Insights into the FAIRness of the German Network University Medicine: A Survey

Michaelis, Lea; Poyraz, Rasim Atakan; Muzoora, Michael Rusongoza; Gierend, Kerstin; Bartschke, Alexander; Dieterich, Christoph; Johann, Tim; Krefting, Dagmar; Waltemath, Dagmar; Thun, Sylvia

doi:10.3233/shti230251

Cited by 1 publication

(1 citation statement)

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“…Remarkably, examination of the result object regarding adherence to FAIR principles and provenance assessment was not performed in any DIC. These findings indicate a lack of awareness for FAIR data management, as has also been observed in a recent survey within the German Network University Medicine [29].…”

Section: Documentation Artifacts From Final Review and Facts About Re...supporting

confidence: 76%

The Status of Data Management Practices Across German Medical Data Integration Centers: Mixed Methods Study

Gierend,

Freiesleben,

Kadioglu

et al. 2023

J Med Internet Res

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Background In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data into research data repositories for secondary use. Data management practices are of importance throughout these processes, and special attention should be given to provenance aspects. Insufficient knowledge can lead to validity risks and reduce the confidence and quality of the processed data. The need to implement maintainable data management practices is undisputed, but there is a great lack of clarity on the status. Objective Our study examines the current data management practices throughout the data life cycle within the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium. We present a framework for the maturity status of data management practices and present recommendations to enable a trustful dissemination and reuse of routine health care data. Methods In this mixed methods study, we conducted semistructured interviews with stakeholders from 10 DICs between July and September 2021. We used a self-designed questionnaire that we tailored to the MIRACUM DICs, to collect qualitative and quantitative data. Our study method is compliant with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist. Results Our study provides insights into the data management practices at the MIRACUM DICs. We identify several traceability issues that can be partially explained with a lack of contextual information within nonharmonized workflow steps, unclear responsibilities, missing or incomplete data elements, and incomplete information about the computational environment information. Based on the identified shortcomings, we suggest a data management maturity framework to reach more clarity and to help define enhanced data management strategies. Conclusions The data management maturity framework supports the production and dissemination of accurate and provenance-enriched data for secondary use. Our work serves as a catalyst for the derivation of an overarching data management strategy, abiding data integrity and provenance characteristics as key factors. We envision that this work will lead to the generation of fairer and maintained health research data of high quality.

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Section: Documentation Artifacts From Final Review and Facts About Re...supporting

confidence: 76%