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Generate simulated erintervention data

dummy_erintervention_mri.Rd

This function creates a dummy dataset with a subset of variables that are contained in the GEMINI "erintervention" table, as seen in GEMINI Data Repository Dictionary.

This function simulates data with CCI codes detailing the type of intervention used in the emergency department.

Usage

dummy_erintervention_mri(
  nid = 1000,
  n_hospitals = 10,
  int_code = NULL,
  cohort = NULL,
  seed = NULL
)

Arguments

nid

(integer)
Number of unique encounter IDs to simulate. Encounter IDs may repeat, resulting in a data table with more rows than nid. Ignored when cohort is provided.

n_hospitals

(integer)
Number of hospitals to simulate. Ignored when cohort is provided.

int_code

(character or vector)
Optional, user-specified intervention codes to include in the returned data table. It needs to be a valid MRI code.

cohort

(data.frame or data.table)
Optional, data frame or data table containing the fields:

  • genc_id (integer): Mock encounter ID number

  • hospital_num (integer): Mock hospital ID number When cohort is not NULL, nid and n_hospitals are ignored.

seed

(integer)
Optional, a number to be used to set the seed for reproducible results

Value

(data.table)
A data.table object similar to the "ipintervention" table that contains the columns:

  • genc_id (integer): Mock encounter ID number; integers starting from 1 or from cohort

  • hospital_num (integer): Mock hospital ID number; integers starting from 1 or from cohort

  • intervention_code (character): Valid CCI code(s) describing the services (procedures/intervention) performed for or on behalf of the patient to improve health. For this simulation, it will be for an MRI.

Examples

dummy_erintervention_mri(nid = 1000, int_code = c("3AN40VA", "3SC40WC"))
#>       genc_id hospital_num intervention_code
#>         <int>        <int>            <char>
#>    1:       1            4           3AN40VA
#>    2:       1            4           3AN40VA
#>    3:       1            4           3AN40VA
#>    4:       1            4           3AN40VA
#>    5:       1            4           3AN40VA
#>   ---                                       
#> 2041:     999            2           3AN40VA
#> 2042:     999            2           3AN40VA
#> 2043:     999            2           3SC40WC
#> 2044:     999            2           3AN40VA
#> 2045:    1000            8           3AN40VA
dummy_erintervention_mri(cohort = dummy_admdad(), int_code = "3AN40VA")
#>       genc_id hospital_num intervention_code
#>         <int>        <int>            <char>
#>    1:       1            7           3AN40VA
#>    2:       1            7           3AN40VA
#>    3:       1            7           3AN40VA
#>    4:       1            7           3AN40VA
#>    5:       2            9           3AN40VA
#>   ---                                       
#> 2032:     999            4           3AN40VA
#> 2033:    1000            4           3AN40VA
#> 2034:    1000            4           3AN40VA
#> 2035:    1000            4           3AN40VA
#> 2036:    1000            4           3AN40VA

dummy_erintervention_mri(nid = 100, n_hospitals = 2, seed = 1)
#>      genc_id hospital_num intervention_code
#>        <int>        <int>            <char>
#>   1:       1            1           3SC40WC
#>   2:       1            1           3ER40VA
#>   3:       2            2           3SC40WC
#>   4:       3            1           3AN40VA
#>   5:       4            1           3AN40VA
#>  ---                                       
#> 208:      98            2           3SC40VA
#> 209:      99            2           3ER40VA
#> 210:     100            1           3YM40VA
#> 211:     100            1           3ID40VA
#> 212:     100            1           3SC40VA