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.


OncMAP - R Package to analyze data from electronic adherence monitoring devices for oncology and other medications

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.

Reference manual

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install.packages("oncmap")

0.1.7 by Michal Kouril, a year ago


Browse source code at https://github.com/cran/oncmap


Authors: Michal Kouril [aut, cre] , Meghan McGrady [aut] , Mara Constance [aut] , Kevin Hommel [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports readr, methods, readxl, dplyr, hms, lubridate, zoo

Suggests knitr, rmarkdown, testthat


See at CRAN