Technical Requirements

1 OHDSI Environment Setup

To run this study you must setup the HADES environment.

2 Supported Databases

You also require your site data to be mapped to the OMOP CDM and administered on one of the following supported database platforms:

  • Microsoft SQL Server
  • PostgreSQL
  • Google BigQuery
  • Amazon Redshift
  • Snowflake

2.1 Downloading JDBC Driver

Prior to starting the study ensure that you have downloaded the appropriate .jar file for your dbms to use with DatabaseConnector. Please follow these steps:

  1. Create a DATABASECONNECTOR_JAR_FOLDER locally
  2. Run command usethis::edit_r_environ() to open your .Renviron which stores your environment variables
  3. Add an environment variable following example. This will serve as default path to driver for all DatabaseConnector commands
DATABASECONNECTOR_JAR_FOLDER="C:/Users/.../Documents/R/jar_folder"
  1. Save .Renviron and restart R session.
  2. Download Jdbc Driver using DatabaseConnector, example below
DatabaseConnector::downloadJdbcDrivers(dbms = "postgresql")

3 Data Quality Control

Prior to running this study, it is expected that the data node has performed some sort of QC of their OMOP ETL process. Open-source tools are available to assist in conducting QC of the ETL:

4 Study Environment

4.1 R Version

This study requires a minimal R version of 4.1.3 (2022-03-10). Link to windows installer.

4.2 R Environment

This study uses renv to reproduce the R environment to execute this study. The study code maintains an renv.lock file in the main branch of the repository. To activate the renv use the following code:

renv::restore()

4.2.1 Conflicts

Some organizational IT setups pose conflicts with renv. One example is if your organization uses the Broadsea Docker. If you have a conflict with renv please complete the following steps:

  1. Run renv::deactivate() in the active ehden .RProj
  2. Review table below with installed versions of R packages
  3. If a dependency is missing, install it manually. The code below provides examples of scenarios on how to install an R package:

# Installing an R package from CRAN ------------

## Installing latest version of R package on CRAN
install.packages("ggplot2")

## Installing archived version of R package on CRAN
packageurl <- "http://cran.r-project.org/src/contrib/Archive/ggplot2/ggplot2_0.9.1.tar.gz"
install.packages(packageurl, repos=NULL, type="source")

# Installing an R package from github -----------------

# Installing current version of R package from github
install.packages("remotes") # note you may also work devtools
remotes::install_github("ohdsi/FeatureExtraction")

# Installing develop version of R package from github
remotes::install_github("ohdsi/Ulysses", ref = "develop")

# Installing old version of R package from github
remotes::install_github("ohdsi/CohortGenerator", ref = "v0.7.0")

It is highly recommended you stick with the renv snapshot as this is the easiest way to reproduce the study execution environment.

4.3 R Packages

The following is an exhaustive list of R packages active during the development of the EHDEN HMB study: