Research data warehouse best practices: catalyzing national data sharing through informatics innovation.
Research Patient Data Repositories (RPDRs) have become essential infrastructure for traditional Clinical and Translational Science Award (CTSA) programs and increasingly for a wide range of research consortia[[1], [3]] and learning health system networks. In the data commons, datasets associated wit...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 29; no. 4; pp. 581 - 585 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Oxford University Press / USA
Apr2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=155812608&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155812608 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Apr2022 vid: 29 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 155812608 155812608 NLM35289371 10.1093/jamia/ocac024 NLM35289371 155812608 ppf: 581 ppct: 4 formats: tig: atl: Research data warehouse best practices: catalyzing national data sharing through informatics innovation. aug: au: Murphy, Shawn N Visweswaran, Shyam Becich, Michael J Campion, Thomas R Knosp, Boyd M Melton-Meaux, Genevieve B Lenert, Leslie A affil: Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts, USA sug: subj: Medical Informatics Communication ab: Research Patient Data Repositories (RPDRs) have become essential infrastructure for traditional Clinical and Translational Science Award (CTSA) programs and increasingly for a wide range of research consortia[[1], [3]] and learning health system networks. In the data commons, datasets associated with various research projects were made findable, accessible, interoperable, and reusable (FAIR) through the open-source Gen3 data platform that enables the interoperation and creation of cloud-based data resources. Compared to on-premises infrastructure, cloud storage is inexpensive and readily available with automatic backups, and secure analytics in the cloud are easily enabled on large datasets containing protected health information. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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