Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal

Abstract

The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring multiple systems is limited. This paper shares our experiences of designing and implementing a complex multi-component EDC system for a community-based four-armed cluster-Randomised Controlled Trial in the rural plains of Nepal, to help other researchers planning to use EDC for complex studies in low-income settings. We designed and implemented three interrelated mobile phone data collection systems to enrol and follow-up pregnant women (trial participants), and to support the implementation of trial interventions (women’s groups, food and cash transfers). 720 field staff used basic phones to send simple coded text messages, 539 women’s group facilitators used Android smartphones with Open Data Kit Collect, and 112 Interviewers, Coordinators and Supervisors used smartphones with CommCare. Barcoded photo ID cards encoded with participant information were generated for each enrolled woman. Automated systems were developed to download, recode and merge data for nearly real-time access by researchers. The systems were successfully rolled out and used by 1371 staff. A total of 25,089 pregnant women were enrolled, and 17,839 follow-up forms completed. Women’s group facilitators recorded 5717 women’s groups and the distribution of 14,647 food and 13,482 cash transfers. Using EDC sped up data collection and processing, although time needed for programming and set-up delayed the study inception. EDC using three interlinked mobile data management systems (FrontlineSMS, ODK and CommCare) was a feasible and effective method of data capture in a complex large-scale trial in the plains of Nepal. Despite challenges including prolonged set-up times, the systems met multiple data collection needs for users with varying levels of literacy and experience.

Do Participatory Learning and Action Women’s Groups Alone or Combined with Cash or Food Transfers Expand Women’s Agency in Rural Nepal?

“…Between 2013 and 2015, more than 60,000 women were enrolled into menstrual monitoring and more than 25,000 pregnancies were detected. The details of the trial surveillance system have been reported elsewhere (Style et al, 2017).…”

“…A household census conducted in 2013 before the start of the intervention identified married women between 10 and 49 years of age who had not had operative family planning and whose husbands had not had a vasectomy. These were asked to consent to take part in the trial surveillance system which identified new pregnancies over the course of the trial, a 'menstrual monitoring system' (Style et al, 2017). As discussed in Section 2, in all intervention areas, women's groups practising PLA were open to all community members to attend, but cash and food transfers were only provided to consenting pregnant women from the third month of pregnancy until the end of pregnancy.…”

Smartphone tool to collect repeated 24 h dietary recall data in Nepal

“…Field surveys, traditionally conducted on paper forms, are increasingly using electronic data capture tools, such as tablets and smartphones. Compared with paper methods, commonly cited relative benefits of electronic data capture include quicker access to data, more options to check data quality and interviewer performance, lower costs for data entry, and reduced risk of data loss during transport and storage (1)(2)(3) .…”

The Use of Tablet-Based Multiple-Pass 24-Hour Dietary Recall Application (MP24Diet) to Collect Dietary Intake of Children under Two Years Old in the Prospective Cohort Study in Indonesia

“…The use of electronic data collection, via mobile phones or tablets, has recently gained attention. Several studies have shown its advantages over paper-based data collection [2,3]. Other studies have shown it is also feasible, in LMICs, to collect dietary data via electronic data capture [4,5].…”

“…Nutrient intakes presented as median (25-75th percentile interquartile range) 2. Somers' D test-adjusted for cluster sampling.…”