In the specific context of this script, the section "Installing the packages" is dedicated to

installing additional packages that are necessary to execute the subsequent analyses. Each line install.packages("package_name") installs a specific package. Press Ctrl + Enter to run the code. The

code is as follows:

install.packages("tidyverse")
install.packages("openxlsx")
install.packages("psych")
install.packages("gtsummary")
install.packages("flextable")
install.packages("magrittr")

Every time you open the software, you should load the following

packages:

library(tidyverse)   # Loads the Tidyverse, a collection of packages for data manipulation and visualization, including popular packages like dplyr and ggplot2.
library(openxlsx)    # Loads the openxlsx library, which is used for spreadsheet manipulation and working with Excel files.
library(psych)       # Loads the psych library, providing functions for statistical analysis and psychometrics.
library(gtsummary)   # Loads the gtsummary library, used for creating summary tables in a concise and elegant manner.
library(flextable)   # Loads the flextable library, providing a flexible approach to creating tables with various formatting options.
library(magrittr)    # Loads the magrittr library, facilitating data manipulation using the pipe operator %>%. The pipe operator is used to chain operations together in a readable and efficient way.

Setting the working directory is important because it determines the default location for reading and writing files.

1- In RStudio, go to the "Session" menu.

2- Select "Set Working Directory" and choose "Choose Directory..."

3- Navigate to the directory

# Alternatively, you can use the command below:

Setwd ( "C:/Path/To/Your/Directory") #put the path of your directory inside the parenthesis

Here we read the data file called "file­.mpr." and store it in a variable called MPR.

# The read.csv2 function is used to read data from a CSV file where the column separator is a semicolon (;).

# The argument "file.mpr" represents the name of the file to be read. You should download the spreadsheet with the medication dispensation data from your institution's dispensation system. In

this example, the obtained spreadsheet contains: Medication name, number of

dispensed units, and patient medical record number. We chose to use the medical

record number to avoid homonyms.

MPR <- read.csv2("file.mpr.csv") #Add .csv after the file name
```\# Now, the variable MPR contains the data from the CSV file, and you can manipulate or perform additional analyses as needed.

Now, we select the columns that are relevant to our analysis and store them in a new variable called MPR1.

MPR1 <- MPR %>%
  select(Drug, Dispensed, Medical.record)

We use the "glimpse" command to visualize the structure of our MPR1 dataset.

glimpse(MPR1)

In this step, we convert the by "Medical.record" column into characters to ensure it is handled correctly.

MPR1$Medical.record <- as.character(MPR1$Medical.record)

We perform calculations in the "Dispensed" column based on the conditions specified for each

"drug".

We also group the data by "Medical.record "and "drug" and calculate the percentagem.

MPR1 <- MPR1 %>%
  mutate(
    Dispensed = Dispensed / 365,  #calculation for a period of 1 year)
    Dispensed = case_when(
      Drug == "Imatinibe 100mg" ~ Dispensed / 2,#referring to two tablets per day. In the case of 3 tablets, divide by 3, and so on.
      Drug == "Dasatinibe 20mg" ~ Dispensed / 2,
      Drug == "Nilotinibe 200mg" ~ Dispensed / 4,
      Drug == "Imatinibe 400mg" ~ Dispensed,
      Drug == "Dasatinibe 100mg" ~ Dispensed
    )
  ) %>%
  group_by(Medical.record, Drug) %>%
  summarise(
    Porcentagem = ifelse(sum(Dispensed) > 100, 100, round(sum(Dispensed), 2) * 100),
    .groups = "drop"  
  ) %>%
  mutate(Porcentagem = ifelse(Porcentagem > 100, 100, Porcentagem),
         Porcentagem = format(Porcentagem, digits = 2, nsmall = 2, scientific = FALSE) %>%
           paste0("%"))

Now we sort the data alphabetically based on the "Drug" column.

MPR1 <- MPR1 %>%
   arrange(Drug)

Here we create a flexible table (ft) and adjust its properties such as width and alignment.

ft <- flextable(MPR1)
set_table_properties(ft,
                    width = 0.99,
                    align = "center")  #Aligns the table contents to the center.

Finally, we save the document with the name "MPR_Percentagem.docx" in the specified location.

save_as_docx(ft, path = "C:/Path/To/Your/Directory/MPR_Percentagem.docx") #put the path of your directory inside the parenthesis