Clinical Data Warehousing: A Scoping Review
Zhan Wang1, Mahanaz Syed1, Shorabuddin Syed1
1University of Texas Health Science Center at San Antonio, San Antonio, TX, US.
Introduction:
A clinical data warehouse (CDW) is a powerful resource that supports clinical decision-making and secondary data use by integrating and presenting heterogeneous data sources. Despite considerable effort within healthcare organizations (HCOs) to develop CDWs, scientific literature surrounding clinical data warehousing methods is limited.
Objectives:
The scoping review aims to characterize the current state of CDW methods within HCOs, to identify extant evidence for practice recommendations, and ultimately to advance the design, implementation, and use of CDWs.
Methods:
The review encompasses CDW articles published from 2011 through 2021 identified through a systematic PubMed search. Article abstracts were systematically screened by two authors. Full-text articles were reviewed and abstracted independently by two authors with discrepancies resolved through consensus.
Results:
137 articles, from 55 journals and 3 conference proceedings, were categorized and analyzed. Areas for increased CDW focus include CDW design (such as data integration of increased data types and sources; extract-transform-load (ETL) optimization; data quality improvement processes; semantic data representation) and CDW governance (such as support tools/documentation and data literacy efforts for staff and end-users; governance structure; and business model/financial support for CDWs including staffing).
Conclusion:
The study indicates the topics that have been significantly developed and the aspects that need additional focus and reporting in CDW between existing general data management best practices and recently articulated requirements for research data. Also, more multi-site and multi-aspect studies are needed to foster maturity at CDWs.
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