Create an empty omop table
Examples
library(omopgenerics)
person <- dplyr::tibble(
person_id = 1, gender_concept_id = 0, year_of_birth = 1990,
race_concept_id = 0, ethnicity_concept_id = 0
)
observation_period <- dplyr::tibble(
observation_period_id = 1, person_id = 1,
observation_period_start_date = as.Date("2000-01-01"),
observation_period_end_date = as.Date("2023-12-31"),
period_type_concept_id = 0
)
cdm <- cdmFromTables(
tables = list("person" = person, "observation_period" = observation_period),
cdmName = "test"
)
#> Warning: ! 5 column in person do not match expected column type:
#> • `person_id` is numeric but expected integer
#> • `gender_concept_id` is numeric but expected integer
#> • `year_of_birth` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> Warning: ! 3 column in observation_period do not match expected column type:
#> • `observation_period_id` is numeric but expected integer
#> • `person_id` is numeric but expected integer
#> • `period_type_concept_id` is numeric but expected integer
cdm <- emptyOmopTable(cdm, "drug_exposure")
cdm$drug_exposure
#> # A tibble: 0 × 23
#> # ℹ 23 variables: drug_exposure_id <int>, person_id <int>,
#> # drug_concept_id <int>, drug_exposure_start_date <date>,
#> # drug_exposure_start_datetime <date>, drug_exposure_end_date <date>,
#> # drug_exposure_end_datetime <date>, verbatim_end_date <date>,
#> # drug_type_concept_id <int>, stop_reason <chr>, refills <int>,
#> # quantity <dbl>, days_supply <int>, sig <chr>, route_concept_id <int>,
#> # lot_number <chr>, provider_id <int>, visit_occurrence_id <int>, …