R/indicators.R

In polypharmacy: Calculate Several Polypharmacy Indicators

#' Provide several polypharmacy indicators at once
#'
#' Wrapper function to run sequentially various polypharmacy functions on a single set of data. Each function corresponds to a different definition of polypharmacy.
#'
#' \strong{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'`.
#'
#' \strong{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.
#'
#' @param processed_tab Name of the table of individual drug treatments to analyze. Created by the \code{\link{data_process}} function.
#' @param stats Polypharmacy cohort descriptive statistics to calculate on every polypharmacy indicator requested. See *Details* for possible values.
#' @param method Names of the functions corresponding to each of the polypharmacy indicators to be calculated.. See *Details* for possible values.
#' @param stdconti_pdays `pdays` argument of the \code{\link{ind_stdcontinuous}} function. Can contain multiple values. See *examples*.
#' @param simult_ind_stats `stats` argument of the \code{\link{ind_simult}} function.
#' @param simult_calendar `TRUE` or `FALSE`. `calendar` argument of the \code{\link{ind_simult}} function.
#' @param stdcumul_nPeriod `nPeriod` argument of the \code{\link{ind_stdcumul}} function. Can contain multiple values. See *examples*.
#' @param cores The number of CPU cores to use when executing \code{\link{ind_simult}}. See \code{\link[parallel]{detectCores}}.
#'
#' @return `list` of the values returned by every function listed in the `method` argument.
#' @export
#' @encoding UTF-8
#' @examples
#' \donttest{
#' 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
#' )
#' }
indicators <- function(
  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()
) {

  ll <- vector("list", length(method)-2 + length(stdcumul_nPeriod) + length(stdcumul_nPeriod))
  i <- 1L

  if ("ind_simult" %in% method) {
    ll[[i]] <- ind_simult(
      processed_tab, individual_stats = simult_ind_stats, stats = stats,
      calendar = simult_calendar, cores = cores
    )
    names(ll)[i] <- "ind_simult"
    i <- i + 1L
  }

  if ("ind_stdcumul" %in% method) {
    for (per in stdcumul_nPeriod) {
      ll[[i]] <- ind_stdcumul(processed_tab, per, stats)
      names(ll)[i] <- paste0("ind_stdcumul_per",per)
      i <- i + 1L
    }
  }

  if ("ind_wcumul" %in% method) {
    ll[[i]] <- ind_wcumul(processed_tab, stats)
    names(ll)[i] <- "ind_wcumul"
    i <- i + 1L
  }

  if ("ind_stdcontinuous" %in% method) {
    for (pdays in stdconti_pdays) {
      ll[[i]] <- ind_stdcontinuous(processed_tab, pdays, stats)
      names(ll)[i] <- paste0("ind_stdcontinuous_pdays", pdays)
      i <- i + 1L
    }
  }

  if ("ind_ucontinuous" %in% method) {
    ll[[i]] <- ind_ucontinuous(processed_tab, stats)
    names(ll)[i] <- "ind_ucontinuous"
  }

  return(ll)

}