It creates column to indicate the date overlap information between a table and a concept

Usage

addConceptIntersectDate(
  x,
  conceptSet,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  window = list(c(0, Inf)),
  targetDate = "event_start_date",
  order = "first",
  inObservation = TRUE,
  nameStyle = "{concept_name}_{window_name}",
  name = NULL
)

Arguments

x: A table containing individuals in a CDM reference.
conceptSet: A named list of concept sets.
indexDate: Name of a date column in x, or a single date to use for all rows, used as the reference date.
censorDate: Date or name of a date column in x on which to censor follow-up. If NULL, no censoring is applied.
window: Window or windows of time relative to indexDate to consider.
targetDate: Name or names of date columns in the target tables to use for the intersection.
order: Which record to use when multiple records occur in a window: "first" or "last".
inObservation: If TRUE, only records that occur during an observation period are considered.
nameStyle: Naming pattern for the added column or columns. It should include the required formatting variables. If more than one tableName is provided, it must include {table_name}.
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(omopgenerics, warn.conflicts = TRUE)
library(dplyr, warn.conflicts = TRUE)

cdm <- mockPatientProfiles(source = "duckdb")
#> duckdb keeps downloaded extensions and secrets in a temporary directory:
#> ℹ /tmp/Rtmp1nF3JK/duckdb
#> This is removed when the R session ends.
#> • Extensions are re-downloaded each session.
#> • Secrets are lost.
#> ℹ Run duckdb(shared_home = TRUE) (or create ~/.duckdb) to keep them (suitable for most users).
#> ℹ Run duckdb(shared_home = FALSE) to accept the temporary directory (and silence this message).
#> ℹ See ?duckdb_storage for details and alternatives.

concept <- tibble(
  concept_id = c(1125315),
  domain_id = "Drug",
  vocabulary_id = NA_character_,
  concept_class_id = "Ingredient",
  standard_concept = "S",
  concept_code = NA_character_,
  valid_start_date = as.Date("1900-01-01"),
  valid_end_date = as.Date("2099-01-01"),
  invalid_reason = NA_character_
) |>
  mutate(concept_name = paste0("concept: ", .data$concept_id))
cdm <- insertTable(cdm, "concept", concept)

cdm$cohort1 |>
  addConceptIntersectDate(conceptSet = list("acetaminophen" = 1125315))
#> Warning: ! `codelist` cast to integers.
#> # A query:  ?? x 5
#> # Database: DuckDB 1.5.5 [unknown@Linux 6.17.0-1020-azure:R 4.6.1/:memory:]
#>    cohort_definition_id subject_id cohort_start_date cohort_end_date
#>                   <int>      <int> <date>            <date>         
#>  1                    3          4 1925-04-29        1927-10-04     
#>  2                    2          5 2010-10-10        2012-03-21     
#>  3                    2         10 1989-11-30        1994-02-24     
#>  4                    3          7 1922-12-20        1939-02-12     
#>  5                    1          9 1953-08-05        1964-11-29     
#>  6                    2          1 1957-11-18        1959-03-25     
#>  7                    3          3 1984-08-17        1985-02-17     
#>  8                    1          8 2006-09-02        2009-06-16     
#>  9                    3          6 1974-08-07        1982-10-15     
#> 10                    3          2 1981-06-08        1982-12-05     
#> # ℹ 1 more variable: acetaminophen_0_to_inf <date>

# }