It creates a column with the field of a desired intersection

Usage

addCohortIntersectField(
  x,
  targetCohortTable,
  field,
  targetCohortId = NULL,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  targetDate = "cohort_start_date",
  order = "first",
  window = list(c(0, Inf)),
  nameStyle = "{cohort_name}_{field}_{window_name}",
  name = NULL
)

Arguments

x: Table with individuals in the cdm.
targetCohortTable: name of the cohort that we want to check for overlap.
field: Column of interest in the targetCohort.
targetCohortId: vector of cohort definition ids to include.
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.
targetDate: Date of interest in the other cohort table. Either cohort_start_date or cohort_end_date.
order: date to use if there are multiple records for an individual during the window of interest. Either first or last.
window: Window of time to identify records relative to the indexDate. Records outside of this time period will be ignored.
nameStyle: naming of the added column or columns, should include required parameters.
name: Name of the new table, if NULL a temporary table is returned.

Value

table with added columns with overlap information.

Examples

# \donttest{
library(PatientProfiles)
library(dplyr)

cdm <- mockPatientProfiles(source = "duckdb")

cdm$cohort2 <- cdm$cohort2 |>
  mutate(even = if_else(subject_id %% 2, "yes", "no")) |>
  compute(name = "cohort2")

cdm$cohort1 |>
  addCohortIntersectFlag(
    targetCohortTable = "cohort2"
  )
#> # Source:   table<og_029_1775495243> [?? x 7]
#> # Database: DuckDB 1.5.1 [unknown@Linux 6.17.0-1008-azure:R 4.5.3/:memory:]
#>    cohort_definition_id subject_id cohort_start_date cohort_end_date
#>                   <int>      <int> <date>            <date>         
#>  1                    1          3 1923-12-15        1927-04-11     
#>  2                    2          7 1948-06-06        1967-07-13     
#>  3                    1         10 1943-09-24        1964-08-03     
#>  4                    3          4 1955-09-22        1963-07-08     
#>  5                    3          6 1967-03-06        1967-05-20     
#>  6                    2          9 1974-02-05        1984-08-03     
#>  7                    3          5 1943-06-11        1944-10-20     
#>  8                    1          8 1960-06-11        1962-10-29     
#>  9                    1          1 1933-01-11        1933-06-19     
#> 10                    1          2 1976-03-25        1977-04-21     
#> # ℹ 3 more variables: cohort_3_0_to_inf <dbl>, cohort_1_0_to_inf <dbl>,
#> #   cohort_2_0_to_inf <dbl>

# }