Clinical Data Warehousing: A Scoping Review

Area of Science:

• Health Informatics
• Data Management
• Clinical Research Informatics

Background:

• Clinical Data Warehouses (CDWs) integrate diverse data for decision-making and secondary use in healthcare organizations (HCOs).
• Limited scientific literature exists on CDW methods despite significant HCO efforts.
• Existing literature often lacks focus on critical areas like data integration, ETL optimization, and governance.

Purpose of the Study:

• To systematically review and characterize current CDW methods in HCOs.
• To identify evidence-based recommendations for CDW practices.
• To guide the advancement of CDW design, implementation, and utilization.

Main Methods:

• A systematic PubMed search identified 137 articles published between 2011 and 2021.
• Abstracts were screened by two authors; full-text articles were independently reviewed and abstracted.
• Discrepancies were resolved through consensus to ensure data accuracy.

Main Results:

• Analysis revealed 137 relevant articles from 55 journals and 3 conference proceedings.
• Key areas needing increased focus include CDW design (data integration, ETL, data quality, semantic representation) and governance (support tools, data literacy, structure, financial models).

Conclusions:

• The study identifies developed CDW topics and areas requiring further attention, bridging general data management practices and research data needs.
• More multi-site and multi-aspect studies are recommended to enhance CDW maturity.
• Improved reporting on CDW design and governance is crucial for advancing the field.