The omock package provides functionality to quickly create a cdm reference containing synthetic data based on population settings specified by the user.
First, let’s load packages required for this vignette.
Now, in three lines of code, we can create a cdm reference with a person and observation period table for 1000 people.
cdm <- emptyCdmReference(cdmName = "synthetic cdm") |>
mockPerson(nPerson = 1000) |>
mockObservationPeriod()
cdm
#>
#> ── # OMOP CDM reference (local) of synthetic cdm ───────────────────────────────
#> • omop tables: person, observation_period
#> • cohort tables: -
#> • achilles tables: -
#> • other tables: -
cdm$person |> glimpse()
#> Rows: 1,000
#> Columns: 18
#> $ person_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,…
#> $ gender_concept_id <int> 8507, 8507, 8532, 8507, 8507, 8532, 8507, …
#> $ year_of_birth <int> 1971, 1982, 1971, 1987, 1959, 1963, 1971, …
#> $ month_of_birth <int> 5, 9, 5, 12, 12, 12, 3, 8, 3, 6, 3, 4, 1, …
#> $ day_of_birth <int> 1, 23, 29, 10, 28, 1, 19, 29, 14, 25, 4, 1…
#> $ race_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ ethnicity_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ birth_datetime <dttm> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
#> $ location_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ provider_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ care_site_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ person_source_value <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ gender_source_value <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ gender_source_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ race_source_value <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ race_source_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ ethnicity_source_value <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ ethnicity_source_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
cdm$observation_period |> glimpse()
#> Rows: 1,000
#> Columns: 5
#> $ observation_period_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1…
#> $ person_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1…
#> $ observation_period_start_date <date> 1992-02-28, 2004-05-08, 2004-04-16, 200…
#> $ observation_period_end_date <date> 2015-01-06, 2014-07-17, 2008-03-29, 201…
#> $ period_type_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
We can add further requirements around the population we create. For example we can require that they were born between 1960 and 1980 like so.