An offline mobile data capture module for health and demographic surveillance system (HDSS) studies

Baguiya, Adama
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Considering the amount of data generated by the International Network for Demographic Evaluation of Populations and Their Health (INDEPTH), affiliated Health and Demographic Surveillance Systems (HDSS), and the complexity of their dynamic cohorts, introducing Information and Communication Technologies (ICT) and mobile technologies for data collection may significantly improve data quality and ease data processing and data management. So far, the level of use of mobile devices in public health research data collection and its determinants are not clearly known. We assessed the level of use of mobile devices for research data collection. We conducted a cross-sectional survey in 29 HDSS sites out of 51, in Africa and Asia, to assess the current use of electronic/mobile devices for their core follow-up as well as the embedded studies. This survey revealed that the use of mobile devices was very (8 sites out of 29) low in the core HDSS follow-up. Meanwhile, a third of sites (34%) used mobile data collection for embedded studies. Motivations for using mobile data collection were data quality improvement and timeliness. On the other hand, devices’ initial cost and unreliable internet connectivity were the major barriers to the use of mobile data collection. For those using paper-based data collection methods, Microsoft Access and Epidata were the two leading platforms for data entry whereas Research Electronic Data Capture (REDcap) was the most used electronic data capture system. INDEPTH network is currently supporting the implementation of Open Health and Demographic System (OpenHDS) in HDSSs. This support can improve the rate of utilisation of mobile devices in HDSS data collection. Electronic Data Capture (EDC) systems can potentially improve and facilitate data management in epidemiological studies. However, some of these systems lack mobile application or module needed for field-based research. The second component of our work was to implement an open source mobile application, CTLS (Clinical Trials and Longitudinal Studies), that can be used with REDCap for electronic data capture. The application should be able to collect data offline and asynchronously upload onto REDCap database server or repository. We use REDCap in accordance with the findings of the survey: it was the most used EDC system. Such an offline mobile data capture feature will aid in overcoming the lack of mobile application and poor internet connectivity on the field, and improving the rate of utilisation of mobile data collection in remote settings. Our module has been tested using the entry and exit forms of the Nairobi Urban Health and Demographic Surveillance System in Kenya. It has been proved to be effective in fetching metadata from REDCap server, entering data offline and loading them to a remote database in an asynchronous fashion upon establishing internet connexion.
A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand in partial fulfilment of the requirements for the degree of Masters of Science In Epidemiology (Research database management) Johannesburg, May 2016
Health and Demographic Surveillance System (HDSS)