Specialized Software Engineering in Clinical Trials. GANfort Study

Objective: We aim to develop and implement a personalized software to accomplish data quality management in real time, reducing the chance of error in data collection and a “real time biostatistics” software linked to a collector datasheet.
Material and methods: We used C++ for programming, R for statistics and JavaScript (AJAX) for the interface. This application was deve-loped for phase 3 GANfort study. This is a multicentric study. The results presented are simulated.
Results: The application presented below has a datasheet collection view with three tabs and a general presentation of the study and patient. The first tab collects data from the first visit (study inclusion and initiating the treatment), the second tab is for surveillance visit and the third tab generates real time statistic parameters.
Discussions: Using this type of software many methodological problems concerning data management can be avoided. “Missing data” and “outliers” or writing and typing errors become non-existent; typing constraints issued by datasheets and real time biostatistics eliminate them. The data can be introduced in the same time in different places and the matching data is performed simultaneously.
Conclusions: The time consuming data quality management is automatically solved using the software we proposed. Statistical parameters are calculated in real time. The end of data collection coincides with a final report of the study.

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