Activating clinical trials: a process improvement approach
Activating clinical trials: a process improvement approach
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DOI：
10.1186/s13063-016-1227-2
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发表时间：
2016-02-24
期刊：
影响因子：
2.5
通讯作者：
Djulbegovic, Benjamin
中科院分区：
文献类型：
--
作者：
Martinez, Diego A.;Tsalatsanis, Athanasios;Djulbegovic, Benjamin
背景：与临床试验激活相关的管理过程一直被批评为昂贵、复杂和耗时。以前的研究集中在识别管理障碍并提出各种解决方案来减少激活时间，从而减少相关成本。在此，我们通过结合社会网络分析和离散事件模拟来扩展以前的研究，以支持流程改进决策。方法：我们在佛罗里达州坦帕市的南佛罗里达大学临床研究办公室搜索与启动行业赞助的临床试验的管理流程相关的所有操作数据。我们将搜索范围限制在2011年7月至2012年6月期间启动和激活的试验。我们使用价值流图描述流程，使用社会网络分析研究流程参与者之间的互动，并使用离散事件模拟对潜在的流程修改进行建模。结果：行政流程包括5个子流程、30个活动、11个决策点、5个循环和8个参与者。平均激活时间为76.6天。速率限制子进程是合同和预算制定的子进程。合同和预算制定过程中的关键参与者是临床研究办公室、赞助商和主要研究人员。模拟结果表明，到达临床研究办公室的试验数量略有增加，将使激活时间增加11%。此外，提高合同和预算制定的效率将使激活时间减少28%。最后，合同和预算制定之间更好的同步将减少批处理文档所花费的时间，但总激活时间不会得到改善。结论：提出的过程改进分析框架不仅识别行政障碍，而且有助于设计和评估潜在的改进方案。我们的框架的优势在于它的系统分析方法，该方法认识到激活过程的随机持续时间以及过程活动和实体之间的相互依赖。
Background: The 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.Methods: We 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.Results: The 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.Conclusion: The 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.