indicators: Provide several polypharmacy indicators at once
In polypharmacy: Calculate Several Polypharmacy Indicators

Description Usage Arguments Details Value Examples

Wrapper function to run sequentially various polypharmacy functions on a single set of data. Each function corresponds to a different definition of polypharmacy.

indicators(
  processed_tab,
  stats = c("mean", "sd", "min", "p5", "p10", "p25", "median", "p75", "p90", "p95",
    "max"),
  method = c("ind_simult", "ind_stdcumul", "ind_wcumul", "ind_stdcontinuous",
    "ind_ucontinuous"),
  stdconti_pdays = 90,
  simult_ind_stats = c("mean", "min", "median", "max"),
  simult_calendar = FALSE,
  stdcumul_nPeriod = c(1, 3),
  cores = parallel::detectCores()
)

`processed_tab`	Name of the table of individual drug treatments to analyze. Created by the `data_process` function.
`stats`	Polypharmacy cohort descriptive statistics to calculate on every polypharmacy indicator requested. See Details for possible values.
`method`	Names of the functions corresponding to each of the polypharmacy indicators to be calculated.. See Details for possible values.
`stdconti_pdays`	`pdays` argument of the `ind_stdcontinuous` function. Can contain multiple values. See examples.
`simult_ind_stats`	`stats` argument of the `ind_simult` function.
`simult_calendar`	`TRUE` or `FALSE`. `calendar` argument of the `ind_simult` function.
`stdcumul_nPeriod`	`nPeriod` argument of the `ind_stdcumul` function. Can contain multiple values. See examples.
`cores`	The number of CPU cores to use when executing `ind_simult`. See `detectCores`.

stats & simult_ind_stats: Possible values are

'mean', 'min', 'median', 'max', 'sd';
'pX' where X is an integer value in ]0, 100];
'q1'='p25', 'q2'='p50'='median', q3='p75'.

method: Possible values are

'ind_simult' to assess polypharmacy based on the daily simultaneous consumption of medication.
'ind_stdcumul to assess polypharmacy based on the cumulative number of distinct medications consumed over a given period of time (i.e. the standard definition).
'ind_wcumul' to assess polypharmacy based on the cumulative number of distinct medication consumed over a given period of time, weighted by the duration of consumption of each medication.
'ind_stdcontinuous' to assess polypharmacy based on the number of medications that are consumed both during the initial and the final period of the study period.
'ind_ucontinuous' to assess polypharmacy based on the uninterrupted consumption of distinct medications over the study period.

list of the values returned by every function listed in the method argument.

dt_indic <- indicators(
  processed_tab = sample_Rx_processed,
  stats = c('mean', 'sd', 'min', 'p5', 'p10', 'p25', 'median', 'p75', 'p90', 'p95', 'max'),
  method = c('ind_simult', 'ind_stdcumul', 'ind_wcumul', 'ind_stdcontinuous', 'ind_ucontinuous'),
  stdconti_pdays = c(30, 90),
  simult_ind_stats = c('mean', 'min', 'median', 'max'),
  simult_calendar = TRUE,
  stdcumul_nPeriod = c(1, 3),
  cores = 1
)