Use of the data system for field management of a clinical study conducted in Kolkata, India. (December 2016) - Park, Ju; Kim, Deok; Haldar, Bisakha; Mallick, Aiyel; Kim, Soon; Dey, Ayan; Nandy, Ranjan; Paul, Dilip; Choudhury, Saugata; Sahoo, Shushama; Wierzba, Thomas; Sur, Dipika; et al.
Abstract Background Designing an appropriate data system is important to the success of a clinical study. However, little information is available on this topic. We share our experiences on designing, developing, and implementation of a data system for management of data and field activities of a complex clinical study. Methods The data system was implemented aiming at determining the biological basis for the underperformance of oral vaccines, such as polio and rotavirus vaccines in children at a site in Kolkata, India. The system included several functionalities to control data and field activities. It was restricted to authorized users based on their access privileges. A relational database platform was chosen, and Microsoft Visual FoxPro 7.0 (Microsoft Corporation, Seattle, WA, USA) was used to develop the system. The system was installed at the clinic and data office to facilitate both the field and data management activities. Results Data were doubly entered by two different data operators to identify keypunching errors in the data. Outliers, duplication, inconsistencies, missing entries, and linkage were also checked. Every modification and users log-in/log-out information was auto-recorded in an audit trail. The system offered tools for preparation of visit schedule of the participants. A visit considered as protocol deviation was documented by the system. The system alerted field staff to every upcoming visit date to organize the field activities and to inform participants which day to come. The system also produced a growth chart for evaluating nutritional status and referring the child to a specialized clinic if found to be severely malnourished. Conclusion The data system offered unique features for controlling for both data and field activities, which led to minimize drop-out rates as well as protocol deviations. Such system is warranted for a successful clinical study.