Compute the number of days of prior observation in the current observation period at a certain date

Usage

addPriorObservation(
  x,
  indexDate = "cohort_start_date",
  priorObservationName = "prior_observation",
  priorObservationType = "days",
  name = NULL,
  type = "numeric"
)

Arguments

x: A table containing individuals in a CDM reference.
indexDate: Name of a date column in x, or a single date to use for all rows, used as the reference date.
priorObservationName: Name of the prior-observation column to add.
priorObservationType: Whether to return a "date" or a number of "days".
name: Name of the new table. If NULL, a temporary table is returned.
type: Type of the created column(s). Counts, days, age, and observation durations can be "numeric" or "integer". Flag columns can also be "logical". Field columns can use "auto" to preserve the source type, or can be converted to "numeric", "integer", "logical", or "character".

Value

cohort table with added column containing prior observation of the individuals.

Examples

# \donttest{
library(PatientProfiles)

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.

cdm$cohort1 |>
  addPriorObservation()
#> # 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          2 1985-06-26        1986-05-26     
#>  2                    2         10 1947-06-26        1948-08-14     
#>  3                    2          4 1935-04-30        1948-10-13     
#>  4                    1          5 1942-07-28        1943-02-10     
#>  5                    2          7 1952-11-23        1973-04-15     
#>  6                    3          8 1982-11-16        1985-09-05     
#>  7                    1          3 1931-08-03        1932-08-01     
#>  8                    1          9 1954-03-30        1962-01-28     
#>  9                    1          6 1957-09-06        1960-04-02     
#> 10                    3          1 1992-05-24        1999-05-23     
#> # ℹ 1 more variable: prior_observation <dbl>

# }