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Scalable Infrastructure Supporting Reproducible Nationwide Healthcare Data Analysis toward FAIR Stewardship

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dc.contributor.authorKim, JW-
dc.contributor.authorKim, C-
dc.contributor.authorKim, KH-
dc.contributor.authorLee, Y-
dc.contributor.authorYu, DH-
dc.contributor.authorYun, J-
dc.contributor.authorBaek, H-
dc.contributor.authorPark, RW-
dc.contributor.authorYou, SC-
dc.date.accessioned2023-11-09T05:00:33Z-
dc.date.available2023-11-09T05:00:33Z-
dc.date.issued2023-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/26520-
dc.description.abstractTransparent and FAIR disclosure of meta-information about healthcare data and infrastructure is essential but has not been well publicized. In this paper, we provide a transparent disclosure of the process of standardizing a common data model and developing a national data infrastructure using national claims data. We established an Observational Medical Outcome Partnership (OMOP) common data model database for national claims data of the Health Insurance Review and Assessment Service of South Korea. To introduce a data openness policy, we built a distributed data analysis environment and released metadata based on the FAIR principle. A total of 10,098,730,241 claims and 56,579,726 patients’ data were converted as OMOP common data model. We also built an analytics environment for distributed research and made the metadata publicly available. Disclosure of this infrastructure to researchers will help to eliminate information inequality and contribute to the generation of high-quality medical evidence.-
dc.language.isoen-
dc.titleScalable Infrastructure Supporting Reproducible Nationwide Healthcare Data Analysis toward FAIR Stewardship-
dc.typeArticle-
dc.identifier.pmid37794003-
dc.identifier.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550904-
dc.contributor.affiliatedAuthorPark, RW-
dc.type.localJournal Papers-
dc.identifier.doi10.1038/s41597-023-02580-7-
dc.citation.titleScientific data-
dc.citation.volume10-
dc.citation.number1-
dc.citation.date2023-
dc.citation.startPage674-
dc.citation.endPage674-
dc.identifier.bibliographicCitationScientific data, 10(1). : 674-674, 2023-
dc.identifier.eissn2052-4463-
dc.relation.journalidJ020524463-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
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