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Clinical Trials
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Web-based communications and management of a multi-center clinical trial: the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) project

Stephen R Wisniewski

Epidemiology Data Center, Graduate School of Public Health, University of Pittsburgh, 127 Parran Hall, 130 Desoto Street, Pittsburgh, PA 15261, USA wisniew{at}edc.pitt.edu

Heather Eng

Leslie Meloro

Robert Gatt

University of Pittsburgh, Pittsburgh, PA, USA

Louise Ritz

National Institute of Mental Health, Bethesda, MD, USA

Diane Stegman

Madhukar Trivedi

Melanie M Biggs

Edward Friedman

Kathy Shores-Wilson

Diane Warden

University of Texas Southwestern Medical Center, Dallas, TX, USA

Douglas Bartolowits

Jeffrey P Martin

University of Pittsburgh, Pittsburgh, PA, USA

A John Rush

University of Texas Southwestern Medical Center, Dallas, TX, USA

While efficient methods of communication are known to be essential in conducting large multicenter clinical trials, very little information is provided on actual methods that can be implemented to improve communication. An integrated technology-based communication system was developed for the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) project, which prospectively defines treatments that are most effective for participants with a diagnosis of a nonpsychotic major depressive disorder (MDD) who report an unsatisfactory clinical outcome to an initial and, if necessary, subsequent treatment(s). This web-based communication system is comprised of a multi-faceted study Web site, including a help desk, document sharing, a project directory and reports. In addition, automated reporting via e-mail and an online data correction mechanism are also available. The STARD communication system improves communication between study personnel and improves the quality of the study's data through the integration of system elements, the integration of those elements with traditional forms of communication, by filling the gaps not addressed by those traditional methods and by reducing the staff workload burden.

Clinical Trials, Vol. 1, No. 4, 387-398 (2004)
DOI: 10.1191/1740774504cn035oa


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