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Format a drug_utilisation object into a visual table.

Usage

tableDrugUtilisation(
  result,
  header = c("cdm_name"),
  groupColumn = c("cohort_name", strataColumns(result)),
  type = "gt",
  hide = c("variable_level", "censor_date", "cohort_table_name", "gap_era", "index_date",
    "restrict_incident"),
  style = "default",
  .options = list()
)

Arguments

result

A summarised_result object.

header

Columns to use as header. See options with availableTableColumns(result).

groupColumn

Columns to group by. See options with availableTableColumns(result).

type

Type of table. Check supported types with visOmopResults::tableType().

hide

Columns to hide from the visualisation. See options with availableTableColumns(result).

style

Named list that specifies how to style the different parts of the table generated. It can either be a pre-defined style ("default" or "darwin" - the latter just for gt and flextable), NULL to get the table default style, or custom. Keep in mind that styling code is different for all table styles. To see the different styles use visOmopResults::tableStyle().

.options

A named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A table with a formatted version of summariseIndication() results.

Examples

# \donttest{
library(DrugUtilisation)
library(CodelistGenerator)

cdm <- mockDrugUtilisation()
codelist <- getDrugIngredientCodes(cdm = cdm, name = "acetaminophen")
cdm <- generateDrugUtilisationCohortSet(cdm = cdm,
                                        name = "dus_cohort",
                                        conceptSet = codelist)
#>  Subsetting drug_exposure table
#>  Checking whether any record needs to be dropped.
#>  Collapsing overlaping records.
#>  Collapsing records with gapEra = 1 days.

drugUse <- cdm$dus_cohort |>
  summariseDrugUtilisation(ingredientConceptId = 1125315)

tableDrugUtilisation(drugUse)
#> cdm_name, cohort_name, variable_level, censor_date, cohort_table_name, gap_era,
#> index_date, and restrict_incident are missing in `columnOrder`, will be added
#> last.
Concept set Ingredient Variable name Estimate name
CDM name
DUS MOCK
161_acetaminophen
overall overall number records N 5
number subjects N 5
ingredient_1125315_descendants overall number exposures missing N (%) 0 (0.00 %)
Mean (SD) 1.00 (0.00)
Median (Q25 - Q75) 1 (1 - 1)
time to exposure missing N (%) 0 (0.00 %)
Mean (SD) 0.00 (0.00)
Median (Q25 - Q75) 0 (0 - 0)
cumulative quantity missing N (%) 0 (0.00 %)
Mean (SD) 59.00 (31.30)
Median (Q25 - Q75) 70.00 (30.00 - 70.00)
initial quantity missing N (%) 0 (0.00 %)
Mean (SD) 59.00 (31.30)
Median (Q25 - Q75) 70.00 (30.00 - 70.00)
initial exposure duration missing N (%) 0 (0.00 %)
Mean (SD) 932.40 (1,240.00)
Median (Q25 - Q75) 127 (15 - 1,871)
number eras missing N (%) 0 (0.00 %)
Mean (SD) 1.00 (0.00)
Median (Q25 - Q75) 1 (1 - 1)
days exposed missing N (%) 0 (0.00 %)
Mean (SD) 932.40 (1,240.00)
Median (Q25 - Q75) 127 (15 - 1,871)
days prescribed missing N (%) 0 (0.00 %)
Mean (SD) 932.40 (1,240.00)
Median (Q25 - Q75) 127 (15 - 1,871)
acetaminophen cumulative dose milligram missing N (%) 0 (0.00 %)
Mean (SD) 154,300.00 (289,683.79)
Median (Q25 - Q75) 35,000.00 (12,500.00 - 40,000.00)
initial daily dose milligram missing N (%) 0 (0.00 %)
Mean (SD) 897.85 (1,081.27)
Median (Q25 - Q75) 254.35 (94.49 - 1,785.71)
# }