summarize_descriptives: Generate Detailed Descriptive Statistics

In hcruR: Estimate, Compare, and Visualize Healthcare Resource Utilization for Real-World Evidence

Generate Detailed Descriptive Statistics

Description

Generate Detailed Descriptive Statistics

Usage

summarize_descriptives(
  data,
  patient_id_col = "patient_id",
  setting_col = "care_setting",
  cohort_col = "cohort",
  encounter_id_col = "encounter_id",
  cost_col = "cost_usd",
  los_col = "length_of_stay",
  readmission_col = "readmission",
  time_window_col = "time_window"
)

Arguments

data	A dataframe with variables to summarize.
patient_id_col	A character specifying the name of patient identifier column
setting_col	A character specifying the name of HRCU setting column
cohort_col	A character specifying the name of cohort column
encounter_id_col	A character specifying the name of encounter/claim column
cost_col	A character specifying the name of cost column
los_col	A character specifying the name of length of stay column
readmission_col	A character specifying the name of readmission column
time_window_col	A character specifying the name of time window column

Value

A table object

Examples

if (requireNamespace("dplyr", quietly = TRUE) &&
    requireNamespace("checkmate", quietly = TRUE)) {
  hcru_sample_data <- data.frame(
    patient_id = rep(1:10, each = 2),
    cohort = rep(c("A", "B"), 10),
    care_setting = rep(c("IP", "OP"), 10),
    admission_date = Sys.Date() - sample(1:100, 20, TRUE),
    discharge_date = Sys.Date() - sample(1:90, 20, TRUE),
    index_date = Sys.Date() - 50,
    visit_date = Sys.Date() - sample(1:100, 20, TRUE),
    encounter_id = 1:20,
    cost_usd = runif(20, 100, 1000)
  )
  df <- preproc_hcru_fun(data = hcru_sample_data)
  summary_df <- summarize_descriptives(data = df)
  # Only keep required columns for demonstration
  summary_df$LOS <- ifelse(summary_df$care_setting == "IP",
    sample(1:10, nrow(summary_df), TRUE), NA)
  summary_df$Readmission <- ifelse(summary_df$care_setting == "IP",
    sample(0:1, nrow(summary_df), TRUE), NA)
  summary_df$time_window <- "Pre"
  summary_df
}

hcruR documentation built on Sept. 2, 2025, 1:09 a.m.