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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

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Managing complex research datasets using electronic tools: a meta-analysis exemplar.

Sharon A Brown¹, Ellen E Martin, Theresa J Garcia

¹School of Nursing, The University of Texas at Austin, Austin, TX 78701, USA. sabrown@mail.utexas.edu

Computers, Informatics, Nursing : CIN

|May 18, 2013

Summary

Implementing electronic tools streamlines complex meta-analyses by improving study management and team communication. This approach enhances efficiency in data extraction, accuracy checks, and document sharing for large-scale research projects.

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Area of Science:

Scientific research methodology
Data management in research

Background:

Large-scale meta-analyses necessitate robust document organization and team coordination.
Existing commercial software offers potential solutions for managing complex research workflows.

Purpose of the Study:

To describe electronic processes for conducting a complex, quantitative model-testing meta-analysis.
To detail the use of commercially available software to enhance meta-analytic efficiency and communication.

Main Methods:

Utilized commercial software (EndNote, Adobe Acrobat Pro, Blackboard, Excel, SPSS) for meta-analysis.
Developed specific electronic workflows for study identification, screening, data extraction, and analysis.
Implemented systems to improve communication and document sharing among research staff.

Main Results:

Electronic tools significantly improved efficiency in locating, screening, and organizing studies.
Data extraction, accuracy checking, and analysis processes were streamlined.
Enhanced communication and document sharing among research team members were achieved.

Conclusions:

A fully electronic system, despite initial setup time, effectively streamlines complex meta-analyses.
Commercial software can be leveraged to enhance efficiency, accuracy, and collaboration in meta-analytic research.