Open-source analysis and visualization of medication adherence from electronic healthcare data


Main features

Explore some of AdhereR’s features

Interactive and publication-quality plotting

AdhereR can generate various real-time interactive plots that allow the easy exploration of individual patients, useful both for research and in the clinical practice.

Access any data

AdhereR can process data from a variety of sources, ranging from local files to distributed large databases.

Efficient on almost any platform

AdhereR is written in R, heavily optimised, and capable of parallel processing.

Not just for R

AdhereR methods can be used with other programming languages and statistical platforms through bridging interfaces.

Visit AdhereR on GitHub

The package is available from The Comprehensive R Archive Network (better known as CRAN) and can be installed in R using the normal procedure (for example, running the command install.packages("AdhereR", dep=TRUE) or, if using it, from RStudio). The package is developed on GitHub, where the latest source code for the stable and various development branches is available and where bugs can be reported, questions can be asked and features requested.


Our Team

Alexandra Dima

since 2015

original idea, theoretical concepts, design, testing…

Dan Dediu

since 2015

original implementation, technical aspects, testing, website…

Samuel Allemann

since 2018

theoretical concepts, technical aspects, testing, website…


Lines of Code


Different Adherence Methods


Peer-reviewed Publications





Follow the latest announcements of new features and bug fixes

Version 0.5 released!

AdhereR version 0.5 is a major release (see for details) that offers multiple functions to link and prepare data from different sources for adherence estimation (see vignette). The funct…

Version 0.4.1 released!

AdhereR version 0.4.1 is a small bugfix release for version 0.4 (see for details). …

Version 0.4 released!

AdhereR version 0.4 is a major release that (see for details) that expands the interactive plotting into a full, self-contained Shiny App (see vignette) that implements a point-and-click us…


Our History

Alexandra, while working on adherence to treatment in various contexts (chronic pain during her PhD between 2005-2009 at the University of Edinburgh, UK, and a Postdoc between 2009-2011 at the University of Southampton, UK, and asthma as a Postdoc at the University of Wageningen in 2012 and then at the University of Amsterdam between 2012-2017, both The Netherlands), grew increasingly frustrated by the lack of clarity and standardization of the various definitions and computations of adherence used in the literature.

So, she decided that she can do better and, together with Dan (a computer scientist and linguist with extensive experience in statistical programming in R), she started (around the summer of 2015) working on bits of R code that would implement in a clear and open manner several definitions found in the literature (some based on preexisting publications, others new). Those bits of R code, developed during evenings, weekends and other “spare” time, turned into an R package released together with the PLoS ONE paper in 2017.

Less than a year later, Alexandra (who moved in April 2017 to Université Claude Bernard Lyon 1, France, with a Marie Skłodowska-Curie Postdoctoral Fellowship) and Dan (at the time still at the Max Planck Institute for Psycholinguistics in Nijmegen, The Netherlands) were approached by Samuel, a pharmacist trained at the University of Basel, Switzerland, who, with the support of a Postdoctoral Fellowship from the Swiss National Science Foundation, wanted to move to Lyon and work with them on developing AdhereR. Samuel’s application was successful, and he moved to Lyon in January 2018.

Dan also moved to Lyon in October 2017 with an EURIAS Fellowship with the Collegium de Lyon.

Since the 1st of October 2018, AdhereR is part of a larger IDEXLyon Fellowship (2018-2021) from the Université de Lyon, called “Variation, Change and Complexity in Linguistic and Health-related Behaviours” (short: V2C) jointly hosted by the Laboratoire Dynamique Du Langage (DDL), Université Lumière Lyon 2 and the Health Services and Performance Research Laboratory (HESPER), Université Claude Bernard Lyon 1. Within this project, we continue developing AdhereR through several collaborations with other research groups and healthcare organisations. If you are interested in using AdhereR in your research project or in contributing to the development, do get in touch!

Get in Touch