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Analyzing Operational Data Systems Essay

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Operational Data Systems There are several systems and technologies commonly used to manage operational data. These tools accessible for data management are referred to as Clinical Data Management Systems (CDMS). The commonly used tools include: CLINTRIAL, ORACLE CLINICAL, RAVE, MACRO and also eClinical Suite (Krishnankutty et al., 2012). With regard to functionality, these software technologies are relatively comparable and there is no substantial lead of one system set against the other. These software technologies are costly and require sophisticated Information Technology infrastructure to function (Krishnankutty et al., 2012). However, other personalized systems and technologies commonly used to manage operational data include: OpenClinica, openCDMS, TrialDB, and PhOSCo. These data management software technologies are free with regards to cost and comparatively effective against their viable equivalents (Krishnankutty et al., 2012).

In this method, the systems and technology employed in this discussion is OpenClinica. To begin with, OpenClinica is a software platform that is web-based. This system was technologically established and advanced by Akaza Research, which manages clinical research studies for several different sites. In particular, OpenClinica enables protocol alignment, designing of case report forms, electronic data capture (EDC), recovery, and data management (Ashwin, 2006). This technology takes...

With respect to data management, the sole significant benefit of OpenClinica is encompassed in the user interface. The workflow is exceedingly spontaneous, and has user indications right from the outset. One more pronounced feature is the capacity to design modus operandi, studies and generate case report forms devoid of any knowledge or proficiency in programming (Ashwin, 2006).
With respect to data management, OpenClinica, in a dynamic manner, produces web-based interfaces for the clinical implements well-defined within a project, and at the same time, executing the authentication logic identified. It offers investigators with instinctive web-based workflows to hand in, probe and export datasets, manage multi-site ventures and oversee project-distinct user rights and responsibilities (Ashwin, 2006). In addition, this technology can also serve the purpose of functioning as a centralized data repository. Through OpenClinica, every researcher or investigator is able to arrange and format his or her own research projects in data management, outline custom clinical appraisal implements, and manage plans and strategies for his or her own research studies in varied clinical research areas. Ashwin (2006) points out that OpenClinica executes a steady security model,…

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Ashwin. (2006). Open Source Clinical Data Management. Retrieved 18 January, 2016 from: http://ashwinnaik.com/blog/open-souce-clinical-data-management/

Krishnankutty, B., Bellary, S., Kumar, N. B., & Moodahadu, L. S. (2012). Data management in clinical research: an overview. Indian journal of pharmacology, 44(2), 168.
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