CohortContrast

The goal of CohortContrast is to facilitate the comparison between cohorts in specified domains across all OMOP CDM datasets. It enables users to analyze and visualize the contrast between target and control cohorts effectively.

Installation

Install the released version from CRAN:

install.packages("CohortContrast")

The development version remains available from GitHub:

# install.packages("devtools")
# devtools::install_github("HealthInformaticsUT/CohortContrast")
install.packages("CohortContrast", repos = c('https://healthinformaticsut.r-universe.dev', 'https://cloud.r-project.org'))

Usage

For complete setup and workflow code, use:

1. CRAN package page: https://CRAN.R-project.org/package=CohortContrast
2. Project wiki (setup + workflow): https://github.com/HealthInformaticsUT/CohortContrast/wiki
3. Package site (function reference + vignettes): https://healthinformaticsut.github.io/CohortContrast/

If you are running CohortContrast on an air-gapped server, see the wiki article here: https://github.com/HealthInformaticsUT/CohortContrast/wiki

Outputs

The CohortContrast package generates the following outputs:

1. Running CohortContrast returns a list of tables (patient level summarised data for target and control) and saves a study folder with parquet files that can be analysed in the GUI directly.
2. Using viewer helpers with runCohortContrastViewer generates plots from parquet-formatted results.
3. Example studies are available under inst/example/st.
4. Public study outputs can be explored at http://omop-apps.cloud.ut.ee/CohortContrast/.
5. A larger example with 1080 diagnosis-level outputs is available in the CohortContrast Atlas at http://omop-apps.cloud.ut.ee/CohortContrastAtlas/.

More information

CohortContrast provides much more insight generation possibilities. See the package site for details: https://healthinformaticsut.github.io/CohortContrast/

For feature requests create issues on Github or contact Markus Haug (markus.haug@ut.ee) personally. Bug reports can be opened at https://github.com/HealthInformaticsUT/CohortContrast/issues.