cordDqChecker

CordDqChecker is a Tool for data quality assessment and reporting in CORD-MI.

Acknowledgement: This work was done within the “Collaboration on Rare Diseases” of the Medical Informatics Initiative (CORD-MI) funded by the German Federal Ministry of Education and Research (BMBF), under grant number: FKZ-01ZZ1911R.

Local Execution

To analyse your data quality locally go to folder ./Local and run cordDqChecker.R to genrate data quality reports.

• The script cordDqChecker.R reads data from FHIR server or from supported file formats such as CSV and Excel. The path varialbe specifies which dataset should be imported. For Example you can define your path as following:

  • path="http://141.5.101.1:8080/fhir/" or
  • path="./Data/medData/dqTestData.csv" or
  • path="./Data/medData/dqTestData.xlsx"

• The default values of local variables are set as follows:

  • reportYear=2020
  • max_FHIRbundles=50
  • INPATIENT_CASE_NO=10000
  • path="http://141.5.101.1:8080/fhir/

Once the source data path and local variables are defined, start the script to check the quality of your data. The genrated repots are saved in folder "./Local/Data/Export"

Distributed Execution

cordDqChecker was successfully tested using Personal Health Train (PHT) and applied on synthetic data stored in multiple FHIR servers. The aggregated results are stored in folder ./PHT/Data/Export. To create a PHT image run ./Dockerfile.

Data Quality Metrics

• The following indicators and key numbers are configured by default data quality reports:

  Dimension	Indicator Name
  completeness	missing_item_rate, missing_value_rate, orphaCoding_completeness_rate
  plausibility	outlier_rate, orphaCoding_plausibility_rate
  uniqueness	rdCase_uniqueness_rate
  concordance	orphaCoding_relativeFrequency, unique_rdCase_relativeFrequency

  Key number	Name
  patient number	patient_no
  case number	case_no
  RD case number	rdCase_no
  orpha code number	orphaCoding_no
  unique RD case number	unique_rdCase_no

• The following references are currently used to assess the quality of orphacoding and can be easily updated with new codes or versions:

  • Alpha-ID-SE list [1]
  • Hamburger list [2] extended with 1-m relationships of ICD-10 to Orpha codes such as E75.2-(324, 487, 355, 512)

  [1] DIMDI/Alpha-ID-SE list: www.dimdi.de

  [2] Schulz M et alt:. Prävalenz seltener Erkrankungen in der ambulanten Versorgung in Deutschland im Zeitraum 2008 bis 2011, Versorgungsatlas-Bericht. 2015;15/13

Examples of local data quality reports

Here are examples of generated data quality reports using sythetic data

Note

Before starting cordDqChecker.R you need to install required libraries using this script installPackages.R

To cite cordDqChecker, please use the following BibTeX entry:

@software{Tahar_cordDqChecker,
author = {Tahar, Kais},title = {{cordDqChecker}},
url = {https://github.com/medizininformatik-initiative/cord-dq-checker},
year = {2021}
}

See also: CORD-MI