Generate a plot visualisation (ggplot2) from the output of summariseIndication

Usage

plotIndication(
  result,
  facet = cdm_name + cohort_name ~ window_name,
  colour = "variable_level"
)

Arguments

result: A summarised_result object.
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).

Value

A ggplot2 object

Examples

# \donttest{
library(DrugUtilisation)
library(CDMConnector)
library(dplyr)

cdm <- mockDrugUtilisation()

indications <- list("headache" = 378253, "asthma" = 317009)
cdm <- generateConceptCohortSet(cdm, indications, "indication_cohorts")

cdm <- generateIngredientCohortSet(
  cdm = cdm, name = "drug_cohort", ingredient = "acetaminophen"
)
#> 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$drug_cohort |>
  summariseIndication(
    indicationCohortName = "indication_cohorts",
    unknownIndicationTable = "condition_occurrence",
    indicationWindow = list(c(-Inf, 0), c(-365, 0))
  )
#> ℹ Intersect with indications table (indication_cohorts)
#> ℹ Summarising indications.

plotIndication(result)

# }