Package: drugprepr 0.0.7.9000

David Selby

drugprepr: Prepare Electronic Prescription Record Data to Estimate Drug Exposure

Prepare prescription data (such as from the Clinical Practice Research Datalink) into an analysis-ready format, with start and stop dates for each patient's prescriptions. Based on Pye et al (2018) <doi:10.1002/pds.4440>.

Authors:Belay Birlie Yimer [aut], David Selby [aut, cre, cph], Meghna Jani [aut], Goran Nenadic [aut], Mark Lunt [aut], William G. Dixon [aut]

drugprepr_0.0.7.9000.tar.gz
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drugprepr_0.0.7.9000.tgz(r-4.6-any)drugprepr_0.0.7.9000.tgz(r-4.5-any)
drugprepr_0.0.7.9000.tar.gz(r-4.7-any)drugprepr_0.0.7.9000.tar.gz(r-4.6-any)
drugprepr_0.0.7.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
drugprepr/json (API)

# Install 'drugprepr' in R:

install.packages('drugprepr', repos = c('https://belayb.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/belayb/drugprepr/issues

Datasets:

cprd - Example data from the Clinical Practice Research Datalink (CPRD).
min_max_dat - Example plausible ranges for prescription quantity and dosage

On CRAN:

4.18 score 3 stars 5 scripts 259 downloads 12 exports 71 dependencies

Last updated from:adef81c334. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	186
source / vignettes	OK	229
linux-release	OK	225
macos-release	OK	186
macos-oldrel	OK	231
windows-devel	OK	114
windows-release	OK	121
windows-oldrel	OK	115
wasm-release	OK	123

Exports:clean_duration close_small_gaps compute_ndd drug_prep example_therapy impute impute_duration impute_ndd impute_qty isolate_overlaps make_decisions shift_interval

Dependencies:askpass bit bit64 blob boot cachem cellranger chron class cli clipr cpp11 crayon curl data.table DBI DescTools doseminer dplyr e1071 Exact expm fastmap forcats fs generics gld glue gsubfn haven hms httr jsonlite lattice lifecycle lmom magrittr MASS Matrix memoise mime mvtnorm openssl pillar pkgconfig prettyunits progress proto proxy purrr R6 Rcpp readr readxl rematch rlang rootSolve RSQLite rstudioapi sqldf stringi stringr sys tibble tidyr tidyselect tzdb utf8 vctrs vroom withr

Introduction to drugprepr

Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2026-07-22
Started: 2021-06-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Clean implausibly-long prescription durations	clean_duration
Close small gaps between successive prescriptions	close_small_gaps
Compute numerical daily dose from free-text prescribing instructions	compute_ndd
Example data from the Clinical Practice Research Datalink (CPRD).	cprd
Decision 1: impute implausible total quantities	decision_1
Decision 10: close small gaps between successive prescriptions	decision_10
Decision 2: impute missing total quantities	decision_2
Decision 3: impute implausible daily doses	decision_3
Decision 4: impute missing daily doses	decision_4
Decision 5: impute implausible prescription durations	decision_5
Decision 6: choose method of calculating prescription duration	decision_6
Decision 7: impute missing prescription durations	decision_7
Decision 8: disambiguate prescriptions with the same start date	decision_8
Decision 9: handle overlapping prescription periods	decision_9
Run drug preparation algorithm	drug_prep
Example electronic prescription dataset	example_therapy
Get the mode (most common value) of a vector	get_mode
Impute missing or implausible values	impute
Replace missing or implausible prescription durations	impute_duration
Replace implausible or missing numerical daily doses (NDD)	impute_ndd
Find implausible entries Replace implausible or missing prescription quantities	impute_qty
Separating overlapping prescription periods	isolate_overlaps
Human-friendly interface to the drug prep algorithm	make_decisions
Example plausible ranges for prescription quantity and dosage	min_max_dat
Do values fall outside a specified 'plausible' range?	outside_range
Shift time intervals until they no longer overlap	shift_interval