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, 17:106

First Online: 24 February 2016Received: 12 August 2015Accepted: 11 February 2016DOI: 10.1186-s13063-016-1227-2

Cite this article as: Martinez, D.A., Tsalatsanis, A., Yalcin, A. et al. Trials 2016 17: 106. doi:10.1186-s13063-016-1227-2


BackgroundThe administrative process associated with clinical trial activation has been criticized as costly, complex, and time-consuming. Prior research has concentrated on identifying administrative barriers and proposing various solutions to reduce activation time, and consequently associated costs. Here, we expand on previous research by incorporating social network analysis and discrete-event simulation to support process improvement decision-making.

MethodsWe searched for all operational data associated with the administrative process of activating industry-sponsored clinical trials at the Office of Clinical Research of the University of South Florida in Tampa, Florida. We limited the search to those trials initiated and activated between July 2011 and June 2012. We described the process using value stream mapping, studied the interactions of the various process participants using social network analysis, and modeled potential process modifications using discrete-event simulation.

ResultsThe administrative process comprised 5 sub-processes, 30 activities, 11 decision points, 5 loops, and 8 participants. The mean activation time was 76.6 days. Rate-limiting sub-processes were those of contract and budget development. Key participants during contract and budget development were the Office of Clinical Research, sponsors, and the principal investigator. Simulation results indicate that slight increments on the number of trials, arriving to the Office of Clinical Research, would increase activation time by 11 %. Also, incrementing the efficiency of contract and budget development would reduce the activation time by 28 %. Finally, better synchronization between contract and budget development would reduce time spent on batching documentation; however, no improvements would be attained in total activation time.

ConclusionThe presented process improvement analytic framework not only identifies administrative barriers, but also helps to devise and evaluate potential improvement scenarios. The strength of our framework lies in its system analysis approach that recognizes the stochastic duration of the activation process and the interdependence between process activities and entities.

KeywordsClinical trials Time factors Quality improvement AbbreviationsDESdiscrete-event simulation

DSRUSF’s Division of Sponsored Research

IRBInstitutional Review Board

OCROffice of Clinical Research

PIprincipal investigator

USFUniversity of South Florida

VSMvalue stream mapping

SNAsocial network analysis

WIRBWestern Institutional Review Board

Electronic supplementary materialThe online version of this article doi:10.1186-s13063-016-1227-2 contains supplementary material, which is available to authorized users.

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Autor: Diego A. Martinez - Athanasios Tsalatsanis - Ali Yalcin - José L. Zayas-Castro - Benjamin Djulbegovic


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