Leveraging a clinical research information system to assist biospecimen data and workflow management: A hybrid approach

Prakash M. Nadkarni, Rowena Kemp, Chirag Parikh

Research output: Contribution to journalArticle

Abstract

Background: Large multi-center clinical studies often involve the collection and analysis of biological samples. It is necessary to ensure timely, complete and accurate recording of analytical results and associated phenotypic and clinical information. The TRIBE-AKI Consortium http://www.yale.edu/tribeaki supports a network of multiple related studies and sample biorepository, thus allowing researchers to take advantage of a larger specimen collection than they might have at an individual institution.Description: We describe a biospecimen data management system (BDMS) that supports TRIBE-AKI and is intended for multi-center collaborative clinical studies that involve shipment of biospecimens between sites. This system works in conjunction with a clinical research information system (CRIS) that stores the clinical data associated with the biospecimens, along with other patient-related parameters. Inter-operation between the two systems is mediated by an interactively invoked suite of Web Services, as well as by batch code. We discuss various challenges involved in integration.Conclusions: Our experience indicates that an approach that emphasizes inter-operability is reasonably optimal in allowing each system to be utilized for the tasks for which it is best suited.

Original languageEnglish (US)
Article number22
JournalJournal of Clinical Bioinformatics
Volume1
Issue number1
DOIs
StatePublished - Aug 25 2011

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Keywords

  • biorepositories
  • Biospecimen data management
  • clinical research information systems
  • multi-center clinical studies

ASJC Scopus subject areas

  • Health Informatics

Cite this

Leveraging a clinical research information system to assist biospecimen data and workflow management : A hybrid approach. / Nadkarni, Prakash M.; Kemp, Rowena; Parikh, Chirag.

In: Journal of Clinical Bioinformatics, Vol. 1, No. 1, 22, 25.08.2011.

Research output: Contribution to journalArticle

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