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Acad Radiol. 2015 Apr;22(4):527-33. doi: 10.1016/j.acra.2014.12.002. Epub 2015 Jan 29.

How I do it: a practical database management system to assist clinical research teams with data collection, organization, and reporting.

Author information

1
Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Sheikh Zayed Tower, Ste 7203, 1800 Orleans St, Baltimore, MD 21287.
2
Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Sheikh Zayed Tower, Ste 7203, 1800 Orleans St, Baltimore, MD 21287. Electronic address: jfg@jhmi.edu.
3
U/S Imaging and Interventions (UII), Philips Research North America, Briarcliff Manor, NY.

Abstract

RATIONALE AND OBJECTIVES:

The objective of this study was to demonstrate that an intra-arterial liver therapy clinical research database system is a more workflow efficient and robust tool for clinical research than a spreadsheet storage system. The database system could be used to generate clinical research study populations easily with custom search and retrieval criteria.

MATERIALS AND METHODS:

A questionnaire was designed and distributed to 21 board-certified radiologists to assess current data storage problems and clinician reception to a database management system. Based on the questionnaire findings, a customized database and user interface system were created to perform automatic calculations of clinical scores including staging systems such as the Child-Pugh and Barcelona Clinic Liver Cancer, and facilitates data input and output.

RESULTS:

Questionnaire participants were favorable to a database system. The interface retrieved study-relevant data accurately and effectively. The database effectively produced easy-to-read study-specific patient populations with custom-defined inclusion/exclusion criteria.

CONCLUSIONS:

The database management system is workflow efficient and robust in retrieving, storing, and analyzing data.

KEYWORDS:

Database; graphical user interface; organization; query; statistical analysis

PMID:
25641319
PMCID:
PMC4355209
DOI:
10.1016/j.acra.2014.12.002
[Indexed for MEDLINE]
Free PMC Article
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