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 + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
oncmap results |
Documentation:
Downloads:
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