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AdhereR

Computation of adherence to medications from Electronic Healthcare Data in R

https://github.com/ddediu/adherer

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: plos.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.3%) to scientific vocabulary

Keywords

adherence-to-medications electronic-healthcare-data hadoop medical-databases medication-histories python r sql visualisation
Last synced: 6 months ago · JSON representation

Repository

Computation of adherence to medications from Electronic Healthcare Data in R

Basic Info
  • Host: GitHub
  • Owner: ddediu
  • Language: HTML
  • Default Branch: main
  • Homepage:
  • Size: 191 MB
Statistics
  • Stars: 31
  • Watchers: 3
  • Forks: 7
  • Open Issues: 37
  • Releases: 5
Topics
adherence-to-medications electronic-healthcare-data hadoop medical-databases medication-histories python r sql visualisation
Created almost 9 years ago · Last pushed about 2 years ago
Metadata Files
Readme

ReadMe.md

AdhereR: two R packages for computing adherence to medications and for visualising medication histories

This is a collection of two packages for the R open-source statistical environment implementing various ways of computing adherence to medications and visualisations of medication histories, both interactive (intended for data exploration) and high quality (intended for publication).

The first package, named AdhereR, implements the actual computations and plotting, while the second package, named AdhereRViz, implements an interactive graphical user interface (a GUI) that allows the user to explore various datasets, computations and visualisations. The two packages are split so that, on the one hand, their development can be decoupled, and, on the other, to avoid the installation of all the dependencies needed only for the interactive GUI by those users wishing (or forced to) access to the actual computations and plotting only (without interactivity). For example, in some server/batch processing settings or on older systems, not all bells and whistles required by an interactive GUI can or should be installed...

More information is given in the packages' various vignettes and in the accompanying paper:

Dima AL, Dediu D (2017). Computation of adherence to medication and visualization of medication histories in R with AdhereR: Towards transparent and reproducible use of electronic healthcare data. PLoS ONE, 12(4): e0174426. doi:10.1371/journal.pone.0174426

While the packages can be created from source or installed using the source packages (.tar.gz) provided in this repository, we recommend that users rather install them directly from The Comprehensive R Archive Network (CRAN) using the normal procedure1 (i.e., install.packages("AdhereR", dep=TRUE) and/or install.packages("AdhereRViz", dep=TRUE)).

The packages are implemented in pure R2, but optimised to work on mid-range hardware even for large databases (stored, for example, in an SQL RDBMS), single-threaded or parallelized in large heterogeneous clusters (using, for example, Apache Hadoop), and runs on any platform that supports R. A standardized interface allows AdhereR to be used transparently from other programming languages or platforms, and a fully functional bridge to Psython 3 is provided as an example.

All the code and example data are released under GPL v3.

Feedback is welcome, preferably by using the GitHub's Issues system for bug reporting and suggestions.

For what is new in each release, please see the NEWS.md file of the concerned package.

Copyright (by period, in alphabetical order by family name; please see individual files for details) (C):

  • 2015-2018: Alexandra Dima, Dan Dediu
  • 2018-2019: Samuel Allemann, Alexandra Dima, Dan Dediu

1 There might be a delay between the release of new versions here and their availability on CRAN; in this case, we would recommend, if possible, to wait for the version to appear on CRAN.

2 We also use some Python for the Python 3 bridge, and HTML/JavaScript/CSS/SVG for generating SVG plots and for the interactive GUI.

Owner

  • Name: Dan Dediu
  • Login: ddediu
  • Kind: user
  • Location: Barcelona, Spain

Software developer turned linguist, working mostly on understanding language evolution and linguistic diversity using databases, statistics and experiments.

GitHub Events

Total
  • Watch event: 4
  • Fork event: 1
Last Year
  • Watch event: 4
  • Fork event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 554
  • Total Committers: 4
  • Avg Commits per committer: 138.5
  • Development Distribution Score (DDS): 0.173
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
ddediu d****u@g****m 458
Masswear m****r@g****h 71
Masswear M****r 24
Ciarán D. McInerney 4****i 1
Committer Domains (Top 20 + Academic)
gmx.ch: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 95
  • Total pull requests: 9
  • Average time to close issues: 4 months
  • Average time to close pull requests: about 11 hours
  • Total issue authors: 9
  • Total pull request authors: 3
  • Average comments per issue: 1.36
  • Average comments per pull request: 0.11
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • ddediu (69)
  • dffyfe (9)
  • alexadima (8)
  • Masswear (3)
  • mumbarkar (2)
  • ck2136 (1)
  • jowendl (1)
  • gustavorps (1)
  • Et9797 (1)
Pull Request Authors
  • ddediu (4)
  • Masswear (4)
  • ciaranmci (2)
Top Labels
Issue Labels
AdhereR(base) (59) enhancement (38) bug (34) suggestion (27) AdhereRViz (24) STUpump (6) SVG interactive (5) sticky/reminder (3) question (2) Stata bridge (2) (partial) work-around (1) wontfix (1) help wanted (1) new release (1) can't reproduce (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • cran 993 last-month
  • Total docker downloads: 57
  • Total dependent packages: 2
    (may contain duplicates)
  • Total dependent repositories: 2
    (may contain duplicates)
  • Total versions: 15
  • Total maintainers: 1
cran.r-project.org: AdhereRViz

Adherence to Medications

  • Versions: 3
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 407 Last month
Rankings
Forks count: 10.8%
Stargazers count: 10.9%
Average: 17.6%
Dependent packages count: 18.1%
Dependent repos count: 23.8%
Downloads: 24.4%
Maintainers (1)
ddediu@gmail.com
Last synced: 6 months ago
cran.r-project.org: AdhereR

Adherence to Medications

  • Versions: 12
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 586 Last month
  • Docker Downloads: 57
Rankings
Forks count: 10.8%
Stargazers count: 10.9%
Dependent packages count: 18.1%
Average: 18.1%
Downloads: 19.9%
Dependent repos count: 23.8%
Docker downloads count: 25.1%
Maintainers (1)
ddediu@gmail.com
Last synced: 6 months ago

Dependencies

AdhereR/DESCRIPTION cran
  • R >= 3.0 depends
  • data.table >= 1.9 imports
  • jpeg >= 0.1 imports
  • lubridate >= 1.5 imports
  • methods * imports
  • parallel >= 3.0 imports
  • png >= 0.1 imports
  • rsvg >= 1.3 imports
  • webp >= 1.0 imports
  • AdhereRViz >= 0.2 suggests
  • R.rsp >= 0.40 suggests
  • base64 >= 2.0 suggests
  • knitr >= 1.20 suggests
  • rmarkdown >= 1.1 suggests
  • viridisLite >= 0.4 suggests
AdhereRViz/DESCRIPTION cran
  • R >= 3.0 depends
  • AdhereR >= 0.7.1 imports
  • DBI >= 1.0 imports
  • RMariaDB >= 1.0.5 imports
  • RSQLite >= 2.1 imports
  • V8 >= 1.5 imports
  • clipr >= 0.4 imports
  • colourpicker >= 1.0 imports
  • data.table >= 1.9 imports
  • highlight >= 0.4 imports
  • knitr >= 1.20 imports
  • manipulate >= 1.0 imports
  • shiny >= 1.0 imports
  • shinyWidgets >= 0.4.4 imports
  • shinyjs >= 1.0 imports
  • viridisLite >= 0.3 imports
  • R.rsp >= 0.40 suggests
  • haven >= 2.0 suggests
  • readODS >= 1.6 suggests
  • readxl >= 1.2 suggests
  • rmarkdown >= 1.1 suggests