An atomic approach to the design and implementation of a research data warehouse.
An atomic approach to the design and implementation of a research data warehouse.
复制标题
研究数据仓库设计和实施的原子方法。
DOI：
10.1093/jamia/ocab204
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发表时间：
2022-03-15
期刊：
影响因子：
--
通讯作者：
Becich MJ
中科院分区：
文献类型：
--
作者：
Visweswaran S;McLay B;Cappella N;Morris M;Milnes JT;Reis SE;Silverstein JC;Becich MJ
As a long-standing Clinical and Translational Science Awards (CTSA) Program hub, the University of Pittsburgh and the University of Pittsburgh Medical Center (UPMC) developed and implemented a modern research data warehouse (RDW) to efficiently provision electronic patient data for clinical and translational research. We designed and implemented an RDW named Neptune to serve the specific needs of our CTSA. Neptune uses an atomic design where data are stored at a high level of granularity as represented in source systems. Neptune contains robust patient identity management tailored for research; integrates patient data from multiple sources, including electronic health records (EHRs), health plans, and research studies; and includes knowledge for mapping to standard terminologies. Neptune contains data for more than 5 million patients longitudinally organized as Health Insurance Portability and Accountability Act (HIPAA) Limited Data with dates and includes structured EHR data, clinical documents, health insurance claims, and research data. Neptune is used as a source for patient data for hundreds of institutional review board-approved research projects by local investigators and for national projects. The design of Neptune was heavily influenced by the large size of UPMC, the varied data sources, and the rich partnership between the University and the healthcare system. It includes several unique aspects, including the physical warehouse straddling the University and UPMC networks and management under an HIPAA Business Associates Agreement. We describe the design and implementation of an RDW at a large academic healthcare system that uses a distinctive atomic design where data are stored at a high level of granularity.
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DOI：
10.1056/nejmsr1809937
发表时间：
2019-08-15
期刊：
The New England journal of medicine
影响因子：
--
作者：
All of Us Research Program Investigators;Denny JC;Rutter JL;Goldstein DB;Philippakis A;Smoller JW;Jenkins G;Dishman E
通讯作者：
Dishman E
影响因子：
4.5
作者：
Hauskrecht, Milos;Batal, Iyad;Hong, Charmgil;Quang Nguyen;Cooper, Gregory F.;Visweswaran, Shyam;Clermont, Gilles
通讯作者：
Clermont, Gilles
DOI：
10.1146/annurev-genom-090314-024956
发表时间：
2016-08-31
影响因子：
8.7
作者：
Denny JC;Bastarache L;Roden DM
通讯作者：
Roden DM
影响因子：
8.8
作者：
Mandl, Kenneth D.;Glauser, Tracy;Zhang, Yu
通讯作者：
Zhang, Yu
DOI：
10.13063/2327-9214.1213
发表时间：
2016-01-01
期刊：
EGEMS (Washington, DC)
影响因子：
--
作者：
Davies, Melanie;Erickson, Kyle;Brown, Jeffrey
通讯作者：
Brown, Jeffrey