This month, Resiliency in Northern Ghana (RING), a five-year USAID-funded project, conducted a survey to assess the gaps in anemia prevention and control during antenatal care (ANC) clinics and to identify the origins of gaps in the supply chain of medicines provided. The findings will inform the Ghana Health Service and implementers on gaps in anemia service delivery that should be targeted. Ultimately, this will result in improved quality of care for pregnant women accessing ANC services.
To more effectively collect data, JSI used Android tablets. Here are a few lessons we learned about mobile data collection and some tips to help in your own work:
Know the benefits. Mobile data collection ensures quality data by building the mobile tool to streamline responses and catch mistakes and omissions. The RING anemia survey had many skips (for example, if a drug wasn’t available in the store, none of the follow-up questions should be asked), and using a mobile tool allowed for the questions to flow according to the skip patterns. Mobile tools can also make questions “required” so that data collectors have to answer them before proceeding with the survey thus ensuring complete data. Mobile data collection makes analysis easier as well, with a web platform where supervisors can see the data being uploaded in real time. Better data quality and faster analysis will provide the RING team with a more accurate picture of programming data to use for project decision-making.
Know the platforms. With many different platforms for mobile data collection, finding the right one for your survey can be a challenge. Understanding the basics can help narrow down the options. Many platforms are based on Open Data Kit, a “free and open-source set of tools which help organizations author, field, and manage mobile data collection solutions.” For the RING anemia survey, we used the Ona platform. The RING M&E team was familiar with this platform for collecting project data, so it was an easy transition to using the mobile tool. Other platforms include SurveyCTO and Magpi. *Interested in learning more about these options? Contact the Applied Technology Center.
Allow for plenty of technology practice time during training. Experience with mobile data collection ranges widely with enumerators – some have used mobile tools in past surveys, some have smartphones or tablets for personal use but haven’t used them for data collection, and some are not familiar with smartphone technology at all. It’s best to plan for those who have no experience and adjust training according to your group of enumerators. For the RING anemia survey, almost all enumerators were somewhat familiar with smartphone technology, and some had previously used mobile data collection. During training, they had a lot of time to go through each of the survey tools to familiarize themselves with how the questions looked on the mobile tool. This was really helpful when data collection started; since they had already practiced with the technology, the enumerators were able to focus on the survey itself.
Make sure the devices are ready for data collection. Besides training the people, part of the preparation for mobile data collection is making sure the devices are ready. Each device should be loaded with internet credit to upload the saved surveys to the server and should have a charger. With the RING anemia assessment, car chargers were also provided in case there was no power in remote districts. The enumerators were trained to keep the tablets charged at all times so there would be enough battery power to go through the tools for ANC observation, facility store, storage conditions, and possibly the district store. If you want to collect geographic data in your survey, make sure the location services for your devices are turned on.
Mobile data collection is an exciting new tool that complements the RING team’s approach to conducting surveys. The data enumerators were confident in using the tablets and expressed their preference for using technology over paper-based tools. The data analysis team also preferred the use of mobile tools, as the data is uploaded online daily and can easily be exported to data analysis software. The electronic transmission saves time and reduces the opportunity for error.
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