To add a new column with the initial daily dose. To add multiple columns use addDrugUtilisation() for efficiency.
Source: R/addDrugUtilisation.R
addInitialDailyDose.RdTo add a new column with the initial daily dose. To add multiple columns use
addDrugUtilisation() for efficiency.
Usage
addInitialDailyDose(
cohort,
ingredientConceptId,
conceptSet = NULL,
indexDate = "cohort_start_date",
censorDate = "cohort_end_date",
restrictIncident = TRUE,
nameStyle = "initial_daily_dose_{concept_name}_{ingredient}",
name = NULL
)Arguments
- cohort
Cohort in the cdm.
- 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.
- nameStyle
Character string to specify the nameStyle of the new columns.
- name
Name of the new computed cohort table, if NULL a temporary tables is created.
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 |>
addInitialDailyDose(ingredientConceptId = 1125315)
#> Warning: ! `codelist` contains numeric values, they are casted to integers.
#> # Source: table<og_074_1730712154> [10 x 5]
#> # Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2/:memory:]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
#> 1 1 8 1971-01-22 1997-03-11
#> 2 2 1 1969-05-30 1971-08-24
#> 3 3 2 2020-05-28 2020-06-12
#> 4 2 3 2014-11-12 2018-01-11
#> 5 3 4 2019-04-22 2020-01-05
#> 6 1 5 1994-08-28 2009-09-30
#> 7 1 6 2014-05-05 2015-04-20
#> 8 1 7 2022-06-29 2022-06-29
#> 9 3 9 1987-11-09 2001-05-11
#> 10 2 10 2020-06-22 2022-02-02
#> # ℹ 1 more variable:
#> # initial_daily_dose_ingredient_1125315_descendants_1125315 <dbl>
# }