isolate_overlaps: Separating overlapping prescription periods

In belayb/drugprepr: Prepare Electronic Prescription Record Data to Estimate Drug Exposure

Description

Run this function and then you can either simply discard overlapping intervals or shift them around using an appropriate algorithm.

Usage

isolate_overlaps(data)

Arguments

data	A data frame including variables patid, start_date, stop_date and prodcode

Details

The older implementation used isolateoverlaps from the intervalaverage package and Overlap from the DescTools package. Here we refactor it using functions from tidyverse instead.

Value

A data frame of patid, prodcode, start_date and stop_date, where intervals are either exactly overlapping or mutually non-overlapping (but not partially overlapping), such that the union of such intervals is equivalent to those originally provided in data

Note

This function currently doesn't use any keys except patid and prodcode. It may be desirable to add a row ID, for matching each partial interval back to the original interval from which it was derived. This may be relevant to models using weighted dosages.

See Also

intervalaverage::isolateoverlaps, foverlaps

Examples

set.seed(1)
overlapping_data <- data.frame(
  rowid = 1:20,
  patid = 1:2,
  prodcode = 'a',
  start_date = Sys.Date() + c(round(rexp(19, 1/7)), -20),
  qty = rpois(20, 64),
  ndd = sample(seq(.5, 12, by = .5), 20, replace = TRUE),
  stringsAsFactors = FALSE
)
overlapping_data <- transform(overlapping_data,
  stop_date = start_date + qty / ndd
)
isolate_overlaps(overlapping_data)

belayb/drugprepr documentation built on Dec. 19, 2021, 7:44 a.m.