ArticleObesity surgery2025
Assessing the FAIRness of Metabolic Bariatric Surgery Registries: a Comparative Analysis of Data Dictionaries from the UK, Germany, France, Netherlands, Norway, and Sweden.
Article in Obesity surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
9 authors.
Funding
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Abstract
backgroundThis study is part of an initiative to improve the FAIRness (Findability, Accessibility, Interoperability, Reusability) of metabolic bariatric surgery (MBS) registries globally. It explores the extent to which European registry data can be manually integrated without first making them FAIR and assesses these registries' current level of FAIRness. The findings establish a baseline for evaluation and provide recommendations to enhance MBS data management practices.
methodsData dictionaries from five national MBS registries in Germany, France, the Netherlands, the UK, and a combined registry for Scandinavia (Norway and Sweden) were evaluated regarding their ability to manually integrate registry datasets with one another. The FAIR Data Maturity Model from the Research Data Alliance (RDA) FAIR Data Maturity Model Working Group was used to assess the FAIRness of both metadata and data of the registries.
resultsThe registries showed significant variability in variables and coding structures, with inconsistent numerical formats and without linkage to international standards such as SNOMED CT, LOINC, or NCIt, making data integration labor-intensive and assumption-heavy. Despite the presence of data dictionaries, all registries failed the FAIR assessment because machine-readable data was unavailable, and only human-readable metadata was available in the form of data dictionaries in a spreadsheet.
conclusionOur study reveals significant inconsistencies in data structuring and a failure to comply with the FAIR Principles, which limit effective data analysis and comparison. This emphasizes the critical need for standardized data management practices. We recommend four next steps to improve the FAIRness of MBS registries: (1) annotate data elements using standardized terminology systems, (2) deposit registry-level metadata in a repository, (3) request globally unique and persistent identifiers for datasets, and (4) define access restrictions.
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