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: | 0.1.7 |
| Depends: | R (≥ 3.60) |
| Imports: | readr, methods,readxl,dplyr,hms,lubridate,zoo |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2025-04-09 |
| 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 + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | oncmap results |
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