Belay B. Yimer, David A. Selby, Meghna Jani, Goran Nenadic, Mark Lunt, William G. Dixon
An algorithm for the transparent and efficient preparation of
electronic prescription data into information on individuals’ drug use
over time. The goal of the drugprepr
package is to allow
users to perform multiverse analyses in a concise and easily
interpretable manner. The drugprepr
package allows
researchers to specify sets of defensible data processing options at
each decision node (e.g., different ways of imputing missing quantity
and daily dose, different ways of handling multiple prescriptions),
implement them all, and then report the outcomes of all analyses
resulting from all possible choice combinations. The package depends on
the R package doseminer
for extracting drug dosage
information from freetext prescription data.
You can install the latest development version from
GitHub
:
devtools::install_github("belayb/drugprepr")
Maintained by Belay Birlie Yimer and David Selby of the Centre for Musculoskeletal Research, University of Manchester, UK. Pull requests and GitHub issues are welcomed.