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Managing Complex Change in Clinical Study Metadata

Affiliation of the authors: Center for Medical Informatics, Yale School of Medicine, New Haven, CT

Correspondence and reprints: Cynthia A. Brandt, MD, MPH, Center for Medical Informatics, Yale School of Medicine, New Haven, CT 06520-8009; e-mail: <cynthia.brandt{at}yale.edu>.

Received for publication: 12/09/03; accepted for publication: 03/24/04.

In highly functional metadata-driven software, the interrelationships within the metadata become complex, and maintenance becomes challenging. We describe an approach to metadata management that uses a knowledge-base subschema to store centralized information about metadata dependencies and use cases involving specific types of metadata modification. Our system borrows ideas from production-rule systems in that some of this information is a high-level specification that is interpreted and executed dynamically by a middleware engine. Our approach is implemented in TrialDB, a generic clinical study data management system. We review approaches that have been used for metadata management in other contexts and describe the features, capabilities, and limitations of our system.