Using the Data Quality Dashboard to Improve the EHDEN Network
Federated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collabo...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/24/11920 |
| _version_ | 1827674251097800704 |
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| author | Clair Blacketer Erica A. Voss Frank DeFalco Nigel Hughes Martijn J. Schuemie Maxim Moinat Peter R. Rijnbeek |
| author_facet | Clair Blacketer Erica A. Voss Frank DeFalco Nigel Hughes Martijn J. Schuemie Maxim Moinat Peter R. Rijnbeek |
| author_sort | Clair Blacketer |
| collection | DOAJ |
| description | Federated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collaboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Fifteen Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance issues but showed less of an impact on completeness and plausibility checks. This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research. |
| first_indexed | 2024-03-10T04:36:55Z |
| format | Article |
| id | doaj.art-acee19a4cb424af8b8bb89ae305ce7ab |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:36:55Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-acee19a4cb424af8b8bb89ae305ce7ab2023-11-23T03:40:24ZengMDPI AGApplied Sciences2076-34172021-12-0111241192010.3390/app112411920Using the Data Quality Dashboard to Improve the EHDEN NetworkClair Blacketer0Erica A. Voss1Frank DeFalco2Nigel Hughes3Martijn J. Schuemie4Maxim Moinat5Peter R. Rijnbeek6Janssen Pharmaceutical Research and Development LLC, Titusville, NJ 08560, USAJanssen Pharmaceutical Research and Development LLC, Titusville, NJ 08560, USAJanssen Pharmaceutical Research and Development LLC, Titusville, NJ 08560, USAJanssen Pharmaceutical Research and Development LLC, Titusville, NJ 08560, USAJanssen Pharmaceutical Research and Development LLC, Titusville, NJ 08560, USADepartment of Medical Informatics, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsDepartment of Medical Informatics, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsFederated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collaboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Fifteen Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance issues but showed less of an impact on completeness and plausibility checks. This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.https://www.mdpi.com/2076-3417/11/24/11920data qualityOMOP CDMEHDENhealthcare datareal world dataRWD |
| spellingShingle | Clair Blacketer Erica A. Voss Frank DeFalco Nigel Hughes Martijn J. Schuemie Maxim Moinat Peter R. Rijnbeek Using the Data Quality Dashboard to Improve the EHDEN Network Applied Sciences data quality OMOP CDM EHDEN healthcare data real world data RWD |
| title | Using the Data Quality Dashboard to Improve the EHDEN Network |
| title_full | Using the Data Quality Dashboard to Improve the EHDEN Network |
| title_fullStr | Using the Data Quality Dashboard to Improve the EHDEN Network |
| title_full_unstemmed | Using the Data Quality Dashboard to Improve the EHDEN Network |
| title_short | Using the Data Quality Dashboard to Improve the EHDEN Network |
| title_sort | using the data quality dashboard to improve the ehden network |
| topic | data quality OMOP CDM EHDEN healthcare data real world data RWD |
| url | https://www.mdpi.com/2076-3417/11/24/11920 |
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