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Archival Research

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...

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TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

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A Temporal Abstraction-based Extract, Transform and Load Process for Creating Registry Databases for Research.

Andrew Post¹, Tahsin Kurc, Marc Overcash

¹Atlanta Clinical and Translational Science Institute Biomedical Informatics Program, Atlanta, GA.

AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science

|January 3, 2012

Summary

This summary is machine-generated.

This study introduces PROTEMPA, a system for integrating diverse clinical data across institutions. It transforms heterogeneous data into a unified format for research, ensuring data accuracy and accessibility.

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Area of Science:

Biomedical Informatics
Clinical Data Management
Health Data Interoperability

Background:

Aggregating and comparing patient populations across institutions is crucial in the Clinical and Translational Science Awards (CTSA) era.
Clinical data warehouses (CDWs) often store data heterogeneously, posing challenges for multi-institutional research.
A standardized data representation is needed to optimize data for investigators.

Purpose of the Study:

To extend the PROTEMPA system for federated data extraction and transformation.
To create a research-optimized data registry from heterogeneous clinical databases.
To enable tailored access control, data representation, and query tools for researchers.

Main Methods:

Extension of the PROTEMPA temporal abstraction-based clinical database query system.
Specification of data types across federated databases.
Extraction, categorization, interpretation, and loading into a refreshable registry database.

Main Results:

The extended PROTEMPA system facilitates the transformation of heterogeneous clinical data into a shared representation.
A registry database is populated, optimized for research needs.
Local databases remain the source of truth, with the registry providing a curated research view.

Conclusions:

The enhanced PROTEMPA system effectively addresses the need for harmonizing multi-institutional clinical data for research.
This approach supports data-driven research by providing a standardized, accessible, and tailored data resource.
Maintaining local databases as the source of truth ensures data integrity while enabling efficient research querying.