miRacumDQA

This is the repository of the MIRACUM data quality assessment tool (DQA tool). The MIRACUM DQA tool is built upon the R packages DQAstats and DQAgui, both available on CRAN.

Besides some customizations for application within the MIRACUM consortium, this repository contains the SQL statements to test the data quality of the MIRACUM research data repositories, as well as a wrapper to import the latest metadata from the centrally deployed MIRACUM metadata repository (M-MDR), which are required to perform the data quality checks. The latter is an enhancement compared to the default setting of DQAstats, which uses a CSV-table as MDR.

In order to provide the information required to perform the DQ checks with miRacumDQA within the MDR, they first need to be added for each new data element to the CSV-file inst/application/_utilities/MDR/mdr.csv. This file then serves as input to the script inst/application/_utilities/MDR/update_dehub_mdr.py, which uses the python library dqa-mdr-connector (big thanks to @FFTibet for his support in developing this MDR-connector) to update the dqa-slots of the respective data elements in the M-MDR.

The following steps are required to let new data elements in the research data repositories be checked by the MIRACUM DQA tool:

1. Add the required metadata to the CSV-MDR inst/application/_utilities/MDR/mdr.csv.
2. Provide the required SQL statements to the appropriate python script in inst/application/_utilities/SQL and run the script to update the respective JSON-file that stores all SQL statements for the respective database.
3. (optionally) Add appropriate value constraints and / or plausibility checks by adding them to the python scripts inst/application/_utilities/MDR/constraints.py and inst/application/_utilities/MDR/plausibilities.py and run those scripts as well.
4. Add the data elements to the list in the file inst/application/_utilities/MDR/dqamdr_config.py.
5. Update the M-MDR by running the script inst/application/_utilities/MDR/update_dehub_mdr.py (please note that a user authentication is required to updated the centrally deployed metadata repository).
6. Create a new version of this miRacumDQA R-package and distribute it to all MIRACUM sites (this step is yet required since the updated SQL statements are only shipped with this R package).

A more detailed description of the steps required to let the DQA tool analyze new data elements is provided in our Wiki.

Currently, the MIRACUM DQA tool is able to analyze data elements stored in the following research data repositories:

• MIRACUM i2b2 (postgres)
• MIRACUM fhir-gateway (postgres)
• OMOP (postgres) (!!! the SQL statements to analyze the OMOP research data repository are deprecated and currently not maintained !!!)

Installation

You can install the with the following commands.

install.packages("remotes")
remotes::install_github("https://github.com/miracum/dqa-miracumdqa.git")

Configuration

The database connection can be configured using environment variables. These can be set using the base R command Sys.setenv().

A detailed description, which environment variables need to be set for the specific databases can be found here.

More Information:

• about MIRACUM: https://www.miracum.org/
• about the Medical Informatics Initiative: https://www.medizininformatik-initiative.de/index.php/de
• about Shiny: https://www.rstudio.com/products/shiny/
• RStudio and Shiny are trademarks of RStudio, Inc.