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. 2022 Mar 15;29(4):671-676.
doi: 10.1093/jamia/ocab256.

Understanding enterprise data warehouses to support clinical and translational research: enterprise information technology relationships, data governance, workforce, and cloud computing

Boyd M Knosp  1 , Catherine K Craven  2 , David A Dorr  3   4 , Elmer V Bernstam  5 , Thomas R Campion  6   7
Affiliations

Understanding enterprise data warehouses to support clinical and translational research: enterprise information technology relationships, data governance, workforce, and cloud computing

Boyd M Knosp et al. J Am Med Inform Assoc. .

Erratum in

Abstract

Objective: Among National Institutes of Health Clinical and Translational Science Award (CTSA) hubs, effective approaches for enterprise data warehouses for research (EDW4R) development, maintenance, and sustainability remain unclear. The goal of this qualitative study was to understand CTSA EDW4R operations within the broader contexts of academic medical centers and technology.

Materials and methods: We performed a directed content analysis of transcripts generated from semistructured interviews with informatics leaders from 20 CTSA hubs.

Results: Respondents referred to services provided by health system, university, and medical school information technology (IT) organizations as "enterprise information technology (IT)." Seventy-five percent of respondents stated that the team providing EDW4R service at their hub was separate from enterprise IT; strong relationships between EDW4R teams and enterprise IT were critical for success. Managing challenges of EDW4R staffing was made easier by executive leadership support. Data governance appeared to be a work in progress, as most hubs reported complex and incomplete processes, especially for commercial data sharing. Although nearly all hubs (n = 16) described use of cloud computing for specific projects, only 2 hubs reported using a cloud-based EDW4R. Respondents described EDW4R cloud migration facilitators, barriers, and opportunities.

Discussion: Descriptions of approaches to how EDW4R teams at CTSA hubs work with enterprise IT organizations, manage workforces, make decisions about data, and approach cloud computing provide insights for institutions seeking to leverage patient data for research.

Conclusion: Identification of EDW4R best practices is challenging, and this study helps identify a breadth of viable options for CTSA hubs to consider when implementing EDW4R services.

Keywords: CTSA; EHR; data warehouse; secondary use.

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