a path to a .yml file that defines a custom style. If NULL, the function will use the explicit default style, unless a global style option is set (see visOmopResults::setGlobalPlotOptions()) or a _brand.yml file is present (in that order). Refer to the visOmopResults package vignette on styles to learn more.

Value

A ggplot2 object.

Examples

# \donttest{
library(DrugUtilisation)
library(PatientProfiles)
library(dplyr, warn.conflicts = FALSE)

cdm <- mockDrugUtilisation(numberIndividuals = 100)
codes <- list(aceta = c(1125315, 1125360, 2905077, 43135274))
cdm <- generateDrugUtilisationCohortSet(cdm = cdm,
                                        name = "cohort",
                                        conceptSet = codes)
#> ℹ Subsetting drug_exposure table
#> ℹ Checking whether any record needs to be dropped.
#> ℹ Collapsing overlaping records.
#> ℹ Collapsing records with gapEra = 1 days.

result <- cdm$cohort |>
  addSex() |>
  summariseDrugUtilisation(
    strata = "sex",
    ingredientConceptId = 1125315,
    estimates = c("min", "q25", "median", "q75", "max", "density")
  )

result |>
  filter(estimate_name == "median") |>
  plotDrugUtilisation(
    variable = "days prescribed",
    plotType = "barplot"
  )


result |>
  plotDrugUtilisation(
    variable = "days exposed",
    facet = cohort_name ~ cdm_name,
    colour = "sex",
    plotType = "boxplot"
  )
#> Ignoring unknown labels:
#> • fill : "Sex"


result |>
  plotDrugUtilisation(
    variable = "cumulative dose milligram",
    plotType = "densityplot",
    facet = "cohort_name",
    colour = "sex"
  )


# }