Enabling Automation in Clinical Research Administration through Good Data Management
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Date
2018-12
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Abstract
The amount of clinical trials moving through the clinical trial lifecycle pipeline continues to increase every year. From 2000 to 2013, the number of registered clinical trials increased by two orders of magnitude. Also increasing are the amount of steps and processes both scientific and administrative required for a clinical trial to proceed through the pipeline. This trend contributes to increasing study complexity and burden of work on clinical research administrators. Traditional methods of facilitating and completing clinical research administrative tasks may not be effective in dealing with increasing numbers of simultaneous trials and increasing number of required processes to complete. There is a risk of further increasing the time of the clinical trial lifecycle due to overloaded clinical research administration. In this paper, concepts of clinical data management are introduced in the context of clinical research administration. Key data points common within clinical research administrative activities are presented, along with application of that data in improving clinical research administration efficiency through both non-programmatic and programmatic automation, reducing administrative work burden, costs, and ensuring current turnaround time for work processes will not be impacted by increasing workload.
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clinical research, clinical data, data management, data analysis