pdc_treatment: Calculates adherence to drug treatments based on the...

In smm52/timeBlocks: Converts Serial Measurement Data into Longitudinal Trajectory of Equally-sized Time Blocks

Calculates adherence to drug treatments based on the proportion of days covered method.

Description

Calculates adherence to drug treatments based on the proportion of days covered method.

Usage

pdc_treatment(
  serialDf,
  startDates,
  endDates,
  atcCode = c(),
  refillPeriod = 90,
  idColumn = "PATIENT",
  dateColumn = "VISIT",
  atcColumn = "ATC",
  treatmentBreakDays = c(),
  absenceDays = NULL,
  createGraphs = F,
  savePrescriptionTable = F
)

Arguments

serialDf	the data frame with prescription data
startDates	a data frame containing the start dates of the study for each patient
endDates	a data frame containing the end dates of the study for each patient
atcCode	a vector containing regular expressions, each encoding for one component/drug class of the treatment
refillPeriod	length of a prescription refill period in days (default 90 days)
idColumn	name of ID column: default is PATIENT
dateColumn	name of date column: default is VISIT. This column has to be of class Date
atcColumn	name of the column with the ATC codes: default is ATC
treatmentBreakDays	a vector containing the number of days (one entry for each drug class) after which the treatment is considered discontinued (default: no breaks applied)
absenceDays	a data frame containing start dates and end dates of absences for each patient. This time will be removed from the calculation. The first day should be stored in a column called START and the final in one called END. (optional)
createGraphs	flag indicating whether graphs should be produced (default: FALSE)
savePrescriptionTable	flag indicating whether the whole prescription table should be saved in a file (default: FALSE)

Value

adherence rates for the full prescription period and between start and end dates

Examples

## Not run: 
 dfStart <- read_tsv('/home/ad/home/s/stefmutt/projects/former/cadGRS/data/bl_all_new.txt') %>%
   select(PATIENT, VISIT)
 dfEnd <- dfStart %>%
   mutate(VISIT = as.Date('2015-12-31'))
 
 kela <- read_tsv('/home/ad/home/s/stefmutt/projects/former/cadGRS/data/kela_all.txt') %>%
   filter(!is.na(ATC)) %>%
   select(-all_ddd) %>%
   filter(PATIENT %in% dfStart$PATIENT)
 
 adherences <- pdc_treatment(serialDf = kela, startDates = dfStart, endDates = dfEnd, atcCode = c('^C09', '^C10'), refillPeriod = 90, 
                          idColumn = "PATIENT", dateColumn = "VISIT", atcColumn = "ATC", createGraphs = T, 
                          treatmentBreakDays = c(181,181), absenceDays = NULL)

## End(Not run)

smm52/timeBlocks documentation built on Nov. 27, 2022, 3:54 a.m.