oncmap: Analyze Data from Electronic Adherence Monitoring Devices

Medication adherence, defined as medication-taking behavior that aligns with the agreed-upon treatment protocol, is critical for realizing the benefits of prescription medications. Medication adherence can be assessed using electronic adherence monitoring devices (EAMDs), pill bottles or boxes that contain a computer chip that records the date and time of each opening (or “actuation”). Before researchers can use EAMD data, they must apply a series of decision rules to transform actuation data into adherence data. The purpose of this R package ('oncmap') is to transform EAMD actuations in the form of a raw .csv file, information about the patient, regimen, and non-monitored periods into two daily adherence values – Dose Taken and Correct Dose Taken.

Version:	0.1.5
Depends:	R (≥ 3.60)
Imports:	readr, methods, readxl, dplyr, hms, lubridate, zoo
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2025-01-27
DOI:	10.32614/CRAN.package.oncmap
Author:	Michal Kouril [aut, cre], Meghan McGrady [aut], Mara Constance [aut], Kevin Hommel [aut]
Maintainer:	Michal Kouril <Michal.Kouril at cchmc.org>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README
CRAN checks:	oncmap results

Documentation:

Reference manual:	oncmap.pdf
Vignettes:	FORMATS (source, R code)

Downloads:

Package source:	oncmap_0.1.5.tar.gz
Windows binaries:	r-devel: not available, r-release: oncmap_0.1.5.zip, r-oldrel: oncmap_0.1.5.zip
macOS binaries:	r-release (arm64): oncmap_0.1.5.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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