This function is used to summarise the dose utilisation table over multiple cohorts.

Usage

summariseDrugUtilisation(
  cohort,
  strata = list(),
  estimates = c("q25", "median", "q75", "mean", "sd", "count_missing",
    "percentage_missing"),
  ingredientConceptId = NULL,
  conceptSet = NULL,
  indexDate = "cohort_start_date",
  censorDate = "cohort_end_date",
  restrictIncident = TRUE,
  gapEra = 1,
  numberExposures = TRUE,
  numberEras = TRUE,
  exposedTime = TRUE,
  timeToExposure = TRUE,
  initialQuantity = TRUE,
  cumulativeQuantity = TRUE,
  initialDailyDose = TRUE,
  cumulativeDose = TRUE
)

Arguments

cohort: Cohort with drug use variables and strata.
strata: Stratification list.
estimates: Estimates that we want for the columns.
ingredientConceptId: Ingredient OMOP concept that we are interested for the study. It is a compulsory input, no default value is provided.
conceptSet: List of concepts to be included. If NULL all the descendants of ingredient concept id will be used.
indexDate: Name of a column that indicates the date to start the analysis.
censorDate: Name of a column that indicates the date to stop the analysis, if NULL end of individuals observation is used.
restrictIncident: Whether to include only incident prescriptions in the analysis. If FALSE all prescriptions that overlap with the study period will be included.
gapEra: Number of days between two continuous exposures to be considered in the same era.
numberExposures: Whether to add a column with the number of exposures.
numberEras: Whether to add a column with the number of eras.
exposedTime: Whether to add a column with the number of exposed days.
timeToExposure: Whether to add a column with the number of days between indexDate and start of the first exposure.
initialQuantity: Whether to add a column with the initial quantity.
cumulativeQuantity: Whether to add a column with the cumulative quantity of the identified prescription.
initialDailyDose: Whether to add a column with the initial daily dose.
cumulativeDose: Whether to add a column with the cumulative dose.

Value

A summary of drug utilisation stratified by cohort_name and strata_name

Examples

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

cdm <- mockDrugUtilisation()
#> Warning: ! 7 column in condition_occurrence do not match expected column type:
#> • `stop_reason` is logical but expected character
#> • `provider_id` is logical but expected integer
#> • `visit_occurrence_id` is logical but expected integer
#> • `visit_detail_id` is logical but expected integer
#> • `condition_source_value` is logical but expected character
#> • `condition_source_concept_id` is logical but expected integer
#> • `condition_status_source_value` is logical but expected character
#> Warning: ! 3 column in concept do not match expected column type:
#> • `valid_start_date` is character but expected date
#> • `valid_end_date` is character but expected date
#> • `invalid_reason` is logical but expected character
#> Warning: ! 4 column in drug_strength do not match expected column type:
#> • `box_size` is logical but expected integer
#> • `valid_start_date` is character but expected date
#> • `valid_end_date` is character but expected date
#> • `invalid_reason` is logical but expected character
codelist <- CodelistGenerator::getDrugIngredientCodes(cdm, "acetaminophen")
#> Warning: ! `codelist` contains numeric values, they are casted to integers.
cdm <- generateDrugUtilisationCohortSet(
  cdm, "dus_cohort", codelist
)
#> 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.
cdm[["dus_cohort"]] |>
  summariseDrugUtilisation(ingredientConceptId = 1125315)
#> Warning: ! `codelist` contains numeric values, they are casted to integers.
#> # A tibble: 58 × 13
#>    result_id cdm_name group_name  group_level       strata_name strata_level
#>        <int> <chr>    <chr>       <chr>             <chr>       <chr>       
#>  1         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  2         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  3         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  4         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  5         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  6         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  7         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  8         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#>  9         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#> 10         1 DUS MOCK cohort_name 161_acetaminophen overall     overall     
#> # ℹ 48 more rows
#> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>,
#> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>,
#> #   additional_name <chr>, additional_level <chr>
# }