polypharmacy (version 1.0.0)

ind_wcumul: Assess polypharmacy based on the number of distinct medications consumed weighted to their respective duration of consumption

Description

Calculates the number of distinct medications weighted by the duration of consumption that are consumed by every individual and provides cohort descriptive statistics on this indicator.

Usage

ind_wcumul(
  processed_tab,
  stats = c("mean", "sd", "min", "p5", "p10", "p25", "median", "p75", "p90", "p95",
    "max")
)

Arguments

processed_tab

Table of individual drug treatments over the study period. Created by data_process function.

stats

Cohort descriptive statistics to calculate on the polypharmacy indicator. See Details for possible values.

Value

list:

• indic: data.table indicating each stats (columns).

• stats_id: data.table indicating the number of drugs use for each individual (all cohort).

Details

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'.

Examples

# NOT RUN {
rx1 <- data.frame(id = c(1, 1, 1, 2),
                  code = c("A", "B", "C", "A"),
                  date = c("2000-01-01", "2000-01-01", "2000-01-26", "2000-01-17"),
                  duration = c(30, 5, 5, 10))
cohort1 <- data.frame(id = as.numeric(1:3),
                      age = c(45, 12, 89),
                      sex = c("F", "F", "M"))
rx_proc1 <- data_process(Rx_deliv = rx1, Rx_id = "id", Rx_drug_code = "code",
                         Rx_drug_deliv = "date", Rx_deliv_dur = "duration",
                         Cohort = cohort1, Cohort_id = "id",
                         study_start = "2000-01-01", study_end = "2000-01-30",
                         cores = 1)
dt_ind_wcumul <- ind_wcumul(processed_tab = rx_proc1)
# }