This function is used to summarise treatments received

Usage

summariseTreatment(
  cohort,
  window,
  treatmentCohortName,
  treatmentCohortId = NULL,
  strata = list(),
  indexDate = "cohort_start_date",
  censorDate = NULL,
  minCellCount = lifecycle::deprecated()
)

Arguments

cohort: A cohort table in a cdm reference.
window: Time window over which to summarise the treatments.
treatmentCohortName: Name of a cohort in the cdm that contains the treatments of interest.
treatmentCohortId: Cohort definition id of interest from treatmentCohortName.
strata: List with column names or vectors of column names groups to stratify results by.
indexDate: Variable in x that contains the date to compute the intersection.
censorDate: Whether to censor overlap events at a specific date or a column date of x. If NULL, end of observation will be used.
minCellCount: \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}

Value

A summary of treatments stratified by cohort_name and strata_name

Examples

# \donttest{
library(DrugUtilisation)

cdm <- mockDrugUtilisation()
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in visit_occurrence do not match expected column type:
#> • `visit_concept_id` is numeric but expected integer
#> • `visit_type_concept_id` is numeric but expected integer
#> Warning: ! 10 column in condition_occurrence do not match expected column type:
#> • `condition_concept_id` is numeric but expected integer
#> • `condition_type_concept_id` is numeric but expected integer
#> • `condition_status_concept_id` is numeric but expected integer
#> • `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: ! 2 column in drug_exposure do not match expected column type:
#> • `drug_concept_id` is numeric but expected integer
#> • `drug_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in observation do not match expected column type:
#> • `observation_concept_id` is numeric but expected integer
#> • `observation_type_concept_id` is numeric but expected integer
#> Warning: ! 4 column in concept do not match expected column type:
#> • `concept_id` is numeric 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
#> Warning: ! 2 column in concept_relationship do not match expected column type:
#> • `concept_id_1` is numeric but expected integer
#> • `concept_id_2` is numeric but expected integer
#> Warning: ! 4 column in concept_ancestor do not match expected column type:
#> • `ancestor_concept_id` is numeric but expected integer
#> • `descendant_concept_id` is numeric but expected integer
#> • `min_levels_of_separation` is numeric but expected integer
#> • `max_levels_of_separation` is numeric but expected integer
#> Warning: ! 9 column in drug_strength do not match expected column type:
#> • `drug_concept_id` is numeric but expected integer
#> • `ingredient_concept_id` is numeric but expected integer
#> • `amount_unit_concept_id` is numeric but expected integer
#> • `numerator_unit_concept_id` is numeric but expected integer
#> • `denominator_unit_concept_id` is numeric but expected integer
#> • `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
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer
cdm$cohort1 |>
  summariseTreatment(
    treatmentCohortName = "cohort2",
    window = list(c(0, 30), c(31, 365))
  )
#> # A tibble: 48 × 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 cohort_1    overall     overall     
#>  2         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  3         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  4         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  5         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  6         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  7         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  8         1 DUS MOCK cohort_name cohort_1    overall     overall     
#>  9         1 DUS MOCK cohort_name cohort_1    overall     overall     
#> 10         1 DUS MOCK cohort_name cohort_1    overall     overall     
#> # ℹ 38 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>
# }